huaxingao commented on code in PR #11390:
URL: https://github.com/apache/iceberg/pull/11390#discussion_r1817447914
##########
spark/v3.5/spark/src/main/java/org/apache/iceberg/spark/source/BaseBatchReader.java:
##########
@@ -81,14 +84,15 @@ private CloseableIterable<ColumnarBatch> newParquetIterable(
SparkDeleteFilter deleteFilter) {
// get required schema if there are deletes
Schema requiredSchema = deleteFilter != null ?
deleteFilter.requiredSchema() : expectedSchema();
+ Schema vectorizationSchema = vectorizationSchema(deleteFilter);
return Parquet.read(inputFile)
.project(requiredSchema)
.split(start, length)
.createBatchedReaderFunc(
fileSchema ->
VectorizedSparkParquetReaders.buildReader(
- requiredSchema, fileSchema, idToConstant, deleteFilter))
+ vectorizationSchema, fileSchema, idToConstant,
deleteFilter))
Review Comment:
Not exactly.
If no deletes, it's `expectedSchema`.
If it's equality delete, it's `deleteFilter.requiredSchema()`, because it
could be `expectedSchema` + equality filter column. For example:
```
SELECT id FROM table
```
supposed the equality delete has data == 'aaa'
then we do need to read the `data` column too, so it's
`deleteFilter.requiredSchema()`, which is `id` + `data`
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