feat(ingest/teradata): view parsing (#9005)

metadata-ingestion/docs/sources/teradata/teradata_pre.md

@@ -18,7 +18,7 @@
    
     If you want to run profiling, you need to grant select permission on all the tables you want to profile.
 
-3. If linege or usage extraction is enabled, please, check if query logging is enabled and it is set to size which
+3. If lineage or usage extraction is enabled, please, check if query logging is enabled and it is set to size which
 will fit for your queries (the default query text size Teradata captures is max 200 chars)
    An example how you can set it for all users:
     ```sql

metadata-ingestion/docs/sources/teradata/teradata_recipe.yml

@@ -3,12 +3,11 @@ source:
   type: teradata
   config:
     host_port: "myteradatainstance.teradata.com:1025"
-    #platform_instance: "myteradatainstance"
     username: myuser
     password: mypassword
     #database_pattern:
     #  allow:
-    #    - "demo_user"
+    #    - "my_database"
     #  ignoreCase: true
     include_table_lineage: true
     include_usage_statistics: true

metadata-ingestion/src/datahub/ingestion/source/sql/teradata.py

@@ -1,5 +1,6 @@
 import logging
 from dataclasses import dataclass
+from datetime import datetime
 from typing import Iterable, Optional, Set, Union
 
 # This import verifies that the dependencies are available.
@@ -11,6 +12,7 @@ from sqlalchemy.engine import Engine
 
 from datahub.configuration.common import AllowDenyPattern
 from datahub.configuration.time_window_config import BaseTimeWindowConfig
+from datahub.emitter.mcp import MetadataChangeProposalWrapper
 from datahub.emitter.sql_parsing_builder import SqlParsingBuilder
 from datahub.ingestion.api.common import PipelineContext
 from datahub.ingestion.api.decorators import (
@@ -32,11 +34,18 @@ from datahub.ingestion.source.sql.two_tier_sql_source import (
 from datahub.ingestion.source.usage.usage_common import BaseUsageConfig
 from datahub.ingestion.source_report.ingestion_stage import IngestionStageReport
 from datahub.ingestion.source_report.time_window import BaseTimeWindowReport
+from datahub.metadata._schema_classes import (
+    MetadataChangeEventClass,
+    SchemaMetadataClass,
+    ViewPropertiesClass,
+)
 from datahub.metadata.com.linkedin.pegasus2avro.schema import (
     BytesTypeClass,
     TimeTypeClass,
 )
+from datahub.utilities.file_backed_collections import FileBackedDict
 from datahub.utilities.sqlglot_lineage import SchemaResolver, sqlglot_lineage
+from datahub.utilities.urns.dataset_urn import DatasetUrn
 
 logger: logging.Logger = logging.getLogger(__name__)
 
@@ -64,6 +73,7 @@ register_custom_type(custom_types.XML, BytesTypeClass)
 @dataclass
 class TeradataReport(ProfilingSqlReport, IngestionStageReport, BaseTimeWindowReport):
     num_queries_parsed: int = 0
+    num_view_ddl_parsed: int = 0
     num_table_parse_failures: int = 0
 
 
@@ -82,17 +92,16 @@ class TeradataConfig(BaseTeradataConfig, BaseTimeWindowConfig):
         "This requires to have the table lineage feature enabled.",
     )
 
+    include_view_lineage = Field(
+        default=True,
+        description="Whether to include view lineage in the ingestion. "
+        "This requires to have the view lineage feature enabled.",
+    )
     usage: BaseUsageConfig = Field(
         description="The usage config to use when generating usage statistics",
         default=BaseUsageConfig(),
     )
 
-    use_schema_resolver: bool = Field(
-        default=True,
-        description="Read SchemaMetadata aspects from DataHub to aid in SQL parsing. Turn off only for testing.",
-        hidden_from_docs=True,
-    )
-
     default_db: Optional[str] = Field(
         default=None,
         description="The default database to use for unqualified table names",
@@ -141,46 +150,47 @@ class TeradataSource(TwoTierSQLAlchemySource):
         self.report: TeradataReport = TeradataReport()
         self.graph: Optional[DataHubGraph] = ctx.graph
 
-        if self.graph:
-            if self.config.use_schema_resolver:
-                self.schema_resolver = (
-                    self.graph.initialize_schema_resolver_from_datahub(
-                        platform=self.platform,
-                        platform_instance=self.config.platform_instance,
-                        env=self.config.env,
-                    )
-                )
-                self.urns = self.schema_resolver.get_urns()
-            else:
-                self.schema_resolver = self.graph._make_schema_resolver(
-                    platform=self.platform,
-                    platform_instance=self.config.platform_instance,
-                    env=self.config.env,
-                )
-                self.urns = None
-        else:
-            self.schema_resolver = SchemaResolver(
-                platform=self.platform,
-                platform_instance=self.config.platform_instance,
-                graph=None,
-                env=self.config.env,
-            )
-            self.urns = None
-
         self.builder: SqlParsingBuilder = SqlParsingBuilder(
             usage_config=self.config.usage
             if self.config.include_usage_statistics
             else None,
-            generate_lineage=self.config.include_table_lineage,
+            generate_lineage=True,
             generate_usage_statistics=self.config.include_usage_statistics,
             generate_operations=self.config.usage.include_operational_stats,
         )
 
+        self.schema_resolver = SchemaResolver(
+            platform=self.platform,
+            platform_instance=self.config.platform_instance,
+            graph=None,
+            env=self.config.env,
+        )
+
+        self._view_definition_cache: FileBackedDict[str] = FileBackedDict()
+
     @classmethod
     def create(cls, config_dict, ctx):
         config = TeradataConfig.parse_obj(config_dict)
         return cls(config, ctx)
 
+    def get_view_lineage(self) -> Iterable[MetadataWorkUnit]:
+        for key in self._view_definition_cache.keys():
+            view_definition = self._view_definition_cache[key]
+            dataset_urn = DatasetUrn.create_from_string(key)
+
+            db_name: Optional[str] = None
+            # We need to get the default db from the dataset urn otherwise the builder generates the wrong urns
+            if "." in dataset_urn.get_dataset_name():
+                db_name = dataset_urn.get_dataset_name().split(".", 1)[0]
+
+            self.report.num_view_ddl_parsed += 1
+            if self.report.num_view_ddl_parsed % 1000 == 0:
+                logger.info(f"Parsed {self.report.num_queries_parsed} view ddl")
+
+            yield from self.gen_lineage_from_query(
+                query=view_definition, default_database=db_name, is_view_ddl=True
+            )
+
     def get_audit_log_mcps(self) -> Iterable[MetadataWorkUnit]:
         engine = self.get_metadata_engine()
         for entry in engine.execute(
@@ -192,27 +202,43 @@ class TeradataSource(TwoTierSQLAlchemySource):
             if self.report.num_queries_parsed % 1000 == 0:
                 logger.info(f"Parsed {self.report.num_queries_parsed} queries")
 
-            result = sqlglot_lineage(
+            yield from self.gen_lineage_from_query(
-                sql=entry.query,
+                query=entry.query,
-                schema_resolver=self.schema_resolver,
+                default_database=entry.default_database,
-                default_db=None,
+                timestamp=entry.timestamp,
-                default_schema=entry.default_database
+                user=entry.user,
-                if entry.default_database
+                is_view_ddl=False,
-                else self.config.default_db,
             )
-            if result.debug_info.table_error:
-                logger.debug(
-                    f"Error parsing table lineage, {result.debug_info.table_error}"
-                )
-                self.report.num_table_parse_failures += 1
-                continue
 
+    def gen_lineage_from_query(
+        self,
+        query: str,
+        default_database: Optional[str] = None,
+        timestamp: Optional[datetime] = None,
+        user: Optional[str] = None,
+        is_view_ddl: bool = False,
+    ) -> Iterable[MetadataWorkUnit]:
+        result = sqlglot_lineage(
+            sql=query,
+            schema_resolver=self.schema_resolver,
+            default_db=None,
+            default_schema=default_database
+            if default_database
+            else self.config.default_db,
+        )
+        if result.debug_info.table_error:
+            logger.debug(
+                f"Error parsing table lineage, {result.debug_info.table_error}"
+            )
+            self.report.num_table_parse_failures += 1
+        else:
             yield from self.builder.process_sql_parsing_result(
                 result,
-                query=entry.query,
+                query=query,
-                query_timestamp=entry.timestamp,
+                is_view_ddl=is_view_ddl,
-                user=f"urn:li:corpuser:{entry.user}",
+                query_timestamp=timestamp,
-                include_urns=self.urns,
+                user=f"urn:li:corpuser:{user}",
+                include_urns=self.schema_resolver.get_urns(),
             )
 
     def get_metadata_engine(self) -> Engine:
@@ -221,8 +247,34 @@ class TeradataSource(TwoTierSQLAlchemySource):
         return create_engine(url, **self.config.options)
 
     def get_workunits_internal(self) -> Iterable[Union[MetadataWorkUnit, SqlWorkUnit]]:
-        yield from super().get_workunits_internal()
+        # Add all schemas to the schema resolver
+        for wu in super().get_workunits_internal():
+            if isinstance(wu.metadata, MetadataChangeEventClass):
+                if wu.metadata.proposedSnapshot:
+                    for aspect in wu.metadata.proposedSnapshot.aspects:
+                        if isinstance(aspect, SchemaMetadataClass):
+                            self.schema_resolver.add_schema_metadata(
+                                wu.metadata.proposedSnapshot.urn,
+                                aspect,
+                            )
+                            break
+            if isinstance(wu.metadata, MetadataChangeProposalWrapper):
+                if (
+                    wu.metadata.entityUrn
+                    and isinstance(wu.metadata.aspect, ViewPropertiesClass)
+                    and wu.metadata.aspect.viewLogic
+                ):
+                    self._view_definition_cache[
+                        wu.metadata.entityUrn
+                    ] = wu.metadata.aspect.viewLogic
+            yield wu
+
+        if self.config.include_view_lineage:
+            self.report.report_ingestion_stage_start("view lineage extraction")
+            yield from self.get_view_lineage()
+
         if self.config.include_table_lineage or self.config.include_usage_statistics:
             self.report.report_ingestion_stage_start("audit log extraction")
             yield from self.get_audit_log_mcps()
-            yield from self.builder.gen_workunits()
+
+        yield from self.builder.gen_workunits()