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262 lines
11 KiB
Python
262 lines
11 KiB
Python
import json
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import pytest
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import requests
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import datahub.metadata.schema_classes as models
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from datahub.emitter.mcp import MetadataChangeProposalWrapper
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from datahub.emitter.rest_emitter import DatahubRestEmitter
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MOCK_GMS_ENDPOINT = "http://fakegmshost:8080"
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basicAuditStamp = models.AuditStampClass(
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time=1618987484580,
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actor="urn:li:corpuser:datahub",
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impersonator=None,
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)
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@pytest.mark.parametrize(
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"record,path,snapshot",
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[
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(
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# Simple test.
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models.MetadataChangeEventClass(
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proposedSnapshot=models.DatasetSnapshotClass(
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urn="urn:li:dataset:(urn:li:dataPlatform:bigquery,downstream,PROD)",
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aspects=[
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models.UpstreamLineageClass(
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upstreams=[
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models.UpstreamClass(
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auditStamp=basicAuditStamp,
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dataset="urn:li:dataset:(urn:li:dataPlatform:bigquery,upstream1,PROD)",
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type="TRANSFORMED",
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),
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models.UpstreamClass(
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auditStamp=basicAuditStamp,
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dataset="urn:li:dataset:(urn:li:dataPlatform:bigquery,upstream2,PROD)",
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type="TRANSFORMED",
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),
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]
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)
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],
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),
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),
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"/entities?action=ingest",
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{
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"entity": {
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"value": {
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"com.linkedin.metadata.snapshot.DatasetSnapshot": {
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"urn": "urn:li:dataset:(urn:li:dataPlatform:bigquery,downstream,PROD)",
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"aspects": [
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{
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"com.linkedin.dataset.UpstreamLineage": {
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"upstreams": [
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{
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"auditStamp": {
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"time": 1618987484580,
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"actor": "urn:li:corpuser:datahub",
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},
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"dataset": "urn:li:dataset:(urn:li:dataPlatform:bigquery,upstream1,PROD)",
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"type": "TRANSFORMED",
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},
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{
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"auditStamp": {
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"time": 1618987484580,
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"actor": "urn:li:corpuser:datahub",
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},
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"dataset": "urn:li:dataset:(urn:li:dataPlatform:bigquery,upstream2,PROD)",
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"type": "TRANSFORMED",
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},
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]
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}
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}
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],
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}
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}
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},
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"systemMetadata": {},
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},
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),
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(
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# Verify the serialization behavior with chart type enums.
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models.MetadataChangeEventClass(
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proposedSnapshot=models.ChartSnapshotClass(
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urn="urn:li:chart:(superset,227)",
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aspects=[
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models.ChartInfoClass(
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title="Weekly Messages",
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description="",
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lastModified=models.ChangeAuditStampsClass(
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created=basicAuditStamp,
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lastModified=basicAuditStamp,
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),
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type=models.ChartTypeClass.SCATTER,
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),
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],
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)
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),
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"/entities?action=ingest",
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{
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"entity": {
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"value": {
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"com.linkedin.metadata.snapshot.ChartSnapshot": {
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"urn": "urn:li:chart:(superset,227)",
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"aspects": [
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{
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"com.linkedin.chart.ChartInfo": {
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"customProperties": {},
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"title": "Weekly Messages",
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"description": "",
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"lastModified": {
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"created": {
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"time": 1618987484580,
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"actor": "urn:li:corpuser:datahub",
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},
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"lastModified": {
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"time": 1618987484580,
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"actor": "urn:li:corpuser:datahub",
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},
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},
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"type": "SCATTER",
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}
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}
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],
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}
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}
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},
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"systemMetadata": {},
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},
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),
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(
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# Verify that DataJobInfo is serialized properly (particularly it's union type).
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models.MetadataChangeEventClass(
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proposedSnapshot=models.DataJobSnapshotClass(
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urn="urn:li:dataJob:(urn:li:dataFlow:(airflow,dag_abc,PROD),task_456)",
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aspects=[
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models.DataJobInfoClass(
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name="User Deletions",
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description="Constructs the fct_users_deleted from logging_events",
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type=models.AzkabanJobTypeClass.SQL,
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)
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],
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)
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),
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"/entities?action=ingest",
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{
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"entity": {
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"value": {
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"com.linkedin.metadata.snapshot.DataJobSnapshot": {
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"urn": "urn:li:dataJob:(urn:li:dataFlow:(airflow,dag_abc,PROD),task_456)",
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"aspects": [
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{
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"com.linkedin.datajob.DataJobInfo": {
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"customProperties": {},
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"name": "User Deletions",
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"description": "Constructs the fct_users_deleted from logging_events",
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"type": {"string": "SQL"},
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}
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}
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],
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}
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}
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},
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"systemMetadata": {},
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},
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),
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(
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# Usage stats ingestion test.
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models.UsageAggregationClass(
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bucket=1623826800000,
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duration="DAY",
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resource="urn:li:dataset:(urn:li:dataPlatform:kafka,SampleKafkaDataset,PROD)",
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metrics=models.UsageAggregationMetricsClass(
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uniqueUserCount=2,
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users=[
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models.UserUsageCountsClass(
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user="urn:li:corpuser:jdoe",
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count=5,
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),
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models.UserUsageCountsClass(
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user="urn:li:corpuser:unknown",
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count=3,
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userEmail="foo@example.com",
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),
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],
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totalSqlQueries=1,
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topSqlQueries=["SELECT * FROM foo"],
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),
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),
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"/usageStats?action=batchIngest",
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{
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"buckets": [
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{
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"bucket": 1623826800000,
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"duration": "DAY",
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"resource": "urn:li:dataset:(urn:li:dataPlatform:kafka,SampleKafkaDataset,PROD)",
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"metrics": {
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"uniqueUserCount": 2,
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"users": [
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{"count": 5, "user": "urn:li:corpuser:jdoe"},
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{
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"count": 3,
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"user": "urn:li:corpuser:unknown",
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"userEmail": "foo@example.com",
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},
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],
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"totalSqlQueries": 1,
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"topSqlQueries": ["SELECT * FROM foo"],
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},
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}
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]
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},
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),
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(
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MetadataChangeProposalWrapper(
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entityUrn="urn:li:dataset:(urn:li:dataPlatform:foo,bar,PROD)",
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aspect=models.OwnershipClass(
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owners=[
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models.OwnerClass(
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owner="urn:li:corpuser:fbar",
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type=models.OwnershipTypeClass.DATAOWNER,
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)
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],
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lastModified=models.AuditStampClass(
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time=0,
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actor="urn:li:corpuser:fbar",
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),
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),
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),
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"/aspects?action=ingestProposal",
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{
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"proposal": {
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"entityType": "dataset",
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"entityUrn": "urn:li:dataset:(urn:li:dataPlatform:foo,bar,PROD)",
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"changeType": "UPSERT",
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"aspectName": "ownership",
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"aspect": {
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"value": '{"owners": [{"owner": "urn:li:corpuser:fbar", "type": "DATAOWNER"}], "ownerTypes": {}, "lastModified": {"time": 0, "actor": "urn:li:corpuser:fbar"}}',
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"contentType": "application/json",
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},
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}
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},
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),
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],
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)
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def test_datahub_rest_emitter(requests_mock, record, path, snapshot):
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def match_request_text(request: requests.Request) -> bool:
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requested_snapshot = request.json()
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assert (
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requested_snapshot == snapshot
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), f"Expected snapshot to be {json.dumps(snapshot)}, got {json.dumps(requested_snapshot)}"
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return True
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requests_mock.post(
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f"{MOCK_GMS_ENDPOINT}{path}",
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request_headers={"X-RestLi-Protocol-Version": "2.0.0"},
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additional_matcher=match_request_text,
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)
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emitter = DatahubRestEmitter(MOCK_GMS_ENDPOINT)
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emitter.emit(record)
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