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From "David Smiley (JIRA)" <>
Subject [jira] [Commented] (LUCENE-7253) Sparse data in doc values and segments merging
Date Mon, 02 May 2016 14:49:12 GMT


David Smiley commented on LUCENE-7253:

bq. The current "sparse" optimizations make the index smaller, but make access slower (log
N). We shouldn't do things like this. We should make things faster.

This issue is not about access-time or index size -- indeed something that is sacred in terms
of upholding access-time speed.  LUCENE-6863, what you refer to, was a delicate balancing

I'm trying to understand your point of view better... which is hard because I'm being told
something that I think is preposterous. Maybe i'm misunderstanding what you even mean by the
term "abuse case".  Lets try and communicate with words we hopefully both understand  ...

Do you believe that it's very _rare_ to populate fields sparsely, even those flagged as DocValues?
 Without much thought, I think probably half the search apps I know have at least one docValues
field that isn't fully dense.  Yonik is basically saying the same.  It isn't rare; I think
it's dubious to claim doing this is an abuse if it's popular to do it.  So I don't think you
mean that.  

Maybe you simply mean that the DocValues API itself shouldn't/doesn't _cater_ to sparsity
even though sparsity is allowed and you understand sparsity is popular and useful for some
use-cases nonetheless? After all, {{DocValues.docsWithValue}} is part of our API including
other methods that return -1 when there's no value -- it's _supported_.  I agree to this;
do you agree to that statement too?  Pawel proposes a change to an internal class that, assuming
benchmarks show, will have an up-side to a _supported_ capability of DocValues.  If it has
no technical down-sides, (these are hypotheticals to be proven out first), isn't vetoing now

bq. This means: {{if (abusecase)}}

What is the abusecase condition?  A condition that is true if dense and false if sparse? 
NumericDocValuesWriter  _already has_ such conditions -- see the hole filling loop which is
a condition that must be evaluated for every sparse whole.  Also see the FixedBitSet docsWithField
which only exists due to the sparsity notion.  Are these now set in stone, not to be changed
because you say so?  But what of it any way -- what's wrong?  I know that, if you had the
time/inclination or could somehow tell other contributors what do do, that it would be solved
in another way (RLE) but why stop someone willing to donate their time to solve it a different
way?  It would not prevent an RLE API from appearing later, assuming RLE turns out to be better,

> Sparse data in doc values and segments merging 
> -----------------------------------------------
>                 Key: LUCENE-7253
>                 URL:
>             Project: Lucene - Core
>          Issue Type: Improvement
>    Affects Versions: 5.5, 6.0
>            Reporter: Pawel Rog
>              Labels: performance
> 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
> 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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