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Merge str value in Hadoop Reducer


Merge str value in Hadoop Reducer

By : Deborah Williams
Date : November 21 2020, 03:00 PM
this will help I tested this code an it looks ok. The most likely reason you're getting output like this is because you're running this reducer as your combiner as well, which would explain why you're getting three values. The combine does the first concatenation, followed by the reduce which does a second.
You need to make sure a combiner isn't being configured in your job setup.
code :


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Hadoop: How can i merge reducer outputs to a single file?

Hadoop: How can i merge reducer outputs to a single file?


By : RDimitrov
Date : March 29 2020, 07:55 AM
To fix the issue you can do
But what should I do if I want to merge these outputs after the job by HDFS API for java?
Why cannot Reducer.class used as a real reducer in Hadoop MapReduce?

Why cannot Reducer.class used as a real reducer in Hadoop MapReduce?


By : Ajay Thakur
Date : March 29 2020, 07:55 AM
should help you out I don't see why it wouldn't as long as the outputs are of the same class as the inputs. The default in the new API just writes out whatever you pass into it, it's implemented as
code :
@SuppressWarnings("unchecked")
protected void reduce(KEYIN key, Iterable<VALUEIN> values, Context context
                       ) throws IOException, InterruptedException {
    for(VALUEIN value: values) {
      context.write((KEYOUT) key, (VALUEOUT) value);
    }
}
hadoop reducer output was read in reducer iteratively

hadoop reducer output was read in reducer iteratively


By : Victor Véliz
Date : March 29 2020, 07:55 AM
will help you Comment out conf.setCombinerClass(Reduce.class); and it should be OK. This is happening because you are using your Reducer as your Combiner as well.
When a combiner is available, the output of the map() is fed to the combine() first. The output of the combine() function is then sent over to the reduce() function on a reducer machine. So the actual input to your reduce() already has 1 Key in Reducer included in it, which gets doubled after passing through the reduce(). That's why you are getting Key in Reducer twice.
Increasing Reducer Count above 1 on a Single Node Hadoop cluster cases serial reducer execution

Increasing Reducer Count above 1 on a Single Node Hadoop cluster cases serial reducer execution


By : JubiantRich
Date : March 29 2020, 07:55 AM
I wish this help you I'm testing some Capacity Schedule settings on a single node HDP 1.3.2 instance before pushing it to a cluster. I am aware that the default number of reducers is 1 for an MR job unless you override it, and I thought there might be some peculiarities working with a single node cluster in respect of reducers too - which might be causing this problem. , Okay the solution was to increase mapred.cluster.reduce.memory.mb
code :
mapred.cluster.reduce.memory.mb=768MB #allowed 2 reducers to run at once
mapred.cluster.reduce.memory.mb=1536MB #allowed all 4 reducers to run at once.
mapred.job.reduce.memory.mb = mapred.cluster.reduce.memory.mb
Hadoop - Merge reducer outputs to a single file using Java

Hadoop - Merge reducer outputs to a single file using Java


By : user3525845
Date : March 29 2020, 07:55 AM
will help you you can use getmerge through shell command to merge multiple file into single file.
code :
Usage: hdfs dfs -getmerge <srcdir> <destinationdir/file.txt>

Example: hdfs dfs -getmerge /output/dir/on/hdfs/ /desired/local/output/file.txt
--Assigning only one reducer in order to generate only one output file.
SET default_parallel 1;
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