Cheng Lian created SPARK-6748:
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Summary: QueryPlan.schema should be a lazy val to avoid creating
excessive duplicate StructType objects
Key: SPARK-6748
URL: https://issues.apache.org/jira/browse/SPARK-6748
Project: Spark
Issue Type: Bug
Affects Versions: 1.3.0
Reporter: Cheng Lian
Spotted this issue while trying to do a simple micro benchmark:
{code}
sc.parallelize(1 to 10000000).
map(i => (i, s"val_$i")).
toDF("key", "value").
saveAsParquetFile("file:///tmp/src.parquet")
sqlContext.parquetFile("file:///tmp/src.parquet").collect()
{code}
YJP profiling result showed that, *10 million {{StructType}}, 10 million
{{StructField \[\]}}, and 20 million {{StructField}} were allocated*.
It turned out that {{DataFrame.collect()}} calls
{{SparkPlan.executeCollect()}}, which consists of a single line:
{code}
execute().map(ScalaReflection.convertRowToScala(_, schema)).collect()
{code}
The problem is that, {{QueryPlan.schema}} is a function, and since 1.3.0,
{{convertRowToScala}} starts returning a {{GenericRowWithSchema}}. These two
facts result in 10 million rows, each with a separate schema object.
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