tustvold commented on a change in pull request #1180:
URL: https://github.com/apache/arrow-rs/pull/1180#discussion_r788857097
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File path: parquet/src/arrow/record_reader.rs
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@@ -167,7 +167,13 @@ where
break;
}
- let batch_size = max(num_records - records_read, MIN_BATCH_SIZE);
+ // If repetition levels present, we don't know how much more to
read
Review comment:
This change I think warrants some explanation:
Parquet effectively flattens nested data when storing it, and stores
sufficient information in the definition levels and repetition levels to
reconstruct the original data. This presents a challenge for readers that want
to read a certain number of rows, as a row count can't be mapped to a value
count in the event of repeated fields - a single row might contain multiple
values from the underlying leaf column.
RecordReader acts to handle this, by reading data to an internal buffer and
then splitting off a certain number of semantic records. Previously this logic
would always read MIN_BATCH_SIZE rows, even if the exact number of values to
read is actually known as there are no repetition levels.
Unfortunately this can result in a situation where the buffers are never
fully drained, consider the scenario where the user is requesting batches of
1024 (the same as MIN_BATCH_SIZE). When transitioning across a row group
boundary, this will read some remainder from the row group `r`, before reading
1024 from the next row group, leaving `1024 + r` in the buffer. The client will
then only split off the `1024` they actually wanted. This will continue
indefinitely, with the buffer continuing to contain at least `r` values.
Aside from wasting cycles splitting and shuffling buffers unnecessarily,
this prevents dictionary preservation from functioning correctly as the buffer
will never be emptied allowing a new dictionary to be registered.
With this change, this degenerate case still exists with repeated fields (as
it did before) but is avoided for the more common case of a non-repeated field.
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