Do not force refresh when write indexing buffer #50769
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dnhatn
added
>enhancement
:Distributed Indexing/Engine
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Pinging @elastic/es-distributed (:Distributed/Engine) |
dnhatn
commented
Jan 8, 2020
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| // TODO: would be cleaner if I could pass this 1kb setting to the single node this test created.... | ||
| IndexingMemoryController imc = new IndexingMemoryController(settings, null, null) { | ||
| public void testSkipRefreshIfShardIsRefreshingAlready() throws Exception { |
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I only added this new test. Other tests are unchanged.
henningandersen
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Jan 9, 2020
server/src/test/java/org/elasticsearch/indices/IndexingMemoryControllerTests.java
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server/src/test/java/org/elasticsearch/indices/IndexingMemoryControllerIT.java
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Yep, I am running it on my CI now. |
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@ywelsch @henningandersen Thanks for reviewing. |
henningandersen
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Jan 10, 2020
The test checked queue size and active count, however, ThreadPoolExecutor pulls out the request from the queue before marking the worker active, risking that we think all tasks are done when they are not. Now check on completed-tasks metric instead, which is guaranteed to be monotonic. Relates elastic#50769
henningandersen
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Jan 10, 2020
The test checked queue size and active count, however, ThreadPoolExecutor pulls out the request from the queue before marking the worker active, risking that we think all tasks are done when they are not. Now check on completed-tasks metric instead, which is guaranteed to be monotonic. Relates #50769
dnhatn
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Jan 11, 2020
Today we periodically check the indexing buffer memory every 5 seconds or after we have used 1/30 of the configured memory. If the total used memory is over the threshold, then we refresh the "largest" shards. If refreshing takes longer these intervals (i.e., 5s or 1/30 buffer), then we continue to enqueue refreshes to these shards. This leads to two issues: - The refresh thread pool can be exhausted and other shards can't refresh - Execute too many refreshes for the "largest" shards With this change, we only refresh the largest shards if they are not refreshing. Here we rely on the periodic check to trigger another refresh if needed. We can harden this by making the ongoing refresh triggers the memory check when it's completed. I opted out this option in this PR for simplicity. See: https://discuss.elastic.co/t/write-queue-continue-to-rise/213652/
dnhatn
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Jan 11, 2020
The test checked queue size and active count, however, ThreadPoolExecutor pulls out the request from the queue before marking the worker active, risking that we think all tasks are done when they are not. Now check on completed-tasks metric instead, which is guaranteed to be monotonic. Relates #50769
SivagurunathanV
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Jan 23, 2020
Today we periodically check the indexing buffer memory every 5 seconds or after we have used 1/30 of the configured memory. If the total used memory is over the threshold, then we refresh the "largest" shards. If refreshing takes longer these intervals (i.e., 5s or 1/30 buffer), then we continue to enqueue refreshes to these shards. This leads to two issues: - The refresh thread pool can be exhausted and other shards can't refresh - Execute too many refreshes for the "largest" shards With this change, we only refresh the largest shards if they are not refreshing. Here we rely on the periodic check to trigger another refresh if needed. We can harden this by making the ongoing refresh triggers the memory check when it's completed. I opted out this option in this PR for simplicity. See: https://discuss.elastic.co/t/write-queue-continue-to-rise/213652/
SivagurunathanV
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Jan 23, 2020
The test checked queue size and active count, however, ThreadPoolExecutor pulls out the request from the queue before marking the worker active, risking that we think all tasks are done when they are not. Now check on completed-tasks metric instead, which is guaranteed to be monotonic. Relates elastic#50769
This was referenced Feb 3, 2020
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Today we periodically check the indexing buffer memory every 5 seconds or after we have used 1/30 of the configured memory. If the total used memory is over the threshold, then we refresh the "largest" shards. If refreshing takes longer these intervals (i.e., 5s or 1/30 buffer), then we continue to enqueue refreshes to these shards. This leads to two issues:
With this change, we only refresh the largest shards if they are not refreshing. Here we rely on the periodic check to trigger another refresh if needed. We can harden this by making the ongoing refresh triggers the memory check when it's completed. I opted out this option in this PR for simplicity.
See: https://discuss.elastic.co/t/write-queue-continue-to-rise/213652/