[ https://issues.apache.org/jira/browse/SPARK-20236?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-20236: ------------------------------------ Assignee: Apache Spark > Overwrite a partitioned data source table should only overwrite related > partitions > ---------------------------------------------------------------------------------- > > Key: SPARK-20236 > URL: https://issues.apache.org/jira/browse/SPARK-20236 > Project: Spark > Issue Type: Improvement > Components: SQL > Affects Versions: 2.2.0 > Reporter: Wenchen Fan > Assignee: Apache Spark > Labels: releasenotes > > When we overwrite a partitioned data source table, currently Spark will > truncate the entire table to write new data, or truncate a bunch of > partitions according to the given static partitions. > For example, {{INSERT OVERWRITE tbl ...}} will truncate the entire table, > {{INSERT OVERWRITE tbl PARTITION (a=1, b)}} will truncate all the partitions > that starts with {{a=1}}. > This behavior is kind of reasonable as we can know which partitions will be > overwritten before runtime. However, hive has a different behavior that it > only overwrites related partitions, e.g. {{INSERT OVERWRITE tbl SELECT > 1,2,3}} will only overwrite partition {{a=2, b=3}}, assuming {{tbl}} has only > one data column and is partitioned by {{a}} and {{b}}. > It seems better if we can follow hive's behavior. -- This message was sent by Atlassian JIRA (v6.4.14#64029) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org