:mod:`airflow.operators.hive_to_druid`
======================================

.. py:module:: airflow.operators.hive_to_druid


Module Contents
---------------

.. data:: LOAD_CHECK_INTERVAL
   :annotation: = 5

   
.. data:: DEFAULT_TARGET_PARTITION_SIZE
   :annotation: = 5000000

   
.. py:class:: HiveToDruidTransfer(sql, druid_datasource, ts_dim, metric_spec=None, hive_cli_conn_id='hive_cli_default', druid_ingest_conn_id='druid_ingest_default', metastore_conn_id='metastore_default', hadoop_dependency_coordinates=None, intervals=None, num_shards=-1, target_partition_size=-1, query_granularity='NONE', segment_granularity='DAY', hive_tblproperties=None, job_properties=None, *args, **kwargs)

   Bases: :class:`airflow.models.BaseOperator`

   Moves data from Hive to Druid, [del]note that for now the data is loaded
   into memory before being pushed to Druid, so this operator should
   be used for smallish amount of data.[/del]

   :param sql: SQL query to execute against the Druid database. (templated)
   :type sql: str
   :param druid_datasource: the datasource you want to ingest into in druid
   :type druid_datasource: str
   :param ts_dim: the timestamp dimension
   :type ts_dim: str
   :param metric_spec: the metrics you want to define for your data
   :type metric_spec: list
   :param hive_cli_conn_id: the hive connection id
   :type hive_cli_conn_id: str
   :param druid_ingest_conn_id: the druid ingest connection id
   :type druid_ingest_conn_id: str
   :param metastore_conn_id: the metastore connection id
   :type metastore_conn_id: str
   :param hadoop_dependency_coordinates: list of coordinates to squeeze
       int the ingest json
   :type hadoop_dependency_coordinates: list[str]
   :param intervals: list of time intervals that defines segments,
       this is passed as is to the json object. (templated)
   :type intervals: list
   :param hive_tblproperties: additional properties for tblproperties in
       hive for the staging table
   :type hive_tblproperties: dict
   :param job_properties: additional properties for job
   :type job_properties: dict

   .. attribute:: template_fields
      :annotation: = ['sql', 'intervals']

      
   .. attribute:: template_ext
      :annotation: = ['.sql']

      
   .. method:: execute(self, context)


   .. method:: construct_ingest_query(self, static_path, columns)

      Builds an ingest query for an HDFS TSV load.

      :param static_path: The path on hdfs where the data is
      :type static_path: str
      :param columns: List of all the columns that are available
      :type columns: list