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Large-Scale Data Engineering in Cloud

Performance Tuning, Cost Optimization / Internals, Research by Dmitry Tolpeko

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  • Auto Scaling,  Presto

    Presto – Query Auto Scaling Limitations – Low Utilization After Upscale – GROUP BY Partitioned Stage, query-manager.required-workers

    December 4, 2019

    One of the powerful features of Presto is auto scaling of compute resources for already running queries. When a cluster is idle you can reduce its size or even terminate the cluster, and then dynamically add nodes when necessary depending on the compute requirements of queries.

    Unfortunately, there are some limitations since not all stages can scale on the fly, so you have to use some workarounds to have reasonable cold start performance.

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    dmtolpeko

Recent Posts

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  • Oct 10, 2023 Spark – Reading Parquet – Pushed Filters, SUBSTR(timestamp, 1, 10), LIKE and StringStartsWith
  • Oct 06, 2023 Spark Stage Restarts – Partial Restarts, Multiple Retry Attempts with Different Task Sets, Accepted Late Results from Failed Stages, Cost of Restarts

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