[jira] [Commented] (SPARK-24965) Spark SQL fails when reading a partitioned hive table with different formats per partition
[ https://issues.apache.org/jira/browse/SPARK-24965?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17383192#comment-17383192 ] tiejiang commented on SPARK-24965: -- I have a similar question, see the link, can anyone answer it, thank you very much! :) https://stackoverflow.com/questions/68437779/error-when-spark-sql-read-parquet-table-with-text-partition > Spark SQL fails when reading a partitioned hive table with different formats > per partition > -- > > Key: SPARK-24965 > URL: https://issues.apache.org/jira/browse/SPARK-24965 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.3.1 >Reporter: Kris Geusebroek >Priority: Major > Labels: bulk-closed, pull-request-available > > When a hive parquet partitioned table contains a partition with a different > format (avro for example) the select * fails with a read exception (avro file > is not a parquet file) > Selecting in hive acts as expected. > To support this a new sql syntax needed to be supported also: > * ALTER TABLE SET FILEFORMAT > This is included in the same PR since the unittest needs this to setup the > testdata. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-24965) Spark SQL fails when reading a partitioned hive table with different formats per partition
[ https://issues.apache.org/jira/browse/SPARK-24965?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16561976#comment-16561976 ] Apache Spark commented on SPARK-24965: -- User 'krisgeus' has created a pull request for this issue: https://github.com/apache/spark/pull/21893 > Spark SQL fails when reading a partitioned hive table with different formats > per partition > -- > > Key: SPARK-24965 > URL: https://issues.apache.org/jira/browse/SPARK-24965 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.3.1 >Reporter: Kris Geusebroek >Priority: Major > Labels: pull-request-available > > When a hive parquet partitioned table contains a partition with a different > format (avro for example) the select * fails with a read exception (avro file > is not a parquet file) > Selecting in hive acts as expected. > To support this a new sql syntax needed to be supported also: > * ALTER TABLE SET FILEFORMAT > This is included in the same PR since the unittest needs this to setup the > testdata. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-24965) Spark SQL fails when reading a partitioned hive table with different formats per partition
[ https://issues.apache.org/jira/browse/SPARK-24965?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16561278#comment-16561278 ] Kris Geusebroek commented on SPARK-24965: - PR: https://github.com/apache/spark/pull/21893 > Spark SQL fails when reading a partitioned hive table with different formats > per partition > -- > > Key: SPARK-24965 > URL: https://issues.apache.org/jira/browse/SPARK-24965 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.3.1 >Reporter: Kris Geusebroek >Priority: Major > Labels: pull-request-available > > When a hive parquet partitioned table contains a partition with a different > format (avro for example) the select * fails with a read exception (avro file > is not a parquet file) > Selecting in hive acts as expected. > To support this a new sql syntax needed to be supported also: > * ALTER TABLE SET FILEFORMAT > This is included in the same PR since the unittest needs this to setup the > testdata. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org