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From David Ortiz <>
Subject Re: Non Deterministic Record Drops
Date Tue, 28 Jul 2015 00:29:40 GMT
Out of curiosity, any reason you went with multiple reads as opposed to
just performing multiple operations on the same PTable? parallelDo returns
a new object rather than modifying the initial one, so a single collection
can start multiple execution flows.

On Mon, Jul 27, 2015, 8:11 PM Jeff Quinn <> wrote:

> Hello,
> We have observed and replicated strange behavior with our crunch
> application while running on MapReduce via the AWS ElasticMapReduce
> service. Running a very simple job which is mostly map only, we see that an
> undetermined subset of records are getting dropped. Specifically, we
> expect 30,136,686 output records and have seen output on different trials
> (running over the same data with the same binary):
> 22,177,119 records
> 26,435,670 records
> 22,362,986 records
> 29,798,528 records
> These are all the things about our application which might be unusual and
> relevant:
> - We use a custom file input format, via From.formattedFile. It looks like
> this (basically a carbon copy
> of org.apache.hadoop.mapreduce.lib.input.TextInputFormat):
> import;
> import;
> import org.apache.hadoop.mapreduce.InputSplit;
> import org.apache.hadoop.mapreduce.RecordReader;
> import org.apache.hadoop.mapreduce.TaskAttemptContext;
> import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
> import org.apache.hadoop.mapreduce.lib.input.LineRecordReader;
> import;
> public class ByteOffsetInputFormat extends FileInputFormat<LongWritable, Text>
>   @Override
>   public RecordReader<LongWritable, Text> createRecordReader(
>       InputSplit split, TaskAttemptContext context) throws IOException,
>       InterruptedException {
>     return new LineRecordReader();
>   }
> }
> - We call org.apache.crunch.Pipeline#read using this InputFormat many times, for the
job in question it is called ~160 times as the input is ~100 different files. Each file ranges
in size from 100MB-8GB. Our job only uses this input format for all input files.
> - For some files org.apache.crunch.Pipeline#read is called twice one the same file, and
the resulting PTables are processed in different ways.
> - It is only the data from these files which org.apache.crunch.Pipeline#read has been
called on more than once during a job that have dropped records, all other files consistently
do not have dropped records
> Curious if any Crunch users have experienced similar behavior before, or if any of these
details about my job raise any red flags.
> Thanks!
> Jeff Quinn
> Data Engineer
> Nuna
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