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Workflow consists of a single input data tool, connected to Redshift via ODBC with custom SQL that returns 38 records across 44 fields.
This workflow runs from Alteryx designer.
Workflow takes less than 10 seconds to run in some cases, and more than 2 minutes to run on others.
Can this be anything other than network latency or database connectivity issues? Suppose not, though community may have other ideas or experiences.
Likewise, is there a way to see an execution plan or something other than performance profiling available to diagnose this inside of Alteryx? I would like to preserve the single tool as decomposing the SQL into multiple tools seems extreme given the workflow executes in a reasonable amount of time.
Just wondering if there are other ways to understand what is going on under the hood. Thanks and appreciate the insights!
I have definitely seen network latency/database connectivity issues have an impact on query time. Some clients also will also connect to a database from their company's VPN which can slow things further.
It is very likely that it is the query to the database that is the bottleneck in your workflow. You can test this out by copying the SQL from your input tool and executing it outside of Alteryx.
@jasonMMedina When are you running your workflow? Is it when there are multiple users also running queries against the Redshift DB? I've heard Redshift isn't great when there are a bunch of concurrent users hitting the DB. The reason I ask about time is if you are running the workflow during the day the more likely other folks are also hitting the DB.
That is correct - performance varies in both Alteryx and SQL editor. No VPN in this case here.
In Alteryx, are there options other than Performance Profiling to asses workflow performance? For example, suppose there is a workflow with one input data tool. Performance profiling won't help since there is just one input data tool.
Within Alteryx, is there anything similar to an EXPLAIN plan to help show how Alteryx is communicating with the database? Or is running an Explain plan against the database the only option to identify overhead cost?