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https://issues.apache.org/jira/browse/CASSANDRA-15907?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17160018#comment-17160018
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Caleb Rackliffe commented on CASSANDRA-15907:
---------------------------------------------
[~adelapena] and I had a quick Slack discussion, and I think we've landed on
the following:
1.) For now, we'll stop at a partition-based lazy first-phase iterator
consumption approach (what's in the main patch branch right now). It's not
clear that a {{min_cache_size}} (that avoid creating tons of "singleton"
{{CachedRowIterator}} instances) would produce something meaningfully different.
2.) In the interest of visibility, we'll explore adding a histogram that
quantifies just how much row caching these queries are doing. It would put some
data behind our assumptions here and might help with tuning the guardrails as
well. (I'll try to have something up for this shortly...)
> Operational Improvements & Hardening for Replica Filtering Protection
> ---------------------------------------------------------------------
>
> Key: CASSANDRA-15907
> URL: https://issues.apache.org/jira/browse/CASSANDRA-15907
> Project: Cassandra
> Issue Type: Improvement
> Components: Consistency/Coordination, Feature/2i Index
> Reporter: Caleb Rackliffe
> Assignee: Caleb Rackliffe
> Priority: Normal
> Labels: 2i, memory
> Fix For: 3.0.x, 3.11.x, 4.0-beta
>
> Time Spent: 4h 20m
> Remaining Estimate: 0h
>
> CASSANDRA-8272 uses additional space on the heap to ensure correctness for 2i
> and filtering queries at consistency levels above ONE/LOCAL_ONE. There are a
> few things we should follow up on, however, to make life a bit easier for
> operators and generally de-risk usage:
> (Note: Line numbers are based on {{trunk}} as of
> {{3cfe3c9f0dcf8ca8b25ad111800a21725bf152cb}}.)
> *Minor Optimizations*
> * {{ReplicaFilteringProtection:114}} - Given we size them up-front, we may be
> able to use simple arrays instead of lists for {{rowsToFetch}} and
> {{originalPartitions}}. Alternatively (or also), we may be able to null out
> references in these two collections more aggressively. (ex. Using
> {{ArrayList#set()}} instead of {{get()}} in {{queryProtectedPartitions()}},
> assuming we pass {{toFetch}} as an argument to {{querySourceOnKey()}}.)
> * {{ReplicaFilteringProtection:323}} - We may be able to use
> {{EncodingStats.merge()}} and remove the custom {{stats()}} method.
> * {{DataResolver:111 & 228}} - Cache an instance of
> {{UnaryOperator#identity()}} instead of creating one on the fly.
> * {{ReplicaFilteringProtection:217}} - We may be able to scatter/gather
> rather than serially querying every row that needs to be completed. This
> isn't a clear win perhaps, given it targets the latency of single queries and
> adds some complexity. (Certainly a decent candidate to kick even out of this
> issue.)
> *Documentation and Intelligibility*
> * There are a few places (CHANGES.txt, tracing output in
> {{ReplicaFilteringProtection}}, etc.) where we mention "replica-side
> filtering protection" (which makes it seem like the coordinator doesn't
> filter) rather than "replica filtering protection" (which sounds more like
> what we actually do, which is protect ourselves against incorrect replica
> filtering results). It's a minor fix, but would avoid confusion.
> * The method call chain in {{DataResolver}} might be a bit simpler if we put
> the {{repairedDataTracker}} in {{ResolveContext}}.
> *Testing*
> * I want to bite the bullet and get some basic tests for RFP (including any
> guardrails we might add here) onto the in-JVM dtest framework.
> *Guardrails*
> * As it stands, we don't have a way to enforce an upper bound on the memory
> usage of {{ReplicaFilteringProtection}} which caches row responses from the
> first round of requests. (Remember, these are later used to merged with the
> second round of results to complete the data for filtering.) Operators will
> likely need a way to protect themselves, i.e. simply fail queries if they hit
> a particular threshold rather than GC nodes into oblivion. (Having control
> over limits and page sizes doesn't quite get us there, because stale results
> _expand_ the number of incomplete results we must cache.) The fun question is
> how we do this, with the primary axes being scope (per-query, global, etc.)
> and granularity (per-partition, per-row, per-cell, actual heap usage, etc.).
> My starting disposition on the right trade-off between
> performance/complexity and accuracy is having something along the lines of
> cached rows per query. Prior art suggests this probably makes sense alongside
> things like {{tombstone_failure_threshold}} in {{cassandra.yaml}}.
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