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Stan Rosenberg commented on CRUNCH-597:
---------------------------------------
The code executes without error after upgrading crunch to use parquet 1.8.1. (See https://github.com/srosenberg/crunch/commit/d78e1793d0313b073264aa607bfebd610bd8c0dd)
Upon some investigation, it appears that the bug was fixed in a later version of parquet-hadoop.
The version used by crunch expects the input split to be of type ParquetInputSplit in ParquetRecordReader.initialize,
{code}
public void initialize(InputSplit inputSplit, TaskAttemptContext context) throws IOException,
InterruptedException {
if(context instanceof TaskInputOutputContext) {
BenchmarkCounter.initCounterFromContext((TaskInputOutputContext)context);
} else {
LOG.error("Can not initialize counter due to context is not a instance of TaskInputOutputContext,
but is " + context.getClass().getCanonicalName());
}
this.initializeInternalReader((ParquetInputSplit)inputSplit, ContextUtil.getConfiguration(context));
}
{code}
whereas the latest implementation converts between FileSplit and ParquetInputSplit,
{code}
public void initialize(InputSplit inputSplit, Configuration configuration, Reporter reporter)
throws IOException, InterruptedException {
BenchmarkCounter.initCounterFromReporter(reporter,configuration);
initializeInternalReader(toParquetSplit(inputSplit), configuration);
}
{code}
> Unable to process parquet files using Hadoop
> --------------------------------------------
>
> Key: CRUNCH-597
> URL: https://issues.apache.org/jira/browse/CRUNCH-597
> Project: Crunch
> Issue Type: Bug
> Components: Core, IO
> Affects Versions: 0.13.0
> Reporter: Stan Rosenberg
> Assignee: Josh Wills
>
> Current version of parquet-hadoop results in the following stack trace while attempting
to read from parquet file.
> {code}
> java.lang.Exception: java.lang.ClassCastException: org.apache.hadoop.mapreduce.lib.input.FileSplit
cannot be cast to parquet.hadoop.ParquetInputSplit
> at org.apache.hadoop.mapred.LocalJobRunner$Job.run(LocalJobRunner.java:406)
> Caused by: java.lang.ClassCastException: org.apache.hadoop.mapreduce.lib.input.FileSplit
cannot be cast to parquet.hadoop.ParquetInputSplit
> at parquet.hadoop.ParquetRecordReader.initialize(ParquetRecordReader.java:107)
> at org.apache.crunch.impl.mr.run.CrunchRecordReader.initialize(CrunchRecordReader.java:140)
> at org.apache.hadoop.mapred.MapTask$NewTrackingRecordReader.initialize(MapTask.java:478)
> at org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:671)
> at org.apache.hadoop.mapred.MapTask.run(MapTask.java:330)
> at org.apache.hadoop.mapred.LocalJobRunner$Job$MapTaskRunnable.run(LocalJobRunner.java:268)
> at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471)
> at java.util.concurrent.FutureTask.run(FutureTask.java:262)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> at java.lang.Thread.run(Thread.java:745)
> {code}
> Here is the relevant code snippet which yields the above stack trace when executed locally,
> {code}
> Pipeline pipeline = new MRPipeline(Crunch.class, conf);
> PCollection<Pair<String, Observation>> observations =
> pipeline.read(AvroParquetFileSource.builder(record).build(new Path(args[0])))
> .parallelDo(new TranslateFn(), Avros.tableOf(Avros.strings(),
Avros.specifics(Observation.class)));
> for (Pair<String, Observation> pair : observations.materialize()) {
> System.out.println(pair.second());
> }
> PipelineResult result = pipeline.done();
> {code}
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