In my job, I'm using tParallelize to load redshift tables using data from AWS S3. There are four parallel flows connected to tParallelize. The job runs successfully but it is taking too long for completion (4 Hrs). May be because data for the first two flows is large.
Can anyone please suggest any improvised way to do this?
PS: I cannot remove tParallelize as the job will take even longer time if it isn't used.
Could you please increase the Xms and Xmx parameters of your Talend job and see the performance difference? As a starting point, change the Xmx to double or triple the current value. At the same time, you need to make sure that your Job server can provide that much memory for the job.
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