[jira] [Assigned] (SPARK-14130) [Table related commands] Alter column
[ https://issues.apache.org/jira/browse/SPARK-14130?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-14130: Assignee: Yin Huai (was: Apache Spark) > [Table related commands] Alter column > - > > Key: SPARK-14130 > URL: https://issues.apache.org/jira/browse/SPARK-14130 > Project: Spark > Issue Type: Sub-task > Components: SQL >Reporter: Yin Huai >Assignee: Yin Huai > > For alter column command, we have the following tokens. > TOK_ALTERTABLE_RENAMECOL > TOK_ALTERTABLE_ADDCOLS > TOK_ALTERTABLE_REPLACECOLS > For data source tables, we should throw exceptions. For Hive tables, we > should support them. *For Hive tables, we should check Hive's behavior to see > if there is any file format that does not any of above command*. > https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/exec/DDLTask.java > is a good reference for Hive's behavior. > Also, for a Hive table stored in a format, we need to make sure that even if > Spark can read this tables after an alter column operation. If we cannot read > the table, even Hive allows the alter column operation, we should still throw > an exception. For example, if renaming a column of a Hive parquet table > causes the renamed column inaccessible (we cannot read values), we should not > allow this renaming operation. -- 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
[jira] [Assigned] (SPARK-14130) [Table related commands] Alter column
[ https://issues.apache.org/jira/browse/SPARK-14130?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-14130: Assignee: Apache Spark (was: Yin Huai) > [Table related commands] Alter column > - > > Key: SPARK-14130 > URL: https://issues.apache.org/jira/browse/SPARK-14130 > Project: Spark > Issue Type: Sub-task > Components: SQL >Reporter: Yin Huai >Assignee: Apache Spark > > For alter column command, we have the following tokens. > TOK_ALTERTABLE_RENAMECOL > TOK_ALTERTABLE_ADDCOLS > TOK_ALTERTABLE_REPLACECOLS > For data source tables, we should throw exceptions. For Hive tables, we > should support them. *For Hive tables, we should check Hive's behavior to see > if there is any file format that does not any of above command*. > https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/exec/DDLTask.java > is a good reference for Hive's behavior. > Also, for a Hive table stored in a format, we need to make sure that even if > Spark can read this tables after an alter column operation. If we cannot read > the table, even Hive allows the alter column operation, we should still throw > an exception. For example, if renaming a column of a Hive parquet table > causes the renamed column inaccessible (we cannot read values), we should not > allow this renaming operation. -- 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
[jira] [Assigned] (SPARK-14130) [Table related commands] Alter column
[ https://issues.apache.org/jira/browse/SPARK-14130?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Andrew Or reassigned SPARK-14130: - Assignee: Andrew Or > [Table related commands] Alter column > - > > Key: SPARK-14130 > URL: https://issues.apache.org/jira/browse/SPARK-14130 > Project: Spark > Issue Type: Sub-task > Components: SQL >Reporter: Yin Huai >Assignee: Andrew Or > > For alter column command, we have the following tokens. > TOK_ALTERTABLE_RENAMECOL > TOK_ALTERTABLE_ADDCOLS > TOK_ALTERTABLE_REPLACECOLS > For data source tables, we should throw exceptions. For Hive tables, we > should support them. *For Hive tables, we should check Hive's behavior to see > if there is any file format that does not any of above command*. > https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/exec/DDLTask.java > is a good reference for Hive's behavior. > Also, for a Hive table stored in a format, we need to make sure that even if > Spark can read this tables after an alter column operation. If we cannot read > the table, even Hive allows the alter column operation, we should still throw > an exception. For example, if renaming a column of a Hive parquet table > causes the renamed column inaccessible (we cannot read values), we should not > allow this renaming operation. -- 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
