kaxil commented on code in PR #62793: URL: https://github.com/apache/airflow/pull/62793#discussion_r2880993764
########## providers/common/ai/src/airflow/providers/common/ai/operators/llm_schema_compare.py: ########## @@ -0,0 +1,316 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. +"""Operator for cross-system schema drift detection powered by LLM reasoning.""" + +from __future__ import annotations + +import json +from collections.abc import Sequence +from functools import cached_property +from typing import TYPE_CHECKING, Any, Literal + +from pydantic import BaseModel, Field + +from airflow.providers.common.ai.operators.llm import LLMOperator +from airflow.providers.common.compat.sdk import AirflowException, BaseHook + +if TYPE_CHECKING: + from airflow.providers.common.sql.config import DataSourceConfig + from airflow.providers.common.sql.hooks.sql import DbApiHook + from airflow.sdk import Context + + +class SchemaMismatch(BaseModel): + """A single schema mismatch between data sources.""" + + source: str = Field(description="Source table") + target: str = Field(description="Target table") + column: str = Field(description="Column name where the mismatch was detected") + source_type: str = Field(description="Data type in the source system") + target_type: str = Field(description="Data type in the target system") + severity: Literal["critical", "warning", "info"] = Field(description="Mismatch severity") + description: str = Field(description="Human-readable description of the mismatch") + suggested_action: str = Field(description="Recommended action to resolve the mismatch") + migration_query: str = Field(description="Provide migration query to resolve the mismatch") + + +class SchemaCompareResult(BaseModel): + """Structured output from schema comparison.""" + + compatible: bool = Field(description="Whether the schemas are compatible for data loading") + mismatches: list[SchemaMismatch] = Field(default_factory=list) + summary: str = Field(description="High-level summary of the comparison") + + +DEFAULT_SYSTEM_PROMPT = ( + "Consider cross-system type equivalences:\n" + "- varchar(n) / text / string / TEXT may be compatible\n" + "- int / integer / int4 / INT32 are equivalent\n" + "- bigint / int8 / int64 / BIGINT are equivalent\n" + "- timestamp / timestamptz / TIMESTAMP_NTZ / datetime may differ in timezone handling\n" + "- numeric(p,s) / decimal(p,s) / NUMBER — check precision and scale\n" + "- boolean / bool / BOOLEAN / tinyint(1) — check semantic equivalence\n\n" + "Severity levels:\n" + "- critical: Will cause data loading failures or data loss " + "(e.g., column missing in target, incompatible types)\n" + "- warning: May cause data quality issues " + "(e.g., precision loss, timezone mismatch)\n" + "- info: Cosmetic differences that won't affect data loading " + "(e.g., varchar length differences within safe range)\n\n" +) + + +class LLMSchemaCompareOperator(LLMOperator): + """ + Compare schemas across different database systems and detect drift using LLM reasoning. + + The LLM handles complex cross-system type mapping that simple equality checks + miss (e.g., ``varchar(255)`` vs ``string``, ``timestamp`` vs ``timestamptz``). + + Accepts data sources via two patterns: + + 1. **data_sources** — a list of + :class:`~airflow.providers.common.sql.config.DataSourceConfig` for each + system. If the connection resolves to a + :class:`~airflow.providers.common.sql.hooks.sql.DbApiHook`, schema is + introspected via SQLAlchemy; otherwise DataFusion is used. + 2. **db_conn_ids + table_names** — shorthand for comparing the same table + across multiple database connections (all must resolve to ``DbApiHook``). + + :param prompt: Instructions for the LLM on what to compare and flag. + :param llm_conn_id: Connection ID for the LLM provider. + :param model_id: Model identifier (e.g. ``"openai:gpt-5"``). + :param system_prompt: Additional instructions appended to the built-in + schema comparison prompt. + :param agent_params: Extra keyword arguments for the pydantic-ai ``Agent``. + :param data_sources: List of DataSourceConfig objects, one per system. + :param db_conn_ids: Connection IDs for databases to compare (used with + ``table_names``). + :param table_names: Tables to introspect from each ``db_conn_id``. + :param context_strategy: ``"basic"`` for column names and types only; + ``"full"`` to include primary keys, foreign keys, and indexes. + Default ``"full"``. + """ + + template_fields: Sequence[str] = ( + *LLMOperator.template_fields, + "data_sources", + "db_conn_ids", + "table_names", + "context_strategy", + ) + + def __init__( + self, + *, + data_sources: list[DataSourceConfig] | None = None, + db_conn_ids: list[str] | None = None, + table_names: list[str] | None = None, + context_strategy: Literal["basic", "full"] = "full", + system_prompt: str = DEFAULT_SYSTEM_PROMPT, Review Comment: Design question: since `system_prompt` defaults to `DEFAULT_SYSTEM_PROMPT` (type equivalences + severity definitions), passing `system_prompt="focus on timestamp columns"` replaces those defaults entirely rather than extending them. A user who wants both the type-equivalence hints AND custom instructions has to manually concatenate: ```python from airflow.providers.common.ai.operators.llm_schema_compare import DEFAULT_SYSTEM_PROMPT LLMSchemaCompareOperator( system_prompt=DEFAULT_SYSTEM_PROMPT + "\nAlso focus on timestamp columns.", ... ) ``` This is a reasonable trade-off (simple, explicit), but worth documenting in the docstring so users know `system_prompt` overrides the default rather than appending to it. The current docstring says "Additional instructions appended to the built-in schema comparison prompt" which implies additive behavior. ########## providers/common/ai/src/airflow/providers/common/ai/operators/llm_schema_compare.py: ########## @@ -0,0 +1,316 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. +"""Operator for cross-system schema drift detection powered by LLM reasoning.""" + +from __future__ import annotations + +import json +from collections.abc import Sequence +from functools import cached_property +from typing import TYPE_CHECKING, Any, Literal + +from pydantic import BaseModel, Field + +from airflow.providers.common.ai.operators.llm import LLMOperator +from airflow.providers.common.compat.sdk import AirflowException, BaseHook + +if TYPE_CHECKING: + from airflow.providers.common.sql.config import DataSourceConfig + from airflow.providers.common.sql.hooks.sql import DbApiHook + from airflow.sdk import Context + + +class SchemaMismatch(BaseModel): + """A single schema mismatch between data sources.""" + + source: str = Field(description="Source table") + target: str = Field(description="Target table") + column: str = Field(description="Column name where the mismatch was detected") + source_type: str = Field(description="Data type in the source system") + target_type: str = Field(description="Data type in the target system") + severity: Literal["critical", "warning", "info"] = Field(description="Mismatch severity") + description: str = Field(description="Human-readable description of the mismatch") + suggested_action: str = Field(description="Recommended action to resolve the mismatch") + migration_query: str = Field(description="Provide migration query to resolve the mismatch") + + +class SchemaCompareResult(BaseModel): + """Structured output from schema comparison.""" + + compatible: bool = Field(description="Whether the schemas are compatible for data loading") + mismatches: list[SchemaMismatch] = Field(default_factory=list) + summary: str = Field(description="High-level summary of the comparison") + + +DEFAULT_SYSTEM_PROMPT = ( + "Consider cross-system type equivalences:\n" + "- varchar(n) / text / string / TEXT may be compatible\n" + "- int / integer / int4 / INT32 are equivalent\n" + "- bigint / int8 / int64 / BIGINT are equivalent\n" + "- timestamp / timestamptz / TIMESTAMP_NTZ / datetime may differ in timezone handling\n" + "- numeric(p,s) / decimal(p,s) / NUMBER — check precision and scale\n" + "- boolean / bool / BOOLEAN / tinyint(1) — check semantic equivalence\n\n" + "Severity levels:\n" + "- critical: Will cause data loading failures or data loss " + "(e.g., column missing in target, incompatible types)\n" + "- warning: May cause data quality issues " + "(e.g., precision loss, timezone mismatch)\n" + "- info: Cosmetic differences that won't affect data loading " + "(e.g., varchar length differences within safe range)\n\n" +) + + +class LLMSchemaCompareOperator(LLMOperator): + """ + Compare schemas across different database systems and detect drift using LLM reasoning. + + The LLM handles complex cross-system type mapping that simple equality checks + miss (e.g., ``varchar(255)`` vs ``string``, ``timestamp`` vs ``timestamptz``). + + Accepts data sources via two patterns: + + 1. **data_sources** — a list of + :class:`~airflow.providers.common.sql.config.DataSourceConfig` for each + system. If the connection resolves to a + :class:`~airflow.providers.common.sql.hooks.sql.DbApiHook`, schema is + introspected via SQLAlchemy; otherwise DataFusion is used. + 2. **db_conn_ids + table_names** — shorthand for comparing the same table + across multiple database connections (all must resolve to ``DbApiHook``). + + :param prompt: Instructions for the LLM on what to compare and flag. + :param llm_conn_id: Connection ID for the LLM provider. + :param model_id: Model identifier (e.g. ``"openai:gpt-5"``). + :param system_prompt: Additional instructions appended to the built-in + schema comparison prompt. + :param agent_params: Extra keyword arguments for the pydantic-ai ``Agent``. + :param data_sources: List of DataSourceConfig objects, one per system. + :param db_conn_ids: Connection IDs for databases to compare (used with + ``table_names``). + :param table_names: Tables to introspect from each ``db_conn_id``. + :param context_strategy: ``"basic"`` for column names and types only; + ``"full"`` to include primary keys, foreign keys, and indexes. + Default ``"full"``. + """ + + template_fields: Sequence[str] = ( + *LLMOperator.template_fields, + "data_sources", + "db_conn_ids", + "table_names", + "context_strategy", + ) + + def __init__( + self, + *, + data_sources: list[DataSourceConfig] | None = None, + db_conn_ids: list[str] | None = None, + table_names: list[str] | None = None, + context_strategy: Literal["basic", "full"] = "full", + system_prompt: str = DEFAULT_SYSTEM_PROMPT, + **kwargs: Any, + ) -> None: + kwargs.pop("output_type", None) + super().__init__(**kwargs) + self.data_sources = data_sources or [] + self.db_conn_ids = db_conn_ids or [] + self.table_names = table_names or [] + self.context_strategy = context_strategy + self.system_prompt = system_prompt + + if not self.data_sources and not self.db_conn_ids: + raise ValueError("Provide at least one of 'data_sources' or 'db_conn_ids'.") + + if self.db_conn_ids and not self.table_names: + raise ValueError("'table_names' is required when using 'db_conn_ids'.") + + total_sources = len(self.db_conn_ids) + len(self.data_sources) + if total_sources < 2: + raise ValueError( + "Provide at-least two combinations of 'db_conn_ids' and 'table_names' or 'data_sources' " + "to compare." + ) + + @staticmethod + def _get_db_hook(conn_id: str) -> DbApiHook: + """Resolve a connection ID to a DbApiHook.""" + from airflow.providers.common.sql.hooks.sql import DbApiHook + + connection = BaseHook.get_connection(conn_id) + hook = connection.get_hook() + if not isinstance(hook, DbApiHook): + raise ValueError( + f"Connection {conn_id!r} does not provide a DbApiHook. Got {type(hook).__name__}." + ) + return hook + + def _is_dbapi_connection(self, conn_id: str) -> bool: + """Check whether a connection resolves to a DbApiHook.""" + from airflow.providers.common.sql.hooks.sql import DbApiHook + + try: + connection = BaseHook.get_connection(conn_id) + hook = connection.get_hook() + return isinstance(hook, DbApiHook) + except (AirflowException, ValueError) as exc: + self.log.debug("Connection %s does not resolve to a DbApiHook: %s", conn_id, exc, exc_info=True) + return False + + def _introspect_db_schema(self, hook: DbApiHook, table_name: str) -> str: + """Introspect schema from a database connection via DbApiHook.""" + columns = hook.get_table_schema(table_name) + if not columns: + self.log.warning("Table %r returned no columns — it may not exist.", table_name) + return "" + + col_info = ", ".join(f"{c['name']} {c['type']}" for c in columns) + parts = [f"Columns: {col_info}"] + + if self.context_strategy == "full": + try: + pks = hook.dialect.get_primary_keys(table_name) + if pks: + parts.append(f"Primary Key: {', '.join(pks)}") + except NotImplementedError: + self.log.warning( + "primary key introspection not implemented for dialect %s", hook.dialect_name + ) + except Exception as ex: + self.log.warning("Could not retrieve PK %s", ex) Review Comment: nit: These warnings would be more useful with the table name for context. When comparing multiple tables, "Could not retrieve PK" doesn't tell you which one failed. ```python self.log.warning("Could not retrieve PK for %r: %s", table_name, ex) ``` Same for FK (line 207) and index (line 219) warnings. ########## providers/common/ai/src/airflow/providers/common/ai/operators/llm_schema_compare.py: ########## @@ -0,0 +1,316 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. +"""Operator for cross-system schema drift detection powered by LLM reasoning.""" + +from __future__ import annotations + +import json +from collections.abc import Sequence +from functools import cached_property +from typing import TYPE_CHECKING, Any, Literal + +from pydantic import BaseModel, Field + +from airflow.providers.common.ai.operators.llm import LLMOperator +from airflow.providers.common.compat.sdk import AirflowException, BaseHook + +if TYPE_CHECKING: + from airflow.providers.common.sql.config import DataSourceConfig + from airflow.providers.common.sql.hooks.sql import DbApiHook + from airflow.sdk import Context + + +class SchemaMismatch(BaseModel): + """A single schema mismatch between data sources.""" + + source: str = Field(description="Source table") + target: str = Field(description="Target table") + column: str = Field(description="Column name where the mismatch was detected") + source_type: str = Field(description="Data type in the source system") + target_type: str = Field(description="Data type in the target system") + severity: Literal["critical", "warning", "info"] = Field(description="Mismatch severity") + description: str = Field(description="Human-readable description of the mismatch") + suggested_action: str = Field(description="Recommended action to resolve the mismatch") + migration_query: str = Field(description="Provide migration query to resolve the mismatch") + + +class SchemaCompareResult(BaseModel): + """Structured output from schema comparison.""" + + compatible: bool = Field(description="Whether the schemas are compatible for data loading") + mismatches: list[SchemaMismatch] = Field(default_factory=list) + summary: str = Field(description="High-level summary of the comparison") + + +DEFAULT_SYSTEM_PROMPT = ( + "Consider cross-system type equivalences:\n" + "- varchar(n) / text / string / TEXT may be compatible\n" + "- int / integer / int4 / INT32 are equivalent\n" + "- bigint / int8 / int64 / BIGINT are equivalent\n" + "- timestamp / timestamptz / TIMESTAMP_NTZ / datetime may differ in timezone handling\n" + "- numeric(p,s) / decimal(p,s) / NUMBER — check precision and scale\n" + "- boolean / bool / BOOLEAN / tinyint(1) — check semantic equivalence\n\n" + "Severity levels:\n" + "- critical: Will cause data loading failures or data loss " + "(e.g., column missing in target, incompatible types)\n" + "- warning: May cause data quality issues " + "(e.g., precision loss, timezone mismatch)\n" + "- info: Cosmetic differences that won't affect data loading " + "(e.g., varchar length differences within safe range)\n\n" +) + + +class LLMSchemaCompareOperator(LLMOperator): + """ + Compare schemas across different database systems and detect drift using LLM reasoning. + + The LLM handles complex cross-system type mapping that simple equality checks + miss (e.g., ``varchar(255)`` vs ``string``, ``timestamp`` vs ``timestamptz``). + + Accepts data sources via two patterns: + + 1. **data_sources** — a list of + :class:`~airflow.providers.common.sql.config.DataSourceConfig` for each + system. If the connection resolves to a + :class:`~airflow.providers.common.sql.hooks.sql.DbApiHook`, schema is + introspected via SQLAlchemy; otherwise DataFusion is used. + 2. **db_conn_ids + table_names** — shorthand for comparing the same table + across multiple database connections (all must resolve to ``DbApiHook``). + + :param prompt: Instructions for the LLM on what to compare and flag. + :param llm_conn_id: Connection ID for the LLM provider. + :param model_id: Model identifier (e.g. ``"openai:gpt-5"``). + :param system_prompt: Additional instructions appended to the built-in + schema comparison prompt. + :param agent_params: Extra keyword arguments for the pydantic-ai ``Agent``. + :param data_sources: List of DataSourceConfig objects, one per system. + :param db_conn_ids: Connection IDs for databases to compare (used with + ``table_names``). + :param table_names: Tables to introspect from each ``db_conn_id``. + :param context_strategy: ``"basic"`` for column names and types only; + ``"full"`` to include primary keys, foreign keys, and indexes. + Default ``"full"``. + """ + + template_fields: Sequence[str] = ( + *LLMOperator.template_fields, + "data_sources", + "db_conn_ids", + "table_names", + "context_strategy", + ) + + def __init__( + self, + *, + data_sources: list[DataSourceConfig] | None = None, + db_conn_ids: list[str] | None = None, + table_names: list[str] | None = None, + context_strategy: Literal["basic", "full"] = "full", + system_prompt: str = DEFAULT_SYSTEM_PROMPT, + **kwargs: Any, + ) -> None: + kwargs.pop("output_type", None) + super().__init__(**kwargs) + self.data_sources = data_sources or [] + self.db_conn_ids = db_conn_ids or [] + self.table_names = table_names or [] + self.context_strategy = context_strategy + self.system_prompt = system_prompt + + if not self.data_sources and not self.db_conn_ids: + raise ValueError("Provide at least one of 'data_sources' or 'db_conn_ids'.") + + if self.db_conn_ids and not self.table_names: + raise ValueError("'table_names' is required when using 'db_conn_ids'.") + + total_sources = len(self.db_conn_ids) + len(self.data_sources) + if total_sources < 2: + raise ValueError( + "Provide at-least two combinations of 'db_conn_ids' and 'table_names' or 'data_sources' " + "to compare." + ) + + @staticmethod + def _get_db_hook(conn_id: str) -> DbApiHook: + """Resolve a connection ID to a DbApiHook.""" + from airflow.providers.common.sql.hooks.sql import DbApiHook + + connection = BaseHook.get_connection(conn_id) + hook = connection.get_hook() + if not isinstance(hook, DbApiHook): + raise ValueError( + f"Connection {conn_id!r} does not provide a DbApiHook. Got {type(hook).__name__}." + ) + return hook + + def _is_dbapi_connection(self, conn_id: str) -> bool: + """Check whether a connection resolves to a DbApiHook.""" + from airflow.providers.common.sql.hooks.sql import DbApiHook + + try: + connection = BaseHook.get_connection(conn_id) + hook = connection.get_hook() + return isinstance(hook, DbApiHook) + except (AirflowException, ValueError) as exc: + self.log.debug("Connection %s does not resolve to a DbApiHook: %s", conn_id, exc, exc_info=True) + return False + + def _introspect_db_schema(self, hook: DbApiHook, table_name: str) -> str: + """Introspect schema from a database connection via DbApiHook.""" + columns = hook.get_table_schema(table_name) + if not columns: + self.log.warning("Table %r returned no columns — it may not exist.", table_name) + return "" + + col_info = ", ".join(f"{c['name']} {c['type']}" for c in columns) + parts = [f"Columns: {col_info}"] + + if self.context_strategy == "full": + try: + pks = hook.dialect.get_primary_keys(table_name) + if pks: + parts.append(f"Primary Key: {', '.join(pks)}") + except NotImplementedError: + self.log.warning( + "primary key introspection not implemented for dialect %s", hook.dialect_name + ) + except Exception as ex: + self.log.warning("Could not retrieve PK %s", ex) + + try: + fks = hook.inspector.get_foreign_keys(table_name) + for fk in fks: + cols = ", ".join(fk.get("constrained_columns", [])) + ref = fk.get("referred_table", "?") + ref_cols = ", ".join(fk.get("referred_columns", [])) + parts.append(f"Foreign Key: ({cols}) -> {ref}({ref_cols})") + except NotImplementedError: + self.log.warning( + "foreign key introspection not implemented for dialect %s", hook.dialect_name + ) + except Exception as ex: + self.log.warning("Could not retrieve FK %s", ex) + + try: + indexes = hook.inspector.get_indexes(table_name) + for idx in indexes: + column_names = [c for c in idx.get("column_names", []) if c is not None] + idx_cols = ", ".join(column_names) + unique = " UNIQUE" if idx.get("unique") else "" + parts.append(f"Index{unique}: {idx.get('name', '?')} ({idx_cols})") + except NotImplementedError: + self.log.warning("index introspection not implemented for dialect %s", hook.dialect_name) + except Exception as ex: + self.log.warning("Could not retrieve index %s", ex) + + return "\n".join(parts) + + if self.context_strategy == "basic": + return "\n".join(parts) + + raise ValueError(f"Invalid context_strategy: {self.context_strategy}") + + def _introspect_datasource_schema(self, ds_config: DataSourceConfig) -> str: + """Introspect schema from a DataSourceConfig, choosing DbApiHook or DataFusion.""" + if self._is_dbapi_connection(ds_config.conn_id): + hook = self._get_db_hook(ds_config.conn_id) + dialect_name = getattr(hook, "dialect_name", "unknown") + schema_text = self._introspect_db_schema(hook, ds_config.table_name) + return ( + f"Source: {ds_config.conn_id} ({dialect_name})\nTable: {ds_config.table_name}\n{schema_text}" + ) + + return self._introspect_schema_from_datafusion(ds_config) + + @cached_property + def _df_engine(self): + try: + from airflow.providers.common.sql.datafusion.engine import DataFusionEngine + except ImportError as e: + from airflow.providers.common.compat.sdk import AirflowOptionalProviderFeatureException + + raise AirflowOptionalProviderFeatureException(e) + engine = DataFusionEngine() + return engine + + def _introspect_schema_from_datafusion(self, ds_config: DataSourceConfig): + self._df_engine.register_datasource(ds_config) + schema_text = self._df_engine.get_schema(ds_config.table_name) + + return f"Source: {ds_config.conn_id} \nFormat: ({ds_config.format})\nTable: {ds_config.table_name}\nColumns: {schema_text}" + + def _build_schema_context(self) -> str: + """Collect schemas from all configured sources each clearly.""" + sections: list[str] = [] + + for conn_id in self.db_conn_ids: + hook = self._get_db_hook(conn_id) + dialect_name = getattr(hook, "dialect_name", "unknown") + for table in self.table_names: + schema_text = self._introspect_db_schema(hook, table) + if schema_text: + sections.append(f"Source: {conn_id} ({dialect_name}\nTable: {table}\n{schema_text}") Review Comment: Bug: Missing closing `)` after `{dialect_name}`. ```python # Current (broken): f"Source: {conn_id} ({dialect_name}\nTable: {table}\n{schema_text}" # LLM sees: "Source: postgres_default (postgresql\nTable: orders\n..." # Fix: f"Source: {conn_id} ({dialect_name})\nTable: {table}\n{schema_text}" ``` The tests pass because they assert on the prefix `"Source: postgres_default (postgresql"` which matches either way. -- This is an automated message from the Apache Git Service. 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