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From "Benedict (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (CASSANDRA-8099) Refactor and modernize the storage engine
Date Wed, 27 May 2015 07:00:39 GMT

    [ https://issues.apache.org/jira/browse/CASSANDRA-8099?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14560526#comment-14560526
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Benedict commented on CASSANDRA-8099:
-------------------------------------

bq. I also think OpOrder.Group.close() does not belong in an iterator close.

This issue is actually much more problematic than I had realised. There are at least two places
in the code already where we explicitly hold onto the OpOrder across operations of indeterminate
length (disk IO, or peer query responses). During 2i rebuild we (I am told) also hold onto
it for the entire duration of a single partition. During a normal read request, if we time
out, as far as I can tell we don't even close the Iterator (so we already have a serious bug).

OpOrder is explicitly not designed for any of these scenarios. Even without the bug, this
can cause the entire cluster to lock up for a period because one node is down (and hasn't
yet been marked such), or for a node to lock itself up because of either low disk throughput,
or one of a rash of bugs we have had recently with tombstone bookkeeping causing heavy CPU
consumption, for instance.

As such I am now totally -1 on leaving OpOrder inside the iterator. Before 3.0 we need to
ensure that we eagerly copy any contents we require from the memtable.

> 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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