Joseph K. Bradley created SPARK-6120:
----------------------------------------
Summary: DecisionTree.save uses too much Java heap space for
default spark shell settings
Key: SPARK-6120
URL: https://issues.apache.org/jira/browse/SPARK-6120
Project: Spark
Issue Type: Bug
Components: MLlib
Affects Versions: 1.3.0
Reporter: Joseph K. Bradley
When the Python DecisionTree example in the programming guide is run, it runs
out of Java Heap Space:
{code}
scala> model.save(sc, "myModelPath")
[Stage 12:>
(0 + 8) /
8]15/03/02 14:19:16 ERROR Executor: Exception in task 1.0 in stage 12.0 (TID 22)
java.lang.OutOfMemoryError: Java heap space
at
parquet.bytes.CapacityByteArrayOutputStream.initSlabs(CapacityByteArrayOutputStream.java:65)
at
parquet.bytes.CapacityByteArrayOutputStream.<init>(CapacityByteArrayOutputStream.java:57)
at
parquet.column.values.plain.PlainValuesWriter.<init>(PlainValuesWriter.java:45)
at
parquet.column.values.dictionary.DictionaryValuesWriter.<init>(DictionaryValuesWriter.java:102)
at
parquet.column.values.dictionary.DictionaryValuesWriter$PlainDoubleDictionaryValuesWriter.<init>(DictionaryValuesWriter.java:471)
at
parquet.column.ParquetProperties.getValuesWriter(ParquetProperties.java:111)
at parquet.column.impl.ColumnWriterImpl.<init>(ColumnWriterImpl.java:74)
at
parquet.column.impl.ColumnWriteStoreImpl.newMemColumn(ColumnWriteStoreImpl.java:68)
at
parquet.column.impl.ColumnWriteStoreImpl.getColumnWriter(ColumnWriteStoreImpl.java:56)
at
parquet.io.MessageColumnIO$MessageColumnIORecordConsumer.<init>(MessageColumnIO.java:178)
at parquet.io.MessageColumnIO.getRecordWriter(MessageColumnIO.java:369)
at
parquet.hadoop.InternalParquetRecordWriter.initStore(InternalParquetRecordWriter.java:108)
at
parquet.hadoop.InternalParquetRecordWriter.<init>(InternalParquetRecordWriter.java:94)
at
parquet.hadoop.ParquetRecordWriter.<init>(ParquetRecordWriter.java:64)
at
parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:282)
at
parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:252)
at
org.apache.spark.sql.parquet.ParquetRelation2.org$apache$spark$sql$parquet$ParquetRelation2$$writeShard$1(newParquet.scala:620)
at
org.apache.spark.sql.parquet.ParquetRelation2$$anonfun$insert$2.apply(newParquet.scala:641)
at
org.apache.spark.sql.parquet.ParquetRelation2$$anonfun$insert$2.apply(newParquet.scala:641)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
at org.apache.spark.scheduler.Task.run(Task.scala:64)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:197)
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}
When saving using JSON format instead of Parquet, this works. It seems to be
caused by Parquet requiring a lot of metadata to describe the schema.
I'm labeling this a bug since it should succeed with the default spark-shell
settings. Potential fixes are:
* increasing spark-shell default heap space settings (This is probably too hard
to agree on currently.)
* not using Parquet for storage (This would be good for small examples but
probably worse for large models, where Parquet would be more efficient than
other formats.)
* compressing the schema (The various values in the DecisionTree model could be
flattened into a single Seq of Double. This may be the best option for now.)
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