[GitHub] [spark] beliefer commented on a change in pull request #34495: [SPARK-36182][SQL] Support TimestampNTZ type in Parquet data source

[GitBox <gi...@apache.org>]

beliefer commented on a change in pull request #34495:
URL: https://github.com/apache/spark/pull/34495#discussion_r744243576



##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetRowConverter.scala
##########
@@ -370,6 +370,31 @@ private[parquet] class ParquetRowConverter(
           }
         }
 
+      // The converter doesn't support the TimestampLTZ Parquet type and TimestampNTZ Catalyst type.
+      // This is to avoid mistakes in reading the timestamp values.
+      case TimestampNTZType
+        if parquetType.asPrimitiveType().getPrimitiveTypeName == INT64 &&
+          parquetType.getLogicalTypeAnnotation.isInstanceOf[TimestampLogicalTypeAnnotation] &&
+          !parquetType.getLogicalTypeAnnotation
+            .asInstanceOf[TimestampLogicalTypeAnnotation].isAdjustedToUTC &&
+          parquetType.getLogicalTypeAnnotation
+            .asInstanceOf[TimestampLogicalTypeAnnotation].getUnit == TimeUnit.MICROS =>
+        new ParquetPrimitiveConverter(updater)
+
+      case TimestampNTZType
+        if parquetType.asPrimitiveType().getPrimitiveTypeName == INT64 &&
+          parquetType.getLogicalTypeAnnotation.isInstanceOf[TimestampLogicalTypeAnnotation] &&
+          !parquetType.getLogicalTypeAnnotation
+            .asInstanceOf[TimestampLogicalTypeAnnotation].isAdjustedToUTC &&
+          parquetType.getLogicalTypeAnnotation
+            .asInstanceOf[TimestampLogicalTypeAnnotation].getUnit == TimeUnit.MILLIS =>

Review comment:
       The condition seems the same as above，could you extract them？

##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetWriteSupport.scala
##########
@@ -223,6 +223,12 @@ class ParquetWriteSupport extends WriteSupport[InternalRow] with Logging {
               recordConsumer.addLong(millis)
         }
 
+      case TimestampNTZType =>
+        // For TimestampNTZType column, Spark always output as INT64 with Timestamp annotation in
+        // MICROS time unit.
+        (row: SpecializedGetters, ordinal: Int) =>
+          recordConsumer.addLong(row.getLong(ordinal))

Review comment:
       (row: SpecializedGetters, ordinal: Int) => recordConsumer.addLong(row.getLong(ordinal))




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