[AWS] S3 input consumes significant amount of memory #9463
Comments
bturquet
changed the title
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Hi @andrewkroh , we are investigating an issue with s3-input (direct polling) performance. We have made some tests to reproduce the memory usage behaviour here: And some examples have been shared through this SDH: We would need your help or guidance to identify the root cause and how we could fix it, thank you ! |
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How can I help? What do you need me to do? I know the SQS mode of the If it is possible to switch to SQS mode for the use-case, then I would recommend that. It's a lot simpler when AWS tells the input what to read and it is stateless (so you it scale it horizontally). |
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Hi @andrewkroh thanks for offering to help! We want help to identify if there is a memory leak in the s3 input for s3 polling mode. So far from @zmoog's perf testing, we do see an increase in memory over time but we haven't got a chance to check if this is a memory leak or it's by design. |
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My main question is how was it designed to store state. Does it keep a record of every S3 object (that would be bad) or does it use some techniques to limit state based on time? If its the latter, then what assumptions does it make (like that no older data is expected to be read)? I will try to spend some time understanding that code. |
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The state tracking in the input is complex. I didn't do any tracing in a debugger or other profiling so there may be some things I'm not understanding.
As it is reading pages of the S3 listing it is storing a state for each S3 object. When it finishes writing all of the S3 objects to ES it exchanges the individual S3 object states for a newest Then when it lists objects again, it will check if the objects are modified after that stored timestamp. If so it will read them. As far as memory usage goes, I can see where it might need a lot memory to track all of the S3 object states while it is reading and persisting. The input will be holding one When the state information is persisted to the Filebeat state store it makes a full copy of the states. This could cause a big malloc too. I think this is what was observed in this comment:
I suspect it makes a copy to avoid needing to hold a lock and block other operations while persisting the state. This might not be an ideal tradeoff to make when there is a lot state to copy. Another avenue of investigation is to check if any S3 object states are orphaned in the registry. IIUC upon successful completion of a poll loop the registry should be left only with keys like |
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Met with @andrewkroh to hand off context on this one, I'll be picking up the fix as part of my overall AWS cleanup work |
…#39131) This is a cleanup of concurrency and error handling in the `aws-s3` input that could cause several known bugs: - Memory leaks ([1](elastic/integrations#9463), [2](#39052)). This issue was caused because the input could run several scans of its s3 bucket simultaneously, which led to the cleanup routine `s3Poller.Purge` being called many times concurrently. Inefficiencies in this function caused it to accumulate over time, creating many copies of the state data which could overload process memory. Fixed by: * Changing the `s3Poller` run loop to only run one scan at a time, and wait for it to complete before starting the next one. * Having each object persist its own state after completing, instead of waiting until the end of a scan and writing an entire bucket worth of metadata at once. - This also allowed the removal of other metadata: there is no longer any reason to track the detailed acknowledgment state of each "listing" (page of ~1K events during bucket enumeration), so the `states` helper object is now much simpler. - Skipped data due to buggy last-modified calculations ([3](#39065)). The most recent scanned timestamp was calculated incorrectly, causing the input to skip a growing number of events as ingestion progressed. * Fixed by removing the bucket-wide last modified check entirely. This feature was already risky, since objects with earlier creation timestamps can appear after ones with later timestamps, so there is always the possibility to miss objects. Since the value was calculated incorrectly and was discarded between runs, we can remove it without breaking compatibility and reimplement it more safely in the future if needed. - Skipped data because rate limiting is treated as permanent failure ([4](#39114)). The input treats all error types the same, which causes many objects to be skipped for ephemeral errors. * Fixed by creating an error, `errS3DownloadFailure`, that is returned when processing failure is caused by a download error. In this case, the S3 workers will not persist the failure to the `states` table, so the object will be retried on the next bucket scan. When this happens the worker also sleeps (using an exponential backoff) before trying the next object. * Exponential backoff was also added to the bucket scanning loop for page listing errors, so the bucket scan is not restarted needlessly.
…#39131) This is a cleanup of concurrency and error handling in the `aws-s3` input that could cause several known bugs: - Memory leaks ([1](elastic/integrations#9463), [2](#39052)). This issue was caused because the input could run several scans of its s3 bucket simultaneously, which led to the cleanup routine `s3Poller.Purge` being called many times concurrently. Inefficiencies in this function caused it to accumulate over time, creating many copies of the state data which could overload process memory. Fixed by: * Changing the `s3Poller` run loop to only run one scan at a time, and wait for it to complete before starting the next one. * Having each object persist its own state after completing, instead of waiting until the end of a scan and writing an entire bucket worth of metadata at once. - This also allowed the removal of other metadata: there is no longer any reason to track the detailed acknowledgment state of each "listing" (page of ~1K events during bucket enumeration), so the `states` helper object is now much simpler. - Skipped data due to buggy last-modified calculations ([3](#39065)). The most recent scanned timestamp was calculated incorrectly, causing the input to skip a growing number of events as ingestion progressed. * Fixed by removing the bucket-wide last modified check entirely. This feature was already risky, since objects with earlier creation timestamps can appear after ones with later timestamps, so there is always the possibility to miss objects. Since the value was calculated incorrectly and was discarded between runs, we can remove it without breaking compatibility and reimplement it more safely in the future if needed. - Skipped data because rate limiting is treated as permanent failure ([4](#39114)). The input treats all error types the same, which causes many objects to be skipped for ephemeral errors. * Fixed by creating an error, `errS3DownloadFailure`, that is returned when processing failure is caused by a download error. In this case, the S3 workers will not persist the failure to the `states` table, so the object will be retried on the next bucket scan. When this happens the worker also sleeps (using an exponential backoff) before trying the next object. * Exponential backoff was also added to the bucket scanning loop for page listing errors, so the bucket scan is not restarted needlessly. (cherry picked from commit e588628) # Conflicts: # x-pack/filebeat/input/awss3/input.go
…ss in the `aws-s3` input (#39262) * Fix concurrency bugs that could cause data loss in the `aws-s3` input (#39131) This is a cleanup of concurrency and error handling in the `aws-s3` input that could cause several known bugs: - Memory leaks ([1](elastic/integrations#9463), [2](#39052)). This issue was caused because the input could run several scans of its s3 bucket simultaneously, which led to the cleanup routine `s3Poller.Purge` being called many times concurrently. Inefficiencies in this function caused it to accumulate over time, creating many copies of the state data which could overload process memory. Fixed by: * Changing the `s3Poller` run loop to only run one scan at a time, and wait for it to complete before starting the next one. * Having each object persist its own state after completing, instead of waiting until the end of a scan and writing an entire bucket worth of metadata at once. - This also allowed the removal of other metadata: there is no longer any reason to track the detailed acknowledgment state of each "listing" (page of ~1K events during bucket enumeration), so the `states` helper object is now much simpler. - Skipped data due to buggy last-modified calculations ([3](#39065)). The most recent scanned timestamp was calculated incorrectly, causing the input to skip a growing number of events as ingestion progressed. * Fixed by removing the bucket-wide last modified check entirely. This feature was already risky, since objects with earlier creation timestamps can appear after ones with later timestamps, so there is always the possibility to miss objects. Since the value was calculated incorrectly and was discarded between runs, we can remove it without breaking compatibility and reimplement it more safely in the future if needed. - Skipped data because rate limiting is treated as permanent failure ([4](#39114)). The input treats all error types the same, which causes many objects to be skipped for ephemeral errors. * Fixed by creating an error, `errS3DownloadFailure`, that is returned when processing failure is caused by a download error. In this case, the S3 workers will not persist the failure to the `states` table, so the object will be retried on the next bucket scan. When this happens the worker also sleeps (using an exponential backoff) before trying the next object. * Exponential backoff was also added to the bucket scanning loop for page listing errors, so the bucket scan is not restarted needlessly. (cherry picked from commit e588628) # Conflicts: # x-pack/filebeat/input/awss3/input.go * fix merge --------- Co-authored-by: Fae Charlton <[email protected]>
Filebeat memory usage of their Agent increases continuously until it becomes unresponsive and they restart the Agent, after which this behavior repeats. Based on the hprof data, looks like S3 integration consumes up to 10GB memory, mostly from
GetStates. Similar behavior in performance testing @zmoog did with aws-s3 input in polling mode: zmoog/public-notes#77The text was updated successfully, but these errors were encountered: