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[SPARK-17477][SQL] SparkSQL cannot handle schema evolution from Int -> Long when parquet files have Int as its type while hive metastore has Long as its type #15264

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[SPARK-17477][SQL] SparkSQL cannot handle schema evolution from Int -> Long when parquet files have Int as its type while hive metastore has Long as its type #15264

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[SPARK-17477][SQL] SparkSQL cannot handle schema evolution from Int -…
wgtmac Sep 27, 2016
1f6ea81
modified comment to pass scalastyle test
wgtmac Sep 28, 2016
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15 changes: 14 additions & 1 deletion ...c/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetRowConverter.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -214,9 +214,22 @@ private[parquet] class ParquetRowConverter(
updater: ParentContainerUpdater): Converter with HasParentContainerUpdater = {

catalystType match {
case BooleanType | IntegerType | LongType | FloatType | DoubleType | BinaryType =>
case BooleanType | IntegerType | FloatType | DoubleType | BinaryType =>
new ParquetPrimitiveConverter(updater)

/**
* [SPARK-17477] When reading a hive table of parquet files with schema evolution
* from Int to Long and if hive metastore has Long as its type while parquet files
* have Int, SparkSQL need to figure out the actual type in the parquet files.
* Otherwise, it will result in java.lang.ClassCastException: [[MutableLong]] cannot
* be cast to [[MutableInt]].
*/
case LongType =>
new ParquetPrimitiveConverter(updater) {
override def addInt(value: Int): Unit =
updater.setLong(value.asInstanceOf[Long])
}

case ByteType =>
new ParquetPrimitiveConverter(updater) {
override def addInt(value: Int): Unit =
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