Max Concurrent executable
2)Partitioning the source and destination ( little bit complicated but most power full way to achieve parallelism, everything is dynamic)
In order achieve parallelism in ETL
1) Source and destination should be partitioned according the Data load
2) Entire work load should be divided to individual tasks
3) Each task should be sub divided into multiple tasks
4) Single unit of task should not not depend up on the other task(dead locks, I/O waits..)
5) before using the maximum threshold CPU for parallelism proper testing should be done, so there are always resources available for system processes Some times Parallelism may degrade the performance
6) If work load is divided in to to many small tasks which may also degrade the performance (ex: Time spent by the Worker thread to wait for child threads may exceed single execution of the process )
Declare variables
Conclusion: Parallelism can be save lot of time in ETL process if utilized properly