adriangb commented on code in PR #16461:
URL: https://github.com/apache/datafusion/pull/16461#discussion_r2157528156
##########
datafusion/datasource-parquet/src/opener.rs:
##########
@@ -879,4 +972,107 @@ mod test {
assert_eq!(num_batches, 0);
assert_eq!(num_rows, 0);
}
+
+ #[tokio::test]
+ async fn test_prune_on_partition_value_and_data_value() {
+ let store = Arc::new(InMemory::new()) as Arc<dyn ObjectStore>;
+
+ // Note: number 3 is missing!
+ let batch = record_batch!(("a", Int32, vec![Some(1), Some(2),
Some(4)])).unwrap();
+ let data_size =
+ write_parquet(Arc::clone(&store), "part=1/file.parquet",
batch.clone()).await;
+
+ let file_schema = batch.schema();
+ let mut file = PartitionedFile::new(
+ "part=1/file.parquet".to_string(),
+ u64::try_from(data_size).unwrap(),
+ );
+ file.partition_values = vec![ScalarValue::Int32(Some(1))];
+
+ let table_schema = Arc::new(Schema::new(vec![
+ Field::new("part", DataType::Int32, false),
+ Field::new("a", DataType::Int32, false),
+ ]));
+
+ let make_opener = |predicate| {
+ ParquetOpener {
+ partition_index: 0,
+ projection: Arc::new([0]),
+ batch_size: 1024,
+ limit: None,
+ predicate: Some(predicate),
+ logical_file_schema: file_schema.clone(),
+ metadata_size_hint: None,
+ metrics: ExecutionPlanMetricsSet::new(),
+ parquet_file_reader_factory: Arc::new(
+ DefaultParquetFileReaderFactory::new(Arc::clone(&store)),
+ ),
+ partition_fields: vec![Arc::new(Field::new(
+ "part",
+ DataType::Int32,
+ false,
+ ))],
+ pushdown_filters: true, // note that this is true!
+ reorder_filters: true,
+ enable_page_index: false,
+ enable_bloom_filter: false,
+ schema_adapter_factory: Arc::new(DefaultSchemaAdapterFactory),
+ enable_row_group_stats_pruning: false, // note that this is
false!
+ coerce_int96: None,
+ }
+ };
+
+ let make_meta = || FileMeta {
+ object_meta: ObjectMeta {
+ location: Path::from("part=1/file.parquet"),
+ last_modified: Utc::now(),
+ size: u64::try_from(data_size).unwrap(),
+ e_tag: None,
+ version: None,
+ },
+ range: None,
+ extensions: None,
+ metadata_size_hint: None,
+ };
+
+ // Filter should match the partition value and data value
+ let expr = col("part").eq(lit(1)).or(col("a").eq(lit(1)));
+ let predicate = logical2physical(&expr, &table_schema);
+ let opener = make_opener(predicate);
+ let stream = opener
+ .open(make_meta(), file.clone())
+ .unwrap()
+ .await
+ .unwrap();
+ let (num_batches, num_rows) = count_batches_and_rows(stream).await;
+ assert_eq!(num_batches, 1);
+ assert_eq!(num_rows, 3);
+
+ // Filter should match the partition value but not the data value
+ let expr = col("part").eq(lit(1)).or(col("a").eq(lit(3)));
+ let predicate = logical2physical(&expr, &table_schema);
+ let opener = make_opener(predicate);
+ let stream = opener.open(make_meta(),
file.clone()).unwrap().await.unwrap();
+ let (num_batches, num_rows) = count_batches_and_rows(stream).await;
+ assert_eq!(num_batches, 1);
+ assert_eq!(num_rows, 3);
+
+ // Filter should not match the partition value but match the data value
+ let expr = col("part").eq(lit(2)).or(col("a").eq(lit(1)));
+ let predicate = logical2physical(&expr, &table_schema);
+ let opener = make_opener(predicate);
+ let stream = opener.open(make_meta(),
file.clone()).unwrap().await.unwrap();
+ let (num_batches, num_rows) = count_batches_and_rows(stream).await;
+ assert_eq!(num_batches, 1);
+ assert_eq!(num_rows, 1);
Review Comment:
This assertion fails on `main`: all 3 rows are passed because the row filter
cannot handle the partition columns. This PR somewhat coincidentally happens to
fix this!
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