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https://issues.apache.org/jira/browse/CASSANDRA-2843?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13068830#comment-13068830
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Yang Yang commented on CASSANDRA-2843:
--------------------------------------
Brandon:
I used commit 4629648899e637e8e03938935f126689cce5ad48 and applied the
2843_c.patch, and also tried the head, but got the following error with the
benchmark pycassa script. how did you succeed with it?
[default@query] create column family NoCache
... with comparator = AsciiType
... and default_validation_class = AsciiType
... and key_validation_class = AsciiType
... and keys_cached = 0
... and rows_cached = 0;
Unable to set Compaction Strategy Class of AsciiType
thanks
Yang
> better performance on long row read
> -----------------------------------
>
> Key: CASSANDRA-2843
> URL: https://issues.apache.org/jira/browse/CASSANDRA-2843
> Project: Cassandra
> Issue Type: New Feature
> Reporter: Yang Yang
> Attachments: 2843.patch, 2843_c.patch, fast_cf_081_trunk.diff,
> incremental.diff, microBenchmark.patch
>
>
> currently if a row contains > 1000 columns, the run time becomes considerably
> slow (my test of
> a row with 30 00 columns (standard, regular) each with 8 bytes in name, and
> 40 bytes in value, is about 16ms.
> this is all running in memory, no disk read is involved.
> through debugging we can find
> most of this time is spent on
> [Wall Time] org.apache.cassandra.db.Table.getRow(QueryFilter)
> [Wall Time]
> org.apache.cassandra.db.ColumnFamilyStore.getColumnFamily(QueryFilter,
> ColumnFamily)
> [Wall Time]
> org.apache.cassandra.db.ColumnFamilyStore.getColumnFamily(QueryFilter, int,
> ColumnFamily)
> [Wall Time]
> org.apache.cassandra.db.ColumnFamilyStore.getTopLevelColumns(QueryFilter,
> int, ColumnFamily)
> [Wall Time]
> org.apache.cassandra.db.filter.QueryFilter.collectCollatedColumns(ColumnFamily,
> Iterator, int)
> [Wall Time]
> org.apache.cassandra.db.filter.SliceQueryFilter.collectReducedColumns(IColumnContainer,
> Iterator, int)
> [Wall Time] org.apache.cassandra.db.ColumnFamily.addColumn(IColumn)
> ColumnFamily.addColumn() is slow because it inserts into an internal
> concurrentSkipListMap() that maps column names to values.
> this structure is slow for two reasons: it needs to do synchronization; it
> needs to maintain a more complex structure of map.
> but if we look at the whole read path, thrift already defines the read output
> to be List<ColumnOrSuperColumn> so it does not make sense to use a luxury map
> data structure in the interium and finally convert it to a list. on the
> synchronization side, since the return CF is never going to be
> shared/modified by other threads, we know the access is always single thread,
> so no synchronization is needed.
> but these 2 features are indeed needed for ColumnFamily in other cases,
> particularly write. so we can provide a different ColumnFamily to
> CFS.getTopLevelColumnFamily(), so getTopLevelColumnFamily no longer always
> creates the standard ColumnFamily, but take a provided returnCF, whose cost
> is much cheaper.
> the provided patch is for demonstration now, will work further once we agree
> on the general direction.
> CFS, ColumnFamily, and Table are changed; a new FastColumnFamily is
> provided. the main work is to let the FastColumnFamily use an array for
> internal storage. at first I used binary search to insert new columns in
> addColumn(), but later I found that even this is not necessary, since all
> calling scenarios of ColumnFamily.addColumn() has an invariant that the
> inserted columns come in sorted order (I still have an issue to resolve
> descending or ascending now, but ascending works). so the current logic is
> simply to compare the new column against the end column in the array, if
> names not equal, append, if equal, reconcile.
> slight temporary hacks are made on getTopLevelColumnFamily so we have 2
> flavors of the method, one accepting a returnCF. but we could definitely
> think about what is the better way to provide this returnCF.
> this patch compiles fine, no tests are provided yet. but I tested it in my
> application, and the performance improvement is dramatic: it offers about 50%
> reduction in read time in the 3000-column case.
> thanks
> Yang
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