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From chenghao-intel <...@git.apache.org>
Subject [GitHub] spark pull request: [SPARK-5738] [SQL] Reuse mutable row for each ...
Date Wed, 11 Feb 2015 15:35:36 GMT
Github user chenghao-intel commented on a diff in the pull request:

    https://github.com/apache/spark/pull/4527#discussion_r24503655
  
    --- Diff: sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala ---
    @@ -39,7 +39,19 @@ private[sql] object JsonRDD extends Logging {
           json: RDD[String],
           schema: StructType,
           columnNameOfCorruptRecords: String): RDD[Row] = {
    -    parseJson(json, columnNameOfCorruptRecords).map(parsed => asRow(parsed, schema))
    +    // Reuse the mutable row for each record, however we still need to 
    +    // create a new row for every nested struct type in each record
    +    val mutableRow = new SpecificMutableRow(schema.fields.map(_.dataType))
    +    parseJson(json, columnNameOfCorruptRecords).mapPartitions( iter => {
    +      iter.map { parsed =>
    +        schema.fields.zipWithIndex.foreach {
    --- End diff --
    
    This is duplicated with the function `asRow`, can we add additional parameter for `asRow`,
says
    ```
    def asRow(json: Map[String,Any], schema: StructType, mutable: GenericMutableRow = null):
Row = {
      row = if (mutable == null) {
         new GenericMutableRow(schema.fields.length)
      } else {
        mutable
      }
    }
    ```


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