Details
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Improvement
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Status: Resolved
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Normal
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Resolution: Fixed
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None
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Operability
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Normal
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All
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None
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Description
We issue writes to Cassandra as logged batches(RF=3, Consistency levels=TWO, QUORUM, or LOCAL_QUORUM)
On clusters of any size - a single extremely slow node causes a ~90% loss of cluster-wide throughput using batched writes. We can replicate this in the lab via CPU or disk throttling. I observe this in 3.11, 4.0, and 4.1.
It appears the mechanism in play is:
Those logged batches are immediately written to two replica nodes and the actual mutations aren't processed until those two nodes acknowledge the batch statements. Those replica nodes are selected randomly from all nodes in the local data center currently up in gossip. If a single node is slow, but still thought to be up in gossip, this eventually causes every other node to have all of its MutationStages to be waiting while the slow replica accepts batch writes.
The code in play appears to be:
See
In the method filterBatchlogEndpoints() there is a
Collections.shuffle() to order the endpoints and a
FailureDetector.isEndpointAlive() to test if the endpoint is acceptable.
This behavior causes Cassandra to move from a multi-node fault tolerant system toa collection of single points of failure.
We try to take administrator actions to kill off the extremely slow nodes, but it would be great to have some notion of "what node is a bad choice" when writing log batches to replica nodes.
Attachments
Attachments
Issue Links
- is related to
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CASSANDRA-20002 Add latest test config for dynamic_remote batchlog_endpoint_strategy and new auth parameterizedClass maps
- Resolved