Thanks for using MS Q&A platform and posting your query.
Here are a few ways to diagnose and address the performance degradation caused by your pipeline in Azure Synapse Analytics. Here's what you can do:
- Query Performance: If the slowdown is due to slow queries within the pipeline, you can use the built-in monitoring tools. Azure Synapse provides query execution details that pinpoint slow-running queries. Look for patterns like:
- Incorrect data distribution: Data skew can overload specific compute nodes. (https://techcommunity.microsoft.com/t5/azure-synapse-analytics/azure-synapse-dedicated-sql-pool-performance-problem/td-p/4005715)
- Outdated statistics: Outdated statistics can lead to inefficient query plans. Consider refreshing statistics on your tables. (https://learn.microsoft.com/en-us/azure/synapse-analytics/)
- Suboptimal indexing: Review your indexing strategy. Clustered columnstore indexes are often beneficial for large tables in Synapse. (https://learn.microsoft.com/en-us/azure/synapse-analytics/)
Resource Optimization:
- Serverless vs Dedicated Pools: If using the serverless pool, consider its resource limitations. Parallel queries can overload resources. Tools like Power BI refreshes might need scheduling optimization to avoid concurrency issues. (https://learn.microsoft.com/en-us/troubleshoot/azure/synapse-analytics/serverless-sql/query-perf/ssql-perf-optimize-querying)
- Resource Scaling (Dedicated Pools): For dedicated pools, consider scaling compute resources if the workload demands more.
General Troubleshooting:
- Monitor Pipeline Execution: Use Azure Monitor to track pipeline execution and identify specific stages causing delays.
- Simplify Pipeline Logic: Break down complex pipelines into smaller, more manageable steps.
- Parallelization (if applicable): If your pipeline processes data independently, explore parallelization options to improve throughput.
Hope this helps. Do let us know if you any further queries.