perf(ingestion/fivetran): Connector performance optimization (datahub…

…-project#10556)

metadata-ingestion/src/datahub/ingestion/api/source_helpers.py

@@ -102,7 +102,6 @@ def auto_status_aspect(
     """
     all_urns: Set[str] = set()
     status_urns: Set[str] = set()
-    skip_urns: Set[str] = set()
     for wu in stream:
         urn = wu.get_urn()
         all_urns.add(urn)
@@ -127,14 +126,13 @@ def auto_status_aspect(
 
         yield wu
 
-    for urn in sorted(all_urns - status_urns - skip_urns):
+    for urn in sorted(all_urns - status_urns):
         entity_type = guess_entity_type(urn)
         if not entity_supports_aspect(entity_type, StatusClass):
             # If any entity does not support aspect 'status' then skip that entity from adding status aspect.
             # Example like dataProcessInstance doesn't suppport status aspect.
             # If not skipped gives error: java.lang.RuntimeException: Unknown aspect status for entity dataProcessInstance
             continue
-
         yield MetadataChangeProposalWrapper(
             entityUrn=urn,
             aspect=StatusClass(removed=False),

metadata-ingestion/src/datahub/ingestion/source/fivetran/config.py

@@ -9,6 +9,7 @@
 from datahub.configuration.common import AllowDenyPattern, ConfigModel
 from datahub.configuration.source_common import DEFAULT_ENV, DatasetSourceConfigMixin
 from datahub.configuration.validate_field_rename import pydantic_renamed_field
+from datahub.ingestion.api.report import Report
 from datahub.ingestion.source.bigquery_v2.bigquery_config import (
     BigQueryConnectionConfig,
 )
@@ -20,6 +21,7 @@
     StatefulIngestionConfigBase,
 )
 from datahub.ingestion.source_config.sql.snowflake import BaseSnowflakeConfig
+from datahub.utilities.perf_timer import PerfTimer
 
 logger = logging.getLogger(__name__)
 
@@ -110,10 +112,26 @@ def validate_destination_platfrom_and_config(cls, values: Dict) -> Dict:
         return values
 
 
+@dataclass
+class MetadataExtractionPerfReport(Report):
+    connectors_metadata_extraction_sec: PerfTimer = dataclass_field(
+        default_factory=PerfTimer
+    )
+    connectors_lineage_extraction_sec: PerfTimer = dataclass_field(
+        default_factory=PerfTimer
+    )
+    connectors_jobs_extraction_sec: PerfTimer = dataclass_field(
+        default_factory=PerfTimer
+    )
+
+
 @dataclass
 class FivetranSourceReport(StaleEntityRemovalSourceReport):
     connectors_scanned: int = 0
     filtered_connectors: List[str] = dataclass_field(default_factory=list)
+    metadata_extraction_perf: MetadataExtractionPerfReport = dataclass_field(
+        default_factory=MetadataExtractionPerfReport
+    )
 
     def report_connectors_scanned(self, count: int = 1) -> None:
         self.connectors_scanned += count
@@ -163,3 +181,7 @@ class FivetranSourceConfig(StatefulIngestionConfigBase, DatasetSourceConfigMixin
         default={},
         description="A mapping of destination dataset to platform instance. Use destination id as key.",
     )
+    history_sync_lookback_period: int = pydantic.Field(
+        7,
+        description="The number of days to look back when extracting connectors' sync history.",
+    )

metadata-ingestion/src/datahub/ingestion/source/fivetran/data_classes.py

@@ -1,5 +1,5 @@
 from dataclasses import dataclass
-from typing import List, Optional
+from typing import List
 
 
 @dataclass
@@ -23,7 +23,7 @@ class Connector:
     paused: bool
     sync_frequency: int
     destination_id: str
-    user_email: Optional[str]
+    user_id: str
     table_lineage: List[TableLineage]
     jobs: List["Job"]
 

metadata-ingestion/src/datahub/ingestion/source/fivetran/fivetran.py

@@ -173,11 +173,12 @@ def _generate_datajob_from_connector(self, connector: Connector) -> DataJob:
             env=self.config.env,
             platform_instance=self.config.platform_instance,
         )
+        owner_email = self.audit_log.get_user_email(connector.user_id)
         datajob = DataJob(
             id=connector.connector_id,
             flow_urn=dataflow_urn,
             name=connector.connector_name,
-            owners={connector.user_email} if connector.user_email else set(),
+            owners={owner_email} if owner_email else set(),
         )
 
         job_property_bag: Dict[str, str] = {}
@@ -281,7 +282,9 @@ def get_workunits_internal(self) -> Iterable[MetadataWorkUnit]:
         """
         logger.info("Fivetran plugin execution is started")
         connectors = self.audit_log.get_allowed_connectors_list(
-            self.config.connector_patterns, self.report
+            self.config.connector_patterns,
+            self.report,
+            self.config.history_sync_lookback_period,
         )
         for connector in connectors:
             logger.info(f"Processing connector id: {connector.connector_id}")

metadata-ingestion/src/datahub/ingestion/source/fivetran/fivetran_log_api.py

@@ -1,3 +1,4 @@
+import functools
 import json
 import logging
 from typing import Any, Dict, List, Optional, Tuple
@@ -151,9 +152,14 @@ def _get_table_lineage(
 
         return table_lineage_list
 
-    def _get_all_connector_sync_logs(self) -> Dict[str, Dict]:
+    def _get_all_connector_sync_logs(self, syncs_interval: int) -> Dict[str, Dict]:
         sync_logs = {}
-        for row in self._query(self.fivetran_log_query.get_sync_logs_query()):
+        for row in self._query(
+            self.fivetran_log_query.get_sync_logs_query().format(
+                db_clause=self.fivetran_log_query.db_clause,
+                syncs_interval=syncs_interval,
+            )
+        ):
             if row[Constant.CONNECTOR_ID] not in sync_logs:
                 sync_logs[row[Constant.CONNECTOR_ID]] = {
                     row[Constant.SYNC_ID]: {
@@ -208,50 +214,62 @@ def _get_jobs_list(
             )
         return jobs
 
-    def _get_user_email(self, user_id: Optional[str]) -> Optional[str]:
+    @functools.lru_cache()
+    def _get_users(self) -> Dict[str, str]:
+        users = self._query(self.fivetran_log_query.get_users_query())
+        if not users:
+            return {}
+        return {user[Constant.USER_ID]: user[Constant.EMAIL] for user in users}
+
+    def get_user_email(self, user_id: str) -> Optional[str]:
         if not user_id:
             return None
-        user_details = self._query(
-            self.fivetran_log_query.get_user_query(user_id=user_id)
-        )
+        return self._get_users().get(user_id)
 
-        if not user_details:
-            return None
+    def _fill_connectors_table_lineage(self, connectors: List[Connector]) -> None:
+        table_lineage_metadata = self._get_connectors_table_lineage_metadata()
+        column_lineage_metadata = self._get_column_lineage_metadata()
+        for connector in connectors:
+            connector.table_lineage = self._get_table_lineage(
+                column_lineage_metadata=column_lineage_metadata,
+                table_lineage_result=table_lineage_metadata.get(connector.connector_id),
+            )
 
-        return f"{user_details[0][Constant.EMAIL]}"
+    def _fill_connectors_jobs(
+        self, connectors: List[Connector], syncs_interval: int
+    ) -> None:
+        sync_logs = self._get_all_connector_sync_logs(syncs_interval)
+        for connector in connectors:
+            connector.jobs = self._get_jobs_list(sync_logs.get(connector.connector_id))
 
     def get_allowed_connectors_list(
-        self, connector_patterns: AllowDenyPattern, report: FivetranSourceReport
+        self,
+        connector_patterns: AllowDenyPattern,
+        report: FivetranSourceReport,
+        syncs_interval: int,
     ) -> List[Connector]:
         connectors: List[Connector] = []
-        sync_logs = self._get_all_connector_sync_logs()
-        table_lineage_metadata = self._get_connectors_table_lineage_metadata()
-        column_lineage_metadata = self._get_column_lineage_metadata()
-        connector_list = self._query(self.fivetran_log_query.get_connectors_query())
-        for connector in connector_list:
-            if not connector_patterns.allowed(connector[Constant.CONNECTOR_NAME]):
-                report.report_connectors_dropped(connector[Constant.CONNECTOR_NAME])
-                continue
-            connectors.append(
-                Connector(
-                    connector_id=connector[Constant.CONNECTOR_ID],
-                    connector_name=connector[Constant.CONNECTOR_NAME],
-                    connector_type=connector[Constant.CONNECTOR_TYPE_ID],
-                    paused=connector[Constant.PAUSED],
-                    sync_frequency=connector[Constant.SYNC_FREQUENCY],
-                    destination_id=connector[Constant.DESTINATION_ID],
-                    user_email=self._get_user_email(
-                        connector[Constant.CONNECTING_USER_ID]
-                    ),
-                    table_lineage=self._get_table_lineage(
-                        column_lineage_metadata=column_lineage_metadata,
-                        table_lineage_result=table_lineage_metadata.get(
-                            connector[Constant.CONNECTOR_ID]
-                        ),
-                    ),
-                    jobs=self._get_jobs_list(
-                        sync_logs.get(connector[Constant.CONNECTOR_ID])
-                    ),
+        with report.metadata_extraction_perf.connectors_metadata_extraction_sec:
+            connector_list = self._query(self.fivetran_log_query.get_connectors_query())
+            for connector in connector_list:
+                if not connector_patterns.allowed(connector[Constant.CONNECTOR_NAME]):
+                    report.report_connectors_dropped(connector[Constant.CONNECTOR_NAME])
+                    continue
+                connectors.append(
+                    Connector(
+                        connector_id=connector[Constant.CONNECTOR_ID],
+                        connector_name=connector[Constant.CONNECTOR_NAME],
+                        connector_type=connector[Constant.CONNECTOR_TYPE_ID],
+                        paused=connector[Constant.PAUSED],
+                        sync_frequency=connector[Constant.SYNC_FREQUENCY],
+                        destination_id=connector[Constant.DESTINATION_ID],
+                        user_id=connector[Constant.CONNECTING_USER_ID],
+                        table_lineage=[],
+                        jobs=[],
+                    )
                 )
-            )
+        with report.metadata_extraction_perf.connectors_lineage_extraction_sec:
+            self._fill_connectors_table_lineage(connectors)
+        with report.metadata_extraction_perf.connectors_jobs_extraction_sec:
+            self._fill_connectors_jobs(connectors, syncs_interval)
         return connectors

metadata-ingestion/src/datahub/ingestion/source/fivetran/fivetran_query.py

@@ -21,24 +21,24 @@ def get_connectors_query(self) -> str:
         FROM {self.db_clause}connector
         WHERE _fivetran_deleted = FALSE"""
 
-    def get_user_query(self, user_id: str) -> str:
+    def get_users_query(self) -> str:
         return f"""
         SELECT id as user_id,
         given_name,
         family_name,
         email
-        FROM {self.db_clause}user
-        WHERE id = '{user_id}'"""
+        FROM {self.db_clause}user"""
 
     def get_sync_logs_query(self) -> str:
-        return f"""
+        return """
         SELECT connector_id,
         sync_id,
         message_event,
         message_data,
         time_stamp
-        FROM {self.db_clause}log
-        WHERE message_event in ('sync_start', 'sync_end')"""
+        FROM {db_clause}log
+        WHERE message_event in ('sync_start', 'sync_end')
+        and time_stamp > CURRENT_TIMESTAMP - INTERVAL '{syncs_interval} days'"""
 
     def get_table_lineage_query(self) -> str:
         return f"""

metadata-ingestion/src/datahub/ingestion/source/state/stale_entity_removal_handler.py

@@ -6,6 +6,7 @@
 import pydantic
 
 from datahub.emitter.mcp import MetadataChangeProposalWrapper
+from datahub.emitter.mcp_builder import entity_supports_aspect
 from datahub.ingestion.api.common import PipelineContext
 from datahub.ingestion.api.ingestion_job_checkpointing_provider_base import JobId
 from datahub.ingestion.api.source_helpers import auto_stale_entity_removal
@@ -23,6 +24,7 @@
 )
 from datahub.metadata.schema_classes import StatusClass
 from datahub.utilities.lossy_collections import LossyList
+from datahub.utilities.urns.urn import guess_entity_type
 
 logger: logging.Logger = logging.getLogger(__name__)
 
@@ -48,10 +50,14 @@ class StatefulStaleMetadataRemovalConfig(StatefulIngestionConfig):
 @dataclass
 class StaleEntityRemovalSourceReport(StatefulIngestionReport):
     soft_deleted_stale_entities: LossyList[str] = field(default_factory=LossyList)
+    last_state_non_deletable_entities: LossyList[str] = field(default_factory=LossyList)
 
     def report_stale_entity_soft_deleted(self, urn: str) -> None:
         self.soft_deleted_stale_entities.append(urn)
 
+    def report_last_state_non_deletable_entities(self, urn: str) -> None:
+        self.last_state_non_deletable_entities.append(urn)
+
 
 class StaleEntityRemovalHandler(
     StatefulIngestionUsecaseHandlerBase["GenericCheckpointState"]
@@ -272,11 +278,19 @@ def gen_removed_entity_workunits(self) -> Iterable[MetadataWorkUnit]:
                 self.add_entity_to_state("", urn)
             return
 
+        report = self.source.get_report()
+        assert isinstance(report, StaleEntityRemovalSourceReport)
+
         # Everything looks good, emit the soft-deletion workunits
         for urn in last_checkpoint_state.get_urns_not_in(
             type="*", other_checkpoint_state=cur_checkpoint_state
         ):
+            if not entity_supports_aspect(guess_entity_type(urn), StatusClass):
+                # If any entity does not support aspect 'status' then skip that entity urn
+                report.report_last_state_non_deletable_entities(urn)
+                continue
             if urn in self._urns_to_skip:
+                report.report_last_state_non_deletable_entities(urn)
                 logger.debug(
                     f"Not soft-deleting entity {urn} since it is in urns_to_skip"
                 )

metadata-ingestion/tests/integration/fivetran/test_fivetran.py

@@ -89,7 +89,7 @@ def default_query_results(
                 "destination_column_name": "name",
             },
         ]
-    elif query == fivetran_log_query.get_user_query("reapply_phone"):
+    elif query == fivetran_log_query.get_users_query():
         return [
             {
                 "user_id": "reapply_phone",
@@ -98,7 +98,9 @@ def default_query_results(
                 "email": "[email protected]",
             }
         ]
-    elif query == fivetran_log_query.get_sync_logs_query():
+    elif query == fivetran_log_query.get_sync_logs_query().format(
+        db_clause=fivetran_log_query.db_clause, syncs_interval=7
+    ):
         return [
             {
                 "connector_id": "calendar_elected",

metadata-ingestion/tests/unit/stateful_ingestion/state/golden_test_checkpoint_state.json

@@ -17,7 +17,7 @@
             "state": {
                 "formatVersion": "1.0",
                 "serde": "utf-8",
-                "payload": "{\"urns\": [\"urn:li:dataset:(urn:li:dataPlatform:postgres,dummy_dataset1,PROD)\", \"urn:li:dataset:(urn:li:dataPlatform:postgres,dummy_dataset2,PROD)\", \"urn:li:dataset:(urn:li:dataPlatform:postgres,dummy_dataset3,PROD)\"]}"
+                "payload": "{\"urns\": [\"urn:li:dataset:(urn:li:dataPlatform:postgres,dummy_dataset1,PROD)\", \"urn:li:dataset:(urn:li:dataPlatform:postgres,dummy_dataset2,PROD)\", \"urn:li:dataset:(urn:li:dataPlatform:postgres,dummy_dataset3,PROD)\", \"urn:li:dataProcessInstance:478810e859f870a54f72c681f41af619\"]}"
             },
             "runId": "dummy-test-stateful-ingestion"
         }

metadata-ingestion/tests/unit/stateful_ingestion/state/golden_test_checkpoint_state_after_deleted.json

@@ -17,7 +17,7 @@
             "state": {
                 "formatVersion": "1.0",
                 "serde": "utf-8",
-                "payload": "{\"urns\": [\"urn:li:dataset:(urn:li:dataPlatform:postgres,dummy_dataset1,PROD)\", \"urn:li:dataset:(urn:li:dataPlatform:postgres,dummy_dataset2,PROD)\"]}"
+                "payload": "{\"urns\": [\"urn:li:dataset:(urn:li:dataPlatform:postgres,dummy_dataset1,PROD)\", \"urn:li:dataset:(urn:li:dataPlatform:postgres,dummy_dataset2,PROD)\", \"urn:li:dataProcessInstance:7f26c3b4d2d82ace47f4b9dd0c9dea26\"]}"
             },
             "runId": "dummy-test-stateful-ingestion"
         }

metadata-ingestion/tests/unit/stateful_ingestion/state/golden_test_stateful_ingestion.json

@@ -46,5 +46,27 @@
         "runId": "dummy-test-stateful-ingestion",
         "lastRunId": "no-run-id-provided"
     }
+},
+{
+    "entityType": "dataProcessInstance",
+    "entityUrn": "urn:li:dataProcessInstance:478810e859f870a54f72c681f41af619",
+    "changeType": "UPSERT",
+    "aspectName": "dataProcessInstanceProperties",
+    "aspect": {
+        "json": {
+            "customProperties": {},
+            "name": "job1",
+            "type": "BATCH_SCHEDULED",
+            "created": {
+                "time": 1586847600000,
+                "actor": "urn:li:corpuser:datahub"
+            }
+        }
+    },
+    "systemMetadata": {
+        "lastObserved": 1586847600000,
+        "runId": "dummy-test-stateful-ingestion",
+        "lastRunId": "no-run-id-provided"
+    }
 }
 ]