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feat(ingestion/dagster): Dagster assetless ingestion (#11262)

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Co-authored-by: shubhamjagtap639 <shubham.jagtap@gslab.com>
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Tamas Nemeth 2024-10-24 16:06:00 +02:00 committed by GitHub
parent 707a02c036
commit f6760436b7
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8 changed files with 1160 additions and 312 deletions
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175
metadata-ingestion-modules/dagster-plugin/src/datahub_dagster_plugin/client/dagster_generator.py
View File

@ -1,4 +1,5 @@
from dataclasses import dataclass
from datetime import datetime, timezone
from logging import Logger
from typing import Any, Callable, Dict, List, NamedTuple, Optional, Sequence, Set
from urllib.parse import urlsplit
@ -12,6 +13,7 @@ from dagster import (
TableSchemaMetadataValue,
)
from dagster._core.execution.stats import RunStepKeyStatsSnapshot, StepEventStatus
from datahub.sql_parsing.sqlglot_utils import get_query_fingerprint
try:
from dagster._core.snap import JobSnapshot # type: ignore[attr-defined]
@ -32,13 +34,22 @@ from datahub.emitter.mce_builder import (
make_data_platform_urn,
make_dataplatform_instance_urn,
make_tag_urn,
make_ts_millis,
)
from datahub.emitter.mcp import MetadataChangeProposalWrapper
from datahub.ingestion.api.workunit import MetadataWorkUnit
from datahub.ingestion.graph.client import DatahubClientConfig, DataHubGraph
from datahub.metadata._schema_classes import (
AuditStampClass,
BrowsePathEntryClass,
BrowsePathsV2Class,
GlobalTagsClass,
QueryLanguageClass,
QueryPropertiesClass,
QuerySourceClass,
QueryStatementClass,
QuerySubjectClass,
QuerySubjectsClass,
TagAssociationClass,
)
from datahub.metadata.com.linkedin.pegasus2avro.schema import (
@ -63,6 +74,7 @@ from datahub.metadata.schema_classes import (
SubTypesClass,
UpstreamClass,
)
from datahub.metadata.urns import CorpUserUrn
from datahub.specific.dataset import DatasetPatchBuilder
from datahub.utilities.urns._urn_base import Urn
from datahub.utilities.urns.data_flow_urn import DataFlowUrn
@ -73,6 +85,8 @@ ASSET_SUBTYPE = "Asset"
DAGSTER_PLATFORM = "dagster"
_DEFAULT_USER_URN = CorpUserUrn("_ingestion")
class Constant:
"""
@ -212,6 +226,16 @@ class DatahubDagsterSourceConfig(DatasetSourceConfigMixin):
description="Whether to materialize asset dependency in DataHub. It emits a datasetKey for each dependencies. Default is False.",
)
emit_queries: Optional[bool] = pydantic.Field(
default=False,
description="Whether to emit queries aspects. Default is False.",
)
emit_assets: Optional[bool] = pydantic.Field(
default=True,
description="Whether to emit assets aspects. Default is True.",
)
debug_mode: Optional[bool] = pydantic.Field(
default=False,
description="Whether to enable debug mode",
@ -243,9 +267,10 @@ def job_url_generator(dagster_url: str, dagster_environment: DagsterEnvironment)
return base_url
class DagsterGenerator:
asset_group_name_cache: Dict[str, str] = {}
DATAHUB_ASSET_GROUP_NAME_CACHE: Dict[str, str] = {}
class DagsterGenerator:
def __init__(
self,
logger: Logger,
@ -298,17 +323,16 @@ class DagsterGenerator:
if asset_def:
for key, group_name in asset_def.group_names_by_key.items():
asset_urn = self.dataset_urn_from_asset(key.path)
DagsterGenerator.asset_group_name_cache[
asset_urn.urn()
] = group_name
DATAHUB_ASSET_GROUP_NAME_CACHE[asset_urn.urn()] = group_name
if self.config.debug_mode:
self.logger.debug(
f"Asset group name cache updated: {asset_urn.urn()} -> {group_name}"
)
if self.config.debug_mode:
self.logger.debug(
f"Asset group name cache: {DagsterGenerator.asset_group_name_cache}"
f"Asset group name cache: {DATAHUB_ASSET_GROUP_NAME_CACHE}"
)
self.logger.info(f"Asset group name cache: {DATAHUB_ASSET_GROUP_NAME_CACHE}")
def path_metadata_resolver(self, value: PathMetadataValue) -> Optional[DatasetUrn]:
"""
@ -347,6 +371,8 @@ class DagsterGenerator:
job_snapshot: JobSnapshot,
env: str,
platform_instance: Optional[str] = None,
remove_double_underscores: bool = True,
add_asset_group_tag: bool = True,
) -> DataFlow:
"""
Generates a Dataflow object from an Dagster Job Snapshot
@ -358,17 +384,34 @@ class DagsterGenerator:
if self.dagster_environment.is_cloud:
id = f"{self.dagster_environment.branch}/{self.dagster_environment.module}/{job_snapshot.name}"
else:
id = f"{self.dagster_environment.module}/{job_snapshot.name}"
module_name = (
self.dagster_environment.module
if self.dagster_environment.module
else self.dagster_environment.branch
)
id = f"{module_name}/{job_snapshot.name}"
flow_name = job_snapshot.name
if remove_double_underscores and flow_name.split("__"):
flow_name = flow_name.split("__")[-1]
dataflow = DataFlow(
orchestrator=Constant.ORCHESTRATOR,
id=id,
env=env,
name=job_snapshot.name,
name=flow_name,
platform_instance=platform_instance,
)
dataflow.description = job_snapshot.description
dataflow.tags = set(job_snapshot.tags.keys())
if add_asset_group_tag:
asset_group = self.get_asset_group_from_op_name(
job_snapshot.name.split("__")
)
if asset_group:
dataflow.tags.add(f"asset_group:{asset_group}")
if self.config.dagster_url:
dataflow.url = f"{job_url_generator(dagster_url=self.config.dagster_url, dagster_environment=self.dagster_environment)}/jobs/{job_snapshot.name}"
flow_property_bag: Dict[str, str] = {}
@ -386,6 +429,8 @@ class DagsterGenerator:
input_datasets: Dict[str, Set[DatasetUrn]],
output_datasets: Dict[str, Set[DatasetUrn]],
platform_instance: Optional[str] = None,
remove_double_underscores: bool = True,
add_asset_group_tag: bool = True,
) -> DataJob:
"""
Generates a Datajob object from an Dagster op snapshot
@ -403,8 +448,13 @@ class DagsterGenerator:
flow_id = f"{self.dagster_environment.branch}/{self.dagster_environment.module}/{job_snapshot.name}"
job_id = f"{self.dagster_environment.branch}/{self.dagster_environment.module}/{op_def_snap.name}"
else:
flow_id = f"{self.dagster_environment.module}/{job_snapshot.name}"
job_id = f"{self.dagster_environment.module}/{op_def_snap.name}"
module_name = (
self.dagster_environment.module
if self.dagster_environment.module
else self.dagster_environment.branch
)
flow_id = f"{module_name}/{job_snapshot.name}"
job_id = f"{module_name}/{op_def_snap.name}"
dataflow_urn = DataFlowUrn.create_from_ids(
orchestrator=Constant.ORCHESTRATOR,
@ -412,10 +462,15 @@ class DagsterGenerator:
env=env,
platform_instance=platform_instance,
)
job_name = op_def_snap.name
if remove_double_underscores and job_name.split("__"):
job_name = job_name.split("__")[-1]
datajob = DataJob(
id=job_id,
flow_urn=dataflow_urn,
name=op_def_snap.name,
name=job_name,
)
if self.config.dagster_url:
@ -424,6 +479,13 @@ class DagsterGenerator:
datajob.description = op_def_snap.description
datajob.tags = set(op_def_snap.tags.keys())
if add_asset_group_tag:
asset_group = self.get_asset_group_from_op_name(
op_def_snap.name.split("__")
)
if asset_group:
datajob.tags.add(f"asset_group:{asset_group}")
inlets: Set[DatasetUrn] = set()
# Add upstream dependencies for this op
for upstream_op_name in step_deps[op_def_snap.name]:
@ -667,9 +729,9 @@ class DagsterGenerator:
if not target_urn:
target_urn = asset_urn
self.logger.info(
f"Getting {asset_urn.urn()} from Asset Cache: {DagsterGenerator.asset_group_name_cache}"
f"Getting {asset_urn.urn()} from Asset Cache: {DATAHUB_ASSET_GROUP_NAME_CACHE}"
)
group_name = DagsterGenerator.asset_group_name_cache.get(asset_urn.urn())
group_name = DATAHUB_ASSET_GROUP_NAME_CACHE.get(asset_urn.urn())
if group_name:
current_tags: Optional[GlobalTagsClass] = graph.get_aspect(
entity_urn=target_urn.urn(),
@ -698,6 +760,20 @@ class DagsterGenerator:
return None
def _gen_entity_browsepath_aspect(
self,
entity_urn: str,
paths: List[str],
) -> MetadataWorkUnit:
entries = [BrowsePathEntryClass(id=path) for path in paths]
if self.config.platform_instance:
urn = make_dataplatform_instance_urn("asset", self.config.platform_instance)
entries = [BrowsePathEntryClass(id=urn, urn=urn)] + entries
return MetadataChangeProposalWrapper(
entityUrn=entity_urn,
aspect=BrowsePathsV2Class(entries),
).as_workunit()
def emit_asset(
self,
graph: DataHubGraph,
@ -771,6 +847,7 @@ class DagsterGenerator:
origin=DatasetUrn.create_from_string(downstream).env,
),
)
if self.config.debug_mode:
self.logger.info(f"mcp: {mcp}")
graph.emit_mcp(mcp)
@ -807,20 +884,38 @@ class DagsterGenerator:
for patch_event in patch_builder.build():
graph.emit_mcp(patch_event)
if self.config.debug_mode:
self.logger.info(f"asset_key: {asset_key}")
self.generate_browse_path(asset_key=asset_key, urn=dataset_urn, graph=graph)
return dataset_urn
def get_asset_group_from_op_name(self, asset_key: Sequence[str]) -> Optional[str]:
"""
Get asset group name from op name
"""
asset_urn = self.dataset_urn_from_asset(asset_key).urn()
asset_group_name = DATAHUB_ASSET_GROUP_NAME_CACHE.get(asset_urn)
if asset_group_name:
self.logger.info(
f"asset_key: {asset_key}, urn: {asset_urn}, asset_group_name: {asset_group_name}"
)
return asset_group_name
else:
self.logger.info(
f"asset_key: {asset_key}, urn: {asset_urn} not in {DATAHUB_ASSET_GROUP_NAME_CACHE}, asset_group_name: None"
)
return None
def generate_browse_path(
self, asset_key: Sequence[str], urn: Urn, graph: DataHubGraph
) -> None:
"""
Generate browse path from asset key
"""
asset_group_name = DagsterGenerator.asset_group_name_cache.get(
self.dataset_urn_from_asset(asset_key).urn()
)
browsePaths: List[BrowsePathEntryClass] = []
asset_group_name = self.get_asset_group_from_op_name(asset_key)
if asset_group_name:
browsePaths.append(BrowsePathEntryClass(asset_group_name))
@ -834,3 +929,51 @@ class DagsterGenerator:
),
)
graph.emit_mcp(mcp)
def gen_query_aspect(
self,
graph: DataHubGraph,
platform: str,
query_subject_urns: List[str],
query: str,
job_urn: Optional[str] = None,
) -> None:
"""
Generate query aspect for lineage
"""
query_id = get_query_fingerprint(query, platform)
aspects = [
QueryPropertiesClass(
statement=QueryStatementClass(
value=query,
language=QueryLanguageClass.SQL,
),
source=QuerySourceClass.SYSTEM,
origin=job_urn if job_urn else None,
created=AuditStampClass(
make_ts_millis(datetime.now(tz=timezone.utc)),
actor=_DEFAULT_USER_URN.urn(),
),
lastModified=AuditStampClass(
make_ts_millis(datetime.now(tz=timezone.utc)),
actor=_DEFAULT_USER_URN.urn(),
),
),
QuerySubjectsClass(
subjects=[QuerySubjectClass(entity=urn) for urn in query_subject_urns]
),
DataPlatformInstanceClass(
platform=make_data_platform_urn(platform),
),
SubTypesClass(
typeNames=["Query"],
),
]
mcps = MetadataChangeProposalWrapper.construct_many(
entityUrn=f"urn:li:query:dagster_{query_id}",
aspects=aspects,
)
for mcp in mcps:
graph.emit_mcp(mcp)

182
metadata-ingestion-modules/dagster-plugin/src/datahub_dagster_plugin/sensors/datahub_sensors.py
View File

@ -46,8 +46,10 @@ from datahub.sql_parsing.sqlglot_lineage import (
create_lineage_sql_parsed_result,
)
from datahub.utilities.urns.dataset_urn import DatasetUrn
from datahub.utilities.urns.error import InvalidUrnError
from datahub_dagster_plugin.client.dagster_generator import (
DATAHUB_ASSET_GROUP_NAME_CACHE,
Constant,
DagsterEnvironment,
DagsterGenerator,
@ -268,7 +270,6 @@ class DatahubSensors:
module = code_pointer.module
else:
context.log.error("Unable to get Module")
return None
dagster_environment = DagsterEnvironment(
is_cloud=os.getenv("DAGSTER_CLOUD_IS_BRANCH_DEPLOYMENT", None) is not None,
@ -326,23 +327,64 @@ class DatahubSensors:
dataset_inputs: Dict[str, Set[DatasetUrn]],
dataset_outputs: Dict[str, Set[DatasetUrn]],
) -> None:
if (
log.dagster_event
and log.dagster_event.event_type == DagsterEventType.ASSET_MATERIALIZATION
):
assert log.step_key
if not self._is_valid_asset_materialization(log):
return
materialization = log.asset_materialization
if not materialization:
asset_materialization = log.asset_materialization
if asset_materialization is None:
return
asset_key = asset_materialization.asset_key.path
asset_downstream_urn = self._get_asset_downstream_urn(
log, context, dagster_generator, list(asset_key)
)
if not asset_downstream_urn:
return
properties = {
key: str(value) for (key, value) in materialization.metadata.items()
key: str(value) for (key, value) in asset_materialization.metadata.items()
}
asset_key = materialization.asset_key.path
upstreams, downstreams = self._process_lineage(
context=context,
dagster_generator=dagster_generator,
log=log,
asset_downstream_urn=asset_downstream_urn,
)
self._emit_or_connect_asset(
context,
dagster_generator,
log,
list(asset_key),
properties,
upstreams,
downstreams,
dataset_inputs,
dataset_outputs,
)
def _is_valid_asset_materialization(self, log: EventLogEntry) -> bool:
return (
log.dagster_event is not None
and log.dagster_event.event_type == DagsterEventType.ASSET_MATERIALIZATION
and log.step_key is not None
and log.asset_materialization is not None
)
def _get_asset_downstream_urn(
self,
log: EventLogEntry,
context: RunStatusSensorContext,
dagster_generator: DagsterGenerator,
asset_key: List[str],
) -> Optional[DatasetUrn]:
materialization = log.asset_materialization
if materialization is None:
return None
asset_downstream_urn: Optional[DatasetUrn] = None
# If DataHub Urn is set then we prefer that as downstream urn
if materialization.metadata.get("datahub_urn") and isinstance(
materialization.metadata.get("datahub_urn"), TextMetadataValue
):
@ -364,24 +406,25 @@ class DatahubSensors:
f"asset_downstream_urn from asset keys: {asset_downstream_urn}"
)
if asset_downstream_urn:
context.log.info(f"asset_downstream_urn: {asset_downstream_urn}")
return asset_downstream_urn
def _process_lineage(
self,
context: RunStatusSensorContext,
dagster_generator: DagsterGenerator,
log: EventLogEntry,
asset_downstream_urn: DatasetUrn,
) -> Tuple[Set[str], Set[str]]:
downstreams = {asset_downstream_urn.urn()}
context.log.info(f"downstreams: {downstreams}")
upstreams: Set[str] = set()
if self.config.enable_asset_query_metadata_parsing:
try:
if (
materialization
and materialization.metadata
and materialization.metadata.get("Query")
and isinstance(
materialization.metadata.get("Query"), TextMetadataValue
)
log.asset_materialization
and self.config.enable_asset_query_metadata_parsing
):
query_metadata = materialization.metadata.get("Query")
assert query_metadata
try:
query_metadata = log.asset_materialization.metadata.get("Query")
if isinstance(query_metadata, TextMetadataValue):
lineage = self.parse_sql(
context=context,
sql_query=str(query_metadata.text),
@ -390,36 +433,82 @@ class DatahubSensors:
"urn:li:dataPlatform:", ""
),
)
# To make sure we don't process select queries check if downstream is present
if lineage and lineage.downstreams:
downstreams = downstreams.union(
set(lineage.downstreams)
if self.config.emit_queries:
dagster_generator.gen_query_aspect(
graph=self.graph,
platform=asset_downstream_urn.platform,
query_subject_urns=lineage.upstreams
+ lineage.downstreams,
query=str(query_metadata.text),
)
downstreams = downstreams.union(set(lineage.downstreams))
upstreams = upstreams.union(set(lineage.upstreams))
context.log.info(
f"Upstreams: {upstreams} Downstreams: {downstreams}"
)
else:
context.log.info(
f"Lineage not found for {query_metadata.text}"
)
context.log.info(f"Lineage not found for {query_metadata.text}")
else:
context.log.info("Query not found in metadata")
except Exception as e:
context.log.info(f"Error in processing asset logs: {e}")
context.log.exception(f"Error in processing asset logs: {e}")
# Emitting asset with upstreams and downstreams
return upstreams, downstreams
def _emit_or_connect_asset(
self,
context: RunStatusSensorContext,
dagster_generator: DagsterGenerator,
log: EventLogEntry,
asset_key: List[str],
properties: Dict[str, str],
upstreams: Set[str],
downstreams: Set[str],
dataset_inputs: Dict[str, Set[DatasetUrn]],
dataset_outputs: Dict[str, Set[DatasetUrn]],
) -> None:
if self.config.emit_assets:
context.log.info("Emitting asset metadata...")
dataset_urn = dagster_generator.emit_asset(
self.graph,
asset_key,
materialization.description,
log.asset_materialization.description
if log.asset_materialization
else None,
properties,
downstreams=downstreams,
upstreams=upstreams,
materialize_dependencies=self.config.materialize_dependencies,
)
if log.step_key:
dataset_outputs[log.step_key].add(dataset_urn)
else:
context.log.info(
"Not emitting assets but connecting materialized dataset to DataJobs"
)
if log.step_key:
dataset_outputs[log.step_key] = dataset_outputs[log.step_key].union(
[DatasetUrn.from_string(d) for d in downstreams]
)
dataset_upstreams: List[DatasetUrn] = []
for u in upstreams:
try:
dataset_upstreams.append(DatasetUrn.from_string(u))
except InvalidUrnError as e:
context.log.error(
f"Error in parsing upstream dataset urn: {e}", exc_info=True
)
continue
dataset_inputs[log.step_key] = dataset_inputs[log.step_key].union(
dataset_upstreams
)
context.log.info(
f"Dataset Inputs: {dataset_inputs[log.step_key]} Dataset Outputs: {dataset_outputs[log.step_key]}"
)
def process_asset_observation(
self,
@ -593,7 +682,9 @@ class DatahubSensors:
dagster_environment=dagster_environment,
)
context.log.info("Emitting asset metadata...")
context.log.info(
f"Updating asset group name cache... {DATAHUB_ASSET_GROUP_NAME_CACHE}"
)
dagster_generator.update_asset_group_name_cache(context)
return SkipReason("Asset metadata processed")
@ -681,9 +772,20 @@ class DatahubSensors:
platform_instance=self.config.platform_instance,
)
if (
dataflow.name
and dataflow.name.startswith("__ASSET_JOB")
and dataflow.name.split("__")
):
dagster_generator.generate_browse_path(
dataflow.name.split("__"), urn=dataflow.urn, graph=self.graph
)
dataflow.name = dataflow.name.split("__")[-1]
dataflow.emit(self.graph)
if self.config.debug_mode:
for mcp in dataflow.generate_mcp():
if self.config.debug_mode:
context.log.debug(f"Emitted MCP: {mcp}")
# Emit dagster job run which get mapped with datahub data process instance entity
@ -721,6 +823,16 @@ class DatahubSensors:
input_datasets=dataset_inputs,
)
if (
datajob.name
and datajob.name.startswith("__ASSET_JOB")
and datajob.name.split("__")
):
dagster_generator.generate_browse_path(
datajob.name.split("__"), urn=datajob.urn, graph=self.graph
)
datajob.name = datajob.name.split("__")[-1]
datajob.emit(self.graph)
if self.config.debug_mode:

21
metadata-ingestion-modules/dagster-plugin/tests/unit/conftest.py Normal file
View File

@ -0,0 +1,21 @@
import pathlib
import site
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from _pytest.config import Parser
def pytest_addoption(parser: "Parser") -> None:
parser.addoption(
"--update-golden-files",
action="store_true",
default=False,
)
# See https://coverage.readthedocs.io/en/latest/subprocess.html#configuring-python-for-sub-process-measurement
coverage_startup_code = "import coverage; coverage.process_startup()"
site_packages_dir = pathlib.Path(site.getsitepackages()[0])
pth_file_path = site_packages_dir / "datahub_coverage_startup.pth"
pth_file_path.write_text(coverage_startup_code)

658
metadata-ingestion-modules/dagster-plugin/tests/unit/golden/golden_test_emit_metadata_mcps.json Normal file
View File

@ -0,0 +1,658 @@
[
{
"entityType": "dataFlow",
"entityUrn": "urn:li:dataFlow:(dagster,prod/etl,PROD)",
"changeType": "UPSERT",
"aspectName": "dataFlowInfo",
"aspect": {
"json": {
"customProperties": {},
"name": "etl",
"env": "PROD"
}
}
},
{
"entityType": "dataFlow",
"entityUrn": "urn:li:dataFlow:(dagster,prod/etl,PROD)",
"changeType": "UPSERT",
"aspectName": "status",
"aspect": {
"json": {
"removed": false
}
}
},
{
"entityType": "dataFlow",
"entityUrn": "urn:li:dataFlow:(dagster,prod/etl,PROD)",
"changeType": "UPSERT",
"aspectName": "ownership",
"aspect": {
"json": {
"owners": [],
"ownerTypes": {},
"lastModified": {
"time": 0,
"actor": "urn:li:corpuser:dagster"
}
}
}
},
{
"entityType": "dataFlow",
"entityUrn": "urn:li:dataFlow:(dagster,prod/etl,PROD)",
"changeType": "UPSERT",
"aspectName": "globalTags",
"aspect": {
"json": {
"tags": []
}
}
},
{
"entityType": "dataFlow",
"entityUrn": "urn:li:dataFlow:(dagster,prod/etl,PROD)",
"changeType": "UPSERT",
"aspectName": "dataFlowInfo",
"aspect": {
"json": {
"customProperties": {},
"name": "etl",
"env": "PROD"
}
}
},
{
"entityType": "dataFlow",
"entityUrn": "urn:li:dataFlow:(dagster,prod/etl,PROD)",
"changeType": "UPSERT",
"aspectName": "status",
"aspect": {
"json": {
"removed": false
}
}
},
{
"entityType": "dataFlow",
"entityUrn": "urn:li:dataFlow:(dagster,prod/etl,PROD)",
"changeType": "UPSERT",
"aspectName": "ownership",
"aspect": {
"json": {
"owners": [],
"ownerTypes": {},
"lastModified": {
"time": 0,
"actor": "urn:li:corpuser:dagster"
}
}
}
},
{
"entityType": "dataFlow",
"entityUrn": "urn:li:dataFlow:(dagster,prod/etl,PROD)",
"changeType": "UPSERT",
"aspectName": "globalTags",
"aspect": {
"json": {
"tags": []
}
}
},
{
"entityType": "dataProcessInstance",
"entityUrn": "urn:li:dataProcessInstance:0fa780ff92120ac3bf49d0bc070bbda2",
"changeType": "UPSERT",
"aspectName": "dataProcessInstanceProperties",
"aspect": {
"json": {
"customProperties": {
"job_snapshot_id": "28d03bf7b3138bea153a21f70f29e7c3ffa6ab0a",
"execution_plan_snapshot_id": "0f504b218cd28750ffa8d90a40e9647acba72021",
"has_repository_load_data": "False",
"tags": "{}",
"steps_succeeded": "2",
"steps_failed": "0",
"materializations": "0",
"expectations": "0",
"start_time": "1720681200.0",
"end_time": "1720681200.0"
},
"name": "12345678123456781234567812345678",
"type": "BATCH_SCHEDULED",
"created": {
"time": 1720681200000,
"actor": "urn:li:corpuser:datahub"
}
}
}
},
{
"entityType": "dataJob",
"entityUrn": "urn:li:dataJob:(urn:li:dataFlow:(dagster,prod/etl,PROD),prod/extract)",
"changeType": "UPSERT",
"aspectName": "dataJobInfo",
"aspect": {
"json": {
"customProperties": {
"output_result": "{'name': 'result', 'dagster_type_key': 'Any', 'description': None, 'is_required': True, 'metadata': {'datahub.outputs': JsonMetadataValue(data=['urn:li:dataset:(urn:li:dataPlatform:snowflake,tableB,PROD)'])}, 'is_dynamic': False}"
},
"name": "extract",
"type": {
"string": "COMMAND"
},
"env": "PROD"
}
}
},
{
"entityType": "dataProcessInstance",
"entityUrn": "urn:li:dataProcessInstance:0fa780ff92120ac3bf49d0bc070bbda2",
"changeType": "UPSERT",
"aspectName": "dataProcessInstanceRelationships",
"aspect": {
"json": {
"parentTemplate": "urn:li:dataFlow:(dagster,prod/etl,PROD)",
"upstreamInstances": []
}
}
},
{
"entityType": "dataJob",
"entityUrn": "urn:li:dataJob:(urn:li:dataFlow:(dagster,prod/etl,PROD),prod/extract)",
"changeType": "UPSERT",
"aspectName": "status",
"aspect": {
"json": {
"removed": false
}
}
},
{
"entityType": "dataProcessInstance",
"entityUrn": "urn:li:dataProcessInstance:0fa780ff92120ac3bf49d0bc070bbda2",
"changeType": "UPSERT",
"aspectName": "dataProcessInstanceRunEvent",
"aspect": {
"json": {
"timestampMillis": 1720681200000,
"partitionSpec": {
"partition": "FULL_TABLE_SNAPSHOT",
"type": "FULL_TABLE"
},
"status": "STARTED"
}
}
},
{
"entityType": "dataProcessInstance",
"entityUrn": "urn:li:dataProcessInstance:0fa780ff92120ac3bf49d0bc070bbda2",
"changeType": "UPSERT",
"aspectName": "dataProcessInstanceRunEvent",
"aspect": {
"json": {
"timestampMillis": 1720681200000,
"partitionSpec": {
"partition": "FULL_TABLE_SNAPSHOT",
"type": "FULL_TABLE"
},
"status": "COMPLETE",
"result": {
"type": "SUCCESS",
"nativeResultType": "dagster"
}
}
}
},
{
"entityType": "dataJob",
"entityUrn": "urn:li:dataJob:(urn:li:dataFlow:(dagster,prod/etl,PROD),prod/extract)",
"changeType": "UPSERT",
"aspectName": "dataJobInputOutput",
"aspect": {
"json": {
"inputDatasets": [],
"outputDatasets": [],
"inputDatajobs": [],
"fineGrainedLineages": []
}
}
},
{
"entityType": "dataJob",
"entityUrn": "urn:li:dataJob:(urn:li:dataFlow:(dagster,prod/etl,PROD),prod/extract)",
"changeType": "UPSERT",
"aspectName": "ownership",
"aspect": {
"json": {
"owners": [],
"ownerTypes": {},
"lastModified": {
"time": 0,
"actor": "urn:li:corpuser:dagster"
}
}
}
},
{
"entityType": "dataJob",
"entityUrn": "urn:li:dataJob:(urn:li:dataFlow:(dagster,prod/etl,PROD),prod/extract)",
"changeType": "UPSERT",
"aspectName": "globalTags",
"aspect": {
"json": {
"tags": []
}
}
},
{
"entityType": "dataJob",
"entityUrn": "urn:li:dataJob:(urn:li:dataFlow:(dagster,prod/etl,PROD),prod/extract)",
"changeType": "UPSERT",
"aspectName": "dataJobInfo",
"aspect": {
"json": {
"customProperties": {
"output_result": "{'name': 'result', 'dagster_type_key': 'Any', 'description': None, 'is_required': True, 'metadata': {'datahub.outputs': JsonMetadataValue(data=['urn:li:dataset:(urn:li:dataPlatform:snowflake,tableB,PROD)'])}, 'is_dynamic': False}"
},
"name": "extract",
"type": {
"string": "COMMAND"
},
"env": "PROD"
}
}
},
{
"entityType": "dataJob",
"entityUrn": "urn:li:dataJob:(urn:li:dataFlow:(dagster,prod/etl,PROD),prod/extract)",
"changeType": "UPSERT",
"aspectName": "status",
"aspect": {
"json": {
"removed": false
}
}
},
{
"entityType": "dataJob",
"entityUrn": "urn:li:dataJob:(urn:li:dataFlow:(dagster,prod/etl,PROD),prod/extract)",
"changeType": "UPSERT",
"aspectName": "dataJobInputOutput",
"aspect": {
"json": {
"inputDatasets": [],
"outputDatasets": [],
"inputDatajobs": [],
"fineGrainedLineages": []
}
}
},
{
"entityType": "dataJob",
"entityUrn": "urn:li:dataJob:(urn:li:dataFlow:(dagster,prod/etl,PROD),prod/extract)",
"changeType": "UPSERT",
"aspectName": "ownership",
"aspect": {
"json": {
"owners": [],
"ownerTypes": {},
"lastModified": {
"time": 0,
"actor": "urn:li:corpuser:dagster"
}
}
}
},
{
"entityType": "dataJob",
"entityUrn": "urn:li:dataJob:(urn:li:dataFlow:(dagster,prod/etl,PROD),prod/extract)",
"changeType": "UPSERT",
"aspectName": "globalTags",
"aspect": {
"json": {
"tags": []
}
}
},
{
"entityType": "dataJob",
"entityUrn": "urn:li:dataJob:(urn:li:dataFlow:(dagster,prod/etl,PROD),prod/transform)",
"changeType": "UPSERT",
"aspectName": "dataJobInfo",
"aspect": {
"json": {
"customProperties": {
"input.data": "{'name': 'data', 'dagster_type_key': 'Any', 'description': None, 'metadata': {'datahub.inputs': JsonMetadataValue(data=['urn:li:dataset:(urn:li:dataPlatform:snowflake,tableA,PROD)'])}}",
"output_result": "{'name': 'result', 'dagster_type_key': 'Any', 'description': None, 'is_required': True, 'metadata': {}, 'is_dynamic': False}"
},
"name": "transform",
"type": {
"string": "COMMAND"
},
"env": "PROD"
}
}
},
{
"entityType": "dataJob",
"entityUrn": "urn:li:dataJob:(urn:li:dataFlow:(dagster,prod/etl,PROD),prod/transform)",
"changeType": "UPSERT",
"aspectName": "status",
"aspect": {
"json": {
"removed": false
}
}
},
{
"entityType": "dataJob",
"entityUrn": "urn:li:dataJob:(urn:li:dataFlow:(dagster,prod/etl,PROD),prod/transform)",
"changeType": "UPSERT",
"aspectName": "dataJobInputOutput",
"aspect": {
"json": {
"inputDatasets": [
"urn:li:dataset:(urn:li:dataPlatform:snowflake,tableA,PROD)"
],
"outputDatasets": [],
"inputDatajobs": [],
"fineGrainedLineages": []
}
}
},
{
"entityType": "dataset",
"entityUrn": "urn:li:dataset:(urn:li:dataPlatform:snowflake,tableA,PROD)",
"changeType": "UPSERT",
"aspectName": "datasetKey",
"aspect": {
"json": {
"platform": "urn:li:dataPlatform:snowflake",
"name": "tableA",
"origin": "PROD"
}
}
},
{
"entityType": "dataProcessInstance",
"entityUrn": "urn:li:dataProcessInstance:8e047f916b20c89e1874518890d6ff7e",
"changeType": "UPSERT",
"aspectName": "dataProcessInstanceProperties",
"aspect": {
"json": {
"customProperties": {
"step_key": "extract",
"attempts": "1",
"start_time": "1720681200.0",
"end_time": "1720681200.0"
},
"name": "12345678123456781234567812345678.prod/extract",
"type": "BATCH_SCHEDULED",
"created": {
"time": 1720681200000,
"actor": "urn:li:corpuser:datahub"
}
}
}
},
{
"entityType": "dataJob",
"entityUrn": "urn:li:dataJob:(urn:li:dataFlow:(dagster,prod/etl,PROD),prod/transform)",
"changeType": "UPSERT",
"aspectName": "ownership",
"aspect": {
"json": {
"owners": [],
"ownerTypes": {},
"lastModified": {
"time": 0,
"actor": "urn:li:corpuser:dagster"
}
}
}
},
{
"entityType": "dataProcessInstance",
"entityUrn": "urn:li:dataProcessInstance:8e047f916b20c89e1874518890d6ff7e",
"changeType": "UPSERT",
"aspectName": "dataProcessInstanceRelationships",
"aspect": {
"json": {
"parentTemplate": "urn:li:dataJob:(urn:li:dataFlow:(dagster,prod/etl,PROD),prod/extract)",
"upstreamInstances": []
}
}
},
{
"entityType": "dataJob",
"entityUrn": "urn:li:dataJob:(urn:li:dataFlow:(dagster,prod/etl,PROD),prod/transform)",
"changeType": "UPSERT",
"aspectName": "globalTags",
"aspect": {
"json": {
"tags": []
}
}
},
{
"entityType": "dataProcessInstance",
"entityUrn": "urn:li:dataProcessInstance:8e047f916b20c89e1874518890d6ff7e",
"changeType": "UPSERT",
"aspectName": "dataProcessInstanceRunEvent",
"aspect": {
"json": {
"timestampMillis": 1720681200000,
"partitionSpec": {
"partition": "FULL_TABLE_SNAPSHOT",
"type": "FULL_TABLE"
},
"status": "STARTED"
}
}
},
{
"entityType": "dataProcessInstance",
"entityUrn": "urn:li:dataProcessInstance:8e047f916b20c89e1874518890d6ff7e",
"changeType": "UPSERT",
"aspectName": "dataProcessInstanceRunEvent",
"aspect": {
"json": {
"timestampMillis": 1720681200000,
"partitionSpec": {
"partition": "FULL_TABLE_SNAPSHOT",
"type": "FULL_TABLE"
},
"status": "COMPLETE",
"result": {
"type": "SUCCESS",
"nativeResultType": "dagster"
}
}
}
},
{
"entityType": "dataJob",
"entityUrn": "urn:li:dataJob:(urn:li:dataFlow:(dagster,prod/etl,PROD),prod/transform)",
"changeType": "UPSERT",
"aspectName": "dataJobInfo",
"aspect": {
"json": {
"customProperties": {
"input.data": "{'name': 'data', 'dagster_type_key': 'Any', 'description': None, 'metadata': {'datahub.inputs': JsonMetadataValue(data=['urn:li:dataset:(urn:li:dataPlatform:snowflake,tableA,PROD)'])}}",
"output_result": "{'name': 'result', 'dagster_type_key': 'Any', 'description': None, 'is_required': True, 'metadata': {}, 'is_dynamic': False}"
},
"name": "transform",
"type": {
"string": "COMMAND"
},
"env": "PROD"
}
}
},
{
"entityType": "dataJob",
"entityUrn": "urn:li:dataJob:(urn:li:dataFlow:(dagster,prod/etl,PROD),prod/transform)",
"changeType": "UPSERT",
"aspectName": "status",
"aspect": {
"json": {
"removed": false
}
}
},
{
"entityType": "dataJob",
"entityUrn": "urn:li:dataJob:(urn:li:dataFlow:(dagster,prod/etl,PROD),prod/transform)",
"changeType": "UPSERT",
"aspectName": "dataJobInputOutput",
"aspect": {
"json": {
"inputDatasets": [
"urn:li:dataset:(urn:li:dataPlatform:snowflake,tableA,PROD)"
],
"outputDatasets": [],
"inputDatajobs": [],
"fineGrainedLineages": []
}
}
},
{
"entityType": "dataset",
"entityUrn": "urn:li:dataset:(urn:li:dataPlatform:snowflake,tableA,PROD)",
"changeType": "UPSERT",
"aspectName": "datasetKey",
"aspect": {
"json": {
"platform": "urn:li:dataPlatform:snowflake",
"name": "tableA",
"origin": "PROD"
}
}
},
{
"entityType": "dataJob",
"entityUrn": "urn:li:dataJob:(urn:li:dataFlow:(dagster,prod/etl,PROD),prod/transform)",
"changeType": "UPSERT",
"aspectName": "ownership",
"aspect": {
"json": {
"owners": [],
"ownerTypes": {},
"lastModified": {
"time": 0,
"actor": "urn:li:corpuser:dagster"
}
}
}
},
{
"entityType": "dataJob",
"entityUrn": "urn:li:dataJob:(urn:li:dataFlow:(dagster,prod/etl,PROD),prod/transform)",
"changeType": "UPSERT",
"aspectName": "globalTags",
"aspect": {
"json": {
"tags": []
}
}
},
{
"entityType": "dataProcessInstance",
"entityUrn": "urn:li:dataProcessInstance:6d553b12b2e5bf4cff8dc527e12e7116",
"changeType": "UPSERT",
"aspectName": "dataProcessInstanceProperties",
"aspect": {
"json": {
"customProperties": {
"step_key": "transform",
"attempts": "1",
"start_time": "1720681200.0",
"end_time": "1720681200.0"
},
"name": "12345678123456781234567812345678.prod/transform",
"type": "BATCH_SCHEDULED",
"created": {
"time": 1720681200000,
"actor": "urn:li:corpuser:datahub"
}
}
}
},
{
"entityType": "dataset",
"entityUrn": "urn:li:dataset:(urn:li:dataPlatform:snowflake,tableA,PROD)",
"changeType": "UPSERT",
"aspectName": "datasetKey",
"aspect": {
"json": {
"platform": "urn:li:dataPlatform:snowflake",
"name": "tableA",
"origin": "PROD"
}
}
},
{
"entityType": "dataProcessInstance",
"entityUrn": "urn:li:dataProcessInstance:6d553b12b2e5bf4cff8dc527e12e7116",
"changeType": "UPSERT",
"aspectName": "dataProcessInstanceRelationships",
"aspect": {
"json": {
"parentTemplate": "urn:li:dataJob:(urn:li:dataFlow:(dagster,prod/etl,PROD),prod/transform)",
"upstreamInstances": []
}
}
},
{
"entityType": "dataProcessInstance",
"entityUrn": "urn:li:dataProcessInstance:6d553b12b2e5bf4cff8dc527e12e7116",
"changeType": "UPSERT",
"aspectName": "dataProcessInstanceInput",
"aspect": {
"json": {
"inputs": [
"urn:li:dataset:(urn:li:dataPlatform:snowflake,tableA,PROD)"
]
}
}
},
{
"entityType": "dataProcessInstance",
"entityUrn": "urn:li:dataProcessInstance:6d553b12b2e5bf4cff8dc527e12e7116",
"changeType": "UPSERT",
"aspectName": "dataProcessInstanceRunEvent",
"aspect": {
"json": {
"timestampMillis": 1720681200000,
"partitionSpec": {
"partition": "FULL_TABLE_SNAPSHOT",
"type": "FULL_TABLE"
},
"status": "STARTED"
}
}
},
{
"entityType": "dataProcessInstance",
"entityUrn": "urn:li:dataProcessInstance:6d553b12b2e5bf4cff8dc527e12e7116",
"changeType": "UPSERT",
"aspectName": "dataProcessInstanceRunEvent",
"aspect": {
"json": {
"timestampMillis": 1720681200000,
"partitionSpec": {
"partition": "FULL_TABLE_SNAPSHOT",
"type": "FULL_TABLE"
},
"status": "COMPLETE",
"result": {
"type": "SUCCESS",
"nativeResultType": "dagster"
}
}
}
}
]

287
metadata-ingestion-modules/dagster-plugin/tests/unit/test_dagster.py
View File

@ -1,6 +1,11 @@
import json
import pathlib
import tempfile
import uuid
from typing import Dict, List, Mapping, Sequence, Set
from unittest.mock import Mock, patch
import pytest
import dagster._core.utils
from dagster import (
DagsterInstance,
In,
@ -11,12 +16,16 @@ from dagster import (
job,
op,
)
from datahub.api.entities.dataprocess.dataprocess_instance import (
DataProcessInstanceKey,
InstanceRunResult,
from dagster._core.definitions.job_definition import JobDefinition
from dagster._core.definitions.repository_definition import (
RepositoryData,
RepositoryDefinition,
)
from datahub.configuration.source_common import DEFAULT_ENV
from dagster._core.definitions.resource_definition import ResourceDefinition
from datahub.emitter.mcp import MetadataChangeProposalWrapper
from datahub.ingestion.graph.client import DatahubClientConfig
from freezegun import freeze_time
from utils.utils import PytestConfig, check_golden_file
from datahub_dagster_plugin.client.dagster_generator import DatahubDagsterSourceConfig
from datahub_dagster_plugin.sensors.datahub_sensors import (
@ -24,12 +33,49 @@ from datahub_dagster_plugin.sensors.datahub_sensors import (
make_datahub_sensor,
)
FROZEN_TIME = "2024-07-11 07:00:00"
@patch("datahub.ingestion.graph.client.DataHubGraph", autospec=True)
@pytest.mark.skip(reason="disabling this test unti it will use proper golden files")
call_num = 0
def make_new_run_id_mock() -> str:
global call_num
call_num += 1
return f"test_run_id_{call_num}"
dagster._core.utils.make_new_run_id = make_new_run_id_mock
@patch("datahub_dagster_plugin.sensors.datahub_sensors.DataHubGraph", autospec=True)
def test_datahub_sensor(mock_emit):
instance = DagsterInstance.ephemeral()
context = build_sensor_context(instance=instance)
class DummyRepositoryData(RepositoryData):
def __init__(self):
self.sensors = []
def get_all_jobs(self) -> Sequence["JobDefinition"]:
return []
def get_top_level_resources(self) -> Mapping[str, "ResourceDefinition"]:
"""Return all top-level resources in the repository as a list,
such as those provided to the Definitions constructor.
Returns:
List[ResourceDefinition]: All top-level resources in the repository.
"""
return {}
def get_env_vars_by_top_level_resource(self) -> Mapping[str, Set[str]]:
return {}
repository_defintion = RepositoryDefinition(
name="testRepository", repository_data=DummyRepositoryData()
)
context = build_sensor_context(
instance=instance, repository_def=repository_defintion
)
mock_emit.return_value = Mock()
config = DatahubDagsterSourceConfig(
@ -44,9 +90,13 @@ def test_datahub_sensor(mock_emit):
assert isinstance(skip_reason, SkipReason)
@patch("datahub_dagster_plugin.sensors.datahub_sensors.DatahubClient", autospec=True)
@pytest.mark.skip(reason="disabling this test unti it will use proper golden files")
def test_emit_metadata(mock_emit):
TEST_UUIDS = ["uuid_{}".format(i) for i in range(10000)]
@patch.object(uuid, "uuid4", side_effect=TEST_UUIDS)
@patch("datahub_dagster_plugin.sensors.datahub_sensors.DataHubGraph", autospec=True)
@freeze_time(FROZEN_TIME)
def test_emit_metadata(mock_emit: Mock, pytestconfig: PytestConfig) -> None:
mock_emitter = Mock()
mock_emit.return_value = mock_emitter
@ -87,7 +137,8 @@ def test_emit_metadata(mock_emit):
transform(extract())
instance = DagsterInstance.ephemeral()
result = etl.execute_in_process(instance=instance)
test_run_id = "12345678123456781234567812345678"
result = etl.execute_in_process(instance=instance, run_id=test_run_id)
# retrieve the DagsterRun
dagster_run = result.dagster_run
@ -103,201 +154,25 @@ def test_emit_metadata(mock_emit):
dagster_event=dagster_event,
)
with tempfile.TemporaryDirectory() as tmp_path:
DatahubSensors()._emit_metadata(run_status_sensor_context)
mcpws: List[Dict] = []
for mock_call in mock_emitter.method_calls:
if not mock_call.args:
continue
mcpw = mock_call.args[0]
if isinstance(mcpw, MetadataChangeProposalWrapper):
mcpws.append(mcpw.to_obj(simplified_structure=True))
expected_dataflow_urn = (
f"urn:li:dataFlow:(dagster,{dagster_run.job_name},{DEFAULT_ENV})"
)
assert mock_emitter.method_calls[1][1][0].aspectName == "dataFlowInfo"
assert mock_emitter.method_calls[1][1][0].entityUrn == expected_dataflow_urn
assert mock_emitter.method_calls[2][1][0].aspectName == "ownership"
assert mock_emitter.method_calls[2][1][0].entityUrn == expected_dataflow_urn
assert mock_emitter.method_calls[3][1][0].aspectName == "globalTags"
assert mock_emitter.method_calls[3][1][0].entityUrn == expected_dataflow_urn
with open(f"{tmp_path}/test_emit_metadata_mcps.json", "w") as f:
json_object = json.dumps(mcpws, indent=2)
f.write(json_object)
dpi_id = DataProcessInstanceKey(
cluster=DEFAULT_ENV,
orchestrator="dagster",
id=dagster_run.run_id,
).guid()
assert (
mock_emitter.method_calls[7][1][0].aspectName == "dataProcessInstanceProperties"
)
assert (
mock_emitter.method_calls[7][1][0].entityUrn
== f"urn:li:dataProcessInstance:{dpi_id}"
)
assert (
mock_emitter.method_calls[8][1][0].aspectName
== "dataProcessInstanceRelationships"
)
assert (
mock_emitter.method_calls[8][1][0].entityUrn
== f"urn:li:dataProcessInstance:{dpi_id}"
)
assert (
mock_emitter.method_calls[9][1][0].aspectName == "dataProcessInstanceRunEvent"
)
assert (
mock_emitter.method_calls[9][1][0].entityUrn
== f"urn:li:dataProcessInstance:{dpi_id}"
)
assert (
mock_emitter.method_calls[10][1][0].aspectName == "dataProcessInstanceRunEvent"
)
assert (
mock_emitter.method_calls[10][1][0].entityUrn
== f"urn:li:dataProcessInstance:{dpi_id}"
)
assert (
mock_emitter.method_calls[10][1][0].aspect.result.type
== InstanceRunResult.SUCCESS
)
assert mock_emitter.method_calls[11][1][0].aspectName == "dataJobInfo"
assert (
mock_emitter.method_calls[11][1][0].entityUrn
== f"urn:li:dataJob:({expected_dataflow_urn},extract)"
)
assert mock_emitter.method_calls[12][1][0].aspectName == "dataJobInputOutput"
assert (
mock_emitter.method_calls[12][1][0].entityUrn
== f"urn:li:dataJob:({expected_dataflow_urn},extract)"
)
assert mock_emitter.method_calls[13][1][0].aspectName == "status"
assert (
mock_emitter.method_calls[13][1][0].entityUrn
== "urn:li:dataset:(urn:li:dataPlatform:snowflake,tableB,PROD)"
)
assert mock_emitter.method_calls[14][1][0].aspectName == "ownership"
assert (
mock_emitter.method_calls[14][1][0].entityUrn
== f"urn:li:dataJob:({expected_dataflow_urn},extract)"
)
assert mock_emitter.method_calls[15][1][0].aspectName == "globalTags"
assert (
mock_emitter.method_calls[15][1][0].entityUrn
== f"urn:li:dataJob:({expected_dataflow_urn},extract)"
)
dpi_id = DataProcessInstanceKey(
cluster=DEFAULT_ENV,
orchestrator="dagster",
id=f"{dagster_run.run_id}.extract",
).guid()
assert (
mock_emitter.method_calls[21][1][0].aspectName
== "dataProcessInstanceProperties"
)
assert (
mock_emitter.method_calls[21][1][0].entityUrn
== f"urn:li:dataProcessInstance:{dpi_id}"
)
assert (
mock_emitter.method_calls[22][1][0].aspectName
== "dataProcessInstanceRelationships"
)
assert (
mock_emitter.method_calls[22][1][0].entityUrn
== f"urn:li:dataProcessInstance:{dpi_id}"
)
assert mock_emitter.method_calls[23][1][0].aspectName == "dataProcessInstanceOutput"
assert (
mock_emitter.method_calls[23][1][0].entityUrn
== f"urn:li:dataProcessInstance:{dpi_id}"
)
assert mock_emitter.method_calls[24][1][0].aspectName == "status"
assert (
mock_emitter.method_calls[24][1][0].entityUrn
== "urn:li:dataset:(urn:li:dataPlatform:snowflake,tableB,PROD)"
)
assert (
mock_emitter.method_calls[25][1][0].aspectName == "dataProcessInstanceRunEvent"
)
assert (
mock_emitter.method_calls[25][1][0].entityUrn
== f"urn:li:dataProcessInstance:{dpi_id}"
)
assert (
mock_emitter.method_calls[26][1][0].aspectName == "dataProcessInstanceRunEvent"
)
assert (
mock_emitter.method_calls[26][1][0].entityUrn
== f"urn:li:dataProcessInstance:{dpi_id}"
)
assert (
mock_emitter.method_calls[26][1][0].aspect.result.type
== InstanceRunResult.SUCCESS
)
assert mock_emitter.method_calls[27][1][0].aspectName == "dataJobInfo"
assert (
mock_emitter.method_calls[27][1][0].entityUrn
== f"urn:li:dataJob:({expected_dataflow_urn},transform)"
)
assert mock_emitter.method_calls[28][1][0].aspectName == "dataJobInputOutput"
assert (
mock_emitter.method_calls[28][1][0].entityUrn
== f"urn:li:dataJob:({expected_dataflow_urn},transform)"
)
assert mock_emitter.method_calls[29][1][0].aspectName == "status"
assert (
mock_emitter.method_calls[29][1][0].entityUrn
== "urn:li:dataset:(urn:li:dataPlatform:snowflake,tableA,PROD)"
)
assert mock_emitter.method_calls[30][1][0].aspectName == "ownership"
assert (
mock_emitter.method_calls[30][1][0].entityUrn
== f"urn:li:dataJob:({expected_dataflow_urn},transform)"
)
assert mock_emitter.method_calls[31][1][0].aspectName == "globalTags"
assert (
mock_emitter.method_calls[31][1][0].entityUrn
== f"urn:li:dataJob:({expected_dataflow_urn},transform)"
)
dpi_id = DataProcessInstanceKey(
cluster=DEFAULT_ENV,
orchestrator="dagster",
id=f"{dagster_run.run_id}.transform",
).guid()
assert (
mock_emitter.method_calls[37][1][0].aspectName
== "dataProcessInstanceProperties"
)
assert (
mock_emitter.method_calls[37][1][0].entityUrn
== f"urn:li:dataProcessInstance:{dpi_id}"
)
assert (
mock_emitter.method_calls[38][1][0].aspectName
== "dataProcessInstanceRelationships"
)
assert (
mock_emitter.method_calls[38][1][0].entityUrn
== f"urn:li:dataProcessInstance:{dpi_id}"
)
assert mock_emitter.method_calls[39][1][0].aspectName == "dataProcessInstanceInput"
assert (
mock_emitter.method_calls[39][1][0].entityUrn
== f"urn:li:dataProcessInstance:{dpi_id}"
)
assert mock_emitter.method_calls[40][1][0].aspectName == "status"
assert (
mock_emitter.method_calls[40][1][0].entityUrn
== "urn:li:dataset:(urn:li:dataPlatform:snowflake,tableA,PROD)"
)
assert (
mock_emitter.method_calls[41][1][0].aspectName == "dataProcessInstanceRunEvent"
)
assert (
mock_emitter.method_calls[41][1][0].entityUrn
== f"urn:li:dataProcessInstance:{dpi_id}"
)
assert (
mock_emitter.method_calls[42][1][0].aspectName == "dataProcessInstanceRunEvent"
)
assert (
mock_emitter.method_calls[42][1][0].entityUrn
== f"urn:li:dataProcessInstance:{dpi_id}"
)
assert (
mock_emitter.method_calls[42][1][0].aspect.result.type
== InstanceRunResult.SUCCESS
check_golden_file(
pytestconfig=pytestconfig,
output_path=pathlib.Path(f"{tmp_path}/test_emit_metadata_mcps.json"),
golden_path=pathlib.Path(
"tests/unit/golden/golden_test_emit_metadata_mcps.json"
),
ignore_paths=["root[*]['systemMetadata']['created']"],
)

0
metadata-ingestion-modules/dagster-plugin/tests/unit/utils/__init__.py Normal file
View File

30
metadata-ingestion-modules/dagster-plugin/tests/unit/utils/utils.py Normal file
View File

@ -0,0 +1,30 @@
import pathlib
from typing import Sequence
from datahub.testing.compare_metadata_json import assert_metadata_files_equal
try:
from pytest import Config as PytestConfig # type: ignore[attr-defined]
except ImportError:
# Support for pytest 6.x.
from _pytest.config import Config as PytestConfig # type: ignore
__all__ = ["PytestConfig"]
def check_golden_file(
pytestconfig: PytestConfig,
output_path: pathlib.Path,
golden_path: pathlib.Path,
ignore_paths: Sequence[str] = (),
) -> None:
update_golden = pytestconfig.getoption("--update-golden-files")
assert_metadata_files_equal(
output_path=output_path,
golden_path=golden_path,
update_golden=update_golden,
copy_output=False,
ignore_paths=ignore_paths,
ignore_order=True,
)

9
metadata-ingestion/developing.md
View File

@ -89,7 +89,16 @@ cd metadata-ingestion-modules/gx-plugin
source venv/bin/activate
datahub version # should print "DataHub CLI version: unavailable (installed in develop mode)"
```
### (Optional) Set up your Python environment for developing on Dagster Plugin
From the repository root:
```shell
cd metadata-ingestion-modules/dagster-plugin
../../gradlew :metadata-ingestion-modules:dagster-plugin:installDev
source venv/bin/activate
datahub version # should print "DataHub CLI version: unavailable (installed in develop mode)"
```
### Common setup issues
Common issues (click to expand):