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Introducing the Dask Active Memory Manager

Talkat PyCon DE & PyData Berlin 2022 · 2022-04-11..04-13· [python]
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A scheduler-side daemon called the Active Memory Manager runs every few seconds and enacts policy suggestions to replicate or drop in-memory task replicas; it is experimental and off by default and is enabled via client.amm.start or config (Dask 2022.2+). Built policies include remove-replicas (on by default) and retire-worker, with planned rebalance and replicate; demo shows total cluster memory capping at 46–47 GB versus much higher without the AMM, preventing hard OOMs and enabling graceful worker retirement.

AI-written summary · about

  1. 0:00Start
  2. 5:14Issues in Memory Management
  3. 8:59Drop a Replica
  4. 13:53Amm Remove Replicas
  5. 17:51Re Reduce Replicas Policy
  6. 23:43How Do You Define a Custom Policy
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