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Sylvain Lebresne commented on CASSANDRA-8099:
---------------------------------------------
I've just rebased and (force) pushed the current version of the patch to [the
usual branch|https://github.com/pcmanus/cassandra/tree/8099_engine_refactor].
It still doesn't handle thrift and misses backward compatibility code for the
internal messages (and I'll start working on those) but it's basically complete
otherwise. It passes all the CQL tests (unit and dtests) we have in particular.
Also seems to be passing other dtests (that don't use thrift) but I'll admit I
haven't had the patience to run them all locally and jenkins since to be in a
bad mood recently, so a couple might require attention but that's likely minor.
Also, I haven't taken the time to upgrade most of our unit tests and this will
be done next with the help of some others, but hopefully the CQL tests and
dtests exercise the code changed enough that they shouldn't be major surprises.
Overall the missing parts are sufficiently isolated that I think initial review
can be started. I've actually written
[here|https://github.com/pcmanus/cassandra/blob/8099_engine_refactor/guide_8099.md]
some kind of overview/guide for the sake of making diving into the patch
easier. I'll be happy to update it if there is something missing that would
help.
> 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
>
> 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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