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https://issues.apache.org/jira/browse/CASSANDRA-8099?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14593271#comment-14593271
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Branimir Lambov commented on CASSANDRA-8099:
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Thinking about this a bit more, I see that this is very difficult to fix. When
the reducer issues a pair one of the markers is out of its place in the stream,
thus we would need to delay the stream to be able to place it correctly. This
would have a non-trivial performance impact.
Instead, I think we should officially permit this kind of disorder (e.g.
{{<39\[71\] 39<=\[7\] <39\[7\] 39<=\[8\]}} from above where {{39<=\[7\]
<39\[7\]}} is invalid and covered by the outer pair of markers) in the
unfiltered stream and remove the invalid ranges in the compaction writer. The
merge algorithm is able to deal with such ranges correctly and filtering just
removes them. We have to document it well and make sure the relevant code is
tested with examples of this.
Even without removal in the compaction writer, the only kind of trouble I can
see such a range introducing is seeking to the wrong marker in a binary /
indexed search, but this should be ok as the correct marker is certain to
follow before any live data.
> Refactor and modernize the storage engine
> -----------------------------------------
>
> Key: CASSANDRA-8099
> URL: https://issues.apache.org/jira/browse/CASSANDRA-8099
> Project: Cassandra
> Issue Type: Improvement
> Reporter: Sylvain Lebresne
> Assignee: Sylvain Lebresne
> Fix For: 3.0 beta 1
>
> Attachments: 8099-nit
>
>
> The current storage engine (which for this ticket I'll loosely define as "the
> code implementing the read/write path") is suffering from old age. One of the
> main problem is that the only structure it deals with is the cell, which
> completely ignores the more high level CQL structure that groups cell into
> (CQL) rows.
> This leads to many inefficiencies, like the fact that during a reads we have
> to group cells multiple times (to count on replica, then to count on the
> coordinator, then to produce the CQL resultset) because we forget about the
> grouping right away each time (so lots of useless cell names comparisons in
> particular). But outside inefficiencies, having to manually recreate the CQL
> structure every time we need it for something is hindering new features and
> makes the code more complex that it should be.
> Said storage engine also has tons of technical debt. To pick an example, the
> fact that during range queries we update {{SliceQueryFilter.count}} is pretty
> hacky and error prone. Or the overly complex ways {{AbstractQueryPager}} has
> to go into to simply "remove the last query result".
> So I want to bite the bullet and modernize this storage engine. I propose to
> do 2 main things:
> # Make the storage engine more aware of the CQL structure. In practice,
> instead of having partitions be a simple iterable map of cells, it should be
> an iterable list of row (each being itself composed of per-column cells,
> though obviously not exactly the same kind of cell we have today).
> # Make the engine more iterative. What I mean here is that in the read path,
> we end up reading all cells in memory (we put them in a ColumnFamily object),
> but there is really no reason to. If instead we were working with iterators
> all the way through, we could get to a point where we're basically
> transferring data from disk to the network, and we should be able to reduce
> GC substantially.
> Please note that such refactor should provide some performance improvements
> right off the bat but it's not it's primary goal either. It's primary goal is
> to simplify the storage engine and adds abstraction that are better suited to
> further optimizations.
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