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From "Robert Stupp (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (CASSANDRA-8099) Refactor and modernize the storage engine
Date Sun, 15 Mar 2015 17:59:41 GMT

    [ https://issues.apache.org/jira/browse/CASSANDRA-8099?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14362475#comment-14362475
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Robert Stupp commented on CASSANDRA-8099:
-----------------------------------------

As you say in [the doc|https://issues.apache.org/jira/browse/CASSANDRA-8971], naming of _atom_
is really bad and should be changed IMO. Some proposals:
* -{{Cluster}} - it's like that - but _cluster_ is an occupied term-
* {{Line}} (slightly similar to _row_)
* {{Assembly}}
* or maybe just {{RawRow}}

{{NamesPartitionFilter}} - not sure whether _names_ is a good word here. Propose {{ClusteringPartitionFilter}}
or {{ClusteredPartitionFilter}}

Good idea to make {{CachePartition}} an interface!

BTW: interesting to see that the term _Doppelgänger_ is known in English ;)

> 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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