dtenedor commented on code in PR #36675:
URL: https://github.com/apache/spark/pull/36675#discussion_r886266739
##########
sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedParquetRecordReader.java:
##########
@@ -270,13 +271,40 @@ private void initBatch(
vectors[i + partitionIdx].setIsConstant();
}
}
+
+ // For Parquet tables whose columns have associated DEFAULT values, this
reader must return
+ // those values instead of NULL when the corresponding columns are not
present in storage (i.e.
+ // belong to the 'missingColumns' field in this class).
+ ColumnVector[] finalColumns = new
ColumnVector[sparkSchema.fields().length];
+ for (int i = 0; i < columnVectors.length; i++) {
+ Object defaultValue = sparkRequestedSchema.existenceDefaultValues()[i];
+ if (defaultValue == null) {
+ finalColumns[i] = vectors[i];
+ } else {
+ WritableColumnVector writable;
+ if (memMode == MemoryMode.OFF_HEAP) {
+ writable = new OffHeapColumnVector(capacity, vectors[i].dataType());
+ } else {
+ writable = new OnHeapColumnVector(capacity, vectors[i].dataType());
+ }
+ Optional<Integer> appended = writable.appendObjects(capacity,
defaultValue);
+ if (!appended.isPresent()) {
+ throw new IOException("Cannot assign default column value to result
column batch in " +
+ "vectorized Parquet reader because the data type is not supported:
" + defaultValue);
+ }
Review Comment:
Good catch, I updated the behavior to be the same.
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