The Actions about an Assertion. In the future, we’ll likely extend this model to support additional parameters or options related to the assertion actions.

Parameters:: type (Union[str, AssertionActionTypeClass])

property type: str | AssertionActionTypeClass: The type of the Action

class datahub.metadata.schema_classes.AssertionActionTypeClass

Bases: object

RAISE_INCIDENT = 'RAISE_INCIDENT'

RESOLVE_INCIDENT = 'RESOLVE_INCIDENT'

class datahub.metadata.schema_classes.AssertionActionsClass(onSuccess=None, onFailure=None)

Bases: _Aspect

The Actions about an Assertion

Parameters:

onSuccess (Optional[List[AssertionActionClass]])
onFailure (Optional[List[AssertionActionClass]])

property onFailure: List[AssertionActionClass]: Actions to be executed on failed assertion run.

property onSuccess: List[AssertionActionClass]: Actions to be executed on successful assertion run.

class datahub.metadata.schema_classes.AssertionInfoClass(type, customProperties=None, externalUrl=None, datasetAssertion=None, freshnessAssertion=None, volumeAssertion=None, sqlAssertion=None, schemaAssertion=None, source=None, description=None)

Bases: _Aspect

Information about an assertion

Parameters:

type (Union[str, AssertionTypeClass])
customProperties (Optional[Dict[str, str]])
externalUrl (Optional[str])
datasetAssertion (Optional[DatasetAssertionInfoClass])
freshnessAssertion (Optional[FreshnessAssertionInfoClass])
volumeAssertion (Optional[VolumeAssertionInfoClass])
sqlAssertion (Optional[SqlAssertionInfoClass])
schemaAssertion (Optional[SchemaAssertionInfoClass])
source (Optional[AssertionSourceClass])
description (Optional[str])

property customProperties: Dict[str, str]: Custom property bag.

property datasetAssertion: None | DatasetAssertionInfoClass: A Dataset Assertion definition. This field is populated when the type is DATASET.

property description: None | str: An optional human-readable description of the assertion

property externalUrl: None | str: URL where the reference exist

property freshnessAssertion: None | FreshnessAssertionInfoClass: An Freshness Assertion definition. This field is populated when the type is FRESHNESS.

property schemaAssertion: None | SchemaAssertionInfoClass: An schema Assertion definition. This field is populated when the type is DATA_SCHEMA

property source: None | AssertionSourceClass

The source or origin of the Assertion definition.

If the source type of the Assertion is EXTERNAL, it is expected to have a corresponding dataPlatformInstance aspect detailing the platform where it was ingested from.

property sqlAssertion: None | SqlAssertionInfoClass: A SQL Assertion definition. This field is populated when the type is SQL.

property type: str | AssertionTypeClass: Type of assertion. Assertion types can evolve to span Datasets, Flows (Pipelines), Models, Features etc.

property volumeAssertion: None | VolumeAssertionInfoClass: An Volume Assertion definition. This field is populated when the type is VOLUME.

class datahub.metadata.schema_classes.AssertionKeyClass(assertionId)

Bases: _Aspect

Key for a Assertion

Parameters:: assertionId (str)

property assertionId: str: Unique id for the assertion.

class datahub.metadata.schema_classes.AssertionResultClass(type, rowCount=None, missingCount=None, unexpectedCount=None, actualAggValue=None, nativeResults=None, externalUrl=None, error=None)

Bases: DictWrapper

The result of running an assertion

Parameters:

type (Union[str, AssertionResultTypeClass])
rowCount (Optional[int])
missingCount (Optional[int])
unexpectedCount (Optional[int])
actualAggValue (Optional[float])
nativeResults (Optional[Dict[str, str]])
externalUrl (Optional[str])
error (Optional[AssertionResultErrorClass])

property actualAggValue: None | float: Observed aggregate value for evaluated batch

property error: None | AssertionResultErrorClass: The error object if AssertionResultType is an Error

property externalUrl: None | str: External URL where full results are available. Only present when assertion source is not native.

property missingCount: None | int: Number of rows with missing value for evaluated batch

property nativeResults: None | Dict[str, str]: Other results of evaluation

property rowCount: None | int: Number of rows for evaluated batch

property type: str | AssertionResultTypeClass: The final result, e.g. either SUCCESS, FAILURE, or ERROR.

property unexpectedCount: None | int: Number of rows with unexpected value for evaluated batch

class datahub.metadata.schema_classes.AssertionResultErrorClass(type, properties=None)

Bases: DictWrapper

An error encountered when evaluating an AssertionResult

Parameters:

type (Union[str, AssertionResultErrorTypeClass])
properties (Optional[Dict[str, str]])

property properties: None | Dict[str, str]: Additional metadata depending on the type of error

property type: str | AssertionResultErrorTypeClass: The type of error encountered

class datahub.metadata.schema_classes.AssertionResultErrorTypeClass

Bases: object

INSUFFICIENT_DATA = 'INSUFFICIENT_DATA'

INVALID_PARAMETERS = 'INVALID_PARAMETERS'

INVALID_SOURCE_TYPE = 'INVALID_SOURCE_TYPE'

SOURCE_CONNECTION_ERROR = 'SOURCE_CONNECTION_ERROR'

SOURCE_QUERY_FAILED = 'SOURCE_QUERY_FAILED'

UNKNOWN_ERROR = 'UNKNOWN_ERROR'

UNSUPPORTED_PLATFORM = 'UNSUPPORTED_PLATFORM'

class datahub.metadata.schema_classes.AssertionResultTypeClass

Bases: object

The final result of evaluating an assertion, e.g. SUCCESS, FAILURE, or ERROR.

ERROR = 'ERROR'

FAILURE = 'FAILURE'

INIT = 'INIT'

SUCCESS = 'SUCCESS'

class datahub.metadata.schema_classes.AssertionRunEventClass(timestampMillis, runId, asserteeUrn, status, assertionUrn, result=None, runtimeContext=None, batchSpec=None, eventGranularity=None, partitionSpec=None, messageId=None)

Bases: _Aspect

An event representing the current status of evaluating an assertion on a batch. AssertionRunEvent should be used for reporting the status of a run as an assertion evaluation progresses.

Parameters:

timestampMillis (int)
runId (str)
asserteeUrn (str)
status (Union[str, AssertionRunStatusClass])
assertionUrn (str)
result (Optional[AssertionResultClass])
runtimeContext (Optional[Dict[str, str]])
batchSpec (Optional[BatchSpecClass])
eventGranularity (Optional[TimeWindowSizeClass])
partitionSpec (Optional[PartitionSpecClass])
messageId (Optional[str])

ASPECT_TYPE: ClassVar[str] = 'timeseries'

property asserteeUrn: str

property assertionUrn: str

property batchSpec: None | BatchSpecClass: Specification of the batch which this run is evaluating

property eventGranularity: None | TimeWindowSizeClass: Granularity of the event if applicable

property messageId: None | str: The optional messageId, if provided serves as a custom user-defined unique identifier for an aspect value.

property partitionSpec: PartitionSpecClass | None: The optional partition specification.

property result: None | AssertionResultClass: Results of assertion, present if the status is COMPLETE

property runId: str: Native (platform-specific) identifier for this run

property runtimeContext: None | Dict[str, str]: Runtime parameters of evaluation

property status: str | AssertionRunStatusClass: The status of the assertion run as per this timeseries event.

property timestampMillis: int: The event timestamp field as epoch at UTC in milli seconds.

class datahub.metadata.schema_classes.AssertionRunStatusClass

Bases: object

The lifecycle status of an assertion run.

COMPLETE = 'COMPLETE'

class datahub.metadata.schema_classes.AssertionSourceClass(type)

Bases: DictWrapper

The source of an assertion

Parameters:: type (Union[str, AssertionSourceTypeClass])

property type: str | AssertionSourceTypeClass: The type of the Assertion Source

class datahub.metadata.schema_classes.AssertionSourceTypeClass

Bases: object

EXTERNAL = 'EXTERNAL'

INFERRED = 'INFERRED'

NATIVE = 'NATIVE'

class datahub.metadata.schema_classes.AssertionStdAggregationClass

Bases: object

The function that is applied to the aggregation input (schema, rows, column values) before evaluating an operator.

COLUMNS = 'COLUMNS'

COLUMN_COUNT = 'COLUMN_COUNT'

IDENTITY = 'IDENTITY'

MAX = 'MAX'

MEAN = 'MEAN'

MEDIAN = 'MEDIAN'

MIN = 'MIN'

NULL_COUNT = 'NULL_COUNT'

NULL_PROPORTION = 'NULL_PROPORTION'

ROW_COUNT = 'ROW_COUNT'

STDDEV = 'STDDEV'

SUM = 'SUM'

UNIQUE_COUNT = 'UNIQUE_COUNT'

UNIQUE_PROPORTION = 'UNIQUE_PROPORTION'

UNIQUE_PROPOTION = 'UNIQUE_PROPOTION'

class datahub.metadata.schema_classes.AssertionStdOperatorClass

Bases: object

A boolean operator that is applied on the input to an assertion, after an aggregation function has been applied.

BETWEEN = 'BETWEEN'

CONTAIN = 'CONTAIN'

END_WITH = 'END_WITH'

EQUAL_TO = 'EQUAL_TO'

GREATER_THAN = 'GREATER_THAN'

GREATER_THAN_OR_EQUAL_TO = 'GREATER_THAN_OR_EQUAL_TO'

IN = 'IN'

LESS_THAN = 'LESS_THAN'

LESS_THAN_OR_EQUAL_TO = 'LESS_THAN_OR_EQUAL_TO'

NOT_IN = 'NOT_IN'

NOT_NULL = 'NOT_NULL'

REGEX_MATCH = 'REGEX_MATCH'

START_WITH = 'START_WITH'

class datahub.metadata.schema_classes.AssertionStdParameterClass(value, type)

Bases: DictWrapper

Single parameter for AssertionStdOperators.

Parameters:

value (str)
type (Union[str, AssertionStdParameterTypeClass])

property type: str | AssertionStdParameterTypeClass: The type of the parameter

property value: str: The parameter value

class datahub.metadata.schema_classes.AssertionStdParameterTypeClass

Bases: object

LIST = 'LIST'

NUMBER = 'NUMBER'

SET = 'SET'

STRING = 'STRING'

UNKNOWN = 'UNKNOWN'

class datahub.metadata.schema_classes.AssertionStdParametersClass(value=None, maxValue=None, minValue=None)

Bases: DictWrapper

Parameters for AssertionStdOperators.

Parameters:

value (Optional[AssertionStdParameterClass])
maxValue (Optional[AssertionStdParameterClass])
minValue (Optional[AssertionStdParameterClass])

property maxValue: None | AssertionStdParameterClass: The maxValue parameter of an assertion

property minValue: None | AssertionStdParameterClass: The minValue parameter of an assertion

property value: None | AssertionStdParameterClass: The value parameter of an assertion

class datahub.metadata.schema_classes.AssertionTypeClass

Bases: object

DATASET = 'DATASET'

DATA_SCHEMA = 'DATA_SCHEMA'

FRESHNESS = 'FRESHNESS'

SQL = 'SQL'

VOLUME = 'VOLUME'

class datahub.metadata.schema_classes.AssertionValueChangeTypeClass

Bases: object

An enum to represent a type of change in an assertion value, metric, or measurement.

ABSOLUTE = 'ABSOLUTE'

PERCENTAGE = 'PERCENTAGE'

class datahub.metadata.schema_classes.AuditStampClass(time, actor, impersonator=None, message=None)

Bases: DictWrapper

Data captured on a resource/association/sub-resource level giving insight into when that resource/association/sub-resource moved into a particular lifecycle stage, and who acted to move it into that specific lifecycle stage.

Parameters:

time (int)
actor (str)
impersonator (Optional[str])
message (Optional[str])

property actor: str: The entity (e.g. a member URN) which will be credited for moving the resource/association/sub-resource into the specific lifecycle stage. It is also the one used to authorize the change.

property impersonator: None | str: The entity (e.g. a service URN) which performs the change on behalf of the Actor and must be authorized to act as the Actor.

property message: None | str

was the change created by an automated process, or manually.

Type:: Additional context around how DataHub was informed of the particular change. For example

property time: int: When did the resource/association/sub-resource move into the specific lifecycle stage represented by this AuditEvent.

class datahub.metadata.schema_classes.AzkabanJobTypeClass

Bases: object

The various types of support azkaban jobs

COMMAND = 'COMMAND'

GLUE = 'GLUE'

HADOOP_JAVA = 'HADOOP_JAVA'

HADOOP_SHELL = 'HADOOP_SHELL'

HIVE = 'HIVE'

PIG = 'PIG'

SQL = 'SQL'

class datahub.metadata.schema_classes.BaseDataClass(dataset, motivation=None, preProcessing=None)

Bases: DictWrapper

BaseData record

Parameters:

dataset (str)
motivation (Optional[str])
preProcessing (Optional[List[str]])

property dataset: str: What dataset were used in the MLModel?

property motivation: None | str: Why was this dataset chosen?

property preProcessing: None | List[str]: How was the data preprocessed (e.g., tokenization of sentences, cropping of images, any filtering such as dropping images without faces)?

class datahub.metadata.schema_classes.BatchSpecClass(customProperties=None, nativeBatchId=None, query=None, limit=None)

Bases: DictWrapper

A batch on which certain operations, e.g. data quality evaluation, is done.

Parameters:

customProperties (Optional[Dict[str, str]])
nativeBatchId (Optional[str])
query (Optional[str])
limit (Optional[int])

property customProperties: Dict[str, str]: Custom property bag.

property limit: None | int: Any limit to the number of rows in the batch, if applied

property nativeBatchId: None | str: The native identifier as specified by the system operating on the batch.

property query: None | str: A query that identifies a batch of data

class datahub.metadata.schema_classes.BinaryJsonSchemaClass(schema)

Bases: DictWrapper

Schema text of binary JSON schema.

Parameters:: schema (str)

property schema: str: The native schema text for binary JSON file format.

class datahub.metadata.schema_classes.BooleanTypeClass

Bases: DictWrapper

Boolean field type.

class datahub.metadata.schema_classes.BrowsePathEntryClass(id, urn=None)

Bases: DictWrapper

Represents a single level in an entity’s browsePathV2

Parameters:

id (str)
urn (Optional[str])

property id: str: The ID of the browse path entry. This is what gets stored in the index. If there’s an urn associated with this entry, id and urn will be the same

property urn: None | str: Optional urn pointing to some entity in DataHub

class datahub.metadata.schema_classes.BrowsePathsClass(paths)

Bases: _Aspect

Shared aspect containing Browse Paths to be indexed for an entity.

Parameters:: paths (List[str])

property paths: List[str]

A list of valid browse paths for the entity.

Browse paths are expected to be forward slash-separated strings. For example: ‘prod/snowflake/datasetName’

class datahub.metadata.schema_classes.BrowsePathsV2Class(path)

Bases: _Aspect

Shared aspect containing a Browse Path to be indexed for an entity.

Parameters:: path (List[BrowsePathEntryClass])

property path: List[BrowsePathEntryClass]

A valid browse path for the entity. This field is provided by DataHub by default. This aspect is a newer version of browsePaths where we can encode more information in the path. This path is also based on containers for a given entity if it has containers.

This is stored in elasticsearch as unit-separator delimited strings and only includes platform specific folders or containers. These paths should not include high level info captured elsewhere ie. Platform and Environment.

class datahub.metadata.schema_classes.BytesTypeClass

Bases: DictWrapper

Bytes field type.

class datahub.metadata.schema_classes.CalendarIntervalClass

Bases: object

DAY = 'DAY'

HOUR = 'HOUR'

MINUTE = 'MINUTE'

MONTH = 'MONTH'

QUARTER = 'QUARTER'

SECOND = 'SECOND'

WEEK = 'WEEK'

YEAR = 'YEAR'

class datahub.metadata.schema_classes.CaveatDetailsClass(needsFurtherTesting=None, caveatDescription=None, groupsNotRepresented=None)

Bases: DictWrapper

This section should list additional concerns that were not covered in the previous sections. For example, did the results suggest any further testing? Were there any relevant groups that were not represented in the evaluation dataset? Are there additional recommendations for model use?

Parameters:

needsFurtherTesting (Optional[bool])
caveatDescription (Optional[str])
groupsNotRepresented (Optional[List[str]])

property caveatDescription: None | str: Caveat Description For ex: Given gender classes are binary (male/not male), which we include as male/female. Further work needed to evaluate across a spectrum of genders.

property groupsNotRepresented: None | List[str]: Relevant groups that were not represented in the evaluation dataset?

property needsFurtherTesting: None | bool: Did the results suggest any further testing?

class datahub.metadata.schema_classes.CaveatsAndRecommendationsClass(caveats=None, recommendations=None, idealDatasetCharacteristics=None)

Bases: _Aspect

Parameters:

caveats (Optional[CaveatDetailsClass])
recommendations (Optional[str])
idealDatasetCharacteristics (Optional[List[str]])

property caveats: None | CaveatDetailsClass: This section should list additional concerns that were not covered in the previous sections. For example, did the results suggest any further testing? Were there any relevant groups that were not represented in the evaluation dataset?

property idealDatasetCharacteristics: None | List[str]: Ideal characteristics of an evaluation dataset for this MLModel

property recommendations: None | str: Recommendations on where this MLModel should be used.

class datahub.metadata.schema_classes.ChangeAuditStampsClass(created=None, lastModified=None, deleted=None)

Bases: DictWrapper

Data captured on a resource/association/sub-resource level giving insight into when that resource/association/sub-resource moved into various lifecycle stages, and who acted to move it into those lifecycle stages. The recommended best practice is to include this record in your record schema, and annotate its fields as @readOnly in your resource. See linkedin/rest.li

Parameters:

created (Optional[AuditStampClass])
lastModified (Optional[AuditStampClass])
deleted (Optional[AuditStampClass])

property created: AuditStampClass: An AuditStamp corresponding to the creation of this resource/association/sub-resource. A value of 0 for time indicates missing data.

property deleted: None | AuditStampClass: An AuditStamp corresponding to the deletion of this resource/association/sub-resource. Logically, deleted MUST have a later timestamp than creation. It may or may not have the same time as lastModified depending upon the resource/association/sub-resource semantics.

property lastModified: AuditStampClass: An AuditStamp corresponding to the last modification of this resource/association/sub-resource. If no modification has happened since creation, lastModified should be the same as created. A value of 0 for time indicates missing data.

class datahub.metadata.schema_classes.ChangeTypeClass

Bases: object

Descriptor for a change action

CREATE = 'CREATE'

DELETE = 'DELETE'

PATCH = 'PATCH'

RESTATE = 'RESTATE'

UPDATE = 'UPDATE'

UPSERT = 'UPSERT'

class datahub.metadata.schema_classes.ChartCellClass(cellId, changeAuditStamps, cellTitle=None)

Bases: DictWrapper

Chart cell in a notebook, which will present content in chart format

Parameters:

cellId (str)
changeAuditStamps (ChangeAuditStampsClass)
cellTitle (Optional[str])

property cellId: str: Unique id for the cell. This id should be globally unique for a Notebook tool even when there are multiple deployments of it. As an example, Notebook URL could be used here for QueryBook such as ‘querybook.com/notebook/773/?cellId=1234’

property cellTitle: None | str: Title of the cell

property changeAuditStamps: ChangeAuditStampsClass: Captures information about who created/last modified/deleted this Notebook cell and when

class datahub.metadata.schema_classes.ChartInfoClass(title, description, lastModified, customProperties=None, externalUrl=None, chartUrl=None, inputs=None, inputEdges=None, type=None, access=None, lastRefreshed=None)

Bases: _Aspect

Information about a chart

Parameters:

title (str)
description (str)
lastModified (ChangeAuditStampsClass)
customProperties (Optional[Dict[str, str]])
externalUrl (Optional[str])
chartUrl (Optional[str])
inputs (Optional[List[str]])
inputEdges (Optional[List[EdgeClass]])
type (Union[None, str, ChartTypeClass])
access (Union[None, str, AccessLevelClass])
lastRefreshed (Optional[int])

property access: None | str | AccessLevelClass: Access level for the chart

property chartUrl: None | str: URL for the chart. This could be used as an external link on DataHub to allow users access/view the chart

property customProperties: Dict[str, str]: Custom property bag.

property description: str: Detailed description about the chart

property externalUrl: None | str: URL where the reference exist

property inputEdges: None | List[EdgeClass]: Data sources for the chart

property inputs: None | List[str]: Data sources for the chart Deprecated! Use inputEdges instead.

property lastModified: ChangeAuditStampsClass: Captures information about who created/last modified/deleted this chart and when

property lastRefreshed: None | int: The time when this chart last refreshed

property title: str: Title of the chart

property type: None | str | ChartTypeClass: Type of the chart

class datahub.metadata.schema_classes.ChartKeyClass(dashboardTool, chartId)

Bases: _Aspect

Key for a Chart

Parameters:

dashboardTool (str)
chartId (str)

property chartId: str: Unique id for the chart. This id should be globally unique for a dashboarding tool even when there are multiple deployments of it. As an example, chart URL could be used here for Looker such as ‘looker.linkedin.com/looks/1234’

property dashboardTool: str: The name of the dashboard tool such as looker, redash etc.

class datahub.metadata.schema_classes.ChartQueryClass(rawQuery, type)

Bases: _Aspect

Information for chart query which is used for getting data of the chart

Parameters:

rawQuery (str)
type (Union[str, ChartQueryTypeClass])

property rawQuery: str: Raw query to build a chart from input datasets

property type: str | ChartQueryTypeClass: Chart query type

class datahub.metadata.schema_classes.ChartQueryTypeClass

Bases: object

LOOKML = 'LOOKML'

SQL = 'SQL'

class datahub.metadata.schema_classes.ChartSnapshotClass(urn, aspects)

Bases: DictWrapper

A metadata snapshot for a specific Chart entity.

Parameters:

urn (str)
aspects (List[Union[ChartKeyClass, ChartInfoClass, ChartQueryClass, EditableChartPropertiesClass, OwnershipClass, StatusClass, GlobalTagsClass, BrowsePathsClass, GlossaryTermsClass, InstitutionalMemoryClass, DataPlatformInstanceClass, BrowsePathsV2Class]])

property aspects: List[ChartKeyClass | ChartInfoClass | ChartQueryClass | EditableChartPropertiesClass | OwnershipClass | StatusClass | GlobalTagsClass | BrowsePathsClass | GlossaryTermsClass | InstitutionalMemoryClass | DataPlatformInstanceClass | BrowsePathsV2Class]: The list of metadata aspects associated with the chart. Depending on the use case, this can either be all, or a selection, of supported aspects.

property urn: str: URN for the entity the metadata snapshot is associated with.

class datahub.metadata.schema_classes.ChartTypeClass

Bases: object

The various types of charts

AREA = 'AREA'

BAR = 'BAR'

BOX_PLOT = 'BOX_PLOT'

COHORT = 'COHORT'

HISTOGRAM = 'HISTOGRAM'

LINE = 'LINE'

PIE = 'PIE'

SCATTER = 'SCATTER'

TABLE = 'TABLE'

TEXT = 'TEXT'

WORD_CLOUD = 'WORD_CLOUD'

class datahub.metadata.schema_classes.ChartUsageStatisticsClass(timestampMillis, eventGranularity=None, partitionSpec=None, messageId=None, viewsCount=None, uniqueUserCount=None, userCounts=None)

Bases: _Aspect

Experimental (Subject to breaking change) – Stats corresponding to chart’s usage.

If this aspect represents the latest snapshot of the statistics about a Chart, the eventGranularity field should be null. If this aspect represents a bucketed window of usage statistics (e.g. over a day), then the eventGranularity field should be set accordingly.

Parameters:

timestampMillis (int)
eventGranularity (Optional[TimeWindowSizeClass])
partitionSpec (Optional[PartitionSpecClass])
messageId (Optional[str])
viewsCount (Optional[int])
uniqueUserCount (Optional[int])
userCounts (Optional[List[ChartUserUsageCountsClass]])

ASPECT_TYPE: ClassVar[str] = 'timeseries'

property eventGranularity: None | TimeWindowSizeClass: Granularity of the event if applicable

property messageId: None | str: The optional messageId, if provided serves as a custom user-defined unique identifier for an aspect value.

property partitionSpec: PartitionSpecClass | None: The optional partition specification.

property timestampMillis: int: The event timestamp field as epoch at UTC in milli seconds.

property uniqueUserCount: None | int: Unique user count

property userCounts: None | List[ChartUserUsageCountsClass]: Users within this bucket, with frequency counts

property viewsCount: None | int: The total number of times chart has been viewed

class datahub.metadata.schema_classes.ChartUserUsageCountsClass(user, viewsCount=None)

Bases: DictWrapper

Records a single user’s usage counts for a given resource

Parameters:

user (str)
viewsCount (Optional[int])

property user: str: The unique id of the user.

property viewsCount: None | int: The number of times the user has viewed the chart

class datahub.metadata.schema_classes.ConditionClass

Bases: object

The matching condition in a filter criterion

CONTAIN = 'CONTAIN'

END_WITH = 'END_WITH'

EQUAL = 'EQUAL'

EXISTS = 'EXISTS'

GREATER_THAN = 'GREATER_THAN'

GREATER_THAN_OR_EQUAL_TO = 'GREATER_THAN_OR_EQUAL_TO'

IN = 'IN'

IS_NULL = 'IS_NULL'

LESS_THAN = 'LESS_THAN'

LESS_THAN_OR_EQUAL_TO = 'LESS_THAN_OR_EQUAL_TO'

START_WITH = 'START_WITH'

class datahub.metadata.schema_classes.ConjunctiveCriterionClass(and_)

Bases: DictWrapper

A list of criterion and’d together.

Parameters:: and_ (List[CriterionClass])

property and_: List[CriterionClass]: A list of and criteria the filter applies to the query

class datahub.metadata.schema_classes.ContainerClass(container)

Bases: _Aspect

Link from an asset to its parent container

Parameters:: container (str)

property container: str: The parent container of an asset

class datahub.metadata.schema_classes.ContainerKeyClass(guid=None)

Bases: _Aspect

Key for an Asset Container

Parameters:: guid (Optional[str])

property guid: None | str: Unique guid for container

class datahub.metadata.schema_classes.ContainerPropertiesClass(name, customProperties=None, externalUrl=None, qualifiedName=None, description=None, created=None, lastModified=None)

Bases: _Aspect

Information about a Asset Container as received from a 3rd party source system

Parameters:

name (str)
customProperties (Optional[Dict[str, str]])
externalUrl (Optional[str])
qualifiedName (Optional[str])
description (Optional[str])
created (Optional[TimeStampClass])
lastModified (Optional[TimeStampClass])

property created: None | TimeStampClass: A timestamp documenting when the asset was created in the source Data Platform (not on DataHub)

property customProperties: Dict[str, str]: Custom property bag.

property description: None | str: Description of the Asset Container as it exists inside a source system

property externalUrl: None | str: URL where the reference exist

property lastModified: None | TimeStampClass: A timestamp documenting when the asset was last modified in the source Data Platform (not on DataHub)

property name: str: Display name of the Asset Container

property qualifiedName: None | str: Fully-qualified name of the Container

class datahub.metadata.schema_classes.CorpGroupEditableInfoClass(description=None, pictureLink=None, slack=None, email=None)

Bases: _Aspect

Group information that can be edited from UI

Parameters:

description (Optional[str])
pictureLink (Optional[str])
slack (Optional[str])
email (Optional[str])

property description: None | str: A description of the group

property email: None | str: Email address to contact the group

property pictureLink: str: A URL which points to a picture which user wants to set as the photo for the group

property slack: None | str: Slack channel for the group

class datahub.metadata.schema_classes.CorpGroupInfoClass(admins, members, groups, displayName=None, email=None, description=None, slack=None, created=None)

Bases: _Aspect

Information about a Corp Group ingested from a third party source

Parameters:

admins (List[str])
members (List[str])
groups (List[str])
displayName (Optional[str])
email (Optional[str])
description (Optional[str])
slack (Optional[str])
created (Optional[AuditStampClass])

property admins: List[str]: owners of this group Deprecated! Replaced by Ownership aspect.

property created: None | AuditStampClass: Created Audit stamp

property description: None | str: A description of the group.

property displayName: None | str: The name of the group.

property email: None | str: email of this group

property groups: List[str]: List of groups in this group. Deprecated! This field is unused.

property members: List[str]: List of ldap urn in this group. Deprecated! Replaced by GroupMembership aspect.

property slack: None | str: Slack channel for the group

class datahub.metadata.schema_classes.CorpGroupKeyClass(name)

Bases: _Aspect

Key for a CorpGroup

Parameters:: name (str)

property name: str: The URL-encoded name of the AD/LDAP group. Serves as a globally unique identifier within DataHub.

class datahub.metadata.schema_classes.CorpGroupSnapshotClass(urn, aspects)

Bases: DictWrapper

A metadata snapshot for a specific CorpGroup entity.

Parameters:

urn (str)
aspects (List[Union[CorpGroupKeyClass, CorpGroupInfoClass, GlobalTagsClass, StatusClass]])

property aspects: List[CorpGroupKeyClass | CorpGroupInfoClass | GlobalTagsClass | StatusClass]: The list of metadata aspects associated with the LdapUser. Depending on the use case, this can either be all, or a selection, of supported aspects.

property urn: str: URN for the entity the metadata snapshot is associated with.

class datahub.metadata.schema_classes.CorpUserAppearanceSettingsClass(showSimplifiedHomepage=None)

Bases: DictWrapper

Settings for a user around the appearance of their DataHub UI

Parameters:: showSimplifiedHomepage (Optional[bool])

property showSimplifiedHomepage: None | bool: Flag whether the user should see a homepage with only datasets, charts and dashboards. Intended for users who have less operational use cases for the datahub tool.

class datahub.metadata.schema_classes.CorpUserCredentialsClass(salt, hashedPassword, passwordResetToken=None, passwordResetTokenExpirationTimeMillis=None)

Bases: _Aspect

Corp user credentials

Parameters:

salt (str)
hashedPassword (str)
passwordResetToken (Optional[str])
passwordResetTokenExpirationTimeMillis (Optional[int])

property hashedPassword: str: Hashed password generated by concatenating salt and password, then hashing

property passwordResetToken: None | str: Optional token needed to reset a user’s password. Can only be set by the admin.

property passwordResetTokenExpirationTimeMillis: None | int: When the password reset token expires.

property salt: str: Salt used to hash password

class datahub.metadata.schema_classes.CorpUserEditableInfoClass(aboutMe=None, teams=None, skills=None, pictureLink=None, displayName=None, title=None, slack=None, phone=None, email=None)

Bases: _Aspect

Linkedin corp user information that can be edited from UI

Parameters:

aboutMe (Optional[str])
teams (Optional[List[str]])
skills (Optional[List[str]])
pictureLink (Optional[str])
displayName (Optional[str])
title (Optional[str])
slack (Optional[str])
phone (Optional[str])
email (Optional[str])

property aboutMe: None | str: About me section of the user

property displayName: None | str: DataHub-native display name

property email: None | str: Email address to contact the user

property phone: None | str: Phone number to contact the user

property pictureLink: str: A URL which points to a picture which user wants to set as a profile photo

property skills: List[str]: Skills that the user possesses e.g. Machine Learning

property slack: None | str: Slack handle for the user

property teams: List[str]: Teams that the user belongs to e.g. Metadata

property title: None | str: DataHub-native Title, e.g. ‘Software Engineer’

class datahub.metadata.schema_classes.CorpUserInfoClass(active, customProperties=None, displayName=None, email=None, title=None, managerUrn=None, departmentId=None, departmentName=None, firstName=None, lastName=None, fullName=None, countryCode=None)

Bases: _Aspect

Linkedin corp user information

Parameters:

active (bool)
customProperties (Optional[Dict[str, str]])
displayName (Optional[str])
email (Optional[str])
title (Optional[str])
managerUrn (Optional[str])
departmentId (Optional[int])
departmentName (Optional[str])
firstName (Optional[str])
lastName (Optional[str])
fullName (Optional[str])
countryCode (Optional[str])

property active: bool

//iwww.corp.linkedin.com/wiki/cf/display/GTSD/Accessing+Active+Directory+via+LDAP+tools

Type:: Deprecated! Use CorpUserStatus instead. Whether the corpUser is active, ref
Type:: https

property countryCode: None | str: two uppercase letters country code. e.g. US

property customProperties: Dict[str, str]: Custom property bag.

property departmentId: None | int: department id this user belong to

property departmentName: None | str: department name this user belong to

property displayName: None | str: displayName of this user , e.g. Hang Zhang(DataHQ)

property email: None | str: email address of this user

property firstName: None | str: first name of this user

property fullName: None | str: Common name of this user, format is firstName + lastName (split by a whitespace)

property lastName: None | str: last name of this user

property managerUrn: None | str: direct manager of this user

property title: None | str: title of this user

class datahub.metadata.schema_classes.CorpUserKeyClass(username)

Bases: _Aspect

Key for a CorpUser

Parameters:: username (str)

property username: str: The name of the AD/LDAP user.

class datahub.metadata.schema_classes.CorpUserSettingsClass(appearance, views=None)

Bases: _Aspect

Settings that a user can customize through the datahub ui

Parameters:

appearance (CorpUserAppearanceSettingsClass)
views (Optional[CorpUserViewsSettingsClass])

property appearance: CorpUserAppearanceSettingsClass: Settings for a user around the appearance of their DataHub U

property views: None | CorpUserViewsSettingsClass: User preferences for the Views feature.

class datahub.metadata.schema_classes.CorpUserSnapshotClass(urn, aspects)

Bases: DictWrapper

A metadata snapshot for a specific CorpUser entity.

Parameters:

urn (str)
aspects (List[Union[CorpUserKeyClass, CorpUserInfoClass, CorpUserEditableInfoClass, CorpUserStatusClass, GroupMembershipClass, GlobalTagsClass, StatusClass]])

property aspects: List[CorpUserKeyClass | CorpUserInfoClass | CorpUserEditableInfoClass | CorpUserStatusClass | GroupMembershipClass | GlobalTagsClass | StatusClass]: The list of metadata aspects associated with the CorpUser. Depending on the use case, this can either be all, or a selection, of supported aspects.

property urn: str: URN for the entity the metadata snapshot is associated with.

class datahub.metadata.schema_classes.CorpUserStatusClass(status, lastModified)

Bases: _Aspect

The status of the user, e.g. provisioned, active, suspended, etc.

Parameters:

status (str)
lastModified (AuditStampClass)

property lastModified: AuditStampClass: Audit stamp containing who last modified the status and when.

property status: str: Status of the user, e.g. PROVISIONED / ACTIVE / SUSPENDED

class datahub.metadata.schema_classes.CorpUserViewsSettingsClass(defaultView=None)

Bases: DictWrapper

Settings related to the ‘Views’ feature.

Parameters:: defaultView (Optional[str])

property defaultView: None | str: The default View which is selected for the user. If none is chosen, then this value will be left blank.

class datahub.metadata.schema_classes.CostClass(costType, cost)

Bases: _Aspect

Parameters:

costType (Union[str, CostTypeClass])
cost (CostCostClass)

property cost: CostCostClass

property costType: str | CostTypeClass

class datahub.metadata.schema_classes.CostCostClass(fieldDiscriminator, costId=None, costCode=None)

Bases: DictWrapper

Parameters:

fieldDiscriminator (Union[str, CostCostDiscriminatorClass])
costId (Optional[float])
costCode (Optional[str])

property costCode: None | str

property costId: None | float

property fieldDiscriminator: str | CostCostDiscriminatorClass: Contains the name of the field that has its value set.

class datahub.metadata.schema_classes.CostCostDiscriminatorClass

Bases: object

costCode = 'costCode'

costId = 'costId'

class datahub.metadata.schema_classes.CostTypeClass

Bases: object

Type of Cost Code

ORG_COST_TYPE = 'ORG_COST_TYPE'

class datahub.metadata.schema_classes.CriterionClass(field, value, values=None, condition=None, negated=None)

Bases: DictWrapper

A criterion for matching a field with given value

Parameters:

field (str)
value (str)
values (Optional[List[str]])
condition (Union[str, ConditionClass, None])
negated (Optional[bool])

property condition: str | ConditionClass: The condition for the criterion, e.g. EQUAL, START_WITH

property field: str: The name of the field that the criterion refers to

property negated: bool: Whether the condition should be negated

property value: str: The value of the intended field

property values: List[str]: Values. one of which the intended field should match Note, if values is set, the above “value” field will be ignored

class datahub.metadata.schema_classes.DashboardInfoClass(title, description, lastModified, customProperties=None, externalUrl=None, charts=None, chartEdges=None, datasets=None, datasetEdges=None, dashboardUrl=None, access=None, lastRefreshed=None)

Bases: _Aspect

Information about a dashboard

Parameters:

title (str)
description (str)
lastModified (ChangeAuditStampsClass)
customProperties (Optional[Dict[str, str]])
externalUrl (Optional[str])
charts (Optional[List[str]])
chartEdges (Optional[List[EdgeClass]])
datasets (Optional[List[str]])
datasetEdges (Optional[List[EdgeClass]])
dashboardUrl (Optional[str])
access (Union[None, str, AccessLevelClass])
lastRefreshed (Optional[int])

property access: None | str | AccessLevelClass: Access level for the dashboard

property chartEdges: None | List[EdgeClass]: Charts in a dashboard

property charts: List[str]: Charts in a dashboard Deprecated! Use chartEdges instead.

property customProperties: Dict[str, str]: Custom property bag.

property dashboardUrl: None | str: URL for the dashboard. This could be used as an external link on DataHub to allow users access/view the dashboard

property datasetEdges: None | List[EdgeClass]: Datasets consumed by a dashboard

property datasets: List[str]: Datasets consumed by a dashboard Deprecated! Use datasetEdges instead.

property description: str: Detailed description about the dashboard

property externalUrl: None | str: URL where the reference exist

property lastModified: ChangeAuditStampsClass: Captures information about who created/last modified/deleted this dashboard and when

property lastRefreshed: None | int: The time when this dashboard last refreshed

property title: str: Title of the dashboard

class datahub.metadata.schema_classes.DashboardKeyClass(dashboardTool, dashboardId)

Bases: _Aspect

Key for a Dashboard

Parameters:

dashboardTool (str)
dashboardId (str)

property dashboardId: str: Unique id for the dashboard. This id should be globally unique for a dashboarding tool even when there are multiple deployments of it. As an example, dashboard URL could be used here for Looker such as ‘looker.linkedin.com/dashboards/1234’

property dashboardTool: str: The name of the dashboard tool such as looker, redash etc.

class datahub.metadata.schema_classes.DashboardSnapshotClass(urn, aspects)

Bases: DictWrapper

A metadata snapshot for a specific Dashboard entity.

Parameters:

urn (str)
aspects (List[Union[DashboardKeyClass, DashboardInfoClass, EditableDashboardPropertiesClass, OwnershipClass, StatusClass, GlobalTagsClass, BrowsePathsClass, GlossaryTermsClass, InstitutionalMemoryClass, DataPlatformInstanceClass, BrowsePathsV2Class]])

property aspects: List[DashboardKeyClass | DashboardInfoClass | EditableDashboardPropertiesClass | OwnershipClass | StatusClass | GlobalTagsClass | BrowsePathsClass | GlossaryTermsClass | InstitutionalMemoryClass | DataPlatformInstanceClass | BrowsePathsV2Class]: The list of metadata aspects associated with the dashboard. Depending on the use case, this can either be all, or a selection, of supported aspects.

property urn: str: URN for the entity the metadata snapshot is associated with.

class datahub.metadata.schema_classes.DashboardUsageStatisticsClass(timestampMillis, eventGranularity=None, partitionSpec=None, messageId=None, viewsCount=None, executionsCount=None, uniqueUserCount=None, userCounts=None, favoritesCount=None, lastViewedAt=None)

Bases: _Aspect

Experimental (Subject to breaking change) – Stats corresponding to dashboard’s usage.

If this aspect represents the latest snapshot of the statistics about a Dashboard, the eventGranularity field should be null. If this aspect represents a bucketed window of usage statistics (e.g. over a day), then the eventGranularity field should be set accordingly.

Parameters:

timestampMillis (int)
eventGranularity (Optional[TimeWindowSizeClass])
partitionSpec (Optional[PartitionSpecClass])
messageId (Optional[str])
viewsCount (Optional[int])
executionsCount (Optional[int])
uniqueUserCount (Optional[int])
userCounts (Optional[List[DashboardUserUsageCountsClass]])
favoritesCount (Optional[int])
lastViewedAt (Optional[int])

ASPECT_TYPE: ClassVar[str] = 'timeseries'

property eventGranularity: None | TimeWindowSizeClass: Granularity of the event if applicable

property executionsCount: None | int: The total number of dashboard executions (refreshes / syncs)

property favoritesCount: None | int: The total number of times that the dashboard has been favorited

property lastViewedAt: None | int

Last viewed at

This should not be set in cases where statistics are windowed.

property messageId: None | str: The optional messageId, if provided serves as a custom user-defined unique identifier for an aspect value.

property partitionSpec: PartitionSpecClass | None: The optional partition specification.

property timestampMillis: int: The event timestamp field as epoch at UTC in milli seconds.

property uniqueUserCount: None | int: Unique user count

property userCounts: None | List[DashboardUserUsageCountsClass]: Users within this bucket, with frequency counts

property viewsCount: None | int: The total number of times dashboard has been viewed

class datahub.metadata.schema_classes.DashboardUserUsageCountsClass(user, viewsCount=None, executionsCount=None, usageCount=None, userEmail=None)

Bases: DictWrapper

Records a single user’s usage counts for a given resource

Parameters:

user (str)
viewsCount (Optional[int])
executionsCount (Optional[int])
usageCount (Optional[int])
userEmail (Optional[str])

property executionsCount: None | int: The number of times the user has executed (refreshed) the dashboard

property usageCount: None | int: Normalized numeric metric representing user’s dashboard usage – the number of times the user executed or viewed the dashboard.

property user: str: The unique id of the user.

property userEmail: None | str: If user_email is set, we attempt to resolve the user’s urn upon ingest

property viewsCount: None | int: The number of times the user has viewed the dashboard

class datahub.metadata.schema_classes.DataContractKeyClass(id)

Bases: _Aspect

Key for a Data Contract

Parameters:: id (str)

property id: str: Unique id for the contract

class datahub.metadata.schema_classes.DataContractPropertiesClass(entity, schema=None, freshness=None, dataQuality=None, rawContract=None)

Bases: _Aspect

Information about a data contract

Parameters:

entity (str)
schema (Optional[List[SchemaContractClass]])
freshness (Optional[List[FreshnessContractClass]])
dataQuality (Optional[List[DataQualityContractClass]])
rawContract (Optional[str])

property dataQuality: None | List[DataQualityContractClass]: An optional set of Data Quality contracts, e.g. table and column level contract constraints.

property entity: str: The entity that this contract is associated with. Currently, we only support Dataset contracts, but in the future we may also support Data Product level contracts.

property freshness: None | List[FreshnessContractClass]: An optional set of FRESHNESS contracts. If this is a dataset contract, there will only be one.

property rawContract: None | str: YAML-formatted contract definition

property schema: None | List[SchemaContractClass]: An optional set of schema contracts. If this is a dataset contract, there will only be one.

class datahub.metadata.schema_classes.DataContractStateClass

Bases: object

ACTIVE = 'ACTIVE'

PENDING = 'PENDING'

class datahub.metadata.schema_classes.DataContractStatusClass(state, customProperties=None)

Bases: _Aspect

Information about the status of a data contract

Parameters:

state (Union[str, DataContractStateClass])
customProperties (Optional[Dict[str, str]])

property customProperties: Dict[str, str]: Custom property bag.

property state: str | DataContractStateClass: The latest state of the data contract

class datahub.metadata.schema_classes.DataFlowInfoClass(name, customProperties=None, externalUrl=None, description=None, project=None, created=None, lastModified=None)

Bases: _Aspect

Information about a Data processing flow

Parameters:

name (str)
customProperties (Optional[Dict[str, str]])
externalUrl (Optional[str])
description (Optional[str])
project (Optional[str])
created (Optional[TimeStampClass])
lastModified (Optional[TimeStampClass])

property created: None | TimeStampClass: A timestamp documenting when the asset was created in the source Data Platform (not on DataHub)

property customProperties: Dict[str, str]: Custom property bag.

property description: None | str: Flow description

property externalUrl: None | str: URL where the reference exist

property lastModified: None | TimeStampClass: A timestamp documenting when the asset was last modified in the source Data Platform (not on DataHub)

property name: str: Flow name

property project: None | str: Optional project/namespace associated with the flow

class datahub.metadata.schema_classes.DataFlowKeyClass(orchestrator, flowId, cluster)

Bases: _Aspect

Key for a Data Flow

Parameters:

orchestrator (str)
flowId (str)
cluster (str)

property cluster: str: Cluster where the flow is executed

property flowId: str: Unique Identifier of the data flow

property orchestrator: str: Workflow manager like azkaban, airflow which orchestrates the flow

class datahub.metadata.schema_classes.DataFlowSnapshotClass(urn, aspects)

Bases: DictWrapper

A metadata snapshot for a specific DataFlow entity.

Parameters:

urn (str)
aspects (List[Union[DataFlowKeyClass, DataFlowInfoClass, EditableDataFlowPropertiesClass, OwnershipClass, StatusClass, GlobalTagsClass, BrowsePathsClass, GlossaryTermsClass, InstitutionalMemoryClass, DataPlatformInstanceClass, BrowsePathsV2Class]])

property aspects: List[DataFlowKeyClass | DataFlowInfoClass | EditableDataFlowPropertiesClass | OwnershipClass | StatusClass | GlobalTagsClass | BrowsePathsClass | GlossaryTermsClass | InstitutionalMemoryClass | DataPlatformInstanceClass | BrowsePathsV2Class]: The list of metadata aspects associated with the data flow. Depending on the use case, this can either be all, or a selection, of supported aspects.

property urn: str: URN for the entity the metadata snapshot is associated with.

class datahub.metadata.schema_classes.DataHubAccessTokenInfoClass(name, actorUrn, ownerUrn, createdAt, expiresAt=None, description=None)

Bases: _Aspect

Information about a DataHub Access Token

Parameters:

name (str)
actorUrn (str)
ownerUrn (str)
createdAt (int)
expiresAt (Optional[int])
description (Optional[str])

property actorUrn: str: Urn of the actor to which this access token belongs to.

property createdAt: int: When the token was created.

property description: None | str: Description of the token if defined.

property expiresAt: None | int: When the token expires.

property name: str: User defined name for the access token if defined.

property ownerUrn: str: Urn of the actor which created this access token.

class datahub.metadata.schema_classes.DataHubAccessTokenKeyClass(id)

Bases: _Aspect

Key for a DataHub Access Token

Parameters:: id (str)

property id: str: Access token’s SHA-256 hashed JWT signature

class datahub.metadata.schema_classes.DataHubActorFilterClass(users=None, groups=None, resourceOwners=None, resourceOwnersTypes=None, allUsers=None, allGroups=None, roles=None)

Bases: DictWrapper

Information used to filter DataHub actors.

Parameters:

users (Optional[List[str]])
groups (Optional[List[str]])
resourceOwners (Optional[bool])
resourceOwnersTypes (Optional[List[str]])
allUsers (Optional[bool])
allGroups (Optional[bool])
roles (Optional[List[str]])

property allGroups: bool: Whether the filter should apply to all groups.

property allUsers: bool: Whether the filter should apply to all users.

property groups: None | List[str]: A specific set of groups to apply the policy to (disjunctive)

property resourceOwners: bool: Whether the filter should return true for owners of a particular resource. Only applies to policies of type ‘Metadata’, which have a resource associated with them.

property resourceOwnersTypes: None | List[str]: Define type of ownership for the policy

property roles: None | List[str]: A specific set of roles to apply the policy to (disjunctive).

property users: None | List[str]: A specific set of users to apply the policy to (disjunctive)

class datahub.metadata.schema_classes.DataHubIngestionSourceConfigClass(recipe, version=None, executorId=None, debugMode=None, extraArgs=None)

Bases: DictWrapper

Parameters:

recipe (str)
version (Optional[str])
executorId (Optional[str])
debugMode (Optional[bool])
extraArgs (Optional[Dict[str, str]])

property debugMode: None | bool: Whether or not to run this ingestion source in debug mode

property executorId: None | str: The id of the executor to use to execute the ingestion run

property extraArgs: None | Dict[str, str]: Extra arguments for the ingestion run.

property recipe: str: The JSON recipe to use for ingestion

property version: None | str: The PyPI version of the datahub CLI to use when executing a recipe

class datahub.metadata.schema_classes.DataHubIngestionSourceInfoClass(name, type, config, platform=None, schedule=None)

Bases: _Aspect

Info about a DataHub ingestion source

Parameters:

name (str)
type (str)
config (DataHubIngestionSourceConfigClass)
platform (Optional[str])
schedule (Optional[DataHubIngestionSourceScheduleClass])

property config: DataHubIngestionSourceConfigClass: Parameters associated with the Ingestion Source

property name: str: The display name of the ingestion source

property platform: None | str: Data Platform URN associated with the source

property schedule: None | DataHubIngestionSourceScheduleClass: The schedule on which the ingestion source is executed

property type: str: The type of the source itself, e.g. mysql, bigquery, bigquery-usage. Should match the recipe.

class datahub.metadata.schema_classes.DataHubIngestionSourceKeyClass(id)

Bases: _Aspect

Key for a DataHub ingestion source

Parameters:: id (str)

property id: str: A unique id for the Ingestion Source, either generated or provided

class datahub.metadata.schema_classes.DataHubIngestionSourceScheduleClass(interval, timezone)

Bases: DictWrapper

The schedule associated with an ingestion source.

Parameters:

interval (str)
timezone (str)

property interval: str: A cron-formatted execution interval, as a cron string, e.g. * * * * *

property timezone: str: Timezone in which the cron interval applies, e.g. America/Los Angeles

class datahub.metadata.schema_classes.DataHubPolicyInfoClass(displayName, description, type, state, privileges, actors, resources=None, editable=None, lastUpdatedTimestamp=None)

Bases: _Aspect

Information about a DataHub (UI) access policy.

Parameters:

displayName (str)
description (str)
type (str)
state (str)
privileges (List[str])
actors (DataHubActorFilterClass)
resources (Optional[DataHubResourceFilterClass])
editable (Optional[bool])
lastUpdatedTimestamp (Optional[int])

property actors: DataHubActorFilterClass: The actors that the policy applies to.

property description: str: Description of the Policy

property displayName: str: Display name of the Policy

property editable: bool: Whether the policy should be editable via the UI

property lastUpdatedTimestamp: None | int: Timestamp when the policy was last updated

property privileges: List[str]: The privileges that the policy grants.

property resources: None | DataHubResourceFilterClass: The resource that the policy applies to. Not required for some ‘Platform’ privileges.

property state: str: The state of policy, ACTIVE or INACTIVE

property type: str: The type of policy

class datahub.metadata.schema_classes.DataHubPolicyKeyClass(id)

Bases: _Aspect

Key for a DataHub Policy

Parameters:: id (str)

property id: str: A unique id for the DataHub access policy record. Generated on the server side at policy creation time.

class datahub.metadata.schema_classes.DataHubPolicySnapshotClass(urn, aspects)

Bases: DictWrapper

A metadata snapshot for DataHub Access Policy data.

Parameters:

urn (str)
aspects (List[Union[DataHubPolicyKeyClass, DataHubPolicyInfoClass]])

property aspects: List[DataHubPolicyKeyClass | DataHubPolicyInfoClass]: The list of metadata aspects associated with the DataHub access policy.

property urn: str: URN for the entity the metadata snapshot is associated with.

class datahub.metadata.schema_classes.DataHubResourceFilterClass(type=None, resources=None, allResources=None, filter=None)

Bases: DictWrapper

Information used to filter DataHub resource.

Parameters:

type (Optional[str])
resources (Optional[List[str]])
allResources (Optional[bool])
filter (Optional[PolicyMatchFilterClass])

property allResources: bool: Whether the policy should be applied to all assets matching the filter.

property filter: None | PolicyMatchFilterClass: Filter to apply privileges to

property resources: None | List[str]: A specific set of resources to apply the policy to, e.g. asset urns

property type: None | str: The type of resource that the policy applies to. This will most often be a data asset entity name, for example ‘dataset’. It is not strictly required because in the future we will want to support filtering a resource by domain, as well.

class datahub.metadata.schema_classes.DataHubRetentionConfigClass(retention)

Bases: _Aspect

Parameters:: retention (RetentionClass)

property retention: RetentionClass

class datahub.metadata.schema_classes.DataHubRetentionKeyClass(entityName, aspectName)

Bases: _Aspect

Key for a DataHub Retention

Parameters:

entityName (str)
aspectName (str)

property aspectName: str: Aspect name to apply retention to. * (or empty) for applying defaults.

property entityName: str: Entity name to apply retention to. * (or empty) for applying defaults.

class datahub.metadata.schema_classes.DataHubRetentionSnapshotClass(urn, aspects)

Bases: DictWrapper

A metadata snapshot for DataHub Access Policy data.

Parameters:

urn (str)
aspects (List[Union[DataHubRetentionKeyClass, DataHubRetentionConfigClass]])

property aspects: List[DataHubRetentionKeyClass | DataHubRetentionConfigClass]: The list of metadata aspects associated with the DataHub access policy.

property urn: str: URN for the entity the metadata snapshot is associated with.

class datahub.metadata.schema_classes.DataHubRoleInfoClass(name, description, editable=None)

Bases: _Aspect

Information about a DataHub Role.

Parameters:

name (str)
description (str)
editable (Optional[bool])

property description: str: Description of the Role

property editable: bool: Whether the role should be editable via the UI

property name: str: Name of the Role

class datahub.metadata.schema_classes.DataHubRoleKeyClass(id)

Bases: _Aspect

Key for a DataHub Role

Parameters:: id (str)

property id: str: A unique id for the DataHub role record. Generated on the server side at role creation time.

class datahub.metadata.schema_classes.DataHubSecretKeyClass(id)

Bases: _Aspect

Key for a DataHub Secret

Parameters:: id (str)

property id: str: A unique id for the Secret

class datahub.metadata.schema_classes.DataHubSecretValueClass(name, value, description=None, created=None)

Bases: _Aspect

The value of a DataHub Secret

Parameters:

name (str)
value (str)
description (Optional[str])
created (Optional[AuditStampClass])

property created: None | AuditStampClass: Created Audit stamp

property description: None | str: Description of the secret

property name: str: The display name for the secret

property value: str: The AES-encrypted value of the DataHub secret.

class datahub.metadata.schema_classes.DataHubStepStateKeyClass(id)

Bases: _Aspect

Key for a DataHub Step State

Parameters:: id (str)

property id: str: A unique id for the state

class datahub.metadata.schema_classes.DataHubStepStatePropertiesClass(lastModified, properties=None)

Bases: _Aspect

The properties associated with a DataHub step state

Parameters:

lastModified (AuditStampClass)
properties (Optional[Dict[str, str]])

property lastModified: AuditStampClass: Audit stamp describing the last person to update it.

property properties: Dict[str, str]: Description of the secret

class datahub.metadata.schema_classes.DataHubUpgradeKeyClass(id)

Bases: _Aspect

Key for a DataHubUpgrade

Parameters:: id (str)

property id: str

class datahub.metadata.schema_classes.DataHubUpgradeRequestClass(timestampMs, version)

Bases: _Aspect

Information collected when kicking off a DataHubUpgrade

Parameters:

timestampMs (int)
version (str)

property timestampMs: int: Timestamp when we started this DataHubUpgrade

property version: str: Version of this upgrade

class datahub.metadata.schema_classes.DataHubUpgradeResultClass(timestampMs, result=None)

Bases: _Aspect

Information collected when a DataHubUpgrade successfully finishes

Parameters:

timestampMs (int)
result (Optional[Dict[str, str]])

property result: None | Dict[str, str]: Result map to place helpful information about this upgrade job

property timestampMs: int: Timestamp when we started this DataHubUpgrade

class datahub.metadata.schema_classes.DataHubViewDefinitionClass(entityTypes, filter)

Bases: DictWrapper

A View definition.

Parameters:

entityTypes (List[str])
filter (FilterClass)

property entityTypes: List[str]: The Entity Types in the scope of the View.

property filter: FilterClass: The filter criteria, which represents the view itself

class datahub.metadata.schema_classes.DataHubViewInfoClass(name, type, definition, created, lastModified, description=None)

Bases: _Aspect

Information about a DataHub View. – TODO: Understand whether an entity type filter is required.

Parameters:

name (str)
type (Union[str, DataHubViewTypeClass])
definition (DataHubViewDefinitionClass)
created (AuditStampClass)
lastModified (AuditStampClass)
description (Optional[str])

property created: AuditStampClass: Audit stamp capturing the time and actor who created the View.

property definition: DataHubViewDefinitionClass: The view itself

property description: None | str: Description of the view

property lastModified: AuditStampClass: Audit stamp capturing the time and actor who last modified the View.

property name: str: The name of the View

property type: str | DataHubViewTypeClass: The type of View

class datahub.metadata.schema_classes.DataHubViewKeyClass(id)

Bases: _Aspect

Key for a DataHub View

Parameters:: id (str)

property id: str: A unique id for the View

class datahub.metadata.schema_classes.DataHubViewTypeClass

Bases: object

GLOBAL = 'GLOBAL'

PERSONAL = 'PERSONAL'

class datahub.metadata.schema_classes.DataJobInfoClass(name, type, customProperties=None, externalUrl=None, description=None, flowUrn=None, created=None, lastModified=None, status=None)

Bases: _Aspect

Information about a Data processing job

Parameters:

name (str)
type (Union[str, AzkabanJobTypeClass])
customProperties (Optional[Dict[str, str]])
externalUrl (Optional[str])
description (Optional[str])
flowUrn (Optional[str])
created (Optional[TimeStampClass])
lastModified (Optional[TimeStampClass])
status (Union[None, str, JobStatusClass])

property created: None | TimeStampClass: A timestamp documenting when the asset was created in the source Data Platform (not on DataHub)

property customProperties: Dict[str, str]: Custom property bag.

property description: None | str: Job description

property externalUrl: None | str: URL where the reference exist

property flowUrn: None | str: DataFlow urn that this job is part of

property lastModified: None | TimeStampClass: A timestamp documenting when the asset was last modified in the source Data Platform (not on DataHub)

property name: str: Job name

property status: None | str | JobStatusClass: Status of the job - Deprecated for Data Process Instance model.

property type: str | AzkabanJobTypeClass: Datajob type NOTE*: AzkabanJobType is deprecated. Please use strings instead.

class datahub.metadata.schema_classes.DataJobInputOutputClass(inputDatasets, outputDatasets, inputDatasetEdges=None, outputDatasetEdges=None, inputDatajobs=None, inputDatajobEdges=None, inputDatasetFields=None, outputDatasetFields=None, fineGrainedLineages=None)

Bases: _Aspect

Information about the inputs and outputs of a Data processing job

Parameters:

inputDatasets (List[str])
outputDatasets (List[str])
inputDatasetEdges (Optional[List[EdgeClass]])
outputDatasetEdges (Optional[List[EdgeClass]])
inputDatajobs (Optional[List[str]])
inputDatajobEdges (Optional[List[EdgeClass]])
inputDatasetFields (Optional[List[str]])
outputDatasetFields (Optional[List[str]])
fineGrainedLineages (Optional[List[FineGrainedLineageClass]])

property fineGrainedLineages: None | List[FineGrainedLineageClass]: Fine-grained column-level lineages Not currently supported in the UI Use UpstreamLineage aspect for datasets to express Column Level Lineage for the UI

property inputDatajobEdges: None | List[EdgeClass]: Input datajobs that this data job depends on

property inputDatajobs: None | List[str]: Input datajobs that this data job depends on Deprecated! Use inputDatajobEdges instead.

property inputDatasetEdges: None | List[EdgeClass]: Input datasets consumed by the data job during processing

property inputDatasetFields: None | List[str]: Fields of the input datasets used by this job

property inputDatasets: List[str]: Input datasets consumed by the data job during processing Deprecated! Use inputDatasetEdges instead.

property outputDatasetEdges: None | List[EdgeClass]: Output datasets produced by the data job during processing

property outputDatasetFields: None | List[str]: Fields of the output datasets this job writes to

property outputDatasets: List[str]: Output datasets produced by the data job during processing Deprecated! Use outputDatasetEdges instead.

class datahub.metadata.schema_classes.DataJobKeyClass(flow, jobId)

Bases: _Aspect

Key for a Data Job

Parameters:

flow (str)
jobId (str)

property flow: str: Standardized data processing flow urn representing the flow for the job

property jobId: str: Unique Identifier of the data job

class datahub.metadata.schema_classes.DataJobSnapshotClass(urn, aspects)

Bases: DictWrapper

A metadata snapshot for a specific DataJob entity.

Parameters:

urn (str)
aspects (List[Union[DataJobKeyClass, DataJobInfoClass, DataJobInputOutputClass, EditableDataJobPropertiesClass, OwnershipClass, StatusClass, GlobalTagsClass, BrowsePathsClass, GlossaryTermsClass, InstitutionalMemoryClass, DataPlatformInstanceClass, BrowsePathsV2Class]])

property aspects: List[DataJobKeyClass | DataJobInfoClass | DataJobInputOutputClass | EditableDataJobPropertiesClass | OwnershipClass | StatusClass | GlobalTagsClass | BrowsePathsClass | GlossaryTermsClass | InstitutionalMemoryClass | DataPlatformInstanceClass | BrowsePathsV2Class]: The list of metadata aspects associated with the data job. Depending on the use case, this can either be all, or a selection, of supported aspects.

property urn: str: URN for the entity the metadata snapshot is associated with.

class datahub.metadata.schema_classes.DataPlatformInfoClass(name, type, datasetNameDelimiter, displayName=None, logoUrl=None)

Bases: _Aspect

Information about a data platform

Parameters:

name (str)
type (Union[str, PlatformTypeClass])
datasetNameDelimiter (str)
displayName (Optional[str])
logoUrl (Optional[str])

property datasetNameDelimiter: str: The delimiter in the dataset names on the data platform, e.g. ‘/’ for HDFS and ‘.’ for Oracle

property displayName: None | str: The name that will be used for displaying a platform type.

property logoUrl: None | str: The URL for a logo associated with the platform

property name: str: Name of the data platform

property type: str | PlatformTypeClass: Platform type this data platform describes

class datahub.metadata.schema_classes.DataPlatformInstanceClass(platform, instance=None)

Bases: _Aspect

The specific instance of the data platform that this entity belongs to

Parameters:

platform (str)
instance (Optional[str])

property instance: None | str: Instance of the data platform (e.g. db instance)

property platform: str: Data Platform

class datahub.metadata.schema_classes.DataPlatformInstanceKeyClass(platform, instance)

Bases: _Aspect

Key for a Dataset

Parameters:

platform (str)
instance (str)

property instance: str: Unique instance id

property platform: str: Data platform urn associated with the instance

class datahub.metadata.schema_classes.DataPlatformInstancePropertiesClass(customProperties=None, externalUrl=None, name=None, description=None)

Bases: _Aspect

Properties associated with a Data Platform Instance

Parameters:

customProperties (Optional[Dict[str, str]])
externalUrl (Optional[str])
name (Optional[str])
description (Optional[str])

property customProperties: Dict[str, str]: Custom property bag.

property description: None | str: Documentation of the Data Platform Instance

property externalUrl: None | str: URL where the reference exist

property name: None | str: Display name of the Data Platform Instance

class datahub.metadata.schema_classes.DataPlatformKeyClass(platformName)

Bases: _Aspect

Key for a Data Platform

Parameters:: platformName (str)

property platformName: str: Data platform name i.e. hdfs, oracle, espresso

class datahub.metadata.schema_classes.DataPlatformSnapshotClass(urn, aspects)

Bases: DictWrapper

A metadata snapshot for a specific dataplatform entity.

Parameters:

urn (str)
aspects (List[Union[DataPlatformKeyClass, DataPlatformInfoClass]])

property aspects: List[DataPlatformKeyClass | DataPlatformInfoClass]: The list of metadata aspects associated with the data platform. Depending on the use case, this can either be all, or a selection, of supported aspects.

property urn: str: URN for the entity the metadata snapshot is associated with.

class datahub.metadata.schema_classes.DataProcessInfoClass(inputs=None, outputs=None)

Bases: _Aspect

The inputs and outputs of this data process

Parameters:

inputs (Optional[List[str]])
outputs (Optional[List[str]])

property inputs: None | List[str]: the inputs of the data process

property outputs: None | List[str]: the outputs of the data process

class datahub.metadata.schema_classes.DataProcessInstanceInputClass(inputs)

Bases: _Aspect

Information about the inputs datasets of a Data process

Parameters:: inputs (List[str])

property inputs: List[str]: Input datasets to be consumed

class datahub.metadata.schema_classes.DataProcessInstanceKeyClass(id)

Bases: _Aspect

Key for an Asset DataProcessInstance

Parameters:: id (str)

property id: str: A unique id for the DataProcessInstance . Should be separate from the name used for displaying a DataProcessInstance.

class datahub.metadata.schema_classes.DataProcessInstanceOutputClass(outputs)

Bases: _Aspect

Information about the outputs of a Data process

Parameters:: outputs (List[str])

property outputs: List[str]: Output datasets to be produced

class datahub.metadata.schema_classes.DataProcessInstancePropertiesClass(name, created, customProperties=None, externalUrl=None, type=None)

Bases: _Aspect

The inputs and outputs of this data process

Parameters:

name (str)
created (AuditStampClass)
customProperties (Optional[Dict[str, str]])
externalUrl (Optional[str])
type (Union[None, str, DataProcessTypeClass])

property created: AuditStampClass: Audit stamp containing who reported the lineage and when

property customProperties: Dict[str, str]: Custom property bag.

property externalUrl: None | str: URL where the reference exist

property name: str: Process name

property type: None | str | DataProcessTypeClass: Process type

class datahub.metadata.schema_classes.DataProcessInstanceRelationshipsClass(upstreamInstances, parentTemplate=None, parentInstance=None)

Bases: _Aspect

Information about Data process relationships

Parameters:

upstreamInstances (List[str])
parentTemplate (Optional[str])
parentInstance (Optional[str])

property parentInstance: None | str: The parent DataProcessInstance where it belongs to. If it is a Airflow Task then it should belong to an Airflow Dag run as well which will be another DataProcessInstance

property parentTemplate: None | str: The parent entity whose run instance it is

property upstreamInstances: List[str]: Input DataProcessInstance which triggered this dataprocess instance

class datahub.metadata.schema_classes.DataProcessInstanceRunEventClass(timestampMillis, status, eventGranularity=None, partitionSpec=None, messageId=None, externalUrl=None, attempt=None, result=None)

Bases: _Aspect

An event representing the current status of data process run. DataProcessRunEvent should be used for reporting the status of a dataProcess’ run.

Parameters:

timestampMillis (int)
status (Union[str, DataProcessRunStatusClass])
eventGranularity (Optional[TimeWindowSizeClass])
partitionSpec (Optional[PartitionSpecClass])
messageId (Optional[str])
externalUrl (Optional[str])
attempt (Optional[int])
result (Optional[DataProcessInstanceRunResultClass])

ASPECT_TYPE: ClassVar[str] = 'timeseries'

property attempt: None | int: Return the try number that this Instance Run is in

property eventGranularity: None | TimeWindowSizeClass: Granularity of the event if applicable

property externalUrl: None | str: URL where the reference exist

property messageId: None | str: The optional messageId, if provided serves as a custom user-defined unique identifier for an aspect value.

property partitionSpec: PartitionSpecClass | None: The optional partition specification.

property result: None | DataProcessInstanceRunResultClass: The final result of the Data Processing run.

property status: str | DataProcessRunStatusClass

property timestampMillis: int: The event timestamp field as epoch at UTC in milli seconds.

class datahub.metadata.schema_classes.DataProcessInstanceRunResultClass(type, nativeResultType)

Bases: DictWrapper

Parameters:

type (Union[str, RunResultTypeClass])
nativeResultType (str)

property nativeResultType: str: It identifies the system where the native result comes from like Airflow, Azkaban, etc..

property type: str | RunResultTypeClass: The final result, e.g. SUCCESS, FAILURE, SKIPPED, or UP_FOR_RETRY.

class datahub.metadata.schema_classes.DataProcessKeyClass(name, orchestrator, origin)

Bases: _Aspect

Key for a Data Process

Parameters:

name (str)
orchestrator (str)
origin (Union[str, FabricTypeClass])

property name: str: Process name i.e. an ETL job name

property orchestrator: str: Standardized Orchestrator where data process is defined. TODO: Migrate towards something that can be validated like DataPlatform urn

property origin: str | FabricTypeClass: Fabric type where dataset belongs to or where it was generated.

class datahub.metadata.schema_classes.DataProcessRunStatusClass

Bases: object

COMPLETE = 'COMPLETE'

STARTED = 'STARTED'

class datahub.metadata.schema_classes.DataProcessSnapshotClass(urn, aspects)

Bases: DictWrapper

A metadata snapshot for a specific Data process entity.

Parameters:

urn (str)
aspects (List[Union[DataProcessKeyClass, OwnershipClass, DataProcessInfoClass, StatusClass]])

property aspects: List[DataProcessKeyClass | OwnershipClass | DataProcessInfoClass | StatusClass]: The list of metadata aspects associated with the data process. Depending on the use case, this can either be all, or a selection, of supported aspects.

property urn: str: URN for the entity the metadata snapshot is associated with.

class datahub.metadata.schema_classes.DataProcessTypeClass

Bases: object

BATCH_AD_HOC = 'BATCH_AD_HOC'

BATCH_SCHEDULED = 'BATCH_SCHEDULED'

STREAMING = 'STREAMING'

class datahub.metadata.schema_classes.DataProductAssociationClass(destinationUrn, sourceUrn=None, created=None, lastModified=None, properties=None)

Bases: DictWrapper

Represents an association of assets to a Data Product.

Parameters:

destinationUrn (str)
sourceUrn (Optional[str])
created (Optional[AuditStampClass])
lastModified (Optional[AuditStampClass])
properties (Optional[Dict[str, str]])

property created: None | AuditStampClass: Audit stamp containing who created this relationship edge and when

property destinationUrn: str: Urn of the destination of this relationship edge.

property lastModified: None | AuditStampClass: Audit stamp containing who last modified this relationship edge and when

property properties: None | Dict[str, str]: A generic properties bag that allows us to store specific information on this graph edge.

property sourceUrn: None | str: Urn of the source of this relationship edge. If not specified, assumed to be the entity that this aspect belongs to.

class datahub.metadata.schema_classes.DataProductKeyClass(id)

Bases: _Aspect

Key for a Query

Parameters:: id (str)

property id: str: A unique id for the Data Product.

class datahub.metadata.schema_classes.DataProductPropertiesClass(customProperties=None, externalUrl=None, name=None, description=None, assets=None)

Bases: _Aspect

The main properties of a Data Product

Parameters:

customProperties (Optional[Dict[str, str]])
externalUrl (Optional[str])
name (Optional[str])
description (Optional[str])
assets (Optional[List[DataProductAssociationClass]])

property assets: None | List[DataProductAssociationClass]: A list of assets that are part of this Data Product

property customProperties: Dict[str, str]: Custom property bag.

property description: None | str: Documentation of the dataset

property externalUrl: None | str: URL where the reference exist

property name: None | str: Display name of the Data Product

class datahub.metadata.schema_classes.DataQualityContractClass(assertion)

Bases: DictWrapper

A data quality contract pertaining to a physical data asset Data Quality contracts are used to make assertions about data quality metrics for a physical data asset

Parameters:: assertion (str)

property assertion: str: The assertion representing the Data Quality contract. E.g. a table or column-level assertion.

class datahub.metadata.schema_classes.DatahubIngestionCheckpointClass(timestampMillis, pipelineName, platformInstanceId, config, state, runId, eventGranularity=None, partitionSpec=None, messageId=None)

Bases: _Aspect

Checkpoint of a datahub ingestion run for a given job.

Parameters:

timestampMillis (int)
pipelineName (str)
platformInstanceId (str)
config (str)
state (IngestionCheckpointStateClass)
runId (str)
eventGranularity (Optional[TimeWindowSizeClass])
partitionSpec (Optional[PartitionSpecClass])
messageId (Optional[str])

ASPECT_TYPE: ClassVar[str] = 'timeseries'

property config: str: Json-encoded string representation of the non-secret members of the config .

property eventGranularity: None | TimeWindowSizeClass: Granularity of the event if applicable

property messageId: None | str: The optional messageId, if provided serves as a custom user-defined unique identifier for an aspect value.

property partitionSpec: PartitionSpecClass | None: The optional partition specification.

property pipelineName: str: The name of the pipeline that ran ingestion, a stable unique user provided identifier. e.g. my_snowflake1-to-datahub.

property platformInstanceId: str: The id of the instance against which the ingestion pipeline ran. e.g.: Bigquery project ids, MySQL hostnames etc.

property runId: str: The run identifier of this job.

property state: IngestionCheckpointStateClass: Opaque blob of the state representation.

property timestampMillis: int: The event timestamp field as epoch at UTC in milli seconds.

class datahub.metadata.schema_classes.DatahubIngestionRunSummaryClass(timestampMillis, pipelineName, platformInstanceId, runId, runStatus, eventGranularity=None, partitionSpec=None, messageId=None, numWorkUnitsCommitted=None, numWorkUnitsCreated=None, numEvents=None, numEntities=None, numAspects=None, numSourceAPICalls=None, totalLatencySourceAPICalls=None, numSinkAPICalls=None, totalLatencySinkAPICalls=None, numWarnings=None, numErrors=None, numEntitiesSkipped=None, config=None, custom_summary=None, softwareVersion=None, systemHostName=None, operatingSystemName=None, numProcessors=None, totalMemory=None, availableMemory=None)

Bases: _Aspect

Summary of a datahub ingestion run for a given platform.

Parameters:

timestampMillis (int)
pipelineName (str)
platformInstanceId (str)
runId (str)
runStatus (Union[str, JobStatusClass])
eventGranularity (Optional[TimeWindowSizeClass])
partitionSpec (Optional[PartitionSpecClass])
messageId (Optional[str])
numWorkUnitsCommitted (Optional[int])
numWorkUnitsCreated (Optional[int])
numEvents (Optional[int])
numEntities (Optional[int])
numAspects (Optional[int])
numSourceAPICalls (Optional[int])
totalLatencySourceAPICalls (Optional[int])
numSinkAPICalls (Optional[int])
totalLatencySinkAPICalls (Optional[int])
numWarnings (Optional[int])
numErrors (Optional[int])
numEntitiesSkipped (Optional[int])
config (Optional[str])
custom_summary (Optional[str])
softwareVersion (Optional[str])
systemHostName (Optional[str])
operatingSystemName (Optional[str])
numProcessors (Optional[int])
totalMemory (Optional[int])
availableMemory (Optional[int])

ASPECT_TYPE: ClassVar[str] = 'timeseries'

property availableMemory: None | int: The available memory on the host the ingestion pipeline ran on.

property config: None | str: The non-sensitive key-value pairs of the yaml config used as json string.

property custom_summary: None | str: Custom value.

property eventGranularity: None | TimeWindowSizeClass: Granularity of the event if applicable

property messageId: None | str: The optional messageId, if provided serves as a custom user-defined unique identifier for an aspect value.

property numAspects: None | int: The total number of aspects produced across all entities.

property numEntities: None | int: The total number of entities produced (unique entity urns).

property numEntitiesSkipped: None | int: Number of entities skipped.

property numErrors: None | int: Number of errors generated.

property numEvents: None | int: The number of events produced (MCE + MCP).

property numProcessors: None | int: The number of processors on the host the ingestion pipeline ran on.

property numSinkAPICalls: None | int: Total number of sink API calls.

property numSourceAPICalls: None | int: Total number of source API calls.

property numWarnings: None | int: Number of warnings generated.

property numWorkUnitsCommitted: None | int: The number of workunits written to sink.

property numWorkUnitsCreated: None | int: The number of workunits that are produced.

property operatingSystemName: None | str: The os the ingestion pipeline ran on.

property partitionSpec: PartitionSpecClass | None: The optional partition specification.

property pipelineName: str: The name of the pipeline that ran ingestion, a stable unique user provided identifier. e.g. my_snowflake1-to-datahub.

property platformInstanceId: str: The id of the instance against which the ingestion pipeline ran. e.g.: Bigquery project ids, MySQL hostnames etc.

property runId: str: The runId for this pipeline instance.

property runStatus: str | JobStatusClass: Run Status - Succeeded/Skipped/Failed etc.

property softwareVersion: None | str: The software version of this ingestion.

property systemHostName: None | str: The hostname the ingestion pipeline ran on.

property timestampMillis: int: The event timestamp field as epoch at UTC in milli seconds.

property totalLatencySinkAPICalls: None | int: Total latency across all sink API calls.

property totalLatencySourceAPICalls: None | int: Total latency across all source API calls.

property totalMemory: None | int: The total amount of memory on the host the ingestion pipeline ran on.

class datahub.metadata.schema_classes.DatasetAssertionInfoClass(dataset, scope, operator, fields=None, aggregation=None, parameters=None, nativeType=None, nativeParameters=None, logic=None)

Bases: DictWrapper

Attributes that are applicable to single-Dataset Assertions

Parameters:

dataset (str)
scope (Union[str, DatasetAssertionScopeClass])
operator (Union[str, AssertionStdOperatorClass])
fields (Optional[List[str]])
aggregation (Union[None, str, AssertionStdAggregationClass])
parameters (Optional[AssertionStdParametersClass])
nativeType (Optional[str])
nativeParameters (Optional[Dict[str, str]])
logic (Optional[str])

property aggregation: None | str | AssertionStdAggregationClass: Standardized assertion operator This field is left blank if there is no selected aggregation or metric for a particular column.

property dataset: str: The dataset targeted by this assertion.

property fields: None | List[str]

One or more dataset schema fields that are targeted by this assertion.

This field is expected to be provided if the assertion scope is DATASET_COLUMN.

property logic: None | str

property nativeParameters: None | Dict[str, str]: Native parameters required for the assertion.

property nativeType: None | str: Native assertion type

property operator: str | AssertionStdOperatorClass: Standardized assertion operator

property parameters: None | AssertionStdParametersClass: Standard parameters required for the assertion. e.g. min_value, max_value, value, columns

property scope: str | DatasetAssertionScopeClass: Scope of the Assertion. What part of the dataset does this assertion apply to?

class datahub.metadata.schema_classes.DatasetAssertionScopeClass

Bases: object

DATASET_COLUMN = 'DATASET_COLUMN'

DATASET_ROWS = 'DATASET_ROWS'

DATASET_SCHEMA = 'DATASET_SCHEMA'

DATASET_STORAGE_SIZE = 'DATASET_STORAGE_SIZE'

UNKNOWN = 'UNKNOWN'

class datahub.metadata.schema_classes.DatasetDeprecationClass(deprecated, note, decommissionTime=None, actor=None)

Bases: _Aspect

Dataset deprecation status Deprecated! This aspect is deprecated in favor of the more-general-purpose ‘Deprecation’ aspect.

Parameters:

deprecated (bool)
note (str)
decommissionTime (Optional[int])
actor (Optional[str])

property actor: None | str: The corpuser URN which will be credited for modifying this deprecation content.

property decommissionTime: None | int: The time user plan to decommission this dataset.

property deprecated: bool: Whether the dataset is deprecated by owner.

property note: str: Additional information about the dataset deprecation plan, such as the wiki, doc, RB.

class datahub.metadata.schema_classes.DatasetFieldForeignKeyClass(parentDataset, currentFieldPaths, parentField)

Bases: DictWrapper

For non-urn based foregin keys.

Parameters:

parentDataset (str)
currentFieldPaths (List[str])
parentField (str)

property currentFieldPaths: List[str]: List of fields in hosting(current) SchemaMetadata that conform a foreign key. List can contain a single entry or multiple entries if several entries in hosting schema conform a foreign key in a single parent dataset.

property parentDataset: str: dataset that stores the resource.

property parentField: str: SchemaField@fieldPath that uniquely identify field in parent dataset that this field references.

class datahub.metadata.schema_classes.DatasetFieldMappingClass(created, transformation, sourceFields, destinationField)

Bases: DictWrapper

Representation of mapping between fields in source dataset to the field in destination dataset

Parameters:

created (AuditStampClass)
transformation (Union[str, TransformationTypeClass, UDFTransformerClass])
sourceFields (List[str])
destinationField (str)

property created: AuditStampClass: Audit stamp containing who reported the field mapping and when

property destinationField: str: Destination field which is derived from source fields

property sourceFields: List[str]: Source fields from which the fine grained lineage is derived

property transformation: str | TransformationTypeClass | UDFTransformerClass: Transfomration function between the fields involved

class datahub.metadata.schema_classes.DatasetFieldProfileClass(fieldPath, uniqueCount=None, uniqueProportion=None, nullCount=None, nullProportion=None, min=None, max=None, mean=None, median=None, stdev=None, quantiles=None, distinctValueFrequencies=None, histogram=None, sampleValues=None)

Bases: DictWrapper

Stats corresponding to fields in a dataset

Parameters:

fieldPath (str)
uniqueCount (Optional[int])
uniqueProportion (Optional[float])
nullCount (Optional[int])
nullProportion (Optional[float])
min (Optional[str])
max (Optional[str])
mean (Optional[str])
median (Optional[str])
stdev (Optional[str])
quantiles (Optional[List[QuantileClass]])
distinctValueFrequencies (Optional[List[ValueFrequencyClass]])
histogram (Optional[HistogramClass])
sampleValues (Optional[List[str]])

property distinctValueFrequencies: None | List[ValueFrequencyClass]

property fieldPath: str

property histogram: None | HistogramClass

property max: None | str

property mean: None | str

property median: None | str

property min: None | str

property nullCount: None | int

property nullProportion: None | float

property quantiles: None | List[QuantileClass]

property sampleValues: None | List[str]

property stdev: None | str

property uniqueCount: None | int

property uniqueProportion: None | float

class datahub.metadata.schema_classes.DatasetFieldUsageCountsClass(fieldPath, count)

Bases: DictWrapper

Records field-level usage counts for a given dataset

Parameters:

fieldPath (str)
count (int)

property count: int: Number of times the field has been used.

property fieldPath: str: The name of the field.

class datahub.metadata.schema_classes.DatasetFilterClass(type, sql=None)

Bases: DictWrapper

A definition of filters that should be used when querying an external Dataset or Table.

Note that this models should NOT be used for working with search / filter on DataHub Platform itself.

Parameters:

type (Union[str, DatasetFilterTypeClass])
sql (Optional[str])

property sql: None | str: The raw where clause string which will be used for monitoring. Required if the type is SQL.

property type: str | DatasetFilterTypeClass

How the partition will be represented in this model.

In the future, we’ll likely add support for more structured predicates.

class datahub.metadata.schema_classes.DatasetFilterTypeClass

Bases: object

SQL = 'SQL'

class datahub.metadata.schema_classes.DatasetKeyClass(platform, name, origin)

Bases: _Aspect

Key for a Dataset

Parameters:

platform (str)
name (str)
origin (Union[str, FabricTypeClass])

property name: str: Unique guid for dataset

property origin: str | FabricTypeClass: Fabric type where dataset belongs to or where it was generated.

property platform: str: Data platform urn associated with the dataset

class datahub.metadata.schema_classes.DatasetLineageTypeClass

Bases: object

The various types of supported dataset lineage

COPY = 'COPY'

TRANSFORMED = 'TRANSFORMED'

VIEW = 'VIEW'

class datahub.metadata.schema_classes.DatasetProfileClass(timestampMillis, eventGranularity=None, partitionSpec=None, messageId=None, rowCount=None, columnCount=None, fieldProfiles=None, sizeInBytes=None)

Bases: _Aspect

Stats corresponding to datasets

Parameters:

timestampMillis (int)
eventGranularity (Optional[TimeWindowSizeClass])
partitionSpec (Optional[PartitionSpecClass])
messageId (Optional[str])
rowCount (Optional[int])
columnCount (Optional[int])
fieldProfiles (Optional[List[DatasetFieldProfileClass]])
sizeInBytes (Optional[int])

ASPECT_TYPE: ClassVar[str] = 'timeseries'

property columnCount: None | int: The total number of columns (or schema fields)

property eventGranularity: None | TimeWindowSizeClass: Granularity of the event if applicable

property fieldProfiles: None | List[DatasetFieldProfileClass]: Profiles for each column (or schema field)

property messageId: None | str: The optional messageId, if provided serves as a custom user-defined unique identifier for an aspect value.

property partitionSpec: PartitionSpecClass | None: The optional partition specification.

property rowCount: None | int: The total number of rows

property sizeInBytes: None | int: Storage size in bytes

property timestampMillis: int: The event timestamp field as epoch at UTC in milli seconds.

class datahub.metadata.schema_classes.DatasetPropertiesClass(customProperties=None, externalUrl=None, name=None, qualifiedName=None, description=None, uri=None, created=None, lastModified=None, tags=None)

Bases: _Aspect

Properties associated with a Dataset

Parameters:

customProperties (Optional[Dict[str, str]])
externalUrl (Optional[str])
name (Optional[str])
qualifiedName (Optional[str])
description (Optional[str])
uri (Optional[str])
created (Optional[TimeStampClass])
lastModified (Optional[TimeStampClass])
tags (Optional[List[str]])

property created: None | TimeStampClass: A timestamp documenting when the asset was created in the source Data Platform (not on DataHub)

property customProperties: Dict[str, str]: Custom property bag.

property description: None | str: Documentation of the dataset

property externalUrl: None | str: URL where the reference exist

property lastModified: None | TimeStampClass: A timestamp documenting when the asset was last modified in the source Data Platform (not on DataHub)

property name: None | str: Display name of the Dataset

property qualifiedName: None | str: Fully-qualified name of the Dataset

property tags: List[str]: [Legacy] Unstructured tags for the dataset. Structured tags can be applied via the GlobalTags aspect. This is now deprecated.

property uri: None | str

///dir/file_name. Uri should not include any environment specific properties. Some datasets might not have a standardized uri, which makes this field optional (i.e. kafka topic).

Type:: The abstracted URI such as hdfs
Type:: ///data/tracking/PageViewEvent, file

class datahub.metadata.schema_classes.DatasetSnapshotClass(urn, aspects)

Bases: DictWrapper

A metadata snapshot for a specific dataset entity.

Parameters:

urn (str)
aspects (List[Union[DatasetKeyClass, DatasetPropertiesClass, EditableDatasetPropertiesClass, DatasetDeprecationClass, DatasetUpstreamLineageClass, UpstreamLineageClass, InstitutionalMemoryClass, OwnershipClass, StatusClass, SchemaMetadataClass, EditableSchemaMetadataClass, GlobalTagsClass, GlossaryTermsClass, BrowsePathsClass, DataPlatformInstanceClass, ViewPropertiesClass, BrowsePathsV2Class]])

property aspects: List[DatasetKeyClass | DatasetPropertiesClass | EditableDatasetPropertiesClass | DatasetDeprecationClass | DatasetUpstreamLineageClass | UpstreamLineageClass | InstitutionalMemoryClass | OwnershipClass | StatusClass | SchemaMetadataClass | EditableSchemaMetadataClass | GlobalTagsClass | GlossaryTermsClass | BrowsePathsClass | DataPlatformInstanceClass | ViewPropertiesClass | BrowsePathsV2Class]: The list of metadata aspects associated with the dataset. Depending on the use case, this can either be all, or a selection, of supported aspects.

property urn: str: URN for the entity the metadata snapshot is associated with.

class datahub.metadata.schema_classes.DatasetUpstreamLineageClass(fieldMappings)

Bases: _Aspect

Fine Grained upstream lineage for fields in a dataset

Parameters:: fieldMappings (List[DatasetFieldMappingClass])

property fieldMappings: List[DatasetFieldMappingClass]: Upstream to downstream field level lineage mappings

class datahub.metadata.schema_classes.DatasetUsageStatisticsClass(timestampMillis, eventGranularity=None, partitionSpec=None, messageId=None, uniqueUserCount=None, totalSqlQueries=None, topSqlQueries=None, userCounts=None, fieldCounts=None)

Bases: _Aspect

Stats corresponding to dataset’s usage.

Parameters:

timestampMillis (int)
eventGranularity (Optional[TimeWindowSizeClass])
partitionSpec (Optional[PartitionSpecClass])
messageId (Optional[str])
uniqueUserCount (Optional[int])
totalSqlQueries (Optional[int])
topSqlQueries (Optional[List[str]])
userCounts (Optional[List[DatasetUserUsageCountsClass]])
fieldCounts (Optional[List[DatasetFieldUsageCountsClass]])

ASPECT_TYPE: ClassVar[str] = 'timeseries'

property eventGranularity: None | TimeWindowSizeClass: Granularity of the event if applicable

property fieldCounts: None | List[DatasetFieldUsageCountsClass]: Field-level usage stats

property messageId: None | str: The optional messageId, if provided serves as a custom user-defined unique identifier for an aspect value.

property partitionSpec: PartitionSpecClass | None: The optional partition specification.

property timestampMillis: int: The event timestamp field as epoch at UTC in milli seconds.

property topSqlQueries: None | List[str]: Frequent SQL queries; mostly makes sense for datasets in SQL databases

property totalSqlQueries: None | int: Total SQL query count

property uniqueUserCount: None | int: Unique user count

property userCounts: None | List[DatasetUserUsageCountsClass]: Users within this bucket, with frequency counts

class datahub.metadata.schema_classes.DatasetUserUsageCountsClass(user, count, userEmail=None)

Bases: DictWrapper

Records a single user’s usage counts for a given resource

Parameters:

user (str)
count (int)
userEmail (Optional[str])

property count: int: Number of times the dataset has been used by the user.

property user: str: The unique id of the user.

property userEmail: None | str: If user_email is set, we attempt to resolve the user’s urn upon ingest

class datahub.metadata.schema_classes.DateTypeClass

Bases: DictWrapper

Date field type.

class datahub.metadata.schema_classes.DeploymentStatusClass

Bases: object

Model endpoint statuses

CREATING = 'CREATING'

DELETING = 'DELETING'

FAILED = 'FAILED'

IN_SERVICE = 'IN_SERVICE'

OUT_OF_SERVICE = 'OUT_OF_SERVICE'

ROLLING_BACK = 'ROLLING_BACK'

UNKNOWN = 'UNKNOWN'

UPDATING = 'UPDATING'

class datahub.metadata.schema_classes.DeprecationClass(deprecated, note, actor, decommissionTime=None)

Bases: _Aspect

Deprecation status of an entity

Parameters:

deprecated (bool)
note (str)
actor (str)
decommissionTime (Optional[int])

property actor: str: The user URN which will be credited for modifying this deprecation content.

property decommissionTime: None | int: The time user plan to decommission this entity.

property deprecated: bool: Whether the entity is deprecated.

property note: str: Additional information about the entity deprecation plan, such as the wiki, doc, RB.

class datahub.metadata.schema_classes.DomainKeyClass(id)

Bases: _Aspect

Key for an Asset Domain

Parameters:: id (str)

property id: str: A unique id for the domain. Should be separate from the name used for displaying a Domain.

class datahub.metadata.schema_classes.DomainPropertiesClass(name, description=None, created=None, parentDomain=None)

Bases: _Aspect

Information about a Domain

Parameters:

name (str)
description (Optional[str])
created (Optional[AuditStampClass])
parentDomain (Optional[str])

property created: None | AuditStampClass: Created Audit stamp

property description: None | str: Description of the Domain

property name: str: Display name of the Domain

property parentDomain: None | str

Parent of the domain

Type:: Optional

class datahub.metadata.schema_classes.DomainsClass(domains)

Bases: _Aspect

Links from an Asset to its Domains

Parameters:: domains (List[str])

property domains: List[str]: The Domains attached to an Asset

class datahub.metadata.schema_classes.EdgeClass(destinationUrn, sourceUrn=None, created=None, lastModified=None, properties=None)

Bases: DictWrapper

A common structure to represent all edges to entities when used inside aspects as collections This ensures that all edges have common structure around audit-stamps and will support PATCH, time-travel automatically.

Parameters:

destinationUrn (str)
sourceUrn (Optional[str])
created (Optional[AuditStampClass])
lastModified (Optional[AuditStampClass])
properties (Optional[Dict[str, str]])

property created: None | AuditStampClass: Audit stamp containing who created this relationship edge and when

property destinationUrn: str: Urn of the destination of this relationship edge.

property lastModified: None | AuditStampClass: Audit stamp containing who last modified this relationship edge and when

property properties: None | Dict[str, str]: A generic properties bag that allows us to store specific information on this graph edge.

property sourceUrn: None | str: Urn of the source of this relationship edge. If not specified, assumed to be the entity that this aspect belongs to.

class datahub.metadata.schema_classes.EditableChartPropertiesClass(created=None, lastModified=None, deleted=None, description=None)

Bases: _Aspect

Stores editable changes made to properties. This separates changes made from ingestion pipelines and edits in the UI to avoid accidental overwrites of user-provided data by ingestion pipelines

Parameters:

created (Optional[AuditStampClass])
lastModified (Optional[AuditStampClass])
deleted (Optional[AuditStampClass])
description (Optional[str])

property created: AuditStampClass: An AuditStamp corresponding to the creation of this resource/association/sub-resource. A value of 0 for time indicates missing data.

property deleted: None | AuditStampClass: An AuditStamp corresponding to the deletion of this resource/association/sub-resource. Logically, deleted MUST have a later timestamp than creation. It may or may not have the same time as lastModified depending upon the resource/association/sub-resource semantics.

property description: None | str: Edited documentation of the chart

property lastModified: AuditStampClass: An AuditStamp corresponding to the last modification of this resource/association/sub-resource. If no modification has happened since creation, lastModified should be the same as created. A value of 0 for time indicates missing data.

class datahub.metadata.schema_classes.EditableContainerPropertiesClass(description=None)

Bases: _Aspect

Editable information about an Asset Container as defined on the DataHub Platform

Parameters:: description (Optional[str])

property description: None | str: Description of the Asset Container as its received on the DataHub Platform

class datahub.metadata.schema_classes.EditableDashboardPropertiesClass(created=None, lastModified=None, deleted=None, description=None)

Bases: _Aspect

Stores editable changes made to properties. This separates changes made from ingestion pipelines and edits in the UI to avoid accidental overwrites of user-provided data by ingestion pipelines

Parameters:

created (Optional[AuditStampClass])
lastModified (Optional[AuditStampClass])
deleted (Optional[AuditStampClass])
description (Optional[str])

property created: AuditStampClass: An AuditStamp corresponding to the creation of this resource/association/sub-resource. A value of 0 for time indicates missing data.

property deleted: None | AuditStampClass: An AuditStamp corresponding to the deletion of this resource/association/sub-resource. Logically, deleted MUST have a later timestamp than creation. It may or may not have the same time as lastModified depending upon the resource/association/sub-resource semantics.

property description: None | str: Edited documentation of the dashboard

property lastModified: AuditStampClass: An AuditStamp corresponding to the last modification of this resource/association/sub-resource. If no modification has happened since creation, lastModified should be the same as created. A value of 0 for time indicates missing data.

class datahub.metadata.schema_classes.EditableDataFlowPropertiesClass(created=None, lastModified=None, deleted=None, description=None)

Bases: _Aspect

Stores editable changes made to properties. This separates changes made from ingestion pipelines and edits in the UI to avoid accidental overwrites of user-provided data by ingestion pipelines

Parameters:

created (Optional[AuditStampClass])
lastModified (Optional[AuditStampClass])
deleted (Optional[AuditStampClass])
description (Optional[str])

property created: AuditStampClass: An AuditStamp corresponding to the creation of this resource/association/sub-resource. A value of 0 for time indicates missing data.

property deleted: None | AuditStampClass: An AuditStamp corresponding to the deletion of this resource/association/sub-resource. Logically, deleted MUST have a later timestamp than creation. It may or may not have the same time as lastModified depending upon the resource/association/sub-resource semantics.

property description: None | str: Edited documentation of the data flow

property lastModified: AuditStampClass: An AuditStamp corresponding to the last modification of this resource/association/sub-resource. If no modification has happened since creation, lastModified should be the same as created. A value of 0 for time indicates missing data.

class datahub.metadata.schema_classes.EditableDataJobPropertiesClass(created=None, lastModified=None, deleted=None, description=None)

Bases: _Aspect

Stores editable changes made to properties. This separates changes made from ingestion pipelines and edits in the UI to avoid accidental overwrites of user-provided data by ingestion pipelines

Parameters:

created (Optional[AuditStampClass])
lastModified (Optional[AuditStampClass])
deleted (Optional[AuditStampClass])
description (Optional[str])

property created: AuditStampClass: An AuditStamp corresponding to the creation of this resource/association/sub-resource. A value of 0 for time indicates missing data.

property deleted: None | AuditStampClass: An AuditStamp corresponding to the deletion of this resource/association/sub-resource. Logically, deleted MUST have a later timestamp than creation. It may or may not have the same time as lastModified depending upon the resource/association/sub-resource semantics.

property description: None | str: Edited documentation of the data job

property lastModified: AuditStampClass: An AuditStamp corresponding to the last modification of this resource/association/sub-resource. If no modification has happened since creation, lastModified should be the same as created. A value of 0 for time indicates missing data.

class datahub.metadata.schema_classes.EditableDatasetPropertiesClass(created=None, lastModified=None, deleted=None, description=None)

Bases: _Aspect

EditableDatasetProperties stores editable changes made to dataset properties. This separates changes made from ingestion pipelines and edits in the UI to avoid accidental overwrites of user-provided data by ingestion pipelines

Parameters:

created (Optional[AuditStampClass])
lastModified (Optional[AuditStampClass])
deleted (Optional[AuditStampClass])
description (Optional[str])

property created: AuditStampClass: An AuditStamp corresponding to the creation of this resource/association/sub-resource. A value of 0 for time indicates missing data.

property deleted: None | AuditStampClass: An AuditStamp corresponding to the deletion of this resource/association/sub-resource. Logically, deleted MUST have a later timestamp than creation. It may or may not have the same time as lastModified depending upon the resource/association/sub-resource semantics.

property description: None | str: Documentation of the dataset

property lastModified: AuditStampClass: An AuditStamp corresponding to the last modification of this resource/association/sub-resource. If no modification has happened since creation, lastModified should be the same as created. A value of 0 for time indicates missing data.

class datahub.metadata.schema_classes.EditableMLFeaturePropertiesClass(description=None)

Bases: _Aspect

Properties associated with a MLFeature editable from the UI

Parameters:: description (Optional[str])

property description: None | str: Documentation of the MLFeature

class datahub.metadata.schema_classes.EditableMLFeatureTablePropertiesClass(description=None)

Bases: _Aspect

Properties associated with a MLFeatureTable editable from the ui

Parameters:: description (Optional[str])

property description: None | str: Documentation of the MLFeatureTable

class datahub.metadata.schema_classes.EditableMLModelGroupPropertiesClass(description=None)

Bases: _Aspect

Properties associated with an ML Model Group editable from the UI

Parameters:: description (Optional[str])

property description: None | str: Documentation of the ml model group

class datahub.metadata.schema_classes.EditableMLModelPropertiesClass(description=None)

Bases: _Aspect

Properties associated with a ML Model editable from the UI

Parameters:: description (Optional[str])

property description: None | str: Documentation of the ml model

class datahub.metadata.schema_classes.EditableMLPrimaryKeyPropertiesClass(description=None)

Bases: _Aspect

Properties associated with a MLPrimaryKey editable from the UI

Parameters:: description (Optional[str])

property description: None | str: Documentation of the MLPrimaryKey

class datahub.metadata.schema_classes.EditableNotebookPropertiesClass(created=None, lastModified=None, deleted=None, description=None)

Bases: _Aspect

Stores editable changes made to properties. This separates changes made from ingestion pipelines and edits in the UI to avoid accidental overwrites of user-provided data by ingestion pipelines Note: This is IN BETA version

Parameters:

created (Optional[AuditStampClass])
lastModified (Optional[AuditStampClass])
deleted (Optional[AuditStampClass])
description (Optional[str])

property created: AuditStampClass: An AuditStamp corresponding to the creation of this resource/association/sub-resource. A value of 0 for time indicates missing data.

property deleted: None | AuditStampClass: An AuditStamp corresponding to the deletion of this resource/association/sub-resource. Logically, deleted MUST have a later timestamp than creation. It may or may not have the same time as lastModified depending upon the resource/association/sub-resource semantics.

property description: None | str: Edited documentation of the Notebook

property lastModified: AuditStampClass: An AuditStamp corresponding to the last modification of this resource/association/sub-resource. If no modification has happened since creation, lastModified should be the same as created. A value of 0 for time indicates missing data.

class datahub.metadata.schema_classes.EditableSchemaFieldInfoClass(fieldPath, description=None, globalTags=None, glossaryTerms=None)

Bases: DictWrapper

SchemaField to describe metadata related to dataset schema.

Parameters:

fieldPath (str)
description (Optional[str])
globalTags (Optional[GlobalTagsClass])
glossaryTerms (Optional[GlossaryTermsClass])

property description: None | str: Description

property fieldPath: str: FieldPath uniquely identifying the SchemaField this metadata is associated with

property globalTags: None | GlobalTagsClass: Tags associated with the field

property glossaryTerms: None | GlossaryTermsClass: Glossary terms associated with the field

class datahub.metadata.schema_classes.EditableSchemaMetadataClass(editableSchemaFieldInfo, created=None, lastModified=None, deleted=None)

Bases: _Aspect

EditableSchemaMetadata stores editable changes made to schema metadata. This separates changes made from ingestion pipelines and edits in the UI to avoid accidental overwrites of user-provided data by ingestion pipelines.

Parameters:

editableSchemaFieldInfo (List[EditableSchemaFieldInfoClass])
created (Optional[AuditStampClass])
lastModified (Optional[AuditStampClass])
deleted (Optional[AuditStampClass])

property created: AuditStampClass: An AuditStamp corresponding to the creation of this resource/association/sub-resource. A value of 0 for time indicates missing data.

property deleted: None | AuditStampClass: An AuditStamp corresponding to the deletion of this resource/association/sub-resource. Logically, deleted MUST have a later timestamp than creation. It may or may not have the same time as lastModified depending upon the resource/association/sub-resource semantics.

property editableSchemaFieldInfo: List[EditableSchemaFieldInfoClass]: Client provided a list of fields from document schema.

property lastModified: AuditStampClass: An AuditStamp corresponding to the last modification of this resource/association/sub-resource. If no modification has happened since creation, lastModified should be the same as created. A value of 0 for time indicates missing data.

class datahub.metadata.schema_classes.EmbedClass(renderUrl=None)

Bases: _Aspect

Information regarding rendering an embed for an asset.

Parameters:: renderUrl (Optional[str])

property renderUrl: None | str: An embed URL to be rendered inside of an iframe.

class datahub.metadata.schema_classes.EntityChangeEventClass(entityType, entityUrn, category, operation, auditStamp, version, modifier=None, parameters=None)

Bases: DictWrapper

Shared fields for all entity change events.

Parameters:

entityType (str)
entityUrn (str)
category (str)
operation (str)
auditStamp (AuditStampClass)
version (int)
modifier (Optional[str])
parameters (Optional[ParametersClass])

property auditStamp: AuditStampClass: Audit stamp of the operation

property category: str: The category type (TAG, GLOSSARY_TERM, OWNERSHIP, TECHNICAL_SCHEMA, etc). This is used to determine what the rest of the schema will look like.

property entityType: str: The type of the entity affected. Corresponds to the entity registry, e.g. ‘dataset’, ‘chart’, ‘dashboard’, etc.

property entityUrn: str: The urn of the entity which was affected.

property modifier: None | str: The urn of the entity which was affected.

property operation: str: The operation type. This is used to determine what the rest of the schema will look like.

property parameters: None | ParametersClass: Arbitrary key-value parameters corresponding to the event.

property version: int: The version of the event type, incremented in integers.

class datahub.metadata.schema_classes.EnumTypeClass

Bases: DictWrapper

Enum field type.

class datahub.metadata.schema_classes.EspressoSchemaClass(documentSchema, tableSchema)

Bases: DictWrapper

Schema text of an espresso table schema.

Parameters:

documentSchema (str)
tableSchema (str)

property documentSchema: str: The native espresso document schema.

property tableSchema: str: The espresso table schema definition.

class datahub.metadata.schema_classes.EthicalConsiderationsClass(data=None, humanLife=None, mitigations=None, risksAndHarms=None, useCases=None)

Bases: _Aspect

This section is intended to demonstrate the ethical considerations that went into MLModel development, surfacing ethical challenges and solutions to stakeholders.

Parameters:

data (Optional[List[str]])
humanLife (Optional[List[str]])
mitigations (Optional[List[str]])
risksAndHarms (Optional[List[str]])
useCases (Optional[List[str]])

property data: None | List[str]: Does the MLModel use any sensitive data (e.g., protected classes)?

property humanLife: None | List[str]: Is the MLModel intended to inform decisions about matters central to human life or flourishing - e.g., health or safety? Or could it be used in such a way?

property mitigations: None | List[str]: What risk mitigation strategies were used during MLModel development?

property risksAndHarms: None | List[str]: What risks may be present in MLModel usage? Try to identify the potential recipients, likelihood, and magnitude of harms. If these cannot be determined, note that they were considered but remain unknown.

property useCases: None | List[str]: Are there any known MLModel use cases that are especially fraught? This may connect directly to the intended use section

class datahub.metadata.schema_classes.EvaluationDataClass(evaluationData)

Bases: _Aspect

All referenced datasets would ideally point to any set of documents that provide visibility into the source and composition of the dataset.

Parameters:: evaluationData (List[BaseDataClass])

property evaluationData: List[BaseDataClass]: Details on the dataset(s) used for the quantitative analyses in the MLModel

class datahub.metadata.schema_classes.ExecutionRequestInputClass(task, args, executorId, source, requestedAt)

Bases: _Aspect

An request to execution some remote logic or action. TODO: Determine who is responsible for emitting execution request success or failure. Executor?

Parameters:

task (str)
args (Dict[str, str])
executorId (str)
source (ExecutionRequestSourceClass)
requestedAt (int)

property args: Dict[str, str]: Arguments provided to the task

property executorId: str

specify a specific executor to route the request to. If none is provided, a “default” executor is used.

Type:: Advanced

property requestedAt: int: Time at which the execution request input was created

property source: ExecutionRequestSourceClass: Source which created the execution request

property task: str: The name of the task to execute, for example RUN_INGEST

class datahub.metadata.schema_classes.ExecutionRequestKeyClass(id)

Bases: _Aspect

Key for an DataHub Execution Request

Parameters:: id (str)

property id: str: A unique id for the DataHub execution request.

class datahub.metadata.schema_classes.ExecutionRequestResultClass(status, report=None, structuredReport=None, startTimeMs=None, durationMs=None)

Bases: _Aspect

The result of an execution request

Parameters:

status (str)
report (Optional[str])
structuredReport (Optional[StructuredExecutionReportClass])
startTimeMs (Optional[int])
durationMs (Optional[int])

property durationMs: None | int: Duration in milliseconds

property report: None | str: The pretty-printed execution report.

property startTimeMs: None | int: Time at which the request was created

property status: str: The status of the execution request

property structuredReport: None | StructuredExecutionReportClass: A structured report if available.

class datahub.metadata.schema_classes.ExecutionRequestSignalClass(signal, createdAt, executorId=None)

Bases: _Aspect

An signal sent to a running execution request

Parameters:

signal (str)
createdAt (AuditStampClass)
executorId (Optional[str])

property createdAt: AuditStampClass: Audit Stamp

property executorId: None | str

specify a specific executor to route the request to. If none is provided, a “default” executor is used.

Type:: Advanced

property signal: str: The signal to issue, e.g. KILL

class datahub.metadata.schema_classes.ExecutionRequestSourceClass(type, ingestionSource=None)

Bases: DictWrapper

Parameters:

type (str)
ingestionSource (Optional[str])

property ingestionSource: None | str: The urn of the ingestion source associated with the ingestion request. Present if type is INGESTION_SOURCE

property type: str: The type of the execution request source, e.g. INGESTION_SOURCE

class datahub.metadata.schema_classes.FabricTypeClass

Bases: object

Fabric group type

CORP = 'CORP'

DEV = 'DEV'

EI = 'EI'

NON_PROD = 'NON_PROD'

PRE = 'PRE'

PROD = 'PROD'

QA = 'QA'

STG = 'STG'

TEST = 'TEST'

UAT = 'UAT'

class datahub.metadata.schema_classes.FieldUsageCountsClass(fieldName, count)

Bases: DictWrapper

Records field-level usage counts for a given resource

Parameters:

fieldName (str)
count (int)

property count: int

property fieldName: str

class datahub.metadata.schema_classes.FilterClass(or_=None, criteria=None)

Bases: DictWrapper

The filter for finding a record or a collection of records

Parameters:

or_ (Optional[List[ConjunctiveCriterionClass]])
criteria (Optional[List[CriterionClass]])

property criteria: None | List[CriterionClass]: Deprecated! A list of conjunctive criterion for the filter. If “or” field is provided, then this field is ignored.

property or_: None | List[ConjunctiveCriterionClass]: A list of disjunctive criterion for the filter. (or operation to combine filters)

class datahub.metadata.schema_classes.FineGrainedLineageClass(upstreamType, downstreamType, upstreams=None, downstreams=None, transformOperation=None, confidenceScore=None)

Bases: DictWrapper

A fine-grained lineage from upstream fields/datasets to downstream field(s)

Parameters:

upstreamType (Union[str, FineGrainedLineageUpstreamTypeClass])
downstreamType (Union[str, FineGrainedLineageDownstreamTypeClass])
upstreams (Optional[List[str]])
downstreams (Optional[List[str]])
transformOperation (Optional[str])
confidenceScore (Optional[float])

property confidenceScore: float: The confidence in this lineage between 0 (low confidence) and 1 (high confidence)

property downstreamType: str | FineGrainedLineageDownstreamTypeClass: The type of downstream field(s)

property downstreams: None | List[str]: Downstream fields in the lineage

property transformOperation: None | str: The transform operation applied to the upstream entities to produce the downstream field(s)

property upstreamType: str | FineGrainedLineageUpstreamTypeClass: The type of upstream entity

property upstreams: None | List[str]: Upstream entities in the lineage

class datahub.metadata.schema_classes.FineGrainedLineageDownstreamTypeClass

Bases: object

The type of downstream field(s) in a fine-grained lineage

FIELD = 'FIELD'

FIELD_SET = 'FIELD_SET'

class datahub.metadata.schema_classes.FineGrainedLineageUpstreamTypeClass

Bases: object

The type of upstream entity in a fine-grained lineage

DATASET = 'DATASET'

FIELD_SET = 'FIELD_SET'

NONE = 'NONE'

class datahub.metadata.schema_classes.FixedIntervalScheduleClass(unit, multiple=None)

Bases: DictWrapper

Attributes defining a relative fixed interval SLA schedule.

Parameters:

unit (Union[str, CalendarIntervalClass])
multiple (Optional[int])

property multiple: int: How many units. Defaults to 1.

property unit: str | CalendarIntervalClass: Interval unit such as minute/hour/day etc.

class datahub.metadata.schema_classes.FixedTypeClass

Bases: DictWrapper

Fixed field type.

class datahub.metadata.schema_classes.ForeignKeyConstraintClass(name, foreignFields, sourceFields, foreignDataset)

Bases: DictWrapper

Description of a foreign key constraint in a schema.

Parameters:

name (str)
foreignFields (List[str])
sourceFields (List[str])
foreignDataset (str)

property foreignDataset: str: Reference to the foreign dataset for ease of lookup

property foreignFields: List[str]: Fields the constraint maps to on the foreign dataset

property name: str: Name of the constraint, likely provided from the source

property sourceFields: List[str]: Fields the constraint maps to on the source dataset

class datahub.metadata.schema_classes.ForeignKeySpecClass(foreignKey)

Bases: DictWrapper

Description of a foreign key in a schema.

Parameters:: foreignKey (Union[DatasetFieldForeignKeyClass, UrnForeignKeyClass])

property foreignKey: DatasetFieldForeignKeyClass | UrnForeignKeyClass: Foreign key definition in metadata schema.

class datahub.metadata.schema_classes.FreshnessAssertionInfoClass(type, entity, schedule, filter=None)

Bases: DictWrapper

Attributes defining a Freshness Assertion.

Parameters:

type (Union[str, FreshnessAssertionTypeClass])
entity (str)
schedule (FreshnessAssertionScheduleClass)
filter (Optional[DatasetFilterClass])

property entity: str: The entity targeted by this Freshness check.

property filter: None | DatasetFilterClass: A definition of the specific filters that should be applied, when performing monitoring. If not provided, there is no filter, and the full table is under consideration.

property schedule: FreshnessAssertionScheduleClass: Produce FAILURE Assertion Result if the asset is not updated on the cadence and within the time range described by the schedule.

property type: str | FreshnessAssertionTypeClass: The type of the freshness assertion being monitored.

class datahub.metadata.schema_classes.FreshnessAssertionScheduleClass(type, cron=None, fixedInterval=None)

Bases: DictWrapper

Attributes defining a single Freshness schedule.

Parameters:

type (Union[str, FreshnessAssertionScheduleTypeClass])
cron (Optional[FreshnessCronScheduleClass])
fixedInterval (Optional[FixedIntervalScheduleClass])

property cron: None | FreshnessCronScheduleClass: A cron schedule. This field is required when type is CRON.

property fixedInterval: None | FixedIntervalScheduleClass: A fixed interval schedule. This field is required when type is FIXED_INTERVAL.

property type: str | FreshnessAssertionScheduleTypeClass

The type of a Freshness Assertion Schedule.

Once we support data-time-relative schedules (e.g. schedules relative to time partitions), we will add those schedule types here.

class datahub.metadata.schema_classes.FreshnessAssertionScheduleTypeClass

Bases: object

CRON = 'CRON'

FIXED_INTERVAL = 'FIXED_INTERVAL'

class datahub.metadata.schema_classes.FreshnessAssertionTypeClass

Bases: object

DATASET_CHANGE = 'DATASET_CHANGE'

DATA_JOB_RUN = 'DATA_JOB_RUN'

class datahub.metadata.schema_classes.FreshnessContractClass(assertion)

Bases: DictWrapper

A contract pertaining to the operational SLAs of a physical data asset

Parameters:: assertion (str)

property assertion: str: The assertion representing the SLA contract.

class datahub.metadata.schema_classes.FreshnessCronScheduleClass(cron, timezone, windowStartOffsetMs=None)

Bases: DictWrapper

Attributes defining a CRON-formatted schedule used for defining a freshness assertion.

Parameters:

cron (str)
timezone (str)
windowStartOffsetMs (Optional[int])

property cron: str: A cron-formatted execution interval, as a cron string, e.g. 1 * * * *

property timezone: str: Timezone in which the cron interval applies, e.g. America/Los Angeles

property windowStartOffsetMs: None | int

An optional offset in milliseconds to SUBTRACT from the timestamp generated by the cron schedule to generate the lower bounds of the “freshness window”, or the window of time in which an event must have occurred in order for the Freshness check to be considering passing.

If left empty, the start of the SLA window will be the _end_ of the previously evaluated Freshness window.

class datahub.metadata.schema_classes.GenericAspectClass(value, contentType)

Bases: DictWrapper

Generic record structure for serializing an Aspect

Parameters:

value (bytes)
contentType (str)

property contentType: str: The content type, which represents the fashion in which the aspect was serialized. The only type currently supported is application/json.

property value: bytes: The value of the aspect, serialized as bytes.

class datahub.metadata.schema_classes.GenericPayloadClass(value, contentType)

Bases: DictWrapper

Generic payload record structure for serializing a Platform Event.

Parameters:

value (bytes)
contentType (str)

property contentType: str: The content type, which represents the fashion in which the event was serialized. The only type currently supported is application/json.

property value: bytes: The value of the event, serialized as bytes.

class datahub.metadata.schema_classes.GlobalSettingsInfoClass(views=None)

Bases: _Aspect

DataHub Global platform settings. Careful - these should not be modified by the outside world!

Parameters:: views (Optional[GlobalViewsSettingsClass])

property views: None | GlobalViewsSettingsClass: Settings related to the Views Feature

class datahub.metadata.schema_classes.GlobalSettingsKeyClass(id)

Bases: _Aspect

Key for a Global Settings

Parameters:: id (str)

property id: str

li:globalSettings:0

Type:: Id for the settings. There should be only 1 global settings urn
Type:: urn

class datahub.metadata.schema_classes.GlobalTagsClass(tags)

Bases: _Aspect

Tag aspect used for applying tags to an entity

Parameters:: tags (List[TagAssociationClass])

property tags: List[TagAssociationClass]: Tags associated with a given entity

class datahub.metadata.schema_classes.GlobalViewsSettingsClass(defaultView=None)

Bases: DictWrapper

Settings for DataHub Views feature.

Parameters:: defaultView (Optional[str])

property defaultView: None | str: The default View for the instance, or organization.

class datahub.metadata.schema_classes.GlossaryNodeInfoClass(definition, parentNode=None, name=None, id=None)

Bases: _Aspect

Properties associated with a GlossaryNode

Parameters:

definition (str)
parentNode (Optional[str])
name (Optional[str])
id (Optional[str])

property definition: str: Definition of business node

property id: None | str: Optional id for the GlossaryNode

property name: None | str: Display name of the node

property parentNode: None | str: Parent node of the glossary term

class datahub.metadata.schema_classes.GlossaryNodeKeyClass(name)

Bases: _Aspect

Key for a GlossaryNode

Parameters:: name (str)

property name: str

class datahub.metadata.schema_classes.GlossaryNodeSnapshotClass(urn, aspects)

Bases: DictWrapper

A metadata snapshot for a specific GlossaryNode entity.

Parameters:

urn (str)
aspects (List[Union[GlossaryNodeKeyClass, GlossaryNodeInfoClass, OwnershipClass, StatusClass]])

property aspects: List[GlossaryNodeKeyClass | GlossaryNodeInfoClass | OwnershipClass | StatusClass]: The list of metadata aspects associated with the GlossaryNode. Depending on the use case, this can either be all, or a selection, of supported aspects.

property urn: str: URN for the entity the metadata snapshot is associated with.

class datahub.metadata.schema_classes.GlossaryRelatedTermsClass(isRelatedTerms=None, hasRelatedTerms=None, values=None, relatedTerms=None)

Bases: _Aspect

Has A / Is A lineage information about a glossary Term reporting the lineage

Parameters:

isRelatedTerms (Optional[List[str]])
hasRelatedTerms (Optional[List[str]])
values (Optional[List[str]])
relatedTerms (Optional[List[str]])

property hasRelatedTerms: None | List[str]: The relationship Has A with glossary term

property isRelatedTerms: None | List[str]: The relationship Is A with glossary term

property relatedTerms: None | List[str]: The relationship isRelatedTo with glossary term

property values: None | List[str]: The relationship Has Value with glossary term. These are fixed value a term has. For example a ColorEnum where RED, GREEN and YELLOW are fixed values.

class datahub.metadata.schema_classes.GlossaryTermAssociationClass(urn, context=None)

Bases: DictWrapper

Properties of an applied glossary term.

Parameters:

urn (str)
context (Optional[str])

property context: None | str: Additional context about the association

property urn: str: Urn of the applied glossary term

class datahub.metadata.schema_classes.GlossaryTermInfoClass(definition, termSource, customProperties=None, id=None, name=None, parentNode=None, sourceRef=None, sourceUrl=None, rawSchema=None)

Bases: _Aspect

Properties associated with a GlossaryTerm

Parameters:

definition (str)
termSource (str)
customProperties (Optional[Dict[str, str]])
id (Optional[str])
name (Optional[str])
parentNode (Optional[str])
sourceRef (Optional[str])
sourceUrl (Optional[str])
rawSchema (Optional[str])

property customProperties: Dict[str, str]: Custom property bag.

property definition: str: Definition of business term.

property id: None | str: Optional id for the term

property name: None | str: Display name of the term

property parentNode: None | str: Parent node of the glossary term

property rawSchema: None | str: Schema definition of the glossary term

property sourceRef: None | str: External Reference to the business-term

property sourceUrl: None | str

//spec.edmcouncil.org/fibo/ontology/FBC/FinancialInstruments/FinancialInstruments/CashInstrument.

Type:: The abstracted URL such as https

property termSource: str: Source of the Business Term (INTERNAL or EXTERNAL) with default value as INTERNAL

class datahub.metadata.schema_classes.GlossaryTermKeyClass(name)

Bases: _Aspect

Key for a GlossaryTerm

Parameters:: name (str)

property name: str: The term name, which serves as a unique id

class datahub.metadata.schema_classes.GlossaryTermSnapshotClass(urn, aspects)

Bases: DictWrapper

A metadata snapshot for a specific GlossaryTerm entity.

Parameters:

urn (str)
aspects (List[Union[GlossaryTermKeyClass, GlossaryTermInfoClass, OwnershipClass, StatusClass, BrowsePathsClass, GlossaryRelatedTermsClass]])

property aspects: List[GlossaryTermKeyClass | GlossaryTermInfoClass | OwnershipClass | StatusClass | BrowsePathsClass | GlossaryRelatedTermsClass]: The list of metadata aspects associated with the GlossaryTerm. Depending on the use case, this can either be all, or a selection, of supported aspects.

property urn: str: URN for the entity the metadata snapshot is associated with.

class datahub.metadata.schema_classes.GlossaryTermsClass(terms, auditStamp)

Bases: _Aspect

Related business terms information

Parameters:

terms (List[GlossaryTermAssociationClass])
auditStamp (AuditStampClass)

property auditStamp: AuditStampClass: Audit stamp containing who reported the related business term

property terms: List[GlossaryTermAssociationClass]: The related business terms

class datahub.metadata.schema_classes.GroupMembershipClass(groups)

Bases: _Aspect

Carries information about the CorpGroups a user is in.

Parameters:: groups (List[str])

property groups: List[str]

class datahub.metadata.schema_classes.HistogramClass(boundaries, heights)

Bases: DictWrapper

Parameters:

boundaries (List[str])
heights (List[float])

property boundaries: List[str]

property heights: List[float]

class datahub.metadata.schema_classes.IncrementingSegmentFieldTransformerClass(type, nativeType=None)

Bases: DictWrapper

The definition of the transformer function that should be applied to a given field / column value in a dataset in order to determine the segment or bucket that it belongs to, which in turn is used to evaluate volume assertions.

Parameters:

type (Union[str, IncrementingSegmentFieldTransformerTypeClass])
nativeType (Optional[str])

property nativeType: None | str: The ‘native’ transformer type, useful as a back door if a custom operator is required. This field is required if the type is NATIVE.

property type: str | IncrementingSegmentFieldTransformerTypeClass: A ‘standard’ transformer type. Note that not all source systems will support all operators.

class datahub.metadata.schema_classes.IncrementingSegmentFieldTransformerTypeClass

Bases: object

CEILING = 'CEILING'

FLOOR = 'FLOOR'

NATIVE = 'NATIVE'

TIMESTAMP_MS_TO_DATE = 'TIMESTAMP_MS_TO_DATE'

TIMESTAMP_MS_TO_HOUR = 'TIMESTAMP_MS_TO_HOUR'

TIMESTAMP_MS_TO_MINUTE = 'TIMESTAMP_MS_TO_MINUTE'

TIMESTAMP_MS_TO_MONTH = 'TIMESTAMP_MS_TO_MONTH'

TIMESTAMP_MS_TO_YEAR = 'TIMESTAMP_MS_TO_YEAR'

class datahub.metadata.schema_classes.IncrementingSegmentRowCountChangeClass(segment, type, operator, parameters)

Bases: DictWrapper

Attributes defining an INCREMENTING_SEGMENT_ROW_COUNT_CHANGE volume assertion.

Parameters:

segment (IncrementingSegmentSpecClass)
type (Union[str, AssertionValueChangeTypeClass])
operator (Union[str, AssertionStdOperatorClass])
parameters (AssertionStdParametersClass)

property operator: str | AssertionStdOperatorClass

The operator you’d like to apply to the row count value

Note that only numeric operators are valid inputs: GREATER_THAN, GREATER_THAN_OR_EQUAL_TO, EQUAL_TO, LESS_THAN, LESS_THAN_OR_EQUAL_TO, BETWEEN.

property parameters: AssertionStdParametersClass

The parameters you’d like to provide as input to the operator.

Note that only numeric parameter types are valid inputs: NUMBER.

property segment: IncrementingSegmentSpecClass: A specification of how the ‘segment’ can be derived using a column and an optional transformer function.

property type: str | AssertionValueChangeTypeClass

a fixed absolute value or a relative percentage.

Type:: The type of the value used to evaluate the assertion

class datahub.metadata.schema_classes.IncrementingSegmentRowCountTotalClass(segment, operator, parameters)

Bases: DictWrapper

Attributes defining an INCREMENTING_SEGMENT_ROW_COUNT_TOTAL volume assertion.

Parameters:

segment (IncrementingSegmentSpecClass)
operator (Union[str, AssertionStdOperatorClass])
parameters (AssertionStdParametersClass)

property operator: str | AssertionStdOperatorClass

The operator you’d like to apply.

Note that only numeric operators are valid inputs: GREATER_THAN, GREATER_THAN_OR_EQUAL_TO, EQUAL_TO, LESS_THAN, LESS_THAN_OR_EQUAL_TO, BETWEEN.

property parameters: AssertionStdParametersClass

The parameters you’d like to provide as input to the operator.

Note that only numeric parameter types are valid inputs: NUMBER.

property segment: IncrementingSegmentSpecClass: A specification of how the ‘segment’ can be derived using a column and an optional transformer function.

class datahub.metadata.schema_classes.IncrementingSegmentSpecClass(field, transformer=None)

Bases: DictWrapper

Core attributes required to identify an incrementing segment in a table. This type is mainly useful for tables that constantly increase with new rows being added on a particular cadence (e.g. fact or event tables)

An incrementing segment represents a logical chunk of data which is INSERTED into a dataset on a regular interval, along with the presence of a constantly-incrementing column value such as an event time, date partition, or last modified column.

An incrementing segment is principally identified by 2 key attributes combined:

A field or column that represents the incrementing value. New rows that are inserted will be identified using this column. Note that the value of this column may not by itself represent the “bucket” or the “segment” in which the row falls.

[Optional] An transformer function that may be applied to the selected column value in order to obtain the final “segment identifier” or “bucket identifier”. Rows that have the same value after applying the transformation will be grouped into the same segment, using which the final value (e.g. row count) will be determined.

Parameters:

field (SchemaFieldSpecClass)
transformer (Optional[IncrementingSegmentFieldTransformerClass])

property field: SchemaFieldSpecClass: The field to use to generate segments. It must be constantly incrementing as new rows are inserted.

property transformer: None | IncrementingSegmentFieldTransformerClass: Optional transformer function to apply to the field in order to obtain the final segment or bucket identifier. If not provided, then no operator will be applied to the field. (identity function)

class datahub.metadata.schema_classes.IngestionCheckpointStateClass(formatVersion, serde, payload=None)

Bases: DictWrapper

The checkpoint state object of a datahub ingestion run for a given job.

Parameters:

formatVersion (str)
serde (str)
payload (Optional[bytes])

property formatVersion: str: The version of the state format.

property payload: None | bytes: Opaque blob of the state representation.

property serde: str: The serialization/deserialization protocol.

class datahub.metadata.schema_classes.InputFieldClass(schemaFieldUrn, schemaField=None)

Bases: DictWrapper

Information about a field a chart or dashboard references

Parameters:

schemaFieldUrn (str)
schemaField (Optional[SchemaFieldClass])

property schemaField: None | SchemaFieldClass: Copied version of the referenced schema field object for indexing purposes

property schemaFieldUrn: str: Urn of the schema being referenced for lineage purposes

class datahub.metadata.schema_classes.InputFieldsClass(fields)

Bases: _Aspect

Information about the fields a chart or dashboard references

Parameters:: fields (List[InputFieldClass])

property fields: List[InputFieldClass]: List of fields being referenced

class datahub.metadata.schema_classes.InstitutionalMemoryClass(elements)

Bases: _Aspect

Institutional memory of an entity. This is a way to link to relevant documentation and provide description of the documentation. Institutional or tribal knowledge is very important for users to leverage the entity.

Parameters:: elements (List[InstitutionalMemoryMetadataClass])

property elements: List[InstitutionalMemoryMetadataClass]: List of records that represent institutional memory of an entity. Each record consists of a link, description, creator and timestamps associated with that record.

class datahub.metadata.schema_classes.InstitutionalMemoryMetadataClass(url, description, createStamp)

Bases: DictWrapper

Metadata corresponding to a record of institutional memory.

Parameters:

url (str)
description (str)
createStamp (AuditStampClass)

property createStamp: AuditStampClass: Audit stamp associated with creation of this record

property description: str: Description of the link.

property url: str: Link to an engineering design document or a wiki page.

class datahub.metadata.schema_classes.IntendedUseClass(primaryUses=None, primaryUsers=None, outOfScopeUses=None)

Bases: _Aspect

Intended Use for the ML Model

Parameters:

primaryUses (Optional[List[str]])
primaryUsers (Optional[List[Union[str, IntendedUserTypeClass]]])
outOfScopeUses (Optional[List[str]])

property outOfScopeUses: None | List[str]: Highlight technology that the MLModel might easily be confused with, or related contexts that users could try to apply the MLModel to.

property primaryUsers: None | List[str | IntendedUserTypeClass]: Primary Intended Users - For example, was the MLModel developed for entertainment purposes, for hobbyists, or enterprise solutions?

property primaryUses: None | List[str]: Primary Use cases for the MLModel.

class datahub.metadata.schema_classes.IntendedUserTypeClass

Bases: object

ENTERPRISE = 'ENTERPRISE'

ENTERTAINMENT = 'ENTERTAINMENT'

HOBBY = 'HOBBY'

class datahub.metadata.schema_classes.InviteTokenClass(token, role=None)

Bases: _Aspect

Aspect used to store invite tokens.

Parameters:

token (str)
role (Optional[str])

property role: None | str: The role that this invite token may be associated with

property token: str: The encrypted invite token.

class datahub.metadata.schema_classes.InviteTokenKeyClass(id)

Bases: _Aspect

Key for an InviteToken.

Parameters:: id (str)

property id: str: A unique id for the invite token.

class datahub.metadata.schema_classes.JobStatusClass

Bases: object

Job statuses

COMPLETED = 'COMPLETED'

FAILED = 'FAILED'

IN_PROGRESS = 'IN_PROGRESS'

SKIPPED = 'SKIPPED'

STARTING = 'STARTING'

STOPPED = 'STOPPED'

STOPPING = 'STOPPING'

UNKNOWN = 'UNKNOWN'

class datahub.metadata.schema_classes.KafkaAuditHeaderClass(time, server, appName, messageId, instance=None, auditVersion=None, fabricUrn=None, clusterConnectionString=None)

Bases: DictWrapper

This header records information about the context of an event as it is emitted into kafka and is intended to be used by the kafka audit application. For more information see go/kafkaauditheader

Parameters:

time (int)
server (str)
appName (str)
messageId (bytes)
instance (Optional[str])
auditVersion (Optional[int])
fabricUrn (Optional[str])
clusterConnectionString (Optional[str])

property appName: str: The name of the application from which the event is being emitted. see go/appname

property auditVersion: None | int

if the schema has an outer KafkaAuditHeader, use the outer audit header timestamp for bucketing; else if the EventHeader has an inner KafkaAuditHeader use that inner audit header’s timestamp for bucketing

Type:: The version that is being used for auditing. In version 0, the audit trail buckets events into 10 minute audit windows based on the EventHeader timestamp. In version 1, the audit trail buckets events as follows

property clusterConnectionString: None | str: This is a String that the client uses to establish some kind of connection with the Kafka cluster. The exact format of it depends on specific versions of clients and brokers. This information could potentially identify the fabric and cluster with which the client is producing to or consuming from.

property fabricUrn: None | str

fabric:{fabric_name}. See go/fabric.

Type:: The fabricUrn of the host from which the event is being emitted. Fabric Urn in the format of urn
Type:: li

property instance: None | str: The instance on the server from which the event is being emitted. e.g. i001

property messageId: bytes: A unique identifier for the message

property server: str: The fully qualified name of the host from which the event is being emitted.

property time: int: The time at which the event was emitted into kafka.

class datahub.metadata.schema_classes.KafkaSchemaClass(documentSchema, documentSchemaType=None, keySchema=None, keySchemaType=None)

Bases: DictWrapper

Schema holder for kafka schema.

Parameters:

documentSchema (str)
documentSchemaType (Optional[str])
keySchema (Optional[str])
keySchemaType (Optional[str])

property documentSchema: str: The native kafka document schema. This is a human readable avro document schema.

property documentSchemaType: None | str: The native kafka document schema type. This can be AVRO/PROTOBUF/JSON.

property keySchema: None | str: The native kafka key schema as retrieved from Schema Registry

property keySchemaType: None | str: The native kafka key schema type. This can be AVRO/PROTOBUF/JSON.

class datahub.metadata.schema_classes.KeyValueSchemaClass(keySchema, valueSchema)

Bases: DictWrapper

Schema text of a key-value store schema.

Parameters:

keySchema (str)
valueSchema (str)

property keySchema: str: The raw schema for the key in the key-value store.

property valueSchema: str: The raw schema for the value in the key-value store.

class datahub.metadata.schema_classes.MLFeatureDataTypeClass

Bases: object

MLFeature Data Type

AUDIO = 'AUDIO'

BINARY = 'BINARY'

BYTE = 'BYTE'

CONTINUOUS = 'CONTINUOUS'

COUNT = 'COUNT'

IMAGE = 'IMAGE'

INTERVAL = 'INTERVAL'

MAP = 'MAP'

NOMINAL = 'NOMINAL'

ORDINAL = 'ORDINAL'

SEQUENCE = 'SEQUENCE'

SET = 'SET'

TEXT = 'TEXT'

TIME = 'TIME'

UNKNOWN = 'UNKNOWN'

USELESS = 'USELESS'

VIDEO = 'VIDEO'

class datahub.metadata.schema_classes.MLFeatureKeyClass(featureNamespace, name)

Bases: _Aspect

Key for an MLFeature

Parameters:

featureNamespace (str)
name (str)

property featureNamespace: str: Namespace for the feature

property name: str: Name of the feature

class datahub.metadata.schema_classes.MLFeaturePropertiesClass(description=None, dataType=None, version=None, sources=None)

Bases: _Aspect

Properties associated with a MLFeature

Parameters:

description (Optional[str])
dataType (Union[None, str, MLFeatureDataTypeClass])
version (Optional[VersionTagClass])
sources (Optional[List[str]])

property dataType: None | str | MLFeatureDataTypeClass: Data Type of the MLFeature

property description: None | str: Documentation of the MLFeature

property sources: None | List[str]: Source of the MLFeature

property version: None | VersionTagClass: Version of the MLFeature

class datahub.metadata.schema_classes.MLFeatureSnapshotClass(urn, aspects)

Bases: DictWrapper

Parameters:

urn (str)
aspects (List[Union[MLFeatureKeyClass, MLFeaturePropertiesClass, OwnershipClass, InstitutionalMemoryClass, StatusClass, DeprecationClass, BrowsePathsClass, GlobalTagsClass, DataPlatformInstanceClass, BrowsePathsV2Class]])

property aspects: List[MLFeatureKeyClass | MLFeaturePropertiesClass | OwnershipClass | InstitutionalMemoryClass | StatusClass | DeprecationClass | BrowsePathsClass | GlobalTagsClass | DataPlatformInstanceClass | BrowsePathsV2Class]: The list of metadata aspects associated with the MLFeature. Depending on the use case, this can either be all, or a selection, of supported aspects.

property urn: str: URN for the entity the metadata snapshot is associated with.

class datahub.metadata.schema_classes.MLFeatureTableKeyClass(platform, name)

Bases: _Aspect

Key for an MLFeatureTable

Parameters:

platform (str)
name (str)

property name: str: Name of the feature table

property platform: str: Data platform urn associated with the feature table

class datahub.metadata.schema_classes.MLFeatureTablePropertiesClass(customProperties=None, description=None, mlFeatures=None, mlPrimaryKeys=None)

Bases: _Aspect

Properties associated with a MLFeatureTable

Parameters:

customProperties (Optional[Dict[str, str]])
description (Optional[str])
mlFeatures (Optional[List[str]])
mlPrimaryKeys (Optional[List[str]])

property customProperties: Dict[str, str]: Custom property bag.

property description: None | str: Documentation of the MLFeatureTable

property mlFeatures: None | List[str]: List of features contained in the feature table

property mlPrimaryKeys: None | List[str]: List of primary keys in the feature table (if multiple, assumed to act as a composite key)

class datahub.metadata.schema_classes.MLFeatureTableSnapshotClass(urn, aspects)

Bases: DictWrapper

Parameters:

urn (str)
aspects (List[Union[MLFeatureTableKeyClass, MLFeatureTablePropertiesClass, OwnershipClass, InstitutionalMemoryClass, StatusClass, DeprecationClass, BrowsePathsClass, GlobalTagsClass, DataPlatformInstanceClass, BrowsePathsV2Class]])

property aspects: List[MLFeatureTableKeyClass | MLFeatureTablePropertiesClass | OwnershipClass | InstitutionalMemoryClass | StatusClass | DeprecationClass | BrowsePathsClass | GlobalTagsClass | DataPlatformInstanceClass | BrowsePathsV2Class]: The list of metadata aspects associated with the MLFeatureTable. Depending on the use case, this can either be all, or a selection, of supported aspects.

property urn: str: URN for the entity the metadata snapshot is associated with.

class datahub.metadata.schema_classes.MLHyperParamClass(name, description=None, value=None, createdAt=None)

Bases: _Aspect

Properties associated with an ML Hyper Param

Parameters:

name (str)
description (Optional[str])
value (Optional[str])
createdAt (Optional[int])

property createdAt: None | int: Date when the MLHyperParam was developed

property description: None | str: Documentation of the MLHyperParam

property name: str: Name of the MLHyperParam

property value: None | str: The value of the MLHyperParam

class datahub.metadata.schema_classes.MLMetricClass(name, description=None, value=None, createdAt=None)

Bases: _Aspect

Properties associated with an ML Metric

Parameters:

name (str)
description (Optional[str])
value (Optional[str])
createdAt (Optional[int])

property createdAt: None | int: Date when the mlMetric was developed

property description: None | str: Documentation of the mlMetric

property name: str: Name of the mlMetric

property value: None | str: The value of the mlMetric

class datahub.metadata.schema_classes.MLModelDeploymentKeyClass(platform, name, origin)

Bases: _Aspect

Key for an ML model deployment

Parameters:

platform (str)
name (str)
origin (Union[str, FabricTypeClass])

property name: str: Name of the MLModelDeployment

property origin: str | FabricTypeClass: Fabric type where model Deployment belongs to or where it was generated

property platform: str: Standardized platform urn for the model Deployment

class datahub.metadata.schema_classes.MLModelDeploymentPropertiesClass(customProperties=None, externalUrl=None, description=None, createdAt=None, version=None, status=None)

Bases: _Aspect

Properties associated with an ML Model Deployment

Parameters:

customProperties (Optional[Dict[str, str]])
externalUrl (Optional[str])
description (Optional[str])
createdAt (Optional[int])
version (Optional[VersionTagClass])
status (Union[None, str, DeploymentStatusClass])

property createdAt: None | int: Date when the MLModelDeployment was developed

property customProperties: Dict[str, str]: Custom property bag.

property description: None | str: Documentation of the MLModelDeployment

property externalUrl: None | str: URL where the reference exist

property status: None | str | DeploymentStatusClass: Status of the deployment

property version: None | VersionTagClass: Version of the MLModelDeployment

class datahub.metadata.schema_classes.MLModelDeploymentSnapshotClass(urn, aspects)

Bases: DictWrapper

Parameters:

urn (str)
aspects (List[Union[MLModelDeploymentKeyClass, MLModelDeploymentPropertiesClass, OwnershipClass, StatusClass, DeprecationClass, GlobalTagsClass, DataPlatformInstanceClass]])

property aspects: List[MLModelDeploymentKeyClass | MLModelDeploymentPropertiesClass | OwnershipClass | StatusClass | DeprecationClass | GlobalTagsClass | DataPlatformInstanceClass]: The list of metadata aspects associated with the MLModelDeployment. Depending on the use case, this can either be all, or a selection, of supported aspects.

property urn: str: URN for the entity the metadata snapshot is associated with.

class datahub.metadata.schema_classes.MLModelFactorPromptsClass(relevantFactors=None, evaluationFactors=None)

Bases: _Aspect

Prompts which affect the performance of the MLModel

Parameters:

relevantFactors (Optional[List[MLModelFactorsClass]])
evaluationFactors (Optional[List[MLModelFactorsClass]])

property evaluationFactors: None | List[MLModelFactorsClass]: Which factors are being reported, and why were these chosen?

property relevantFactors: None | List[MLModelFactorsClass]: What are foreseeable salient factors for which MLModel performance may vary, and how were these determined?

class datahub.metadata.schema_classes.MLModelFactorsClass(groups=None, instrumentation=None, environment=None)

Bases: DictWrapper

Factors affecting the performance of the MLModel.

Parameters:

groups (Optional[List[str]])
instrumentation (Optional[List[str]])
environment (Optional[List[str]])

property environment: None | List[str]: A further factor affecting MLModel performance is the environment in which it is deployed.

property groups: None | List[str]: Groups refers to distinct categories with similar characteristics that are present in the evaluation data instances. For human-centric machine learning MLModels, groups are people who share one or multiple characteristics.

property instrumentation: None | List[str]: The performance of a MLModel can vary depending on what instruments were used to capture the input to the MLModel. For example, a face detection model may perform differently depending on the camera’s hardware and software, including lens, image stabilization, high dynamic range techniques, and background blurring for portrait mode.

class datahub.metadata.schema_classes.MLModelGroupKeyClass(platform, name, origin)

Bases: _Aspect

Key for an ML model group

Parameters:

platform (str)
name (str)
origin (Union[str, FabricTypeClass])

property name: str: Name of the MLModelGroup

property origin: str | FabricTypeClass: Fabric type where model group belongs to or where it was generated

property platform: str: Standardized platform urn for the model group

class datahub.metadata.schema_classes.MLModelGroupPropertiesClass(customProperties=None, description=None, createdAt=None, version=None)

Bases: _Aspect

Properties associated with an ML Model Group

Parameters:

customProperties (Optional[Dict[str, str]])
description (Optional[str])
createdAt (Optional[int])
version (Optional[VersionTagClass])

property createdAt: None | int: Date when the MLModelGroup was developed

property customProperties: Dict[str, str]: Custom property bag.

property description: None | str: Documentation of the MLModelGroup

property version: None | VersionTagClass: Version of the MLModelGroup

class datahub.metadata.schema_classes.MLModelGroupSnapshotClass(urn, aspects)

Bases: DictWrapper

Parameters:

urn (str)
aspects (List[Union[MLModelGroupKeyClass, MLModelGroupPropertiesClass, OwnershipClass, StatusClass, DeprecationClass, BrowsePathsClass, GlobalTagsClass, DataPlatformInstanceClass, BrowsePathsV2Class]])

property aspects: List[MLModelGroupKeyClass | MLModelGroupPropertiesClass | OwnershipClass | StatusClass | DeprecationClass | BrowsePathsClass | GlobalTagsClass | DataPlatformInstanceClass | BrowsePathsV2Class]: The list of metadata aspects associated with the MLModelGroup. Depending on the use case, this can either be all, or a selection, of supported aspects.

property urn: str: URN for the entity the metadata snapshot is associated with.

class datahub.metadata.schema_classes.MLModelKeyClass(platform, name, origin)

Bases: _Aspect

Key for an ML model

Parameters:

platform (str)
name (str)
origin (Union[str, FabricTypeClass])

property name: str: Name of the MLModel

property origin: str | FabricTypeClass: Fabric type where model belongs to or where it was generated

property platform: str: Standardized platform urn for the model

class datahub.metadata.schema_classes.MLModelPropertiesClass(customProperties=None, externalUrl=None, description=None, date=None, version=None, type=None, hyperParameters=None, hyperParams=None, trainingMetrics=None, onlineMetrics=None, mlFeatures=None, tags=None, deployments=None, trainingJobs=None, downstreamJobs=None, groups=None)

Bases: _Aspect

Properties associated with a ML Model

Parameters:

customProperties (Optional[Dict[str, str]])
externalUrl (Optional[str])
description (Optional[str])
date (Optional[int])
version (Optional[VersionTagClass])
type (Optional[str])
hyperParameters (Optional[Dict[str, Union[str, int, float, bool]]])
hyperParams (Optional[List[MLHyperParamClass]])
trainingMetrics (Optional[List[MLMetricClass]])
onlineMetrics (Optional[List[MLMetricClass]])
mlFeatures (Optional[List[str]])
tags (Optional[List[str]])
deployments (Optional[List[str]])
trainingJobs (Optional[List[str]])
downstreamJobs (Optional[List[str]])
groups (Optional[List[str]])

property customProperties: Dict[str, str]: Custom property bag.

property date: None | int: Date when the MLModel was developed

property deployments: None | List[str]: Deployments for the MLModel

property description: None | str: Documentation of the MLModel

property downstreamJobs: None | List[str]: List of jobs (if any) that use the model

property externalUrl: None | str: URL where the reference exist

property groups: None | List[str]: Groups the model belongs to

property hyperParameters: None | Dict[str, str | int | float | bool]

Hyper Parameters of the MLModel

NOTE: these are deprecated in favor of hyperParams

property hyperParams: None | List[MLHyperParamClass]: Hyperparameters of the MLModel

property mlFeatures: None | List[str]: List of features used for MLModel training

property onlineMetrics: None | List[MLMetricClass]: Metrics of the MLModel used in production

property tags: List[str]: Tags for the MLModel

property trainingJobs: None | List[str]: List of jobs (if any) used to train the model

property trainingMetrics: None | List[MLMetricClass]: Metrics of the MLModel used in training

property type: None | str: Type of Algorithm or MLModel such as whether it is a Naive Bayes classifier, Convolutional Neural Network, etc

property version: None | VersionTagClass: Version of the MLModel

class datahub.metadata.schema_classes.MLModelSnapshotClass(urn, aspects)

Bases: DictWrapper

MLModel Snapshot entity details.

property aspects: List[MLModelKeyClass | OwnershipClass | MLModelPropertiesClass | IntendedUseClass | MLModelFactorPromptsClass | MetricsClass | EvaluationDataClass | TrainingDataClass | QuantitativeAnalysesClass | EthicalConsiderationsClass | CaveatsAndRecommendationsClass | InstitutionalMemoryClass | SourceCodeClass | StatusClass | CostClass | DeprecationClass | BrowsePathsClass | GlobalTagsClass | DataPlatformInstanceClass | BrowsePathsV2Class]: The list of metadata aspects associated with the MLModel. Depending on the use case, this can either be all, or a selection, of supported aspects.

property urn: str: URN for the entity the metadata snapshot is associated with.

class datahub.metadata.schema_classes.MLPrimaryKeyKeyClass(featureNamespace, name)

Bases: _Aspect

Key for an MLPrimaryKey

Parameters:

featureNamespace (str)
name (str)

property featureNamespace: str: Namespace for the primary key

property name: str: Name of the primary key

class datahub.metadata.schema_classes.MLPrimaryKeyPropertiesClass(sources, description=None, dataType=None, version=None)

Bases: _Aspect

Properties associated with a MLPrimaryKey

Parameters:

sources (List[str])
description (Optional[str])
dataType (Union[None, str, MLFeatureDataTypeClass])
version (Optional[VersionTagClass])

property dataType: None | str | MLFeatureDataTypeClass: Data Type of the MLPrimaryKey

property description: None | str: Documentation of the MLPrimaryKey

property sources: List[str]: Source of the MLPrimaryKey

property version: None | VersionTagClass: Version of the MLPrimaryKey

class datahub.metadata.schema_classes.MLPrimaryKeySnapshotClass(urn, aspects)

Bases: DictWrapper

Parameters:

urn (str)
aspects (List[Union[MLPrimaryKeyKeyClass, MLPrimaryKeyPropertiesClass, OwnershipClass, InstitutionalMemoryClass, StatusClass, DeprecationClass, GlobalTagsClass, DataPlatformInstanceClass]])

property aspects: List[MLPrimaryKeyKeyClass | MLPrimaryKeyPropertiesClass | OwnershipClass | InstitutionalMemoryClass | StatusClass | DeprecationClass | GlobalTagsClass | DataPlatformInstanceClass]: The list of metadata aspects associated with the MLPrimaryKey. Depending on the use case, this can either be all, or a selection, of supported aspects.

property urn: str: URN for the entity the metadata snapshot is associated with.

class datahub.metadata.schema_classes.MapTypeClass(keyType=None, valueType=None)

Bases: DictWrapper

Map field type.

Parameters:

keyType (Optional[str])
valueType (Optional[str])

property keyType: None | str: Key type in a map

property valueType: None | str: Type of the value in a map

class datahub.metadata.schema_classes.MediaClass(type, location)

Bases: DictWrapper

Carries information about which roles a user is assigned to.

Parameters:

type (Union[str, MediaTypeClass])
location (str)

property location: str: Where the media content is stored.

property type: str | MediaTypeClass: Type of content the Media is storing, e.g. image, video, etc.

class datahub.metadata.schema_classes.MediaTypeClass

Bases: object

Enum defining the type of content a Media object holds.

IMAGE = 'IMAGE'

class datahub.metadata.schema_classes.MetadataChangeEventClass(proposedSnapshot, auditHeader=None, proposedDelta=None, systemMetadata=None)

Bases: DictWrapper

Kafka event for proposing a metadata change for an entity. A corresponding MetadataAuditEvent is emitted when the change is accepted and committed, otherwise a FailedMetadataChangeEvent will be emitted instead.

Parameters:

proposedSnapshot (Union[ChartSnapshotClass, CorpGroupSnapshotClass, CorpUserSnapshotClass, DashboardSnapshotClass, DataFlowSnapshotClass, DataJobSnapshotClass, DatasetSnapshotClass, DataProcessSnapshotClass, DataPlatformSnapshotClass, MLModelSnapshotClass, MLPrimaryKeySnapshotClass, MLFeatureSnapshotClass, MLFeatureTableSnapshotClass, MLModelDeploymentSnapshotClass, MLModelGroupSnapshotClass, TagSnapshotClass, GlossaryTermSnapshotClass, GlossaryNodeSnapshotClass, DataHubPolicySnapshotClass, SchemaFieldSnapshotClass, DataHubRetentionSnapshotClass])
auditHeader (Optional[KafkaAuditHeaderClass])
proposedDelta (None)
systemMetadata (Optional[SystemMetadataClass])

property auditHeader: None | KafkaAuditHeaderClass: Kafka audit header. See go/kafkaauditheader for more info.

property proposedDelta: None: Delta of the proposed metadata partial update.

property proposedSnapshot: ChartSnapshotClass | CorpGroupSnapshotClass | CorpUserSnapshotClass | DashboardSnapshotClass | DataFlowSnapshotClass | DataJobSnapshotClass | DatasetSnapshotClass | DataProcessSnapshotClass | DataPlatformSnapshotClass | MLModelSnapshotClass | MLPrimaryKeySnapshotClass | MLFeatureSnapshotClass | MLFeatureTableSnapshotClass | MLModelDeploymentSnapshotClass | MLModelGroupSnapshotClass | TagSnapshotClass | GlossaryTermSnapshotClass | GlossaryNodeSnapshotClass | DataHubPolicySnapshotClass | SchemaFieldSnapshotClass | DataHubRetentionSnapshotClass: Snapshot of the proposed metadata change. Include only the aspects affected by the change in the snapshot.

property systemMetadata: None | SystemMetadataClass: Metadata around how the snapshot was ingested

class datahub.metadata.schema_classes.MetadataChangeLogClass(entityType, changeType, auditHeader=None, entityUrn=None, entityKeyAspect=None, aspectName=None, aspect=None, systemMetadata=None, previousAspectValue=None, previousSystemMetadata=None, created=None)

Bases: DictWrapper

Kafka event for capturing update made to an entity’s metadata.

Parameters:

entityType (str)
changeType (Union[str, ChangeTypeClass])
auditHeader (Optional[KafkaAuditHeaderClass])
entityUrn (Optional[str])
entityKeyAspect (Optional[GenericAspectClass])
aspectName (Optional[str])
aspect (Optional[GenericAspectClass])
systemMetadata (Optional[SystemMetadataClass])
previousAspectValue (Optional[GenericAspectClass])
previousSystemMetadata (Optional[SystemMetadataClass])
created (Optional[AuditStampClass])

property aspect: None | GenericAspectClass: The value of the new aspect.

property aspectName: None | str: Aspect of the entity being written to Not filling this out implies that the writer wants to affect the entire entity Note: This is only valid for CREATE, UPSERT, and DELETE operations.

property auditHeader: None | KafkaAuditHeaderClass: Kafka audit header. Currently remains unused in the open source.

property changeType: str | ChangeTypeClass: Type of change being proposed

property created: None | AuditStampClass: An audit stamp detailing who and when the aspect was changed by. Required for all intents and purposes.

property entityKeyAspect: None | GenericAspectClass: Key aspect of the entity being written

property entityType: str: Type of the entity being written to

property entityUrn: None | str: Urn of the entity being written

property previousAspectValue: None | GenericAspectClass: The previous value of the aspect that has changed.

property previousSystemMetadata: None | SystemMetadataClass: The previous value of the system metadata field that has changed.

property systemMetadata: None | SystemMetadataClass: A string->string map of custom properties that one might want to attach to an event

class datahub.metadata.schema_classes.MetadataChangeProposalClass(entityType, changeType, auditHeader=None, entityUrn=None, entityKeyAspect=None, aspectName=None, aspect=None, systemMetadata=None)

Bases: DictWrapper

Kafka event for proposing a metadata change for an entity. A corresponding MetadataChangeLog is emitted when the change is accepted and committed, otherwise a FailedMetadataChangeProposal will be emitted instead.

Parameters:

entityType (str)
changeType (Union[str, ChangeTypeClass])
auditHeader (Optional[KafkaAuditHeaderClass])
entityUrn (Optional[str])
entityKeyAspect (Optional[GenericAspectClass])
aspectName (Optional[str])
aspect (Optional[GenericAspectClass])
systemMetadata (Optional[SystemMetadataClass])

property aspect: None | GenericAspectClass: The value of the new aspect.

property aspectName: None | str: Aspect of the entity being written to Not filling this out implies that the writer wants to affect the entire entity Note: This is only valid for CREATE, UPSERT, and DELETE operations.

property auditHeader: None | KafkaAuditHeaderClass: Kafka audit header. Currently remains unused in the open source.

property changeType: str | ChangeTypeClass: Type of change being proposed

property entityKeyAspect: None | GenericAspectClass: Key aspect of the entity being written

property entityType: str: Type of the entity being written to

property entityUrn: None | str: Urn of the entity being written

property systemMetadata: None | SystemMetadataClass: A string->string map of custom properties that one might want to attach to an event

class datahub.metadata.schema_classes.MetricsClass(performanceMeasures=None, decisionThreshold=None)

Bases: _Aspect

Metrics to be featured for the MLModel.

Parameters:

performanceMeasures (Optional[List[str]])
decisionThreshold (Optional[List[str]])

property decisionThreshold: None | List[str]: Decision Thresholds used (if any)?

property performanceMeasures: None | List[str]: Measures of MLModel performance

class datahub.metadata.schema_classes.MySqlDDLClass(tableSchema)

Bases: DictWrapper

Schema holder for MySql data definition language that describes an MySql table.

Parameters:: tableSchema (str)

property tableSchema: str: The native schema in the dataset’s platform. This is a human readable (json blob) table schema.

class datahub.metadata.schema_classes.NativeGroupMembershipClass(nativeGroups)

Bases: _Aspect

Carries information about the native CorpGroups a user is in.

Parameters:: nativeGroups (List[str])

property nativeGroups: List[str]

class datahub.metadata.schema_classes.NotebookCellClass(type, textCell=None, queryCell=None, chartCell=None)

Bases: DictWrapper

A record of all supported cells for a Notebook. Only one type of cell will be non-null.

Parameters:

type (Union[str, NotebookCellTypeClass])
textCell (Optional[TextCellClass])
queryCell (Optional[QueryCellClass])
chartCell (Optional[ChartCellClass])

property chartCell: None | ChartCellClass: The chart cell content. The will be non-null only when all other cell field is null.

property queryCell: None | QueryCellClass: The query cell content. The will be non-null only when all other cell field is null.

property textCell: None | TextCellClass: The text cell content. The will be non-null only when all other cell field is null.

property type: str | NotebookCellTypeClass: The type of this Notebook cell

class datahub.metadata.schema_classes.NotebookCellTypeClass

Bases: object

Type of Notebook Cell

CHART_CELL = 'CHART_CELL'

QUERY_CELL = 'QUERY_CELL'

TEXT_CELL = 'TEXT_CELL'

class datahub.metadata.schema_classes.NotebookContentClass(cells=None)

Bases: _Aspect

Content in a Notebook Note: This is IN BETA version

Parameters:: cells (Optional[List[NotebookCellClass]])

property cells: List[NotebookCellClass]: The content of a Notebook which is composed by a list of NotebookCell

class datahub.metadata.schema_classes.NotebookInfoClass(title, changeAuditStamps, customProperties=None, externalUrl=None, description=None)

Bases: _Aspect

Information about a Notebook Note: This is IN BETA version

Parameters:

title (str)
changeAuditStamps (ChangeAuditStampsClass)
customProperties (Optional[Dict[str, str]])
externalUrl (Optional[str])
description (Optional[str])

property changeAuditStamps: ChangeAuditStampsClass: Captures information about who created/last modified/deleted this Notebook and when

property customProperties: Dict[str, str]: Custom property bag.

property description: None | str: Detailed description about the Notebook

property externalUrl: None | str: URL where the reference exist

property title: str: Title of the Notebook

class datahub.metadata.schema_classes.NotebookKeyClass(notebookTool, notebookId)

Bases: _Aspect

Key for a Notebook

Parameters:

notebookTool (str)
notebookId (str)

property notebookId: str: Unique id for the Notebook. This id should be globally unique for a Notebook tool even when there are multiple deployments of it. As an example, Notebook URL could be used here for QueryBook such as ‘querybook.com/notebook/773’

property notebookTool: str: The name of the Notebook tool such as QueryBook, etc.

class datahub.metadata.schema_classes.NullTypeClass

Bases: DictWrapper

Null field type.

class datahub.metadata.schema_classes.NumberTypeClass

Bases: DictWrapper

Number data type: long, integer, short, etc..

class datahub.metadata.schema_classes.OperationClass(timestampMillis, operationType, lastUpdatedTimestamp, eventGranularity=None, partitionSpec=None, messageId=None, actor=None, customOperationType=None, numAffectedRows=None, affectedDatasets=None, sourceType=None, customProperties=None)

Bases: _Aspect

Operational info for an entity.

Parameters:

timestampMillis (int)
operationType (Union[str, OperationTypeClass])
lastUpdatedTimestamp (int)
eventGranularity (Optional[TimeWindowSizeClass])
partitionSpec (Optional[PartitionSpecClass])
messageId (Optional[str])
actor (Optional[str])
customOperationType (Optional[str])
numAffectedRows (Optional[int])
affectedDatasets (Optional[List[str]])
sourceType (Union[None, str, OperationSourceTypeClass])
customProperties (Optional[Dict[str, str]])

ASPECT_TYPE: ClassVar[str] = 'timeseries'

property actor: None | str: Actor who issued this operation.

property affectedDatasets: None | List[str]: Which other datasets were affected by this operation.

property customOperationType: None | str: A custom type of operation. Required if operationType is CUSTOM.

property customProperties: None | Dict[str, str]: Custom properties

property eventGranularity: None | TimeWindowSizeClass: Granularity of the event if applicable

property lastUpdatedTimestamp: int: The time at which the operation occurred. Would be better named ‘operationTime’

property messageId: None | str: The optional messageId, if provided serves as a custom user-defined unique identifier for an aspect value.

property numAffectedRows: None | int: How many rows were affected by this operation.

property operationType: str | OperationTypeClass: Operation type of change.

property partitionSpec: PartitionSpecClass | None: The optional partition specification.

property sourceType: None | str | OperationSourceTypeClass: Source Type

property timestampMillis: int: The event timestamp field as epoch at UTC in milli seconds.

class datahub.metadata.schema_classes.OperationSourceTypeClass

Bases: object

The source of an operation

DATA_PLATFORM = 'DATA_PLATFORM'

DATA_PROCESS = 'DATA_PROCESS'

class datahub.metadata.schema_classes.OperationTypeClass

Bases: object

Enum to define the operation type when an entity changes.

ALTER = 'ALTER'

CREATE = 'CREATE'

CUSTOM = 'CUSTOM'

DELETE = 'DELETE'

DROP = 'DROP'

INSERT = 'INSERT'

UNKNOWN = 'UNKNOWN'

UPDATE = 'UPDATE'

class datahub.metadata.schema_classes.OracleDDLClass(tableSchema)

Bases: DictWrapper

Schema holder for oracle data definition language that describes an oracle table.

Parameters:: tableSchema (str)

property tableSchema: str: The native schema in the dataset’s platform. This is a human readable (json blob) table schema.

class datahub.metadata.schema_classes.OrcSchemaClass(schema)

Bases: DictWrapper

Schema text of an ORC schema.

Parameters:: schema (str)

property schema: str: The native schema for ORC file format.

class datahub.metadata.schema_classes.OriginClass(type, externalType=None)

Bases: _Aspect

Carries information about where an entity originated from.

Parameters:

type (Union[str, OriginTypeClass])
externalType (Optional[str])

property externalType: None | str: Only populated if type is EXTERNAL. The externalType of the entity, such as the name of the identity provider.

property type: str | OriginTypeClass: Where an entity originated from. Either NATIVE or EXTERNAL.

class datahub.metadata.schema_classes.OriginTypeClass

Bases: object

Enum to define where an entity originated from.

EXTERNAL = 'EXTERNAL'

NATIVE = 'NATIVE'

class datahub.metadata.schema_classes.OtherSchemaClass(rawSchema)

Bases: DictWrapper

Schema holder for undefined schema types.

Parameters:: rawSchema (str)

property rawSchema: str: The native schema in the dataset’s platform.

class datahub.metadata.schema_classes.OwnerClass(owner, type, typeUrn=None, source=None)

Bases: DictWrapper

Ownership information

Parameters:

owner (str)
type (Union[str, OwnershipTypeClass])
typeUrn (Optional[str])
source (Optional[OwnershipSourceClass])

property owner: str

corpuser:ldap, urn:li:corpGroup:group_name, and urn:li:multiProduct:mp_name (Caveat: only corpuser is currently supported in the frontend.)

Type:: Owner URN, e.g. urn
Type:: li

property source: None | OwnershipSourceClass: Source information for the ownership

property type: str | OwnershipTypeClass: The type of the ownership

property typeUrn: None | str: The type of the ownership Urn of type O

class datahub.metadata.schema_classes.OwnershipClass(owners, lastModified=None)

Bases: _Aspect

Ownership information of an entity.

Parameters:

owners (List[OwnerClass])
lastModified (Optional[AuditStampClass])

property lastModified: AuditStampClass: Audit stamp containing who last modified the record and when. A value of 0 in the time field indicates missing data.

property owners: List[OwnerClass]: List of owners of the entity.

class datahub.metadata.schema_classes.OwnershipSourceClass(type, url=None)

Bases: DictWrapper

Source/provider of the ownership information

Parameters:

type (Union[str, OwnershipSourceTypeClass])
url (Optional[str])

property type: str | OwnershipSourceTypeClass: The type of the source

property url: None | str: A reference URL for the source

class datahub.metadata.schema_classes.OwnershipSourceTypeClass

Bases: object

AUDIT = 'AUDIT'

DATABASE = 'DATABASE'

FILE_SYSTEM = 'FILE_SYSTEM'

ISSUE_TRACKING_SYSTEM = 'ISSUE_TRACKING_SYSTEM'

MANUAL = 'MANUAL'

OTHER = 'OTHER'

SERVICE = 'SERVICE'

SOURCE_CONTROL = 'SOURCE_CONTROL'

class datahub.metadata.schema_classes.OwnershipTypeClass

Bases: object

Asset owner types

BUSINESS_OWNER = 'BUSINESS_OWNER'

CONSUMER = 'CONSUMER'

CUSTOM = 'CUSTOM'

DATAOWNER = 'DATAOWNER'

DATA_STEWARD = 'DATA_STEWARD'

DELEGATE = 'DELEGATE'

DEVELOPER = 'DEVELOPER'

NONE = 'NONE'

PRODUCER = 'PRODUCER'

STAKEHOLDER = 'STAKEHOLDER'

TECHNICAL_OWNER = 'TECHNICAL_OWNER'

class datahub.metadata.schema_classes.OwnershipTypeInfoClass(name, created, lastModified, description=None)

Bases: _Aspect

Information about an ownership type

Parameters:

name (str)
created (AuditStampClass)
lastModified (AuditStampClass)
description (Optional[str])

property created: AuditStampClass: Audit stamp capturing the time and actor who created the Ownership Type.

property description: None | str: Description of the Ownership Type

property lastModified: AuditStampClass: Audit stamp capturing the time and actor who last modified the Ownership Type.

property name: str: Display name of the Ownership Type

class datahub.metadata.schema_classes.OwnershipTypeKeyClass(id)

Bases: _Aspect

Key for a Ownership Type

Parameters:: id (str)

property id: str: Unique ID for the data ownership type name i.e. Business Owner, Data Steward, Technical Owner, etc.. Should be separate from the name used for displaying an Ownership Type.

class datahub.metadata.schema_classes.ParametersClass

Bases: DictWrapper

Arbitrary key-value parameters for an Entity Change Event. (any record).

class datahub.metadata.schema_classes.PartitionSpecClass(partition, type=None, timePartition=None)

Bases: DictWrapper

Defines how the data is partitioned

Parameters:

partition (str)
type (Union[str, PartitionTypeClass, None])
timePartition (Optional[TimeWindowClass])

property partition: str: String representation of the partition

property timePartition: None | TimeWindowClass: Time window of the partition if applicable

property type: str | PartitionTypeClass

class datahub.metadata.schema_classes.PartitionTypeClass

Bases: object

FULL_TABLE = 'FULL_TABLE'

PARTITION = 'PARTITION'

QUERY = 'QUERY'

class datahub.metadata.schema_classes.PlatformEventClass(header, name, payload)

Bases: DictWrapper

A DataHub Platform Event.

Parameters:

header (PlatformEventHeaderClass)
name (str)
payload (GenericPayloadClass)

property header: PlatformEventHeaderClass: Header information stored with the event.

property name: str: The name of the event, e.g. the type of event. For example, ‘notificationRequestEvent’, ‘entityChangeEvent’

property payload: GenericPayloadClass: The event payload.

class datahub.metadata.schema_classes.PlatformEventHeaderClass(timestampMillis)

Bases: DictWrapper

A header included with each DataHub platform event.

Parameters:: timestampMillis (int)

property timestampMillis: int: The event timestamp field as epoch at UTC in milli seconds.

class datahub.metadata.schema_classes.PlatformTypeClass

Bases: object

Platform types available at LinkedIn

FILE_SYSTEM = 'FILE_SYSTEM'

KEY_VALUE_STORE = 'KEY_VALUE_STORE'

MESSAGE_BROKER = 'MESSAGE_BROKER'

OBJECT_STORE = 'OBJECT_STORE'

OLAP_DATASTORE = 'OLAP_DATASTORE'

OTHERS = 'OTHERS'

QUERY_ENGINE = 'QUERY_ENGINE'

RELATIONAL_DB = 'RELATIONAL_DB'

SEARCH_ENGINE = 'SEARCH_ENGINE'

class datahub.metadata.schema_classes.PolicyMatchConditionClass

Bases: object

The matching condition in a filter criterion

EQUALS = 'EQUALS'

class datahub.metadata.schema_classes.PolicyMatchCriterionClass(field, values, condition=None)

Bases: DictWrapper

A criterion for matching a field with given value

Parameters:

field (str)
values (List[str])
condition (Union[str, PolicyMatchConditionClass, None])

property condition: str | PolicyMatchConditionClass: The condition for the criterion

property field: str: The name of the field that the criterion refers to

property values: List[str]: Values. Matches criterion if any one of the values matches condition (OR-relationship)

class datahub.metadata.schema_classes.PolicyMatchFilterClass(criteria)

Bases: DictWrapper

The filter for specifying the resource or actor to apply privileges to

Parameters:: criteria (List[PolicyMatchCriterionClass])

property criteria: List[PolicyMatchCriterionClass]: A list of criteria to apply conjunctively (so all criteria must pass)

class datahub.metadata.schema_classes.PostContentClass(title, type, description=None, link=None, media=None)

Bases: DictWrapper

Content stored inside a Post.

Parameters:

title (str)
type (Union[str, PostContentTypeClass])
description (Optional[str])
link (Optional[str])
media (Optional[MediaClass])

property description: None | str: Optional description of the post.

property link: None | str: Optional link that the post is associated with.

property media: None | MediaClass: Optional media that the post is storing

property title: str: Title of the post.

property type: str | PostContentTypeClass: Type of content held in the post.

class datahub.metadata.schema_classes.PostContentTypeClass

Bases: object

Enum defining the type of content held in a Post.

LINK = 'LINK'

TEXT = 'TEXT'

class datahub.metadata.schema_classes.PostInfoClass(type, content, created, lastModified)

Bases: _Aspect

Information about a DataHub Post.

Parameters:

type (Union[str, PostTypeClass])
content (PostContentClass)
created (int)
lastModified (int)

property content: PostContentClass: Content stored in the post.

property created: int: The time at which the post was initially created

property lastModified: int: The time at which the post was last modified

property type: str | PostTypeClass: Type of the Post.

class datahub.metadata.schema_classes.PostKeyClass(id)

Bases: _Aspect

Key for a Post.

Parameters:: id (str)

property id: str: A unique id for the DataHub Post record. Generated on the server side at Post creation time.

class datahub.metadata.schema_classes.PostTypeClass

Bases: object

Enum defining types of Posts.

HOME_PAGE_ANNOUNCEMENT = 'HOME_PAGE_ANNOUNCEMENT'

class datahub.metadata.schema_classes.PrestoDDLClass(rawSchema)

Bases: DictWrapper

Schema holder for presto data definition language that describes a presto view.

Parameters:: rawSchema (str)

property rawSchema: str: The raw schema in the dataset’s platform. This includes the DDL and the columns extracted from DDL.

class datahub.metadata.schema_classes.QuantileClass(quantile, value)

Bases: DictWrapper

Parameters:

quantile (str)
value (str)

property quantile: str

property value: str

class datahub.metadata.schema_classes.QuantitativeAnalysesClass(unitaryResults=None, intersectionalResults=None)

Bases: _Aspect

Quantitative analyses should be disaggregated, that is, broken down by the chosen factors. Quantitative analyses should provide the results of evaluating the MLModel according to the chosen metrics, providing confidence interval values when possible.

Parameters:

unitaryResults (Optional[str])
intersectionalResults (Optional[str])

property intersectionalResults: None | str: Link to a dashboard with results showing how the MLModel performed with respect to the intersection of evaluated factors?

property unitaryResults: None | str: Link to a dashboard with results showing how the MLModel performed with respect to each factor

class datahub.metadata.schema_classes.QueryCellClass(cellId, changeAuditStamps, rawQuery, cellTitle=None, lastExecuted=None)

Bases: DictWrapper

Query cell in a Notebook, which will present content in query format

Parameters:

cellId (str)
changeAuditStamps (ChangeAuditStampsClass)
rawQuery (str)
cellTitle (Optional[str])
lastExecuted (Optional[AuditStampClass])

property cellId: str: Unique id for the cell. This id should be globally unique for a Notebook tool even when there are multiple deployments of it. As an example, Notebook URL could be used here for QueryBook such as ‘querybook.com/notebook/773/?cellId=1234’

property cellTitle: None | str: Title of the cell

property changeAuditStamps: ChangeAuditStampsClass: Captures information about who created/last modified/deleted this Notebook cell and when

property lastExecuted: None | AuditStampClass: Captures information about who last executed this query cell and when

property rawQuery: str: Raw query to explain some specific logic in a Notebook

class datahub.metadata.schema_classes.QueryKeyClass(id)

Bases: _Aspect

Key for a Query

Parameters:: id (str)

property id: str: A unique id for the Query.

class datahub.metadata.schema_classes.QueryLanguageClass

Bases: object

SQL = 'SQL'

class datahub.metadata.schema_classes.QueryPropertiesClass(statement, source, created, lastModified, name=None, description=None)

Bases: _Aspect

Information about a Query against one or more data assets (e.g. Tables or Views).

Parameters:

statement (QueryStatementClass)
source (Union[str, QuerySourceClass])
created (AuditStampClass)
lastModified (AuditStampClass)
name (Optional[str])
description (Optional[str])

property created: AuditStampClass: Audit stamp capturing the time and actor who created the Query.

property description: None | str: The Query description.

property lastModified: AuditStampClass: Audit stamp capturing the time and actor who last modified the Query.

property name: None | str: Optional display name to identify the query.

property source: str | QuerySourceClass: The source of the Query

property statement: QueryStatementClass: The Query Statement.

class datahub.metadata.schema_classes.QuerySourceClass

Bases: object

MANUAL = 'MANUAL'

class datahub.metadata.schema_classes.QueryStatementClass(value, language=None)

Bases: DictWrapper

A query statement against one or more data assets.

Parameters:

value (str)
language (Union[str, QueryLanguageClass, None])

property language: str | QueryLanguageClass: The language of the Query, e.g. SQL.

property value: str: The query text

class datahub.metadata.schema_classes.QuerySubjectClass(entity)

Bases: DictWrapper

A single subject of a particular query. In the future, we may evolve this model to include richer details about the Query Subject in relation to the query.

Parameters:: entity (str)

property entity: str: An entity which is the subject of a query.

class datahub.metadata.schema_classes.QuerySubjectsClass(subjects)

Bases: _Aspect

Information about the subjects of a particular Query, i.e. the assets being queried.

Parameters:: subjects (List[QuerySubjectClass])

property subjects: List[QuerySubjectClass]

One or more subjects of the query.

In single-asset queries (e.g. table select), this will contain the Table reference and optionally schema field references.

In multi-asset queries (e.g. table joins), this may contain multiple Table references and optionally schema field references.

class datahub.metadata.schema_classes.RecordTypeClass

Bases: DictWrapper

Record field type.

class datahub.metadata.schema_classes.RetentionClass(version=None, time=None)

Bases: DictWrapper

Base class that encapsulates different retention policies. Only one of the fields should be set

Parameters:

version (Optional[VersionBasedRetentionClass])
time (Optional[TimeBasedRetentionClass])

property time: None | TimeBasedRetentionClass

property version: None | VersionBasedRetentionClass

class datahub.metadata.schema_classes.RoleAssociationClass(urn)

Bases: DictWrapper

Properties of an applied Role. For now, just an Urn

Parameters:: urn (str)

property urn: str: Urn of the External Role

class datahub.metadata.schema_classes.RoleKeyClass(id)

Bases: _Aspect

Key for a External AccessManagement

Parameters:: id (str)

property id: str: A unique id for the access management IAM.

class datahub.metadata.schema_classes.RoleMembershipClass(roles)

Bases: _Aspect

Carries information about which roles a user is assigned to.

Parameters:: roles (List[str])

property roles: List[str]

class datahub.metadata.schema_classes.RolePropertiesClass(name, type, description=None, requestUrl=None, created=None)

Bases: _Aspect

Information about a ExternalRoleProperties

Parameters:

name (str)
type (str)
description (Optional[str])
requestUrl (Optional[str])
created (Optional[AuditStampClass])

property created: None | AuditStampClass: Created Audit stamp

property description: None | str: Description of the IAM Role

property name: str: Display name of the IAM Role in the external system

property requestUrl: None | str: Link to access external access management

property type: str: Can be READ, ADMIN, WRITE

class datahub.metadata.schema_classes.RoleUserClass(user)

Bases: DictWrapper

Provisioned users of a role

Parameters:: user (str)

property user: str: Link provisioned corp user for a role

class datahub.metadata.schema_classes.RowCountChangeClass(type, operator, parameters)

Bases: DictWrapper

Attributes defining a ROW_COUNT_CHANGE volume assertion.

Parameters:

type (Union[str, AssertionValueChangeTypeClass])
operator (Union[str, AssertionStdOperatorClass])
parameters (AssertionStdParametersClass)

property operator: str | AssertionStdOperatorClass

The operator you’d like to apply.

Note that only numeric operators are valid inputs: GREATER_THAN, GREATER_THAN_OR_EQUAL_TO, EQUAL_TO, LESS_THAN, LESS_THAN_OR_EQUAL_TO, BETWEEN.

property parameters: AssertionStdParametersClass

The parameters you’d like to provide as input to the operator.

Note that only numeric parameter types are valid inputs: NUMBER.

property type: str | AssertionValueChangeTypeClass

a fixed absolute value or a relative percentage.

Type:: The type of the value used to evaluate the assertion

class datahub.metadata.schema_classes.RowCountTotalClass(operator, parameters)

Bases: DictWrapper

Attributes defining a ROW_COUNT_TOTAL volume assertion.

Parameters:

operator (Union[str, AssertionStdOperatorClass])
parameters (AssertionStdParametersClass)

property operator: str | AssertionStdOperatorClass

The operator you’d like to apply.

Note that only numeric operators are valid inputs: GREATER_THAN, GREATER_THAN_OR_EQUAL_TO, EQUAL_TO, LESS_THAN, LESS_THAN_OR_EQUAL_TO, BETWEEN.

property parameters: AssertionStdParametersClass

The parameters you’d like to provide as input to the operator.

Note that only numeric parameter types are valid inputs: NUMBER.

class datahub.metadata.schema_classes.RunResultTypeClass

Bases: object

FAILURE = 'FAILURE'

SKIPPED = 'SKIPPED'

SUCCESS = 'SUCCESS'

UP_FOR_RETRY = 'UP_FOR_RETRY'

class datahub.metadata.schema_classes.SchemaAssertionInfoClass(entity, schema)

Bases: DictWrapper

Attributes that are applicable to schema assertions

Parameters:

entity (str)
schema (SchemaMetadataClass)

property entity: str: The entity targeted by the assertion

property schema: SchemaMetadataClass

A definition of the expected structure for the asset

Note that many of the fields of this model, especially those related to metadata (tags, terms) will go unused in this context.

class datahub.metadata.schema_classes.SchemaContractClass(assertion)

Bases: DictWrapper

Expectations for a logical schema

Parameters:: assertion (str)

property assertion: str: The assertion representing the schema contract.

class datahub.metadata.schema_classes.SchemaFieldClass(fieldPath, type, nativeDataType, jsonPath=None, nullable=None, description=None, label=None, created=None, lastModified=None, recursive=None, globalTags=None, glossaryTerms=None, isPartOfKey=None, isPartitioningKey=None, jsonProps=None)

Bases: DictWrapper

SchemaField to describe metadata related to dataset schema.

Parameters:

fieldPath (str)
type (SchemaFieldDataTypeClass)
nativeDataType (str)
jsonPath (Optional[str])
nullable (Optional[bool])
description (Optional[str])
label (Optional[str])
created (Optional[AuditStampClass])
lastModified (Optional[AuditStampClass])
recursive (Optional[bool])
globalTags (Optional[GlobalTagsClass])
glossaryTerms (Optional[GlossaryTermsClass])
isPartOfKey (Optional[bool])
isPartitioningKey (Optional[bool])
jsonProps (Optional[str])

property created: None | AuditStampClass: An AuditStamp corresponding to the creation of this schema field.

property description: None | str: Description

property fieldPath: str: Flattened name of the field. Field is computed from jsonPath field.

property globalTags: None | GlobalTagsClass: Tags associated with the field

property glossaryTerms: None | GlossaryTermsClass: Glossary terms associated with the field

property isPartOfKey: bool: For schema fields that are part of complex keys, set this field to true We do this to easily distinguish between value and key fields

property isPartitioningKey: None | bool: For Datasets which are partitioned, this determines the partitioning key.

property jsonPath: None | str: Flattened name of a field in JSON Path notation.

property jsonProps: None | str: For schema fields that have other properties that are not modeled explicitly, use this field to serialize those properties into a JSON string

property label: None | str: Label of the field. Provides a more human-readable name for the field than field path. Some sources will provide this metadata but not all sources have the concept of a label. If just one string is associated with a field in a source, that is most likely a description.

property lastModified: None | AuditStampClass: An AuditStamp corresponding to the last modification of this schema field.

property nativeDataType: str: The native type of the field in the dataset’s platform as declared by platform schema.

property nullable: bool: Indicates if this field is optional or nullable

property recursive: bool: There are use cases when a field in type B references type A. A field in A references field of type B. In such cases, we will mark the first field as recursive.

property type: SchemaFieldDataTypeClass: Platform independent field type of the field.

class datahub.metadata.schema_classes.SchemaFieldDataTypeClass(type)

Bases: DictWrapper

Schema field data types

Parameters:: type (Union[BooleanTypeClass, FixedTypeClass, StringTypeClass, BytesTypeClass, NumberTypeClass, DateTypeClass, TimeTypeClass, EnumTypeClass, NullTypeClass, MapTypeClass, ArrayTypeClass, UnionTypeClass, RecordTypeClass])

property type: BooleanTypeClass | FixedTypeClass | StringTypeClass | BytesTypeClass | NumberTypeClass | DateTypeClass | TimeTypeClass | EnumTypeClass | NullTypeClass | MapTypeClass | ArrayTypeClass | UnionTypeClass | RecordTypeClass: Data platform specific types

class datahub.metadata.schema_classes.SchemaFieldKeyClass(parent, fieldPath)

Bases: _Aspect

Key for a SchemaField

Parameters:

parent (str)
fieldPath (str)

property fieldPath: str: fieldPath identifying the schema field

property parent: str: Parent associated with the schema field

class datahub.metadata.schema_classes.SchemaFieldSnapshotClass(urn, aspects)

Bases: DictWrapper

A metadata snapshot for a specific schema field entity.

Parameters:

urn (str)
aspects (List[SchemaFieldKeyClass])

property aspects: List[SchemaFieldKeyClass]: The list of metadata aspects associated with the dataset. Depending on the use case, this can either be all, or a selection, of supported aspects.

property urn: str: URN for the entity the metadata snapshot is associated with.

class datahub.metadata.schema_classes.SchemaFieldSpecClass(path, type, nativeType)

Bases: DictWrapper

Lightweight spec used for referencing a particular schema field.

Parameters:

path (str)
type (str)
nativeType (str)

property nativeType: str: The native field type

property path: str: The field path

property type: str: The DataHub standard schema field type.

class datahub.metadata.schema_classes.SchemaMetadataClass(schemaName, platform, version, hash, platformSchema, fields, created=None, lastModified=None, deleted=None, dataset=None, cluster=None, primaryKeys=None, foreignKeysSpecs=None, foreignKeys=None)

Bases: _Aspect

SchemaMetadata to describe metadata related to store schema

Parameters:

schemaName (str)
platform (str)
version (int)
hash (str)
platformSchema (Union[EspressoSchemaClass, OracleDDLClass, MySqlDDLClass, PrestoDDLClass, KafkaSchemaClass, BinaryJsonSchemaClass, OrcSchemaClass, SchemalessClass, KeyValueSchemaClass, OtherSchemaClass])
fields (List[SchemaFieldClass])
created (Optional[AuditStampClass])
lastModified (Optional[AuditStampClass])
deleted (Optional[AuditStampClass])
dataset (Optional[str])
cluster (Optional[str])
primaryKeys (Optional[List[str]])
foreignKeysSpecs (Optional[Dict[str, ForeignKeySpecClass]])
foreignKeys (Optional[List[ForeignKeyConstraintClass]])

property cluster: None | str: The cluster this schema metadata resides from

property created: AuditStampClass: An AuditStamp corresponding to the creation of this resource/association/sub-resource. A value of 0 for time indicates missing data.

property dataset: None | str: Dataset this schema metadata is associated with.

property deleted: None | AuditStampClass: An AuditStamp corresponding to the deletion of this resource/association/sub-resource. Logically, deleted MUST have a later timestamp than creation. It may or may not have the same time as lastModified depending upon the resource/association/sub-resource semantics.

property fields: List[SchemaFieldClass]: Client provided a list of fields from document schema.

property foreignKeys: None | List[ForeignKeyConstraintClass]: List of foreign key constraints for the schema

property foreignKeysSpecs: None | Dict[str, ForeignKeySpecClass]: Map captures all the references schema makes to external datasets. Map key is ForeignKeySpecName typeref.

property hash: str: the SHA1 hash of the schema content

property lastModified: AuditStampClass: An AuditStamp corresponding to the last modification of this resource/association/sub-resource. If no modification has happened since creation, lastModified should be the same as created. A value of 0 for time indicates missing data.

property platform: str

platform:{platform_name})

Type:: Standardized platform urn where schema is defined. The data platform Urn (urn
Type:: li

property platformSchema: EspressoSchemaClass | OracleDDLClass | MySqlDDLClass | PrestoDDLClass | KafkaSchemaClass | BinaryJsonSchemaClass | OrcSchemaClass | SchemalessClass | KeyValueSchemaClass | OtherSchemaClass: The native schema in the dataset’s platform.

property primaryKeys: None | List[str]: Client provided list of fields that define primary keys to access record. Field order defines hierarchical espresso keys. Empty lists indicates absence of primary key access patter. Value is a SchemaField@fieldPath.

property schemaName: str: Schema name e.g. PageViewEvent, identity.Profile, ams.account_management_tracking

property version: int: Every change to SchemaMetadata in the resource results in a new version. Version is server assigned. This version is differ from platform native schema version.

class datahub.metadata.schema_classes.SchemalessClass

Bases: DictWrapper

The dataset has no specific schema associated with it

class datahub.metadata.schema_classes.SiblingsClass(siblings, primary)

Bases: _Aspect

Siblings information of an entity.

Parameters:

siblings (List[str])
primary (bool)

property primary: bool: If this is the leader entity of the set of siblings

property siblings: List[str]: List of sibling entities

class datahub.metadata.schema_classes.SourceCodeClass(sourceCode)

Bases: _Aspect

Source Code

Parameters:: sourceCode (List[SourceCodeUrlClass])

property sourceCode: List[SourceCodeUrlClass]: Source Code along with types

class datahub.metadata.schema_classes.SourceCodeUrlClass(type, sourceCodeUrl)

Bases: DictWrapper

Source Code Url Entity

Parameters:

type (Union[str, SourceCodeUrlTypeClass])
sourceCodeUrl (str)

property sourceCodeUrl: str: Source Code Url

property type: str | SourceCodeUrlTypeClass: Source Code Url Types

class datahub.metadata.schema_classes.SourceCodeUrlTypeClass

Bases: object

EVALUATION_PIPELINE_SOURCE_CODE = 'EVALUATION_PIPELINE_SOURCE_CODE'

ML_MODEL_SOURCE_CODE = 'ML_MODEL_SOURCE_CODE'

TRAINING_PIPELINE_SOURCE_CODE = 'TRAINING_PIPELINE_SOURCE_CODE'

class datahub.metadata.schema_classes.SqlAssertionInfoClass(type, entity, statement, operator, parameters, changeType=None)

Bases: DictWrapper

Attributes defining a SQL Assertion

Parameters:

type (Union[str, SqlAssertionTypeClass])
entity (str)
statement (str)
operator (Union[str, AssertionStdOperatorClass])
parameters (AssertionStdParametersClass)
changeType (Union[None, str, AssertionValueChangeTypeClass])

property changeType: None | str | AssertionValueChangeTypeClass

a fixed absolute value or a relative percentage. This value is required if the type is METRIC_CHANGE.

Type:: The type of the value used to evaluate the assertion

property entity: str: The entity targeted by this SQL check.

property operator: str | AssertionStdOperatorClass

The operator you’d like to apply to the result of the SQL query.

Note that at this time, only numeric operators are valid inputs: GREATER_THAN, GREATER_THAN_OR_EQUAL_TO, EQUAL_TO, LESS_THAN, LESS_THAN_OR_EQUAL_TO, BETWEEN.

property parameters: AssertionStdParametersClass

The parameters you’d like to provide as input to the operator.

Note that only numeric parameter types are valid inputs: NUMBER.

property statement: str

The SQL statement to be executed when evaluating the assertion (or computing the metric). This should be a valid and complete statement, executable by itself.

Usually this should be a SELECT query statement.

property type: str | SqlAssertionTypeClass: The type of the SQL assertion being monitored.

class datahub.metadata.schema_classes.SqlAssertionTypeClass

Bases: object

METRIC = 'METRIC'

METRIC_CHANGE = 'METRIC_CHANGE'

class datahub.metadata.schema_classes.StatusClass(removed=None)

Bases: _Aspect

The lifecycle status metadata of an entity, e.g. dataset, metric, feature, etc. This aspect is used to represent soft deletes conventionally.

Parameters:: removed (Optional[bool])

property removed: bool: Whether the entity has been removed (soft-deleted).

class datahub.metadata.schema_classes.StringTypeClass

Bases: DictWrapper

String field type.

class datahub.metadata.schema_classes.StructuredExecutionReportClass(type, serializedValue, contentType)

Bases: DictWrapper

A flexible carrier for structured results of an execution request. The goal is to allow for free flow of structured responses from execution tasks to the orchestrator or observer. The full spectrum of different execution report types is not intended to be modeled by this object.

Parameters:

type (str)
serializedValue (str)
contentType (str)

property contentType: str: The content-type of the serialized value (e.g. application/json, application/json;gzip etc.)

property serializedValue: str: The serialized value of the structured report

property type: str: The type of the structured report. (e.g. INGESTION_REPORT, TEST_CONNECTION_REPORT, etc.)

class datahub.metadata.schema_classes.SubTypesClass(typeNames)

Bases: _Aspect

Sub Types. Use this aspect to specialize a generic Entity e.g. Making a Dataset also be a View or also be a LookerExplore

Parameters:: typeNames (List[str])

property typeNames: List[str]: The names of the specific types.

class datahub.metadata.schema_classes.SystemMetadataClass(lastObserved=None, runId=None, lastRunId=None, pipelineName=None, registryName=None, registryVersion=None, properties=None)

Bases: DictWrapper

Metadata associated with each metadata change that is processed by the system

Parameters:

lastObserved (Optional[int])
runId (Optional[str])
lastRunId (Optional[str])
pipelineName (Optional[str])
registryName (Optional[str])
registryVersion (Optional[str])
properties (Optional[Dict[str, str]])

property lastObserved: int | None: The timestamp the metadata was observed at

property lastRunId: str | None: The last run id that produced the metadata. Populated in case of batch-ingestion.

property pipelineName: None | str: The ingestion pipeline id that produced the metadata. Populated in case of batch ingestion.

property properties: None | Dict[str, str]: Additional properties

property registryName: None | str: The model registry name that was used to process this event

property registryVersion: None | str: The model registry version that was used to process this event

property runId: str | None: The original run id that produced the metadata. Populated in case of batch-ingestion.

class datahub.metadata.schema_classes.TagAssociationClass(tag, context=None)

Bases: DictWrapper

Properties of an applied tag. For now, just an Urn. In the future we can extend this with other properties, e.g. propagation parameters.

Parameters:

tag (str)
context (Optional[str])

property context: None | str: Additional context about the association

property tag: str: Urn of the applied tag

class datahub.metadata.schema_classes.TagKeyClass(name)

Bases: _Aspect

Key for a Tag

Parameters:: name (str)

property name: str: The tag name, which serves as a unique id

class datahub.metadata.schema_classes.TagPropertiesClass(name, description=None, colorHex=None)

Bases: _Aspect

Properties associated with a Tag

Parameters:

name (str)
description (Optional[str])
colorHex (Optional[str])

property colorHex: None | str: The color associated with the Tag in Hex. For example #FFFFFF.

property description: None | str: Documentation of the tag

property name: str: Display name of the tag

class datahub.metadata.schema_classes.TagSnapshotClass(urn, aspects)

Bases: DictWrapper

A metadata snapshot for a specific dataset entity.

Parameters:

urn (str)
aspects (List[Union[TagKeyClass, OwnershipClass, TagPropertiesClass, StatusClass]])

property aspects: List[TagKeyClass | OwnershipClass | TagPropertiesClass | StatusClass]: The list of metadata aspects associated with the dataset. Depending on the use case, this can either be all, or a selection, of supported aspects.

property urn: str: URN for the entity the metadata snapshot is associated with.

class datahub.metadata.schema_classes.TelemetryClientIdClass(clientId)

Bases: _Aspect

A simple wrapper around a String to persist the client ID for telemetry in DataHub’s backend DB

Parameters:: clientId (str)

property clientId: str: A string representing the telemetry client ID

class datahub.metadata.schema_classes.TelemetryKeyClass(name)

Bases: _Aspect

Key for the telemetry client ID, only one should ever exist

Parameters:: name (str)

property name: str: The telemetry entity name, which serves as a unique id

class datahub.metadata.schema_classes.TestDefinitionClass(type, json=None)

Bases: DictWrapper

Parameters:

type (Union[str, TestDefinitionTypeClass])
json (Optional[str])

property json: None | str: JSON format configuration for the test

property type: str | TestDefinitionTypeClass: The Test Definition Type

class datahub.metadata.schema_classes.TestDefinitionTypeClass

Bases: object

JSON = 'JSON'

class datahub.metadata.schema_classes.TestInfoClass(name, category, definition, description=None)

Bases: _Aspect

Information about a DataHub Test

Parameters:

name (str)
category (str)
definition (TestDefinitionClass)
description (Optional[str])

property category: str: Category of the test

property definition: TestDefinitionClass: Configuration for the Test

property description: None | str: Description of the test

property name: str: The name of the test

class datahub.metadata.schema_classes.TestKeyClass(id)

Bases: _Aspect

Key for a Test

Parameters:: id (str)

property id: str: Unique id for the test

class datahub.metadata.schema_classes.TestResultClass(test, type)

Bases: DictWrapper

Information about a Test Result

Parameters:

test (str)
type (Union[str, TestResultTypeClass])

property test: str: The urn of the test

property type: str | TestResultTypeClass: The type of the result

class datahub.metadata.schema_classes.TestResultTypeClass

Bases: object

FAILURE = 'FAILURE'

SUCCESS = 'SUCCESS'

class datahub.metadata.schema_classes.TestResultsClass(failing, passing)

Bases: _Aspect

Information about a Test Result

Parameters:

failing (List[TestResultClass])
passing (List[TestResultClass])

property failing: List[TestResultClass]: Results that are failing

property passing: List[TestResultClass]: Results that are passing

class datahub.metadata.schema_classes.TextCellClass(cellId, changeAuditStamps, text, cellTitle=None)

Bases: DictWrapper

Text cell in a Notebook, which will present content in text format

Parameters:

cellId (str)
changeAuditStamps (ChangeAuditStampsClass)
text (str)
cellTitle (Optional[str])

property cellId: str: Unique id for the cell. This id should be globally unique for a Notebook tool even when there are multiple deployments of it. As an example, Notebook URL could be used here for QueryBook such as ‘querybook.com/notebook/773/?cellId=1234’

property cellTitle: None | str: Title of the cell

property changeAuditStamps: ChangeAuditStampsClass: Captures information about who created/last modified/deleted this Notebook cell and when

property text: str: The actual text in a TextCell in a Notebook

class datahub.metadata.schema_classes.TimeBasedRetentionClass(maxAgeInSeconds)

Bases: DictWrapper

Keep records that are less than X seconds old

Parameters:: maxAgeInSeconds (int)

property maxAgeInSeconds: int

class datahub.metadata.schema_classes.TimeStampClass(time, actor=None)

Bases: DictWrapper

A standard event timestamp

Parameters:

time (int)
actor (Optional[str])

property actor: None | str

The actor urn involved in the event.

Type:: Optional

property time: int: When did the event occur

class datahub.metadata.schema_classes.TimeTypeClass

Bases: DictWrapper

Time field type. This should also be used for datetimes.

class datahub.metadata.schema_classes.TimeWindowClass(startTimeMillis, length)

Bases: DictWrapper

Parameters:

startTimeMillis (int)
length (TimeWindowSizeClass)

property length: TimeWindowSizeClass: The length of the window.

property startTimeMillis: int: Start time as epoch at UTC.

class datahub.metadata.schema_classes.TimeWindowSizeClass(unit, multiple=None)

Bases: DictWrapper

Defines the size of a time window.

Parameters:

unit (Union[str, CalendarIntervalClass])
multiple (Optional[int])

property multiple: int: How many units. Defaults to 1.

property unit: str | CalendarIntervalClass: Interval unit such as minute/hour/day etc.

class datahub.metadata.schema_classes.TrainingDataClass(trainingData)

Bases: _Aspect

Ideally, the MLModel card would contain as much information about the training data as the evaluation data. However, there might be cases where it is not feasible to provide this level of detailed information about the training data. For example, the data may be proprietary, or require a non-disclosure agreement. In these cases, we advocate for basic details about the distributions over groups in the data, as well as any other details that could inform stakeholders on the kinds of biases the model may have encoded.

Parameters:: trainingData (List[BaseDataClass])

property trainingData: List[BaseDataClass]: Details on the dataset(s) used for training the MLModel

class datahub.metadata.schema_classes.TransformationTypeClass

Bases: object

Type of the transformation involved in generating destination fields from source fields.

BLACKBOX = 'BLACKBOX'

IDENTITY = 'IDENTITY'

class datahub.metadata.schema_classes.UDFTransformerClass(udf)

Bases: DictWrapper

Field transformation expressed in UDF

Parameters:: udf (str)

property udf: str: A UDF mentioning how the source fields got transformed to destination field. This is the FQCN(Fully Qualified Class Name) of the udf.

class datahub.metadata.schema_classes.UnionTypeClass(nestedTypes=None)

Bases: DictWrapper

Union field type.

Parameters:: nestedTypes (Optional[List[str]])

property nestedTypes: None | List[str]: List of types in union type.

class datahub.metadata.schema_classes.UpstreamClass(dataset, type, auditStamp=None, created=None, properties=None)

Bases: DictWrapper

Upstream lineage information about a dataset including the source reporting the lineage

Parameters:

dataset (str)
type (Union[str, DatasetLineageTypeClass])
auditStamp (Optional[AuditStampClass])
created (Optional[AuditStampClass])
properties (Optional[Dict[str, str]])

property auditStamp: AuditStampClass: Audit stamp containing who reported the lineage and when.

property created: None | AuditStampClass: Audit stamp containing who created the lineage and when.

property dataset: str: The upstream dataset the lineage points to

property properties: None | Dict[str, str]: A generic properties bag that allows us to store specific information on this graph edge.

property type: str | DatasetLineageTypeClass: The type of the lineage

class datahub.metadata.schema_classes.UpstreamLineageClass(upstreams, fineGrainedLineages=None)

Bases: _Aspect

Upstream lineage of a dataset

Parameters:

upstreams (List[UpstreamClass])
fineGrainedLineages (Optional[List[FineGrainedLineageClass]])

property fineGrainedLineages: None | List[FineGrainedLineageClass]: List of fine-grained lineage information, including field-level lineage

property upstreams: List[UpstreamClass]: List of upstream dataset lineage information

class datahub.metadata.schema_classes.UrnForeignKeyClass(currentFieldPath)

Bases: DictWrapper

If SchemaMetadata fields make any external references and references are of type com.linkedin.pegasus2avro.common.Urn or any children, this models can be used to mark it.

Parameters:: currentFieldPath (str)

property currentFieldPath: str: Field in hosting(current) SchemaMetadata.

class datahub.metadata.schema_classes.UsageAggregationClass(bucket, duration, resource, metrics)

Bases: DictWrapper

Usage data for a given resource, rolled up into a bucket.

Parameters:

bucket (int)
duration (Union[str, WindowDurationClass])
resource (str)
metrics (UsageAggregationMetricsClass)

property bucket: int: Bucket start time in milliseconds

property duration: str | WindowDurationClass: Bucket duration

property metrics: UsageAggregationMetricsClass: Metrics associated with this bucket

property resource: str: Resource associated with these usage stats

class datahub.metadata.schema_classes.UsageAggregationMetricsClass(uniqueUserCount=None, users=None, totalSqlQueries=None, topSqlQueries=None, fields=None)

Bases: DictWrapper

Metrics for usage data for a given resource and bucket. Not all fields make sense for all buckets, so every field is optional.

Parameters:

uniqueUserCount (Optional[int])
users (Optional[List[UserUsageCountsClass]])
totalSqlQueries (Optional[int])
topSqlQueries (Optional[List[str]])
fields (Optional[List[FieldUsageCountsClass]])

property fields: None | List[FieldUsageCountsClass]: Field-level usage stats

property topSqlQueries: None | List[str]: Frequent SQL queries; mostly makes sense for datasets in SQL databases

property totalSqlQueries: None | int: Total SQL query count

property uniqueUserCount: None | int: Unique user count

property users: None | List[UserUsageCountsClass]: Users within this bucket, with frequency counts

class datahub.metadata.schema_classes.UserUsageCountsClass(count, user=None, userEmail=None)

Bases: DictWrapper

Records a single user’s usage counts for a given resource

Parameters:

count (int)
user (Optional[str])
userEmail (Optional[str])

property count: int

property user: None | str

property userEmail: None | str: If user_email is set, we attempt to resolve the user’s urn upon ingest

class datahub.metadata.schema_classes.ValueFrequencyClass(value, frequency)

Bases: DictWrapper

Parameters:

value (str)
frequency (int)

property frequency: int

property value: str

class datahub.metadata.schema_classes.VersionBasedRetentionClass(maxVersions)

Bases: DictWrapper

Keep max N latest records

Parameters:: maxVersions (int)

property maxVersions: int

class datahub.metadata.schema_classes.VersionInfoClass(version, versionType, customProperties=None, externalUrl=None)

Bases: _Aspect

Information about a Data processing job

Parameters:

version (str)
versionType (str)
customProperties (Optional[Dict[str, str]])
externalUrl (Optional[str])

property customProperties: Dict[str, str]: Custom property bag.

property externalUrl: None | str: URL where the reference exist

property version: str: The version which can indentify a job version like a commit hash or md5 hash

property versionType: str: The type of the version like git hash or md5 hash

class datahub.metadata.schema_classes.VersionTagClass(versionTag=None)

Bases: DictWrapper

A resource-defined string representing the resource state for the purpose of concurrency control

Parameters:: versionTag (Optional[str])

property versionTag: None | str

class datahub.metadata.schema_classes.ViewPropertiesClass(materialized, viewLogic, viewLanguage)

Bases: _Aspect

Details about a View. e.g. Gets activated when subTypes is view

Parameters:

materialized (bool)
viewLogic (str)
viewLanguage (str)

property materialized: bool: Whether the view is materialized

property viewLanguage: str: The view logic language / dialect

property viewLogic: str: The view logic

class datahub.metadata.schema_classes.VolumeAssertionInfoClass(type, entity, rowCountTotal=None, rowCountChange=None, incrementingSegmentRowCountTotal=None, incrementingSegmentRowCountChange=None, filter=None)

Bases: DictWrapper

Attributes defining a dataset Volume Assertion

Parameters:

type (Union[str, VolumeAssertionTypeClass])
entity (str)
rowCountTotal (Optional[RowCountTotalClass])
rowCountChange (Optional[RowCountChangeClass])
incrementingSegmentRowCountTotal (Optional[IncrementingSegmentRowCountTotalClass])
incrementingSegmentRowCountChange (Optional[IncrementingSegmentRowCountChangeClass])
filter (Optional[DatasetFilterClass])

property entity: str: The entity targeted by this Volume check.

property filter: None | DatasetFilterClass: A definition of the specific filters that should be applied, when performing monitoring. If not provided, there is no filter, and the full table is under consideration.

property incrementingSegmentRowCountChange: None | IncrementingSegmentRowCountChangeClass: Produce FAILURE Assertion Result if the asset’s incrementing segment row count delta does not meet specific requirements. Required if type is ‘INCREMENTING_SEGMENT_ROW_COUNT_CHANGE’

property incrementingSegmentRowCountTotal: None | IncrementingSegmentRowCountTotalClass: Produce FAILURE Assertion Result if the asset’s latest incrementing segment row count total does not meet specific requirements. Required if type is ‘INCREMENTING_SEGMENT_ROW_COUNT_TOTAL’

property rowCountChange: None | RowCountChangeClass: Produce FAILURE Assertion Result if the delta row count of the asset does not meet specific requirements within a given period of time. Required if type is ‘ROW_COUNT_CHANGE’

property rowCountTotal: None | RowCountTotalClass: Produce FAILURE Assertion Result if the row count of the asset does not meet specific requirements. Required if type is ‘ROW_COUNT_TOTAL’

property type: str | VolumeAssertionTypeClass: The type of the freshness assertion being monitored.

class datahub.metadata.schema_classes.VolumeAssertionTypeClass

Bases: object

INCREMENTING_SEGMENT_ROW_COUNT_CHANGE = 'INCREMENTING_SEGMENT_ROW_COUNT_CHANGE'

INCREMENTING_SEGMENT_ROW_COUNT_TOTAL = 'INCREMENTING_SEGMENT_ROW_COUNT_TOTAL'

ROW_COUNT_CHANGE = 'ROW_COUNT_CHANGE'

ROW_COUNT_TOTAL = 'ROW_COUNT_TOTAL'

class datahub.metadata.schema_classes.WindowDurationClass

Bases: object

Enum to define the length of a bucket when doing aggregations

DAY = 'DAY'

HOUR = 'HOUR'

MONTH = 'MONTH'

WEEK = 'WEEK'

YEAR = 'YEAR'

datahub.metadata.schema_classes.get_schema_type(fullname)

Parameters:: fullname (str)
Return type:: RecordSchema

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