houqp commented on a change in pull request #2000:
URL: https://github.com/apache/arrow-datafusion/pull/2000#discussion_r835982496
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File path: datafusion/src/physical_plan/file_format/parquet.rs
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@@ -435,6 +448,50 @@ fn build_row_group_predicate(
)
}
+fn read_partition_no_file_columns(
+ object_store: &dyn ObjectStore,
+ partition: &[PartitionedFile],
+ batch_size: usize,
+ response_tx: Sender<ArrowResult<RecordBatch>>,
+ limit: Option<usize>,
+ mut partition_column_projector: PartitionColumnProjector,
+) -> Result<()> {
+ use parquet::file::reader::FileReader;
+ let mut limit = limit.unwrap_or(usize::MAX);
+ for partitioned_file in partition {
+ let object_reader =
+
object_store.file_reader(partitioned_file.file_meta.sized_file.clone())?;
+ let file_reader =
SerializedFileReader::new(ChunkObjectReader(object_reader))?;
+ let mut file_rows: usize = file_reader
+ .metadata()
+ .file_metadata()
+ .num_rows()
+ .try_into()
+ .expect("Row count should always be greater than or equal to 0");
+ file_rows = limit.min(file_rows);
+ limit -= file_rows;
+ while file_rows >= batch_size {
+ send_result(
+ &response_tx,
+ partition_column_projector
+ .project_empty(batch_size,
&partitioned_file.partition_values),
Review comment:
minor optimization, if it's sending the same recordbatch for a
partition, we could create the record batch once at the beginning, then reuse
it with `.clone()` for this loop and `.slide()` for the final send_result below.
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