Analyzing Process Skew to Tune Queries

Shared-nothing MPP databases benefit from parallelized work when all the components can work equally. If there are specific components (node slices) that get far more work than others, the overall time to complete the job is impacted by the time it takes for the longest slice to finish it's work.  
Redshift provides underlying system tables that contain detailed information about the work done on each slices to execute the query.  
The Aginity Workbench for Redshift allows you to get quick access to this information and presents it in an easy way to visualize and analyze processing for skew and bottlenecks.  
To get to this feature, click the View menu and select Server Query History. Once you have used the table to locate the query of interest, you can right-click on the query and select Show Iterators for this Execution. You will then be presented with a view of the work occurring on each slice.

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