[jira] [Created] (SPARK-6748) QueryPlan.schema should be a lazy val to avoid creating excessive duplicate StructType objects

["Cheng Lian (JIRA)" <ji...@apache.org>]

Cheng Lian created SPARK-6748:
---------------------------------

             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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