alexott commented on code in PR #28950: URL: https://github.com/apache/airflow/pull/28950#discussion_r1089952944
########## airflow/providers/databricks/sensors/databricks_partition.py: ########## @@ -0,0 +1,157 @@ +# +# 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. +# +"""This module contains Databricks sensors.""" + +from __future__ import annotations + +from typing import Any, Callable, Sequence + +from airflow.exceptions import AirflowException +from airflow.providers.common.sql.hooks.sql import fetch_one_handler +from airflow.providers.databricks.hooks.databricks_sql import DatabricksSqlHook +from airflow.providers.databricks.sensors.databricks_sql import DatabricksSqlSensor +from airflow.utils.context import Context + +template_fields: Sequence[str] = ("databricks_conn_id", "catalog", "schema", "table_name", "partition_name") + + +class DatabricksPartitionSensor(DatabricksSqlSensor): + """Sensor to detect the existence of partitions in a Delta table. + + :param databricks_conn_id: Reference to :ref:`Databricks + connection id<howto/connection:databricks>` (templated). + :param http_path: Optional string specifying HTTP path of Databricks SQL Endpoint or cluster. + If not specified, it should be either specified in the Databricks connection's extra parameters, + or ``sql_endpoint_name`` must be specified. + :param sql_endpoint_name: Optional name of Databricks SQL Endpoint. + If not specified, ``http_path`` must be provided as described above. + :param session_configuration: An optional dictionary of Spark session parameters. If not specified, + it could be specified in the Databricks connection's extra parameters. + :param http_headers: An optional list of (k, v) pairs that will be set + as HTTP headers on every request. (templated) + :param catalog: An optional initial catalog to use. Requires DBR version 9.0+ (templated) + :param schema: An optional initial schema to use. Requires DBR version 9.0+ (templated) + :param table_name: Table name to generate the SQL query. + :param partition_name: Partition to check. + :param handler: Handler for DbApiHook.run() to return results, defaults to fetch_one_handler + :param caller: String passed to name a hook to Databricks, defaults to "DatabricksPartitionSensor" + :param client_parameters: Additional parameters internal to Databricks SQL Connector parameters. + :param partition_operator: Comparison operator for partitions. + """ + + template_fields: Sequence[str] = ( + "databricks_conn_id", + "schema", + "http_headers", + "catalog", + "table_name", + "partition_name", + ) + + def __init__( + self, + *, + databricks_conn_id: str = DatabricksSqlHook.default_conn_name, + http_path: str | None = None, + sql_endpoint_name: str | None = None, + session_configuration=None, + http_headers: list[tuple[str, str]] | None = None, + catalog: str = "", + schema: str = "default", + table_name: str = "", + partition_name: dict, + handler: Callable[[Any], Any] = fetch_one_handler, + caller: str = "DatabricksPartitionSensor", Review Comment: let hardcode `caller` instead of passing it as an argument. ########## airflow/providers/databricks/provider.yaml: ########## @@ -92,6 +92,16 @@ hooks: python-modules: - airflow.providers.databricks.hooks.databricks_sql +sensors: + - integration-name: Databricks SQL + python-modules: + - airflow.providers.databricks.sensors.databricks_sql + - integration-name: Databricks Partition + python-modules: + - airflow.providers.databricks.sensors.databricks_partition + - integration-name: Databricks Table Changes + python-modules: + - airflow.providers.databricks.sensors.databricks_table_changes Review Comment: We can combine all of them under the `Databricks SQL` umbrella ########## airflow/providers/databricks/sensors/databricks_partition.py: ########## @@ -0,0 +1,157 @@ +# +# 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. +# +"""This module contains Databricks sensors.""" + +from __future__ import annotations + +from typing import Any, Callable, Sequence + +from airflow.exceptions import AirflowException +from airflow.providers.common.sql.hooks.sql import fetch_one_handler +from airflow.providers.databricks.hooks.databricks_sql import DatabricksSqlHook +from airflow.providers.databricks.sensors.databricks_sql import DatabricksSqlSensor +from airflow.utils.context import Context + +template_fields: Sequence[str] = ("databricks_conn_id", "catalog", "schema", "table_name", "partition_name") + + +class DatabricksPartitionSensor(DatabricksSqlSensor): + """Sensor to detect the existence of partitions in a Delta table. + + :param databricks_conn_id: Reference to :ref:`Databricks + connection id<howto/connection:databricks>` (templated). + :param http_path: Optional string specifying HTTP path of Databricks SQL Endpoint or cluster. + If not specified, it should be either specified in the Databricks connection's extra parameters, + or ``sql_endpoint_name`` must be specified. + :param sql_endpoint_name: Optional name of Databricks SQL Endpoint. + If not specified, ``http_path`` must be provided as described above. + :param session_configuration: An optional dictionary of Spark session parameters. If not specified, + it could be specified in the Databricks connection's extra parameters. + :param http_headers: An optional list of (k, v) pairs that will be set + as HTTP headers on every request. (templated) + :param catalog: An optional initial catalog to use. Requires DBR version 9.0+ (templated) + :param schema: An optional initial schema to use. Requires DBR version 9.0+ (templated) + :param table_name: Table name to generate the SQL query. + :param partition_name: Partition to check. + :param handler: Handler for DbApiHook.run() to return results, defaults to fetch_one_handler + :param caller: String passed to name a hook to Databricks, defaults to "DatabricksPartitionSensor" + :param client_parameters: Additional parameters internal to Databricks SQL Connector parameters. + :param partition_operator: Comparison operator for partitions. + """ + + template_fields: Sequence[str] = ( + "databricks_conn_id", + "schema", + "http_headers", + "catalog", + "table_name", + "partition_name", + ) + + def __init__( + self, + *, + databricks_conn_id: str = DatabricksSqlHook.default_conn_name, + http_path: str | None = None, + sql_endpoint_name: str | None = None, + session_configuration=None, + http_headers: list[tuple[str, str]] | None = None, + catalog: str = "", + schema: str = "default", + table_name: str = "", + partition_name: dict, + handler: Callable[[Any], Any] = fetch_one_handler, + caller: str = "DatabricksPartitionSensor", + client_parameters: dict[str, Any] | None = None, + partition_operator: str = "=", + **kwargs, + ) -> None: + super().__init__(**kwargs) + self.databricks_conn_id = databricks_conn_id + self._http_path = http_path + self._sql_endpoint_name = sql_endpoint_name + self.session_config = session_configuration + self.http_headers = http_headers + self.catalog = catalog + self.schema = schema + self.table_name = table_name + self.partition_name = partition_name + self.caller = caller + self.client_parameters = client_parameters or {} + self.hook_params = kwargs.pop("hook_params", {}) + self.handler = handler + self.partition_operator = partition_operator + + def _get_hook(self) -> DatabricksSqlHook: + return DatabricksSqlHook( + self.databricks_conn_id, + self._http_path, + self._sql_endpoint_name, + self.session_config, + self.http_headers, + self.catalog, + self.schema, + self.caller, + **self.client_parameters, + **self.hook_params, + ) + + def _sql_sensor(self, sql): + hook = self._get_hook() + sql_result = hook.run( + sql, + handler=self.handler if self.do_xcom_push else None, + ) + return sql_result + + def _check_table_partitions(self) -> list: + if self.catalog is not None: + complete_table_name = str(self.catalog + "." + self.schema + "." + self.table_name) + self.log.debug("Table name generated from arguments: %s", complete_table_name) + else: + raise AirflowException("Catalog name not specified, aborting query execution.") + partition_columns = self._sql_sensor(f"describe detail {complete_table_name}")[7] + self.log.debug("table_info: %s", partition_columns) + if len(partition_columns) < 1: + raise AirflowException("Table %s does not have partitions", complete_table_name) + partitions_list = [] + for partition_col, partition_value in self.partition_name.items(): + if partition_col in partition_columns: + if isinstance(partition_value, list): + partitions_list.append(f"""{partition_col} in {tuple(partition_value)}""") + if isinstance(partition_value, (int, float, complex)): + partitions_list.append(f"""{partition_col}{self.partition_operator}{partition_value}""") + if isinstance(partition_value, str): + partitions_list.append( + f"""{partition_col}{self.partition_operator}\"{partition_value}\"""" + ) + else: + raise AirflowException( + "Column %s not part of table partitions: %s", partition_col, partition_columns + ) + partitions = " AND ".join(partitions_list) + partition_sql = f"SELECT 1 FROM {complete_table_name} WHERE {partitions}" Review Comment: we should add `LIMIT 1` to avoid selecting too much from the table... ########## airflow/providers/databricks/sensors/databricks_partition.py: ########## @@ -0,0 +1,157 @@ +# +# 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. +# +"""This module contains Databricks sensors.""" + +from __future__ import annotations + +from typing import Any, Callable, Sequence + +from airflow.exceptions import AirflowException +from airflow.providers.common.sql.hooks.sql import fetch_one_handler +from airflow.providers.databricks.hooks.databricks_sql import DatabricksSqlHook +from airflow.providers.databricks.sensors.databricks_sql import DatabricksSqlSensor +from airflow.utils.context import Context + +template_fields: Sequence[str] = ("databricks_conn_id", "catalog", "schema", "table_name", "partition_name") + + +class DatabricksPartitionSensor(DatabricksSqlSensor): + """Sensor to detect the existence of partitions in a Delta table. + + :param databricks_conn_id: Reference to :ref:`Databricks + connection id<howto/connection:databricks>` (templated). + :param http_path: Optional string specifying HTTP path of Databricks SQL Endpoint or cluster. + If not specified, it should be either specified in the Databricks connection's extra parameters, + or ``sql_endpoint_name`` must be specified. + :param sql_endpoint_name: Optional name of Databricks SQL Endpoint. + If not specified, ``http_path`` must be provided as described above. + :param session_configuration: An optional dictionary of Spark session parameters. If not specified, + it could be specified in the Databricks connection's extra parameters. + :param http_headers: An optional list of (k, v) pairs that will be set + as HTTP headers on every request. (templated) + :param catalog: An optional initial catalog to use. Requires DBR version 9.0+ (templated) + :param schema: An optional initial schema to use. Requires DBR version 9.0+ (templated) + :param table_name: Table name to generate the SQL query. + :param partition_name: Partition to check. + :param handler: Handler for DbApiHook.run() to return results, defaults to fetch_one_handler + :param caller: String passed to name a hook to Databricks, defaults to "DatabricksPartitionSensor" + :param client_parameters: Additional parameters internal to Databricks SQL Connector parameters. + :param partition_operator: Comparison operator for partitions. + """ + + template_fields: Sequence[str] = ( + "databricks_conn_id", + "schema", + "http_headers", + "catalog", + "table_name", + "partition_name", + ) + + def __init__( + self, + *, + databricks_conn_id: str = DatabricksSqlHook.default_conn_name, + http_path: str | None = None, + sql_endpoint_name: str | None = None, + session_configuration=None, + http_headers: list[tuple[str, str]] | None = None, + catalog: str = "", + schema: str = "default", + table_name: str = "", + partition_name: dict, + handler: Callable[[Any], Any] = fetch_one_handler, + caller: str = "DatabricksPartitionSensor", + client_parameters: dict[str, Any] | None = None, + partition_operator: str = "=", + **kwargs, + ) -> None: + super().__init__(**kwargs) + self.databricks_conn_id = databricks_conn_id + self._http_path = http_path + self._sql_endpoint_name = sql_endpoint_name + self.session_config = session_configuration + self.http_headers = http_headers + self.catalog = catalog + self.schema = schema + self.table_name = table_name + self.partition_name = partition_name + self.caller = caller + self.client_parameters = client_parameters or {} + self.hook_params = kwargs.pop("hook_params", {}) + self.handler = handler + self.partition_operator = partition_operator + + def _get_hook(self) -> DatabricksSqlHook: Review Comment: If we pass all parameters to the `DatabricksSqlSensor`, then we can simply inherit that hook from it. ########## airflow/providers/databricks/sensors/databricks_table_changes.py: ########## @@ -0,0 +1,164 @@ +# +# 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. +# +"""This module contains Databricks sensors.""" + +from __future__ import annotations + +from datetime import datetime, timedelta +from typing import Any, Callable, Sequence + +from airflow.exceptions import AirflowException +from airflow.providers.common.sql.hooks.sql import fetch_all_handler +from airflow.providers.databricks.hooks.databricks_sql import DatabricksSqlHook +from airflow.providers.databricks.sensors.databricks_sql import DatabricksSqlSensor +from airflow.utils.context import Context + + +class DatabricksTableChangesSensor(DatabricksSqlSensor): + """Sensor to detect changes in a Delta table. + + + :param databricks_conn_id: Reference to :ref:`Databricks + connection id<howto/connection:databricks>` (templated), defaults to + DatabricksSqlHook.default_conn_name + :param http_path: Optional string specifying HTTP path of Databricks SQL Endpoint or cluster. + If not specified, it should be either specified in the Databricks connection's + extra parameters, or ``sql_endpoint_name`` must be specified. + :param sql_endpoint_name: Optional name of Databricks SQL Endpoint. If not specified, ``http_path`` must + be provided as described above, defaults to None + :param session_configuration: An optional dictionary of Spark session parameters. If not specified, + it could be specified in the Databricks connection's extra parameters., defaults to None + :param http_headers: An optional list of (k, v) pairs + that will be set as HTTP headers on every request. (templated). + :param catalog: An optional initial catalog to use. + Requires DBR version 9.0+ (templated), defaults to "" + :param schema: An optional initial schema to use. + Requires DBR version 9.0+ (templated), defaults to "default" + :param table_name: Table name to generate the SQL query, defaults to "" + :param handler: Handler for DbApiHook.run() to return results, defaults to fetch_all_handler + :param caller: String passed to name a hook to Databricks, defaults to "DatabricksPartitionSensor" + :param client_parameters: Additional parameters internal to Databricks SQL Connector parameters. + :param timestamp: Timestamp to check event history for a Delta table, + defaults to datetime.now()-timedelta(days=7) + """ + + template_fields: Sequence[str] = ("databricks_conn_id", "catalog", "schema", "table_name", "timestamp") + + def __init__( + self, + *, + databricks_conn_id: str = DatabricksSqlHook.default_conn_name, + http_path: str | None = None, + sql_endpoint_name: str | None = None, + session_configuration=None, + http_headers: list[tuple[str, str]] | None = None, + catalog: str = "", + schema: str = "default", + table_name: str = "", + handler: Callable[[Any], Any] = fetch_all_handler, + timestamp: datetime = datetime.now() - timedelta(days=7), + caller: str = "DatabricksTableChangesSensor", + client_parameters: dict[str, Any] | None = None, Review Comment: Same comments as for partition sensor ########## airflow/providers/databricks/sensors/databricks_table_changes.py: ########## @@ -0,0 +1,164 @@ +# +# 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. +# +"""This module contains Databricks sensors.""" + +from __future__ import annotations + +from datetime import datetime, timedelta +from typing import Any, Callable, Sequence + +from airflow.exceptions import AirflowException +from airflow.providers.common.sql.hooks.sql import fetch_all_handler +from airflow.providers.databricks.hooks.databricks_sql import DatabricksSqlHook +from airflow.providers.databricks.sensors.databricks_sql import DatabricksSqlSensor +from airflow.utils.context import Context + + +class DatabricksTableChangesSensor(DatabricksSqlSensor): + """Sensor to detect changes in a Delta table. + + + :param databricks_conn_id: Reference to :ref:`Databricks + connection id<howto/connection:databricks>` (templated), defaults to + DatabricksSqlHook.default_conn_name + :param http_path: Optional string specifying HTTP path of Databricks SQL Endpoint or cluster. + If not specified, it should be either specified in the Databricks connection's + extra parameters, or ``sql_endpoint_name`` must be specified. + :param sql_endpoint_name: Optional name of Databricks SQL Endpoint. If not specified, ``http_path`` must + be provided as described above, defaults to None + :param session_configuration: An optional dictionary of Spark session parameters. If not specified, + it could be specified in the Databricks connection's extra parameters., defaults to None + :param http_headers: An optional list of (k, v) pairs + that will be set as HTTP headers on every request. (templated). + :param catalog: An optional initial catalog to use. + Requires DBR version 9.0+ (templated), defaults to "" + :param schema: An optional initial schema to use. + Requires DBR version 9.0+ (templated), defaults to "default" + :param table_name: Table name to generate the SQL query, defaults to "" + :param handler: Handler for DbApiHook.run() to return results, defaults to fetch_all_handler + :param caller: String passed to name a hook to Databricks, defaults to "DatabricksPartitionSensor" + :param client_parameters: Additional parameters internal to Databricks SQL Connector parameters. + :param timestamp: Timestamp to check event history for a Delta table, + defaults to datetime.now()-timedelta(days=7) + """ + + template_fields: Sequence[str] = ("databricks_conn_id", "catalog", "schema", "table_name", "timestamp") + + def __init__( + self, + *, + databricks_conn_id: str = DatabricksSqlHook.default_conn_name, + http_path: str | None = None, + sql_endpoint_name: str | None = None, + session_configuration=None, + http_headers: list[tuple[str, str]] | None = None, + catalog: str = "", + schema: str = "default", + table_name: str = "", + handler: Callable[[Any], Any] = fetch_all_handler, + timestamp: datetime = datetime.now() - timedelta(days=7), + caller: str = "DatabricksTableChangesSensor", + client_parameters: dict[str, Any] | None = None, + **kwargs, + ) -> None: + super().__init__(**kwargs) + self.databricks_conn_id = databricks_conn_id + self._http_path = http_path + self._sql_endpoint_name = sql_endpoint_name + self.session_config = session_configuration + self.http_headers = http_headers + self.catalog = catalog + self.schema = schema + self.table_name = table_name + self.timestamp = timestamp + self.caller = caller + self.client_parameters = client_parameters or {} + self.hook_params = kwargs.pop("hook_params", {}) + self.handler = handler + + def _get_hook(self) -> DatabricksSqlHook: + return DatabricksSqlHook( + self.databricks_conn_id, + self._http_path, + self._sql_endpoint_name, + self.session_config, + self.http_headers, + self.catalog, + self.schema, + self.caller, + **self.client_parameters, + **self.hook_params, + ) + + def _sql_sensor(self, sql): + hook = self._get_hook() + sql_result = hook.run( + sql, + handler=self.handler if self.do_xcom_push else None, + ) + return sql_result + + @staticmethod + def get_previous_version(context: Context, lookup_key): + return context["ti"].xcom_pull(key=lookup_key, include_prior_dates=True) + + @staticmethod + def set_version(context: Context, lookup_key, version): + context["ti"].xcom_push(key=lookup_key, value=version) + + def get_current_table_version(self, table_name, time_range): + change_sql = ( + f"SELECT COUNT(version) as versions from " Review Comment: what about selecting `max(version)` instead of count? ########## airflow/providers/databricks/sensors/databricks_partition.py: ########## @@ -0,0 +1,157 @@ +# +# 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. +# +"""This module contains Databricks sensors.""" + +from __future__ import annotations + +from typing import Any, Callable, Sequence + +from airflow.exceptions import AirflowException +from airflow.providers.common.sql.hooks.sql import fetch_one_handler +from airflow.providers.databricks.hooks.databricks_sql import DatabricksSqlHook +from airflow.providers.databricks.sensors.databricks_sql import DatabricksSqlSensor +from airflow.utils.context import Context + +template_fields: Sequence[str] = ("databricks_conn_id", "catalog", "schema", "table_name", "partition_name") + + +class DatabricksPartitionSensor(DatabricksSqlSensor): + """Sensor to detect the existence of partitions in a Delta table. + + :param databricks_conn_id: Reference to :ref:`Databricks + connection id<howto/connection:databricks>` (templated). + :param http_path: Optional string specifying HTTP path of Databricks SQL Endpoint or cluster. + If not specified, it should be either specified in the Databricks connection's extra parameters, + or ``sql_endpoint_name`` must be specified. + :param sql_endpoint_name: Optional name of Databricks SQL Endpoint. + If not specified, ``http_path`` must be provided as described above. + :param session_configuration: An optional dictionary of Spark session parameters. If not specified, + it could be specified in the Databricks connection's extra parameters. + :param http_headers: An optional list of (k, v) pairs that will be set + as HTTP headers on every request. (templated) + :param catalog: An optional initial catalog to use. Requires DBR version 9.0+ (templated) + :param schema: An optional initial schema to use. Requires DBR version 9.0+ (templated) + :param table_name: Table name to generate the SQL query. + :param partition_name: Partition to check. + :param handler: Handler for DbApiHook.run() to return results, defaults to fetch_one_handler + :param caller: String passed to name a hook to Databricks, defaults to "DatabricksPartitionSensor" + :param client_parameters: Additional parameters internal to Databricks SQL Connector parameters. + :param partition_operator: Comparison operator for partitions. + """ + + template_fields: Sequence[str] = ( + "databricks_conn_id", + "schema", + "http_headers", + "catalog", + "table_name", + "partition_name", + ) + + def __init__( + self, + *, + databricks_conn_id: str = DatabricksSqlHook.default_conn_name, + http_path: str | None = None, + sql_endpoint_name: str | None = None, + session_configuration=None, + http_headers: list[tuple[str, str]] | None = None, + catalog: str = "", + schema: str = "default", + table_name: str = "", + partition_name: dict, + handler: Callable[[Any], Any] = fetch_one_handler, + caller: str = "DatabricksPartitionSensor", + client_parameters: dict[str, Any] | None = None, + partition_operator: str = "=", + **kwargs, + ) -> None: + super().__init__(**kwargs) + self.databricks_conn_id = databricks_conn_id + self._http_path = http_path + self._sql_endpoint_name = sql_endpoint_name + self.session_config = session_configuration + self.http_headers = http_headers + self.catalog = catalog + self.schema = schema + self.table_name = table_name + self.partition_name = partition_name + self.caller = caller + self.client_parameters = client_parameters or {} + self.hook_params = kwargs.pop("hook_params", {}) + self.handler = handler + self.partition_operator = partition_operator + + def _get_hook(self) -> DatabricksSqlHook: + return DatabricksSqlHook( + self.databricks_conn_id, + self._http_path, + self._sql_endpoint_name, + self.session_config, + self.http_headers, + self.catalog, + self.schema, + self.caller, + **self.client_parameters, + **self.hook_params, + ) + + def _sql_sensor(self, sql): + hook = self._get_hook() + sql_result = hook.run( + sql, + handler=self.handler if self.do_xcom_push else None, + ) + return sql_result + + def _check_table_partitions(self) -> list: + if self.catalog is not None: Review Comment: it will be always executed this way because we're passing empty string as default. Also, we can continue to rely on two-level and even one level naming, relying on default catalog & default schema... ########## airflow/providers/databricks/sensors/databricks_partition.py: ########## @@ -0,0 +1,157 @@ +# +# 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. +# +"""This module contains Databricks sensors.""" + +from __future__ import annotations + +from typing import Any, Callable, Sequence + +from airflow.exceptions import AirflowException +from airflow.providers.common.sql.hooks.sql import fetch_one_handler +from airflow.providers.databricks.hooks.databricks_sql import DatabricksSqlHook +from airflow.providers.databricks.sensors.databricks_sql import DatabricksSqlSensor +from airflow.utils.context import Context + +template_fields: Sequence[str] = ("databricks_conn_id", "catalog", "schema", "table_name", "partition_name") + + +class DatabricksPartitionSensor(DatabricksSqlSensor): + """Sensor to detect the existence of partitions in a Delta table. + + :param databricks_conn_id: Reference to :ref:`Databricks + connection id<howto/connection:databricks>` (templated). + :param http_path: Optional string specifying HTTP path of Databricks SQL Endpoint or cluster. + If not specified, it should be either specified in the Databricks connection's extra parameters, + or ``sql_endpoint_name`` must be specified. + :param sql_endpoint_name: Optional name of Databricks SQL Endpoint. + If not specified, ``http_path`` must be provided as described above. + :param session_configuration: An optional dictionary of Spark session parameters. If not specified, + it could be specified in the Databricks connection's extra parameters. + :param http_headers: An optional list of (k, v) pairs that will be set + as HTTP headers on every request. (templated) + :param catalog: An optional initial catalog to use. Requires DBR version 9.0+ (templated) + :param schema: An optional initial schema to use. Requires DBR version 9.0+ (templated) + :param table_name: Table name to generate the SQL query. + :param partition_name: Partition to check. + :param handler: Handler for DbApiHook.run() to return results, defaults to fetch_one_handler + :param caller: String passed to name a hook to Databricks, defaults to "DatabricksPartitionSensor" + :param client_parameters: Additional parameters internal to Databricks SQL Connector parameters. + :param partition_operator: Comparison operator for partitions. + """ + + template_fields: Sequence[str] = ( + "databricks_conn_id", + "schema", + "http_headers", + "catalog", + "table_name", + "partition_name", + ) + + def __init__( + self, + *, + databricks_conn_id: str = DatabricksSqlHook.default_conn_name, + http_path: str | None = None, + sql_endpoint_name: str | None = None, + session_configuration=None, + http_headers: list[tuple[str, str]] | None = None, + catalog: str = "", + schema: str = "default", + table_name: str = "", + partition_name: dict, Review Comment: `partition_name` isn't intuitively understandable. I suggest to rename it to something like `partitions` or `partition_spec`... ########## airflow/providers/databricks/sensors/databricks_partition.py: ########## @@ -0,0 +1,157 @@ +# +# 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. +# +"""This module contains Databricks sensors.""" + +from __future__ import annotations + +from typing import Any, Callable, Sequence + +from airflow.exceptions import AirflowException +from airflow.providers.common.sql.hooks.sql import fetch_one_handler +from airflow.providers.databricks.hooks.databricks_sql import DatabricksSqlHook +from airflow.providers.databricks.sensors.databricks_sql import DatabricksSqlSensor +from airflow.utils.context import Context + +template_fields: Sequence[str] = ("databricks_conn_id", "catalog", "schema", "table_name", "partition_name") + + +class DatabricksPartitionSensor(DatabricksSqlSensor): + """Sensor to detect the existence of partitions in a Delta table. + + :param databricks_conn_id: Reference to :ref:`Databricks + connection id<howto/connection:databricks>` (templated). + :param http_path: Optional string specifying HTTP path of Databricks SQL Endpoint or cluster. + If not specified, it should be either specified in the Databricks connection's extra parameters, + or ``sql_endpoint_name`` must be specified. + :param sql_endpoint_name: Optional name of Databricks SQL Endpoint. + If not specified, ``http_path`` must be provided as described above. + :param session_configuration: An optional dictionary of Spark session parameters. If not specified, + it could be specified in the Databricks connection's extra parameters. + :param http_headers: An optional list of (k, v) pairs that will be set + as HTTP headers on every request. (templated) + :param catalog: An optional initial catalog to use. Requires DBR version 9.0+ (templated) + :param schema: An optional initial schema to use. Requires DBR version 9.0+ (templated) + :param table_name: Table name to generate the SQL query. + :param partition_name: Partition to check. + :param handler: Handler for DbApiHook.run() to return results, defaults to fetch_one_handler + :param caller: String passed to name a hook to Databricks, defaults to "DatabricksPartitionSensor" + :param client_parameters: Additional parameters internal to Databricks SQL Connector parameters. + :param partition_operator: Comparison operator for partitions. + """ + + template_fields: Sequence[str] = ( + "databricks_conn_id", + "schema", + "http_headers", + "catalog", + "table_name", + "partition_name", + ) + + def __init__( + self, + *, + databricks_conn_id: str = DatabricksSqlHook.default_conn_name, + http_path: str | None = None, + sql_endpoint_name: str | None = None, + session_configuration=None, + http_headers: list[tuple[str, str]] | None = None, + catalog: str = "", + schema: str = "default", Review Comment: I would prefer not to hardcode default schema but relying on the cluster/warehouse defaults. ########## airflow/providers/databricks/sensors/databricks_partition.py: ########## @@ -0,0 +1,157 @@ +# +# 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. +# +"""This module contains Databricks sensors.""" + +from __future__ import annotations + +from typing import Any, Callable, Sequence + +from airflow.exceptions import AirflowException +from airflow.providers.common.sql.hooks.sql import fetch_one_handler +from airflow.providers.databricks.hooks.databricks_sql import DatabricksSqlHook +from airflow.providers.databricks.sensors.databricks_sql import DatabricksSqlSensor +from airflow.utils.context import Context + +template_fields: Sequence[str] = ("databricks_conn_id", "catalog", "schema", "table_name", "partition_name") + + +class DatabricksPartitionSensor(DatabricksSqlSensor): + """Sensor to detect the existence of partitions in a Delta table. + + :param databricks_conn_id: Reference to :ref:`Databricks + connection id<howto/connection:databricks>` (templated). + :param http_path: Optional string specifying HTTP path of Databricks SQL Endpoint or cluster. + If not specified, it should be either specified in the Databricks connection's extra parameters, + or ``sql_endpoint_name`` must be specified. + :param sql_endpoint_name: Optional name of Databricks SQL Endpoint. + If not specified, ``http_path`` must be provided as described above. + :param session_configuration: An optional dictionary of Spark session parameters. If not specified, + it could be specified in the Databricks connection's extra parameters. + :param http_headers: An optional list of (k, v) pairs that will be set + as HTTP headers on every request. (templated) + :param catalog: An optional initial catalog to use. Requires DBR version 9.0+ (templated) + :param schema: An optional initial schema to use. Requires DBR version 9.0+ (templated) + :param table_name: Table name to generate the SQL query. + :param partition_name: Partition to check. + :param handler: Handler for DbApiHook.run() to return results, defaults to fetch_one_handler + :param caller: String passed to name a hook to Databricks, defaults to "DatabricksPartitionSensor" + :param client_parameters: Additional parameters internal to Databricks SQL Connector parameters. + :param partition_operator: Comparison operator for partitions. + """ + + template_fields: Sequence[str] = ( + "databricks_conn_id", + "schema", + "http_headers", + "catalog", + "table_name", + "partition_name", + ) + + def __init__( + self, + *, + databricks_conn_id: str = DatabricksSqlHook.default_conn_name, + http_path: str | None = None, + sql_endpoint_name: str | None = None, + session_configuration=None, + http_headers: list[tuple[str, str]] | None = None, + catalog: str = "", + schema: str = "default", + table_name: str = "", Review Comment: Can we inherit most of the parameters from `DatabricksSqlSensor`? ########## airflow/providers/databricks/sensors/databricks_partition.py: ########## @@ -0,0 +1,157 @@ +# +# 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. +# +"""This module contains Databricks sensors.""" + +from __future__ import annotations + +from typing import Any, Callable, Sequence + +from airflow.exceptions import AirflowException +from airflow.providers.common.sql.hooks.sql import fetch_one_handler +from airflow.providers.databricks.hooks.databricks_sql import DatabricksSqlHook +from airflow.providers.databricks.sensors.databricks_sql import DatabricksSqlSensor +from airflow.utils.context import Context + +template_fields: Sequence[str] = ("databricks_conn_id", "catalog", "schema", "table_name", "partition_name") + + +class DatabricksPartitionSensor(DatabricksSqlSensor): + """Sensor to detect the existence of partitions in a Delta table. + + :param databricks_conn_id: Reference to :ref:`Databricks + connection id<howto/connection:databricks>` (templated). + :param http_path: Optional string specifying HTTP path of Databricks SQL Endpoint or cluster. + If not specified, it should be either specified in the Databricks connection's extra parameters, + or ``sql_endpoint_name`` must be specified. + :param sql_endpoint_name: Optional name of Databricks SQL Endpoint. + If not specified, ``http_path`` must be provided as described above. + :param session_configuration: An optional dictionary of Spark session parameters. If not specified, + it could be specified in the Databricks connection's extra parameters. + :param http_headers: An optional list of (k, v) pairs that will be set + as HTTP headers on every request. (templated) + :param catalog: An optional initial catalog to use. Requires DBR version 9.0+ (templated) + :param schema: An optional initial schema to use. Requires DBR version 9.0+ (templated) + :param table_name: Table name to generate the SQL query. + :param partition_name: Partition to check. + :param handler: Handler for DbApiHook.run() to return results, defaults to fetch_one_handler + :param caller: String passed to name a hook to Databricks, defaults to "DatabricksPartitionSensor" + :param client_parameters: Additional parameters internal to Databricks SQL Connector parameters. + :param partition_operator: Comparison operator for partitions. + """ + + template_fields: Sequence[str] = ( + "databricks_conn_id", + "schema", + "http_headers", + "catalog", + "table_name", + "partition_name", + ) + + def __init__( + self, + *, + databricks_conn_id: str = DatabricksSqlHook.default_conn_name, + http_path: str | None = None, + sql_endpoint_name: str | None = None, + session_configuration=None, + http_headers: list[tuple[str, str]] | None = None, + catalog: str = "", + schema: str = "default", + table_name: str = "", + partition_name: dict, + handler: Callable[[Any], Any] = fetch_one_handler, + caller: str = "DatabricksPartitionSensor", + client_parameters: dict[str, Any] | None = None, + partition_operator: str = "=", + **kwargs, + ) -> None: + super().__init__(**kwargs) + self.databricks_conn_id = databricks_conn_id + self._http_path = http_path + self._sql_endpoint_name = sql_endpoint_name + self.session_config = session_configuration + self.http_headers = http_headers + self.catalog = catalog + self.schema = schema + self.table_name = table_name + self.partition_name = partition_name + self.caller = caller + self.client_parameters = client_parameters or {} + self.hook_params = kwargs.pop("hook_params", {}) + self.handler = handler + self.partition_operator = partition_operator + + def _get_hook(self) -> DatabricksSqlHook: + return DatabricksSqlHook( + self.databricks_conn_id, + self._http_path, + self._sql_endpoint_name, + self.session_config, + self.http_headers, + self.catalog, + self.schema, + self.caller, + **self.client_parameters, + **self.hook_params, + ) + + def _sql_sensor(self, sql): + hook = self._get_hook() + sql_result = hook.run( + sql, + handler=self.handler if self.do_xcom_push else None, + ) + return sql_result + + def _check_table_partitions(self) -> list: + if self.catalog is not None: + complete_table_name = str(self.catalog + "." + self.schema + "." + self.table_name) + self.log.debug("Table name generated from arguments: %s", complete_table_name) + else: + raise AirflowException("Catalog name not specified, aborting query execution.") + partition_columns = self._sql_sensor(f"describe detail {complete_table_name}")[7] + self.log.debug("table_info: %s", partition_columns) + if len(partition_columns) < 1: + raise AirflowException("Table %s does not have partitions", complete_table_name) + partitions_list = [] + for partition_col, partition_value in self.partition_name.items(): + if partition_col in partition_columns: + if isinstance(partition_value, list): + partitions_list.append(f"""{partition_col} in {tuple(partition_value)}""") + if isinstance(partition_value, (int, float, complex)): + partitions_list.append(f"""{partition_col}{self.partition_operator}{partition_value}""") + if isinstance(partition_value, str): + partitions_list.append( + f"""{partition_col}{self.partition_operator}\"{partition_value}\"""" + ) Review Comment: it's better to use formatting functions from sql connector, similar to what is done in the `DatabricksCopyIntoOperator` - otherwise we have a chance of getting SQL injection. ########## airflow/providers/databricks/sensors/databricks_partition.py: ########## @@ -0,0 +1,157 @@ +# +# 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. +# +"""This module contains Databricks sensors.""" + +from __future__ import annotations + +from typing import Any, Callable, Sequence + +from airflow.exceptions import AirflowException +from airflow.providers.common.sql.hooks.sql import fetch_one_handler +from airflow.providers.databricks.hooks.databricks_sql import DatabricksSqlHook +from airflow.providers.databricks.sensors.databricks_sql import DatabricksSqlSensor +from airflow.utils.context import Context + +template_fields: Sequence[str] = ("databricks_conn_id", "catalog", "schema", "table_name", "partition_name") + + +class DatabricksPartitionSensor(DatabricksSqlSensor): + """Sensor to detect the existence of partitions in a Delta table. + + :param databricks_conn_id: Reference to :ref:`Databricks + connection id<howto/connection:databricks>` (templated). + :param http_path: Optional string specifying HTTP path of Databricks SQL Endpoint or cluster. + If not specified, it should be either specified in the Databricks connection's extra parameters, + or ``sql_endpoint_name`` must be specified. + :param sql_endpoint_name: Optional name of Databricks SQL Endpoint. + If not specified, ``http_path`` must be provided as described above. + :param session_configuration: An optional dictionary of Spark session parameters. If not specified, + it could be specified in the Databricks connection's extra parameters. + :param http_headers: An optional list of (k, v) pairs that will be set + as HTTP headers on every request. (templated) + :param catalog: An optional initial catalog to use. Requires DBR version 9.0+ (templated) + :param schema: An optional initial schema to use. Requires DBR version 9.0+ (templated) + :param table_name: Table name to generate the SQL query. + :param partition_name: Partition to check. + :param handler: Handler for DbApiHook.run() to return results, defaults to fetch_one_handler + :param caller: String passed to name a hook to Databricks, defaults to "DatabricksPartitionSensor" + :param client_parameters: Additional parameters internal to Databricks SQL Connector parameters. + :param partition_operator: Comparison operator for partitions. + """ + + template_fields: Sequence[str] = ( + "databricks_conn_id", + "schema", + "http_headers", + "catalog", + "table_name", + "partition_name", + ) + + def __init__( + self, + *, + databricks_conn_id: str = DatabricksSqlHook.default_conn_name, + http_path: str | None = None, + sql_endpoint_name: str | None = None, + session_configuration=None, + http_headers: list[tuple[str, str]] | None = None, + catalog: str = "", + schema: str = "default", + table_name: str = "", + partition_name: dict, + handler: Callable[[Any], Any] = fetch_one_handler, + caller: str = "DatabricksPartitionSensor", + client_parameters: dict[str, Any] | None = None, + partition_operator: str = "=", + **kwargs, + ) -> None: + super().__init__(**kwargs) + self.databricks_conn_id = databricks_conn_id + self._http_path = http_path + self._sql_endpoint_name = sql_endpoint_name + self.session_config = session_configuration + self.http_headers = http_headers + self.catalog = catalog + self.schema = schema + self.table_name = table_name + self.partition_name = partition_name + self.caller = caller + self.client_parameters = client_parameters or {} + self.hook_params = kwargs.pop("hook_params", {}) + self.handler = handler + self.partition_operator = partition_operator + + def _get_hook(self) -> DatabricksSqlHook: + return DatabricksSqlHook( + self.databricks_conn_id, + self._http_path, + self._sql_endpoint_name, + self.session_config, + self.http_headers, + self.catalog, + self.schema, + self.caller, + **self.client_parameters, + **self.hook_params, + ) + + def _sql_sensor(self, sql): + hook = self._get_hook() + sql_result = hook.run( + sql, + handler=self.handler if self.do_xcom_push else None, + ) + return sql_result + + def _check_table_partitions(self) -> list: + if self.catalog is not None: + complete_table_name = str(self.catalog + "." + self.schema + "." + self.table_name) + self.log.debug("Table name generated from arguments: %s", complete_table_name) + else: + raise AirflowException("Catalog name not specified, aborting query execution.") + partition_columns = self._sql_sensor(f"describe detail {complete_table_name}")[7] + self.log.debug("table_info: %s", partition_columns) + if len(partition_columns) < 1: + raise AirflowException("Table %s does not have partitions", complete_table_name) + partitions_list = [] + for partition_col, partition_value in self.partition_name.items(): + if partition_col in partition_columns: + if isinstance(partition_value, list): + partitions_list.append(f"""{partition_col} in {tuple(partition_value)}""") + if isinstance(partition_value, (int, float, complex)): + partitions_list.append(f"""{partition_col}{self.partition_operator}{partition_value}""") + if isinstance(partition_value, str): + partitions_list.append( + f"""{partition_col}{self.partition_operator}\"{partition_value}\"""" + ) + else: + raise AirflowException( + "Column %s not part of table partitions: %s", partition_col, partition_columns + ) + partitions = " AND ".join(partitions_list) + partition_sql = f"SELECT 1 FROM {complete_table_name} WHERE {partitions}" + return self._sql_sensor(partition_sql) + + def poke(self, context: Context) -> bool: + result = self._check_table_partitions() + self.log.debug("Partition sensor result: %s", result) + if len(result) < 1: + raise AirflowException("Databricks SQL partition sensor failed.") + return True Review Comment: We can use the same function defined in the parent, but simply have an overridable function something like, `_get_results` that will implement the logic. ########## airflow/providers/databricks/sensors/databricks_table_changes.py: ########## @@ -0,0 +1,164 @@ +# +# 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. +# +"""This module contains Databricks sensors.""" + +from __future__ import annotations + +from datetime import datetime, timedelta +from typing import Any, Callable, Sequence + +from airflow.exceptions import AirflowException +from airflow.providers.common.sql.hooks.sql import fetch_all_handler +from airflow.providers.databricks.hooks.databricks_sql import DatabricksSqlHook +from airflow.providers.databricks.sensors.databricks_sql import DatabricksSqlSensor +from airflow.utils.context import Context + + +class DatabricksTableChangesSensor(DatabricksSqlSensor): + """Sensor to detect changes in a Delta table. + + + :param databricks_conn_id: Reference to :ref:`Databricks + connection id<howto/connection:databricks>` (templated), defaults to + DatabricksSqlHook.default_conn_name + :param http_path: Optional string specifying HTTP path of Databricks SQL Endpoint or cluster. + If not specified, it should be either specified in the Databricks connection's + extra parameters, or ``sql_endpoint_name`` must be specified. + :param sql_endpoint_name: Optional name of Databricks SQL Endpoint. If not specified, ``http_path`` must + be provided as described above, defaults to None + :param session_configuration: An optional dictionary of Spark session parameters. If not specified, + it could be specified in the Databricks connection's extra parameters., defaults to None + :param http_headers: An optional list of (k, v) pairs + that will be set as HTTP headers on every request. (templated). + :param catalog: An optional initial catalog to use. + Requires DBR version 9.0+ (templated), defaults to "" + :param schema: An optional initial schema to use. + Requires DBR version 9.0+ (templated), defaults to "default" + :param table_name: Table name to generate the SQL query, defaults to "" + :param handler: Handler for DbApiHook.run() to return results, defaults to fetch_all_handler + :param caller: String passed to name a hook to Databricks, defaults to "DatabricksPartitionSensor" + :param client_parameters: Additional parameters internal to Databricks SQL Connector parameters. + :param timestamp: Timestamp to check event history for a Delta table, + defaults to datetime.now()-timedelta(days=7) + """ + + template_fields: Sequence[str] = ("databricks_conn_id", "catalog", "schema", "table_name", "timestamp") + + def __init__( + self, + *, + databricks_conn_id: str = DatabricksSqlHook.default_conn_name, + http_path: str | None = None, + sql_endpoint_name: str | None = None, + session_configuration=None, + http_headers: list[tuple[str, str]] | None = None, + catalog: str = "", + schema: str = "default", + table_name: str = "", + handler: Callable[[Any], Any] = fetch_all_handler, + timestamp: datetime = datetime.now() - timedelta(days=7), + caller: str = "DatabricksTableChangesSensor", + client_parameters: dict[str, Any] | None = None, + **kwargs, + ) -> None: + super().__init__(**kwargs) + self.databricks_conn_id = databricks_conn_id + self._http_path = http_path + self._sql_endpoint_name = sql_endpoint_name + self.session_config = session_configuration + self.http_headers = http_headers + self.catalog = catalog + self.schema = schema + self.table_name = table_name + self.timestamp = timestamp + self.caller = caller + self.client_parameters = client_parameters or {} + self.hook_params = kwargs.pop("hook_params", {}) + self.handler = handler + + def _get_hook(self) -> DatabricksSqlHook: + return DatabricksSqlHook( + self.databricks_conn_id, + self._http_path, + self._sql_endpoint_name, + self.session_config, + self.http_headers, + self.catalog, + self.schema, + self.caller, + **self.client_parameters, + **self.hook_params, + ) + + def _sql_sensor(self, sql): + hook = self._get_hook() + sql_result = hook.run( + sql, + handler=self.handler if self.do_xcom_push else None, + ) + return sql_result + + @staticmethod + def get_previous_version(context: Context, lookup_key): + return context["ti"].xcom_pull(key=lookup_key, include_prior_dates=True) + + @staticmethod + def set_version(context: Context, lookup_key, version): + context["ti"].xcom_push(key=lookup_key, value=version) + + def get_current_table_version(self, table_name, time_range): + change_sql = ( + f"SELECT COUNT(version) as versions from " + f"(DESCRIBE HISTORY {table_name}) " + f"WHERE timestamp >= '{time_range}'" Review Comment: if time_range doesn't change between calls, we may return true all the time. Why not compare with the latest version instead? ########## airflow/providers/databricks/sensors/databricks_table_changes.py: ########## @@ -0,0 +1,164 @@ +# +# 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. +# +"""This module contains Databricks sensors.""" + +from __future__ import annotations + +from datetime import datetime, timedelta +from typing import Any, Callable, Sequence + +from airflow.exceptions import AirflowException +from airflow.providers.common.sql.hooks.sql import fetch_all_handler +from airflow.providers.databricks.hooks.databricks_sql import DatabricksSqlHook +from airflow.providers.databricks.sensors.databricks_sql import DatabricksSqlSensor +from airflow.utils.context import Context + + +class DatabricksTableChangesSensor(DatabricksSqlSensor): + """Sensor to detect changes in a Delta table. + + + :param databricks_conn_id: Reference to :ref:`Databricks + connection id<howto/connection:databricks>` (templated), defaults to + DatabricksSqlHook.default_conn_name + :param http_path: Optional string specifying HTTP path of Databricks SQL Endpoint or cluster. + If not specified, it should be either specified in the Databricks connection's + extra parameters, or ``sql_endpoint_name`` must be specified. + :param sql_endpoint_name: Optional name of Databricks SQL Endpoint. If not specified, ``http_path`` must + be provided as described above, defaults to None + :param session_configuration: An optional dictionary of Spark session parameters. If not specified, + it could be specified in the Databricks connection's extra parameters., defaults to None + :param http_headers: An optional list of (k, v) pairs + that will be set as HTTP headers on every request. (templated). + :param catalog: An optional initial catalog to use. + Requires DBR version 9.0+ (templated), defaults to "" + :param schema: An optional initial schema to use. + Requires DBR version 9.0+ (templated), defaults to "default" + :param table_name: Table name to generate the SQL query, defaults to "" + :param handler: Handler for DbApiHook.run() to return results, defaults to fetch_all_handler + :param caller: String passed to name a hook to Databricks, defaults to "DatabricksPartitionSensor" + :param client_parameters: Additional parameters internal to Databricks SQL Connector parameters. + :param timestamp: Timestamp to check event history for a Delta table, + defaults to datetime.now()-timedelta(days=7) + """ + + template_fields: Sequence[str] = ("databricks_conn_id", "catalog", "schema", "table_name", "timestamp") + + def __init__( + self, + *, + databricks_conn_id: str = DatabricksSqlHook.default_conn_name, + http_path: str | None = None, + sql_endpoint_name: str | None = None, + session_configuration=None, + http_headers: list[tuple[str, str]] | None = None, + catalog: str = "", + schema: str = "default", + table_name: str = "", + handler: Callable[[Any], Any] = fetch_all_handler, + timestamp: datetime = datetime.now() - timedelta(days=7), + caller: str = "DatabricksTableChangesSensor", + client_parameters: dict[str, Any] | None = None, + **kwargs, + ) -> None: + super().__init__(**kwargs) + self.databricks_conn_id = databricks_conn_id + self._http_path = http_path + self._sql_endpoint_name = sql_endpoint_name + self.session_config = session_configuration + self.http_headers = http_headers + self.catalog = catalog + self.schema = schema + self.table_name = table_name + self.timestamp = timestamp + self.caller = caller + self.client_parameters = client_parameters or {} + self.hook_params = kwargs.pop("hook_params", {}) + self.handler = handler + + def _get_hook(self) -> DatabricksSqlHook: + return DatabricksSqlHook( + self.databricks_conn_id, + self._http_path, + self._sql_endpoint_name, + self.session_config, + self.http_headers, + self.catalog, + self.schema, + self.caller, + **self.client_parameters, + **self.hook_params, + ) + + def _sql_sensor(self, sql): + hook = self._get_hook() + sql_result = hook.run( + sql, + handler=self.handler if self.do_xcom_push else None, + ) + return sql_result + + @staticmethod + def get_previous_version(context: Context, lookup_key): + return context["ti"].xcom_pull(key=lookup_key, include_prior_dates=True) + + @staticmethod + def set_version(context: Context, lookup_key, version): + context["ti"].xcom_push(key=lookup_key, value=version) + + def get_current_table_version(self, table_name, time_range): + change_sql = ( + f"SELECT COUNT(version) as versions from " + f"(DESCRIBE HISTORY {table_name}) " + f"WHERE timestamp >= '{time_range}'" + ) + result = self._sql_sensor(change_sql)[0][0] + return result + + def _check_table_changes(self, context: Context) -> bool: + if self.catalog is not None: + complete_table_name = str(self.catalog + "." + self.schema + "." + self.table_name) + self.log.debug("Table name generated from arguments: %s", complete_table_name) + else: + raise AirflowException("Catalog name not specified, aborting query execution.") Review Comment: Same comment as for partition sensor. ########## airflow/providers/databricks/sensors/databricks_table_changes.py: ########## @@ -0,0 +1,164 @@ +# +# 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. +# +"""This module contains Databricks sensors.""" + +from __future__ import annotations + +from datetime import datetime, timedelta +from typing import Any, Callable, Sequence + +from airflow.exceptions import AirflowException +from airflow.providers.common.sql.hooks.sql import fetch_all_handler +from airflow.providers.databricks.hooks.databricks_sql import DatabricksSqlHook +from airflow.providers.databricks.sensors.databricks_sql import DatabricksSqlSensor +from airflow.utils.context import Context + + +class DatabricksTableChangesSensor(DatabricksSqlSensor): + """Sensor to detect changes in a Delta table. + + + :param databricks_conn_id: Reference to :ref:`Databricks + connection id<howto/connection:databricks>` (templated), defaults to + DatabricksSqlHook.default_conn_name + :param http_path: Optional string specifying HTTP path of Databricks SQL Endpoint or cluster. + If not specified, it should be either specified in the Databricks connection's + extra parameters, or ``sql_endpoint_name`` must be specified. + :param sql_endpoint_name: Optional name of Databricks SQL Endpoint. If not specified, ``http_path`` must + be provided as described above, defaults to None + :param session_configuration: An optional dictionary of Spark session parameters. If not specified, + it could be specified in the Databricks connection's extra parameters., defaults to None + :param http_headers: An optional list of (k, v) pairs + that will be set as HTTP headers on every request. (templated). + :param catalog: An optional initial catalog to use. + Requires DBR version 9.0+ (templated), defaults to "" + :param schema: An optional initial schema to use. + Requires DBR version 9.0+ (templated), defaults to "default" + :param table_name: Table name to generate the SQL query, defaults to "" + :param handler: Handler for DbApiHook.run() to return results, defaults to fetch_all_handler + :param caller: String passed to name a hook to Databricks, defaults to "DatabricksPartitionSensor" + :param client_parameters: Additional parameters internal to Databricks SQL Connector parameters. + :param timestamp: Timestamp to check event history for a Delta table, + defaults to datetime.now()-timedelta(days=7) + """ + + template_fields: Sequence[str] = ("databricks_conn_id", "catalog", "schema", "table_name", "timestamp") + + def __init__( + self, + *, + databricks_conn_id: str = DatabricksSqlHook.default_conn_name, + http_path: str | None = None, + sql_endpoint_name: str | None = None, + session_configuration=None, + http_headers: list[tuple[str, str]] | None = None, + catalog: str = "", + schema: str = "default", + table_name: str = "", + handler: Callable[[Any], Any] = fetch_all_handler, + timestamp: datetime = datetime.now() - timedelta(days=7), + caller: str = "DatabricksTableChangesSensor", + client_parameters: dict[str, Any] | None = None, + **kwargs, + ) -> None: + super().__init__(**kwargs) + self.databricks_conn_id = databricks_conn_id + self._http_path = http_path + self._sql_endpoint_name = sql_endpoint_name + self.session_config = session_configuration + self.http_headers = http_headers + self.catalog = catalog + self.schema = schema + self.table_name = table_name + self.timestamp = timestamp + self.caller = caller + self.client_parameters = client_parameters or {} + self.hook_params = kwargs.pop("hook_params", {}) + self.handler = handler + + def _get_hook(self) -> DatabricksSqlHook: + return DatabricksSqlHook( + self.databricks_conn_id, + self._http_path, + self._sql_endpoint_name, + self.session_config, + self.http_headers, + self.catalog, + self.schema, + self.caller, + **self.client_parameters, + **self.hook_params, + ) + + def _sql_sensor(self, sql): + hook = self._get_hook() + sql_result = hook.run( + sql, + handler=self.handler if self.do_xcom_push else None, + ) + return sql_result + + @staticmethod + def get_previous_version(context: Context, lookup_key): + return context["ti"].xcom_pull(key=lookup_key, include_prior_dates=True) + + @staticmethod + def set_version(context: Context, lookup_key, version): + context["ti"].xcom_push(key=lookup_key, value=version) + + def get_current_table_version(self, table_name, time_range): + change_sql = ( + f"SELECT COUNT(version) as versions from " + f"(DESCRIBE HISTORY {table_name}) " + f"WHERE timestamp >= '{time_range}'" Review Comment: Does it make sense to report only data changes? Otherwise we'll get not necessary changes like after `VACUUM`, `OPTIMIZE`, ... ########## airflow/providers/databricks/sensors/databricks_sql.py: ########## @@ -0,0 +1,123 @@ +# +# 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. +# +"""This module contains Databricks sensors.""" + +from __future__ import annotations + +from typing import Any, Callable, Sequence + +from airflow.providers.common.sql.hooks.sql import fetch_all_handler +from airflow.providers.databricks.hooks.databricks_sql import DatabricksSqlHook +from airflow.sensors.base import BaseSensorOperator +from airflow.utils.context import Context + + +class DatabricksSqlSensor(BaseSensorOperator): + """Generic SQL sensor for Databricks + + :param databricks_conn_id: connection id from Airflow to databricks, + defaults to DatabricksSqlHook.default_conn_name + :param http_path: Optional string specifying HTTP path of + Databricks SQL Endpoint or cluster.If not specified, it should be either specified + in the Databricks connection's extra parameters, or ``sql_endpoint_name`` must be specified. + :param sql_endpoint_name: Optional name of Databricks SQL Endpoint. + If not specified, ``http_path`` must be provided as described above. + :param session_configuration: An optional dictionary of Spark session parameters. + Defaults to None. If not specified, it could be specified in the + Databricks connection's extra parameters. + :param http_headers: An optional list of (k, v) pairs that will be set as HTTP headers on every request. + :param caller: String passed to name a hook to Databricks, defaults to "DatabricksSqlSensor" + :param client_parameters: Additional parameters internal to Databricks SQL Connector parameters. + :param sql: SQL query to be executed. + """ + + template_fields: Sequence[str] = ( + "databricks_conn_id", + "sql", + "catalog", + "http_headers", + ) + + template_ext: Sequence[str] = (".sql",) + template_fields_renderers = {"sql": "sql"} + + def __init__( + self, + *, + databricks_conn_id: str = DatabricksSqlHook.default_conn_name, + http_path: str | None = None, + sql_endpoint_name: str | None = None, + session_configuration=None, + http_headers: list[tuple[str, str]] | None = None, + catalog: str = "", + schema: str = "default", + table_name: str = "", + handler: Callable[[Any], Any] = fetch_all_handler, + caller: str = "DatabricksSqlSensor", + client_parameters: dict[str, Any] | None = None, + sql: str = "", + **kwargs, + ) -> None: + super().__init__(**kwargs) + self.databricks_conn_id = databricks_conn_id + self._http_path = http_path + self._sql_endpoint_name = sql_endpoint_name + self.session_config = session_configuration + self.http_headers = http_headers + self.catalog = catalog + self.schema = schema + self.table_name = table_name + self.sql = sql + self.caller = caller + self.client_parameters = client_parameters or {} + self.hook_params = kwargs.pop("hook_params", {}) + self.handler = handler + + def _get_hook(self) -> DatabricksSqlHook: + return DatabricksSqlHook( + self.databricks_conn_id, + self._http_path, + self._sql_endpoint_name, + self.session_config, + self.http_headers, + self.catalog, + self.schema, + self.caller, + **self.client_parameters, + **self.hook_params, + ) + + def _sql_sensor(self, sql): + hook = self._get_hook() + sql_result = hook.run( + sql, + handler=self.handler if self.do_xcom_push else None, + ) + return sql_result + + def poke(self, context: Context) -> bool: + result = self._sql_sensor(self.sql) + self.log.debug("SQL result: %s", result) + if isinstance(result, list): + if len(result) >= 1: + return True + else: + return False Review Comment: this is really just `return len(result) > 0` -- This is an automated message from the Apache Git Service. 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