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 option:
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 https://github.com/Knewton/KassandraMRHelper)
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:
http://techblog.netflix.com/2012/02/aegisthus-bulk-data-pipeline-out-of.html),
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.
Yong
> From: dean.hil...@nrel.gov
> To: user@cassandra.apache.org
> 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
