Python UDF constraints
Within the constraints listed in this topic, you can use UDFs anywhere you use the Amazon Redshift built-in scalar functions. For more information, see SQL functions reference.
Amazon Redshift Python UDFs have the following constraints:
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Python UDFs cannot access the network or read or write to the file system.
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The total size of user-installed Python libraries cannot exceed 100 MB.
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Amazon Redshift can only run one Python UDF at a time for provisioned clusters using automatic workload management (WLM) and for serverless workgroups. If you try to run more than one UDF concurrently, Amazon Redshift queues the remaining Python UDFs to run in the workload management queues. SQL UDFs don’t have a concurrency limit when using automatic WLM.
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When using manual WLM for provisioned clusters, the number of Python UDFs that can run concurrently per cluster is limited to one-fourth of the cluster’s total concurrency level. For example, a provisioned cluster with a concurrency of 15 can run a maximum of three concurrent Python UDFs.
When using Python UDFs, Amazon Redshift doesn't support the SUPER and HLLSKETCH data types.
