[ https://issues.apache.org/jira/browse/SPARK-14459?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Cheng Lian resolved SPARK-14459. -------------------------------- Resolution: Fixed Fix Version/s: 2.0.0 Issue resolved by pull request 12239 [https://github.com/apache/spark/pull/12239] > SQL partitioning must match existing tables, but is not checked. > ---------------------------------------------------------------- > > Key: SPARK-14459 > URL: https://issues.apache.org/jira/browse/SPARK-14459 > Project: Spark > Issue Type: Bug > Components: SQL > Affects Versions: 2.0.0 > Reporter: Ryan Blue > Assignee: Ryan Blue > Fix For: 2.0.0 > > > Writing into partitioned Hive tables has unexpected results because the > table's partitioning is not detected and applied during the analysis phase. > For example, if I have two tables, {{source}} and {{partitioned}}, with the > same column types: > {code} > CREATE TABLE source (id bigint, data string, part string); > CREATE TABLE partitioned (id bigint, data string) PARTITIONED BY (part > string); > // copy from source to partitioned > sqlContext.table("source").write.insertInto("partitioned") > {code} > Copying from {{source}} to {{partitioned}} succeeds, but results in 0 rows. > This works if I explicitly partition by adding > {{...write.partitionBy("part").insertInto(...)}}. This work-around isn't > obvious and is prone to error because the {{partitionBy}} must match the > table's partitioning, though it is not checked. > I think when relations are resolved, the partitioning should be checked and > updated if it isn't set. -- 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