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From "Jonathan Ellis (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (CASSANDRA-2864) Alternative Row Cache Implementation
Date Thu, 10 May 2012 16:18:53 GMT

    [ https://issues.apache.org/jira/browse/CASSANDRA-2864?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13272453#comment-13272453
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Jonathan Ellis commented on CASSANDRA-2864:
-------------------------------------------

This is going to be an entirely different code path though, not just a new CacheProvider.
 (So we'd still have SCP and CLHCP, but they'd both use this new design.)  I'd like to drop
the old code path entirely instead of leaving both around, if we can make that work.
                
> Alternative Row Cache Implementation
> ------------------------------------
>
>                 Key: CASSANDRA-2864
>                 URL: https://issues.apache.org/jira/browse/CASSANDRA-2864
>             Project: Cassandra
>          Issue Type: Improvement
>          Components: Core
>            Reporter: Daniel Doubleday
>            Assignee: Daniel Doubleday
>              Labels: cache
>             Fix For: 1.2
>
>
> we have been working on an alternative implementation to the existing row cache(s)
> We have 2 main goals:
> - Decrease memory -> get more rows in the cache without suffering a huge performance
penalty
> - Reduce gc pressure
> This sounds a lot like we should be using the new serializing cache in 0.8. 
> Unfortunately our workload consists of loads of updates which would invalidate the cache
all the time.
> *Note: Updated Patch Description (Please check history if you're interested where this
was comming from)*
> h3. Rough Idea
> - Keep serialized row (ByteBuffer) in mem which represents unfiltered but collated columns
of all ssts but not memtable columns
> - Writes dont affect the cache at all. They go only to the memtables
> - Reads collect columns from memtables and row cache
> - Serialized Row is re-written (merged) with mem tables when flushed
> h3. Some Implementation Details
> h4. Reads
> - Basically the read logic differ from regular uncached reads only in that a special
CollationController which is deserializing columns from in memory bytes
> - In the first version of this cache the serialized in memory format was the same as
the fs format but test showed that performance sufferd because a lot of unnecessary deserialization
takes place and that columns seeks are O( n ) whithin one block
> - To improve on that a different in memory format was used. It splits length meta info
and data of columns so that the names can be binary searched. 
> {noformat}
> ===========================
> Header (24)                    
> ===========================
> MaxTimestamp:        long  
> LocalDeletionTime:   int   
> MarkedForDeleteAt:   long  
> NumColumns:          int   
> ===========================
> Column Index (num cols * 12)              
> ===========================
> NameOffset:          int   
> ValueOffset:         int   
> ValueLength:         int   
> ===========================
> Column Data                
> ===========================
> Name:                byte[]
> Value:               byte[]
> SerializationFlags:  byte  
> Misc:                ?     
> Timestamp:           long  
> ---------------------------
> Misc Counter Column        
> ---------------------------
> TSOfLastDelete:      long  
> ---------------------------
> Misc Expiring Column       
> ---------------------------
> TimeToLive:          int   
> LocalDeletionTime:   int   
> ===========================
> {noformat}
> - These rows are read by 2 new column interators which correspond to SSTableNamesIterator
and SSTableSliceIterator. During filtering only columns that actually match are constructed.
The searching / skipping is performed on the raw ByteBuffer and does not create any objects.
> - A special CollationController is used to access and collate via cache and said new
iterators. It also supports skipping the cached row by max update timestamp
> h4. Writes
> - Writes dont update or invalidate the cache.
> - In CFS.replaceFlushed memtables are merged before the data view is switched. I fear
that this is killing counters because they would be overcounted but my understading of counters
is somewhere between weak and non-existing. I guess that counters if one wants to support
them here would need an additional unique local identifier in memory and in serialized cache
to be able to filter duplicates or something like that.
> {noformat}
>     void replaceFlushed(Memtable memtable, SSTableReader sstable)
>     {
>         if (sstCache.getCapacity() > 0) {
>             mergeSSTCache(memtable);
>         }
>         data.replaceFlushed(memtable, sstable);
>         CompactionManager.instance.submitBackground(this);
>     }
> {noformat}
> Test Results: See comments below

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