We have many small files that need combining. In Scalding you can use TextLine
to read files as text lines. The problem is we get 1 mapper per file, but we want to combine multiple files so that they are processed by 1 mapper.
I understand we need to change the input format to an implementation of CombineFileInputFormat
, and this may involve using cascadings CombinedHfs
. We cannot work out how to do this, but it should be just a handful of lines of code to define our own Scalding source called, say, CombineTextLine
.
Many thanks to anyone who can provide the code to do this.
As a side question, we have some data that is in s3, it would be great if the solution given works for s3 files - I guess it depends on whether CombineFileInputFormat
or CombinedHfs
works for s3.
You get the idea in your question, so here is what possibly is a solution for you.
Create your own input format that extends the CombineFileInputFormat and uses your own custom RecordReader. I am showing you Java code, but you could easily convert it to scala if you want.
import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.FileSplit;
import org.apache.hadoop.mapred.InputSplit;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapred.LineRecordReader;
import org.apache.hadoop.mapred.RecordReader;
import org.apache.hadoop.mapred.Reporter;
import org.apache.hadoop.mapred.lib.CombineFileInputFormat;
import org.apache.hadoop.mapred.lib.CombineFileRecordReader;
import org.apache.hadoop.mapred.lib.CombineFileSplit;
public class CombinedInputFormat<K, V> extends CombineFileInputFormat<K, V> {
public static class MyKeyValueLineRecordReader implements RecordReader<LongWritable,Text> {
private final RecordReader<LongWritable,Text> delegate;
public MyKeyValueLineRecordReader(CombineFileSplit split, Configuration conf, Reporter reporter, Integer idx) throws IOException {
FileSplit fileSplit = new FileSplit(split.getPath(idx), split.getOffset(idx), split.getLength(idx), split.getLocations());
delegate = new LineRecordReader(conf, fileSplit);
}
@Override
public boolean next(LongWritable key, Text value) throws IOException {
return delegate.next(key, value);
}
@Override
public LongWritable createKey() {
return delegate.createKey();
}
@Override
public Text createValue() {
return delegate.createValue();
}
@Override
public long getPos() throws IOException {
return delegate.getPos();
}
@Override
public void close() throws IOException {
delegate.close();
}
@Override
public float getProgress() throws IOException {
return delegate.getProgress();
}
}
@Override
public RecordReader getRecordReader(InputSplit split, JobConf job, Reporter reporter) throws IOException {
return new CombineFileRecordReader(job, (CombineFileSplit) split, reporter, (Class) MyKeyValueLineRecordReader.class);
}
}
Then you need to extend the TextLine class and make it use your own input format you just defined (Scala code from now on).
import cascading.scheme.hadoop.TextLine
import cascading.flow.FlowProcess
import org.apache.hadoop.mapred.{OutputCollector, RecordReader, JobConf}
import cascading.tap.Tap
import com.twitter.scalding.{FixedPathSource, TextLineScheme}
import cascading.scheme.Scheme
class CombineFileTextLine extends TextLine{
override def sourceConfInit(flowProcess: FlowProcess[JobConf], tap: Tap[JobConf, RecordReader[_, _], OutputCollector[_, _]], conf: JobConf) {
super.sourceConfInit(flowProcess, tap, conf)
conf.setInputFormat(classOf[CombinedInputFormat[String, String]])
}
}
Create a scheme for the for your combined input.
trait CombineFileTextLineScheme extends TextLineScheme{
override def hdfsScheme = new CombineFileTextLine().asInstanceOf[Scheme[JobConf,RecordReader[_,_],OutputCollector[_,_],_,_]]
}
Finally, create your source class:
case class CombineFileMultipleTextLine(p : String*) extends FixedPathSource(p :_*) with CombineFileTextLineScheme
If you want to use a single path instead of multiple ones, the change to your source class is trivial.
I hope that helps.
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With