Problem or anti-pattern workloads

You must be aware of the guidelines for moving antipattern or problematic workloads.

Follow these guildelines to move problem or anti-pattern workloads.

• Select workloads that are complex and are complaining about impala performance, queuing issues, pool sizes, insufficient memory limits, scanning random datasets.
• Use WXM to identify the workloads that miss SLAs in WXM, that are killed due to running out of memory, that are running slow and would benefit from data caching.
• Consider using Hue or Impala Shell or some thick client JDBC tool like Dbeaver or Squirrel SQL for JDBC workloads.
  • You must be aware of the standard JDBC compatibilty issue for thick clients.
• Segregate each problem workload by assigning it to its own VW.
• Redirect BI tool to point to the VW for these workloads.
• A large sized VW is recommended for these workloads to perform better in CDW PvC 1.3.1 than on CDP Private Cloud base.
• To optimize performance, set a high value for EXEC_TIME_LIMIT_S.