I'm trying to insert 50 million rows from hive table into a SQLServer table using SparkSQL JDBC Writer.Below is the line of code that I'm using to insert the data
mdf1.coalesce(4).write.mode(SaveMode.Append).jdbc(connectionString, "dbo.TEST_TABLE", connectionProperties)
The spark job is failing after processing 10 million rows with the below error
java.sql.BatchUpdateException: The instance of the SQL Server Database Engine cannot obtain a LOCK resource at this time. Rerun your statement when there are fewer active users. Ask the database administrator to check the lock and memory configuration for this instance, or to check for long-running transactions.
But the same job succeeds if I use the below line of code.
mdf1.coalesce(1).write.mode(SaveMode.Append).jdbc(connectionString, "dbo.TEST_TABLE", connectionProperties)
I'm trying to open 4 parallel connections to the SQLServer to optimize the performance. But the job keeps failing with "cannot aquire locks error" after processing 10 million rows. Also, If I limit the dataframe to just few million rows(less than 10 million), the job succeeds even with four parallel connections
Can anybody suggest me if SparkSQL can be used to export huge volumes of data into RDBMS and if I need to make any configuration changes on SQL server table.
Thanks in Advance.