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From chenghao-intel <>
Subject [GitHub] spark pull request: [SPARK-5738] [SQL] Reuse mutable row for each ...
Date Wed, 11 Feb 2015 15:31:17 GMT
Github user chenghao-intel commented on a diff in the pull request:
    --- 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(
    --- End diff --
    Move this inside of  `mapPartitions`, to reduce the closure serialization overhead. And
I didn't see any benefit when using the `SpecificMutableRow`, why not just use the `GenericMutableRow`

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