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From java8964 java8964 <>
Subject RE: map/reduce performance time and sstable readerŠ.
Date Tue, 03 Sep 2013 18:06:20 GMT
I am trying to do the same thing, as in our project, we want to load the data from Cassandra
into Hadoop cluster, and SSTable is one obvious option, as you can get the changed data since
last batch loading directly from the SSTable incremental backup files.
But, based on so far my research (I maybe wrong, as I just did limited research about the
SSTable, I hope someone in this forum can tell me that I am wrong), it maybe is NOT a good
1) sstable2json looks like NOT a scalable solution to get the data out from the Cassandra,
and it needs the access to "data" directory to get some meta data from system keyspace for
the column family data dumped, which maybe is not an option in your MR environment.2) So far
I am thinking reuse the same API as being used in the sstable2json, but I have to provide
these metadata in the API, like validator types/partitioner etc. I am surprised that as a
backup, the column family SSTable dump files DOESN't contain these information by itself.
Shouldn't it find out this from the SSTable files(ONLY) by itself?3) The big trouble comes
this if you want to parse the SSTables in  your MR code. The API internal will load the Index/Compression_Info
information from the Index/Compression files, which it assumes located in the same place 
as the data file, but it will use the FileSteam internal. So if these data files are in the
DFS (Distributed File System), so far, I didn't find a way to tell the API to use the stream
from the DFS, instead of Local File Input stream. So basically you have 2 options: a) Copy
these files from DSF to local file system (Same as what Knewton guys did at
b) Develop your own API to access the SStable files directly ( My guess is that Netflix guys
probably did this way. They have a project called "Aegisthus" (See here:,
but it is not open source.4) About the performance, I am not sure, as SSTable2Json underline
is using the same Cassandra API, but running in MR give us some support in scalability, as
we can reuse the Hadoop framework for a lot of benefits it can bring.

> From:
> To:
> Date: Fri, 30 Aug 2013 07:25:09 -0600
> Subject: map/reduce performance time and sstable readerŠ.
> Has anyone done performance tests on sstable reading vs. M/R?  I did a quick test on
reading all SSTAbles in a LCS column family on 23 tables and took the average time it took
sstable2json(to /dev/null to make it faster) which was 7 seconds per table.  (reading to stdout
took 16 seconds per table).  This then worked out to an estimation of 12.5 hours up to 27
hours(from to stdout calculation).  I am suspecting the map/reduce time may be much worse
since there are not as many repeated rows in LCS????
> Ie. I am wondering if I should just read from SSTAbles directly instead of map/reduce?
  I am about to dig around in the code of M/R and sstable2json to see what each is doing specifically.
> Thanks,
> Dean
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