Source code for airflow.macros.hive

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import datetime



[docs]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()



[docs]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()

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