hadoop-hdfs-user mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Vinod Kumar Vavilapalli <vino...@apache.org>
Subject Re: chaining (the output of) jobs/ reducers
Date Fri, 13 Sep 2013 04:26:38 GMT

Other than the short term solutions that others have proposed, Apache Tez solves this exact
problem. It can M-M-R-R-R chains, and mult-way mappers and reducers, and your own custom processors
- all without persisting the intermediate outputs to HDFS.

It works on top of YARN, though the first release of Tez is yet to happen.

You can learn about it more here: http://tez.incubator.apache.org/

HTH,
+Vinod

On Sep 12, 2013, at 6:36 AM, Adrian CAPDEFIER wrote:

> Howdy,
> 
> My application requires 2 distinct processing steps (reducers) to be performed on the
input data. The first operation generates changes the key values and, records that had different
keys in step 1 can end up having the same key in step 2.
> 
> The heavy lifting of the operation is in step1 and step2 only combines records where
keys were changed.
> 
> In short the overview is:
> Sequential file -> Step 1 -> Step 2 -> Output.
> 
> 
> To implement this in hadoop, it seems that I need to create a separate job for each step.

> 
> Now I assumed, there would some sort of job management under hadoop to link Job 1 and
2, but the only thing I could find was related to job scheduling and nothing on how to synchronize
the input/output of the linked jobs.
> 
> 
> 
> The only crude solution that I can think of is to use a temporary file under HDFS, but
even so I'm not sure if this will work.
> 
> The overview of the process would be:
> Sequential Input (lines) => Job A[Mapper (key1, value1) => ChainReducer (key2,
value2)] => Temporary file => Job B[Mapper (key2, value2) => Reducer (key2, value
3)] => output.
> 
> Is there a better way to pass the output from Job A as input to Job B (e.g. using network
streams or some built in java classes that don't do disk i/o)? 
> 
> 
> 
> The temporary file solution will work in a single node configuration, but I'm not sure
about an MPP config.
> 
> Let's say Job A runs on nodes 0 and 1 and job B runs on nodes 2 and 3 or both jobs run
on all 4 nodes - will HDFS be able to redistribute automagically the records between nodes
or does this need to be coded somehow? 


-- 
CONFIDENTIALITY NOTICE
NOTICE: This message is intended for the use of the individual or entity to 
which it is addressed and may contain information that is confidential, 
privileged and exempt from disclosure under applicable law. If the reader 
of this message is not the intended recipient, you are hereby notified that 
any printing, copying, dissemination, distribution, disclosure or 
forwarding of this communication is strictly prohibited. If you have 
received this communication in error, please contact the sender immediately 
and delete it from your system. Thank You.

Mime
View raw message