# # 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. import datetime def max_partition( table, schema="default", field=None, filter_map=None, metastore_conn_id='metastore_default' ): """ Gets the max partition for a table. :param schema: The hive schema the table lives in :type schema: str :param table: The hive table you are interested in, supports the dot notation as in "my_database.my_table", if a dot is found, the schema param is disregarded :type table: str :param metastore_conn_id: The hive connection you are interested in. If your default is set you don't need to use this parameter. :type metastore_conn_id: str :param filter_map: partition_key:partition_value map used for partition filtering, e.g. {'key1': 'value1', 'key2': 'value2'}. Only partitions matching all partition_key:partition_value pairs will be considered as candidates of max partition. :type filter_map: dict :param field: the field to get the max value from. If there's only one partition field, this will be inferred :type field: str >>> max_partition('airflow.static_babynames_partitioned') '2015-01-01' """ from airflow.providers.apache.hive.hooks.hive import HiveMetastoreHook if '.' in table: schema, table = table.split('.') hive_hook = HiveMetastoreHook(metastore_conn_id=metastore_conn_id) return hive_hook.max_partition(schema=schema, table_name=table, field=field, filter_map=filter_map) def _closest_date(target_dt, date_list, before_target=None): """ This function finds the date in a list closest to the target date. An optional parameter can be given to get the closest before or after. :param target_dt: The target date :type target_dt: datetime.date :param date_list: The list of dates to search :type date_list: list[datetime.date] :param before_target: closest before or after the target :type before_target: bool or None :returns: The closest date :rtype: datetime.date or None """ time_before = lambda d: target_dt - d if d <= target_dt else datetime.timedelta.max time_after = lambda d: d - target_dt if d >= target_dt else datetime.timedelta.max any_time = lambda d: target_dt - d if d < target_dt else d - target_dt if before_target is None: return min(date_list, key=any_time).date() if before_target: return min(date_list, key=time_before).date() else: return min(date_list, key=time_after).date() def closest_ds_partition(table, ds, before=True, schema="default", metastore_conn_id='metastore_default'): """ This function finds the date in a list closest to the target date. An optional parameter can be given to get the closest before or after. :param table: A hive table name :type table: str :param ds: A datestamp ``%Y-%m-%d`` e.g. ``yyyy-mm-dd`` :type ds: list[datetime.date] :param before: closest before (True), after (False) or either side of ds :type before: bool or None :param schema: table schema :type schema: str :param metastore_conn_id: which metastore connection to use :type metastore_conn_id: str :returns: The closest date :rtype: str or None >>> tbl = 'airflow.static_babynames_partitioned' >>> closest_ds_partition(tbl, '2015-01-02') '2015-01-01' """ from airflow.providers.apache.hive.hooks.hive import HiveMetastoreHook if '.' in table: schema, table = table.split('.') hive_hook = HiveMetastoreHook(metastore_conn_id=metastore_conn_id) partitions = hive_hook.get_partitions(schema=schema, table_name=table) if not partitions: return None part_vals = [list(p.values())[0] for p in partitions] if ds in part_vals: return ds else: parts = [datetime.datetime.strptime(pv, '%Y-%m-%d') for pv in part_vals] target_dt = datetime.datetime.strptime(ds, '%Y-%m-%d') closest_ds = _closest_date(target_dt, parts, before_target=before) return closest_ds.isoformat()