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From "Hiller, Dean" <>
Subject Re: map/reduce performance time and sstable readerŠ.
Date Tue, 03 Sep 2013 18:23:37 GMT
We are considering creating our own InputFormat for hadoop and running the tasktrackers on
every 3rd node(ie. RF=3) such that we cover all ranges.  Our M/R overhead appears to be 13
days vs. 12.5 hours on just reading SSTAbles directly on our current data set.

I personally don't think parsing SSTables(using the hadoop M/R framework) is a big deal from
us since we run task trackers on the cassandra nodes we need it on.  Ie. We don't need to
copy to DFS to do this I believe(at least not in our situation).

I already wrote a client on the SSTableReader parsing out sstables to take a look at some
of our data while our 13 day M/R job is running(we are 4 days in already with no failures
and no performance degradation).


From: java8964 java8964 <<>>
Reply-To: "<>" <<>>
Date: Tuesday, September 3, 2013 12:06 PM
To: "<>" <<>>
Subject: RE: map/reduce performance time and sstable readerŠ.

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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