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Henrik Behrens commented on SPARK-10856: ---------------------------------------- Thank you for creating a pull request, I did it the same way at my site. In the mean time, I found two other types that need a special mapping for MS SQL Server: 1. java.sql.types.BIT needs to be mapped to BIT instead of BIT[n], otherwise we get the following error message with Spark: com.microsoft.sqlserver.jdbc.SQLServerException: Column, parameter, or variable #10: Cannot specify a column width on data type bit. 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) at org.apache.spark.sql.DataFrameWriter.jdbc(DataFrameWriter.scala:277) 2. Strings of unlimited length should be mapped to NVARCHAR(MAX) in SQL Server instead of TEXT, because TEXT is deprecated (see https://msdn.microsoft.com/en-us/library/ms187993.aspx). I tested the following patch successfully: override def getJDBCType(dt: DataType): Option[JdbcType] = dt match { case TimestampType => Some(JdbcType("DATETIME", java.sql.Types.TIMESTAMP)) case StringType => Some(JdbcType("NVARCHAR(MAX)", java.sql.Types.NVARCHAR)) case BooleanType => Some(JdbcType("BIT", java.sql.Types.BIT)) case _ => None } Please consider including the other two changes into your pull request. I you prefer, I can create two new bug reports. > 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. -- 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