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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2015/10/05 09:48:26 UTC
[jira] [Commented] (SPARK-10856) SQL Server dialect needs to map
java.sql.Timestamp to DATETIME instead of TIMESTAMP
[ https://issues.apache.org/jira/browse/SPARK-10856?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14943017#comment-14943017 ]
Apache Spark commented on SPARK-10856:
--------------------------------------
User 'viirya' has created a pull request for this issue:
https://github.com/apache/spark/pull/8978
> SQL Server dialect needs to map java.sql.Timestamp to DATETIME instead of TIMESTAMP
> -----------------------------------------------------------------------------------
>
> Key: SPARK-10856
> URL: https://issues.apache.org/jira/browse/SPARK-10856
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.4.0, 1.4.1, 1.5.0
> Reporter: Henrik Behrens
> Labels: patch
>
> When saving a DataFrame to MS SQL Server, en error is thrown if there is more than one TIMESTAMP column:
> df.printSchema
> root
> |-- Id: string (nullable = false)
> |-- TypeInformation_CreatedBy: string (nullable = false)
> |-- TypeInformation_ModifiedBy: string (nullable = true)
> |-- TypeInformation_TypeStatus: integer (nullable = false)
> |-- TypeInformation_CreatedAtDatabase: timestamp (nullable = false)
> |-- TypeInformation_ModifiedAtDatabase: timestamp (nullable = true)
> df.write.mode("overwrite").jdbc(url, tablename, props)
> com.microsoft.sqlserver.jdbc.SQLServerException: A table can only have one timestamp column. Because table 'DebtorTypeSet1' already has one, the column 'TypeInformation_ModifiedAtDatabase' cannot be added.
> at com.microsoft.sqlserver.jdbc.SQLServerException.makeFromDatabaseError
> (SQLServerException.java:217)
> at com.microsoft.sqlserver.jdbc.SQLServerStatement.getNextResult(SQLServ
> erStatement.java:1635)
> at com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement.doExecutePrep
> aredStatement(SQLServerPreparedStatement.java:426)
> at com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement$PrepStmtExecC
> md.doExecute(SQLServerPreparedStatement.java:372)
> at com.microsoft.sqlserver.jdbc.TDSCommand.execute(IOBuffer.java:6276)
> at com.microsoft.sqlserver.jdbc.SQLServerConnection.executeCommand(SQLSe
> rverConnection.java:1793)
> at com.microsoft.sqlserver.jdbc.SQLServerStatement.executeCommand(SQLSer
> verStatement.java:184)
> at com.microsoft.sqlserver.jdbc.SQLServerStatement.executeStatement(SQLS
> erverStatement.java:159)
> at com.microsoft.sqlserver.jdbc.SQLServerPreparedStatement.executeUpdate
> (SQLServerPreparedStatement.java:315)
> I tested this on Windows and SQL Server 12 using Spark 1.4.1.
> I think this can be fixed in a similar way to Spark-10419.
> As a refererence, here is the type mapping according to the SQL Server JDBC driver (basicDT.java, extracted from sqljdbc_4.2.6420.100_enu.exe):
> private static void displayRow(String title, ResultSet rs) {
> try {
> System.out.println(title);
> System.out.println(rs.getInt(1) + " , " + // SQL integer type.
> rs.getString(2) + " , " + // SQL char type.
> rs.getString(3) + " , " + // SQL varchar type.
> rs.getBoolean(4) + " , " + // SQL bit type.
> rs.getDouble(5) + " , " + // SQL decimal type.
> rs.getDouble(6) + " , " + // SQL money type.
> rs.getTimestamp(7) + " , " + // SQL datetime type.
> rs.getDate(8) + " , " + // SQL date type.
> rs.getTime(9) + " , " + // SQL time type.
> rs.getTimestamp(10) + " , " + // SQL datetime2 type.
> ((SQLServerResultSet)rs).getDateTimeOffset(11)); // SQL datetimeoffset type.
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