sdd commented on code in PR #652:
URL: https://github.com/apache/iceberg-rust/pull/652#discussion_r1875544707
##########
crates/iceberg/src/arrow/reader.rs:
##########
@@ -176,6 +188,350 @@ impl ArrowReader {
return Ok(rx.boxed());
}
+ // retrieve all delete files concurrently from FileIO and parse them
+ // into `Deletes` objects
+ async fn get_deletes(
+ delete_file_entries: Option<Arc<Vec<FileScanTaskDeleteFile>>>,
+ file_io: FileIO,
+ concurrency_limit_data_files: usize,
+ ) -> Result<Option<Vec<Deletes>>> {
+ let Some(delete_file_entries) = delete_file_entries else {
+ return Ok(None);
+ };
+
+ let (tx, rx) = channel(concurrency_limit_data_files);
+ let mut channel_for_error = tx.clone();
+
+ spawn(async move {
+ #[allow(clippy::redundant_closure)] // recommendation from Clippy
fails to compile
+ let result =
+ futures::stream::iter(delete_file_entries.iter().map(|df|
crate::Result::Ok(df)))
+ .try_for_each_concurrent(concurrency_limit_data_files,
|entry| {
+ let file_io = file_io.clone();
+ let mut tx = tx.clone();
+ async move {
+ let FileScanTaskDeleteFile {
+ ref file_path,
+ file_type,
+ } = entry;
+
+ let record_batch_stream =
+
Self::create_parquet_record_batch_stream_builder(
+ file_path,
+ file_io.clone(),
+ false,
+ )
+ .await?
+ .build()?
+ .map(|item| match item {
+ Ok(val) => Ok(val),
+ Err(err) => {
+ Err(Error::new(ErrorKind::DataInvalid,
err.to_string())
+ .with_source(err))
+ }
+ })
+ .boxed();
+
+ let result = match file_type {
+ DataContentType::PositionDeletes => {
+
parse_positional_delete_file(record_batch_stream).await
+ }
+ DataContentType::EqualityDeletes => {
+
parse_equality_delete_file(record_batch_stream).await
+ }
+ _ => Err(Error::new(
+ ErrorKind::Unexpected,
+ "Expected equality or positional delete",
+ )),
+ }?;
+
+ tx.send(Ok(result)).await?;
+ Ok(())
+ }
+ })
+ .await;
+
+ if let Err(error) = result {
+ let _ = channel_for_error.send(Err(error)).await;
+ }
+ });
+
+ let results = rx.try_collect::<Vec<_>>().await?;
+ if results.is_empty() {
+ Ok(None)
+ } else {
+ Ok(Some(results))
+ }
+ }
+
+ fn get_positional_delete_indexes(
+ data_file_path: &str,
+ deletes: &[Deletes],
+ ) -> Option<Vec<usize>> {
+ let mut results = deletes
+ .iter()
+ .filter_map(|d| {
+ if let Deletes::Positional(map) = d {
+ if let Some(indices) = map.get(data_file_path) {
+ return Some(indices.iter().map(|&i| i as usize));
+ }
+ }
+
+ None
+ })
+ .peekable();
+
+ if results.peek().is_none() {
+ None
+ } else {
+ Some(results.flatten().collect())
+ }
+ }
+
+ fn get_equality_deletes(
+ delete_files: &[Deletes],
+ snapshot_schema: SchemaRef,
+ ) -> Result<Option<BoundPredicate>> {
+ let mut result_predicate = AlwaysFalse;
+
+ for delete_file in delete_files {
+ if let Deletes::Equality(record_batches) = delete_file {
+ for record_batch in record_batches {
+ let batch_schema_arrow = record_batch.schema();
+ let batch_schema_iceberg =
arrow_schema_to_schema(batch_schema_arrow.as_ref())?;
+
+ let datum_columns_with_names: Result<Vec<_>> = record_batch
+ .columns()
+ .iter()
+ .zip(batch_schema_iceberg.as_struct().fields())
+ .map(|(column, field)| {
+ let col_as_datum_vec =
+
Self::equality_delete_column_to_datum_vec(column, field);
+ col_as_datum_vec.map(|c| (c,
field.name.to_string()))
+ })
+ .collect();
+ let datum_columns_with_names = datum_columns_with_names?;
+
+ for row_idx in 0..record_batch.num_rows() {
+ let mut row_predicate = AlwaysTrue;
+ for (column, field_name) in &datum_columns_with_names {
+ if let Some(Some(datum)) = column.get(row_idx) {
+ row_predicate = row_predicate
+
.and(Reference::new(field_name).equal_to(datum.clone()));
+ }
+ }
+ result_predicate = result_predicate.or(row_predicate);
+ }
+ }
+ }
+ }
+
+ Ok(if result_predicate == AlwaysFalse {
+ None
+ } else {
+ // This is a deletion filter, not a selection filter, so we need
to invert it
+ result_predicate = result_predicate.negate();
+ Some(result_predicate.bind(snapshot_schema, true)?)
+ })
+ }
+
+ fn equality_delete_column_to_datum_vec(
+ column: &ArrayRef,
+ field: &NestedFieldRef,
+ ) -> Result<Vec<Option<Datum>>> {
Review Comment:
Do you mean that it should return `Result<HashSet<Struct>>`?
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