[jira] [Commented] (LUCENE-7253) Sparse data in doc values and segments merging

["Robert Muir (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/LUCENE-7253?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15257206#comment-15257206 ] 

Robert Muir commented on LUCENE-7253:
-------------------------------------

The correct solution is to have a more next/advance type api geared at forward iteration rather than one that mimics an array. Then nulls can be handled in typical ways in various situations (eg rle). It should be possible esp that scoring is in order.

But otherwise, i dont think we should do something messy to optimize sparse cases at all. Clean solutions that are simpler and faster are good though.

> Sparse data in doc values and segments merging 
> -----------------------------------------------
>
>                 Key: LUCENE-7253
>                 URL: https://issues.apache.org/jira/browse/LUCENE-7253
>             Project: Lucene - Core
>          Issue Type: Improvement
>    Affects Versions: 5.5, 6.0
>            Reporter: Pawel Rog
>
> Doc Values were optimized recently to efficiently store sparse data. Unfortunately there is still big problem with Doc Values merges for sparse fields. When we imagine 1 billion documents index it seems it doesn't matter if all documents have value for this field or there is only 1 document with value. Segment merge time is the same for both cases. In most cases this is not a problem but there are several cases in which one can expect having many fields with sparse doc values.
> I can describe an example. During performance tests of a system with large number of sparse fields I realized that Doc Values merges are a bottleneck. I had hundreds of different numeric fields. Each document contained only small subset of all fields. Average document contains 5-7 different numeric values. As you can see data was very sparse in these fields. It turned out that ingestion process was CPU-bound. Most of CPU time was spent in DocValues related methods (SingletonSortedNumericDocValues#setDocument, DocValuesConsumer$10$1#next, DocValuesConsumer#isSingleValued, DocValuesConsumer$4$1#setNext, ...) - mostly during merging segments.
> Adrien Grand suggested to reduce the number of sparse fields and replace them with smaller number of denser fields. This helped a lot but complicated fields naming. 
> I am not much familiar with Doc Values source code but I have small suggestion how to improve Doc Values merges for sparse fields. I realized that Doc Values producers and consumers use Iterators. Let's take an example of numeric Doc Values. Would it be possible to replace Iterator which "travels" through all documents with Iterator over collection of non empty values? Of course this would require storing object (instead of numeric) which contains value and document ID. Such an iterator could significantly improve merge time of sparse Doc Values fields. IMHO this won't cause big overhead for dense structures but it can be game changer for sparse structures.
> This is what happens in NumericDocValuesWriter on flush
> {code}
>     dvConsumer.addNumericField(fieldInfo,
>                                new Iterable<Number>() {
>                                  @Override
>                                  public Iterator<Number> iterator() {
>                                    return new NumericIterator(maxDoc, values, docsWithField);
>                                  }
>                                });
> {code}
> Before this happens during addValue, this loop is executed to fill holes.
> {code}
>     // Fill in any holes:
>     for (int i = (int)pending.size(); i < docID; ++i) {
>       pending.add(MISSING);
>     }
> {code}
> It turns out that variable called pending is used only internally in NumericDocValuesWriter. I know pending is PackedLongValues and it wouldn't be good to change it with different class (some kind of list) because this may break DV performance for dense fields. I hope someone can suggest interesting solutions for this problem :).
> It would be great if discussion about sparse Doc Values merge performance can start here.



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