[ https://issues.apache.org/jira/browse/SPARK-18572?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Michael Allman updated SPARK-18572: ----------------------------------- Description: Currently Spark answers the {{SHOW PARTITIONS}} query by fetching all of the table's partition metadata from the external catalog and constructing partition names therefrom. The Hive client has a {{getPartitionNames}} method which is orders of magnitude faster, with the performance improvement scaling up with the number of partitions in the table. I believe we can use this method to great effect. Further details are provided in the associated PR. was: Currently Spark answers the {{SHOW PARTITIONS}} query by fetching all of the table's partition metadata from the external catalog and constructing partition names therefrom. The Hive client has a {{getPartitionNames}} method which is orders of magnitude faster, with the performance improvement scaling up with the number of partitions in the table. I believe we can use this method to great effect. Further details are provided in the associated PR (coming shortly). > Use the hive client method "getPartitionNames" to answer "SHOW PARTITIONS" > queries on partitioned Hive tables > ------------------------------------------------------------------------------------------------------------- > > Key: SPARK-18572 > URL: https://issues.apache.org/jira/browse/SPARK-18572 > Project: Spark > Issue Type: Improvement > Components: SQL > Reporter: Michael Allman > > Currently Spark answers the {{SHOW PARTITIONS}} query by fetching all of the > table's partition metadata from the external catalog and constructing > partition names therefrom. The Hive client has a {{getPartitionNames}} method > which is orders of magnitude faster, with the performance improvement scaling > up with the number of partitions in the table. I believe we can use this > method to great effect. > Further details are provided in the associated PR. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org