In the case when an index is sorted on a low-cardinality field, or the index
sort order correlates with the order in which documents get ingested, we can
optimize `SortedDocIDMerger` by doing a single comparison with the doc ID on
the next sub. This checks covers at the same time whether the priority queue
needs reordering and whether the current sub reached `NO_MORE_DOCS`.
On the NYC taxis dataset on my local machine, switching from
`Arrays#compareUnsigned` to `ArrayUtil#getUnsignedComparator` yielded a 15%
speedup of BKD merging.
When #672 was introduced, it added many nice rewrite optimizations. However, in the case when there are many multiple nested Boolean queries under a top level Boolean#filter clause, its runtime grows exponentially.
The key issue was how the BooleanQuery#rewriteNoScoring redirected yet again to the ConstantScoreQuery#rewrite. This causes BooleanQuery#rewrite to be called again recursively , even though it was previously called in ConstantScoreQuery#rewrite, and THEN BooleanQuery#rewriteNoScoring is called again, recursively.
This causes exponential growth in rewrite time based on query depth. The change here hopes to short-circuit that and only grow (near) linearly by calling BooleanQuery#rewriteNoScoring directly, instead if attempting to redirect through ConstantScoreQuery#rewrite.
closes: #12069
Today Lucene allows creating indexed binary fields, e.g. via
`StringField(String, BytesRef, Field.Store)`, but not reusing them: calling
`setBytesValue` on a `StringField` throws.
This commit removes the check that prevents reusing fields with binary values.
I considered an alternative that consisted of failing if calling
`setBytesValue` on a field that is indexed and tokenized, but we currently
don't have such checks e.g. on numeric values, so it did not feel consistent.
Doing this change would help improve the [nightly benchmarks for the NYC taxis
dataset](http://people.apache.org/~mikemccand/lucenebench/sparseResults.html)
by doing the String -> UTF-8 conversion only once for keywords, instead of once
for the `StringField` and one for the `SortedDocValuesField`, while still
reusing fields.
Today Lucene allows creating indexed binary fields, e.g. via
`StringField(String, BytesRef, Field.Store)`, but not reusing them: calling
`setBytesValue` on a `StringField` throws.
This commit removes the check that prevents reusing fields with binary values.
I considered an alternative that consisted of failing if calling
`setBytesValue` on a field that is indexed and tokenized, but we currently
don't have such checks e.g. on numeric values, so it did not feel consistent.
Doing this change would help improve the [nightly benchmarks for the NYC taxis
dataset](http://people.apache.org/~mikemccand/lucenebench/sparseResults.html)
by doing the String -> UTF-8 conversion only once for keywords, instead of once
for the `StringField` and one for the `SortedDocValuesField`, while still
reusing fields.
`ConcurrentMergeScheduler` uses the rate at which a merge writes bytes as a
proxy for CPU usage, in order to prevent merging from disrupting searches too
much. However creating compound files are lightweight CPU-wise and do not need
throttling.
Closes#12068
This iterates on #399 to also optimize the case when an index sort is
configured. When cutting over the NYC taxis benchmark to the new numeric
fields,
[flush times](http://people.apache.org/~mikemccand/lucenebench/sparseResults.html#flush_times)
stayed mostly the same when index sorting is disabled and increased by 7-8%
when index sorting is enabled. I expect this change to address this slowdown.
When flushing segments that have an index sort configured, postings lists get
loaded into arrays and get reordered according to the index sort.
This reordering is implemented with `TimSorter`, a variant of merge sort. Like
merge sort, an important part of `TimSorter` consists of merging two contiguous
sorted slices of the array into a combined sorted slice. This merging can be
done either with external memory, which is the classical approach, or in-place,
which still runs in linear time but with a much higher factor. Until now we
were allocating a fixed budget of `maxDoc/64` for doing these merges with
external memory. If this is not enough, sorted slices would be merged in place.
I've been looking at some profiles recently for an index where a non-negligible
chunk of the time was spent on in-place merges. So I would like to propose the
following change:
- Increase the maximum RAM budget to `maxDoc / 8`. This should help avoid
in-place merges for all postings up to `docFreq = maxDoc / 4`.
- Make this RAM budget lazily allocated, rather than eagerly like today. This
would help not allocate memory in O(maxDoc) for fields like primary keys
that only have a couple postings per term.
So overall memory usage would never be more than 50% higher than what it is
today, because `TimSorter` never needs more than X temporary slots if the
postings list doesn't have at least 2*X entries, and these 2*X entries already
get loaded into memory today. And for fields that have short postings, memory
usage should actually be lower.
They currently call `Arrays#sort`, which incurs a tiny bit of overhead due to
range checks and some logic to determine the optimal sorting algorithm to use
depending on the number of values. We can skip this overhead in the case when
there is a single value.
When FMA is not supported by the hardware, these methods fall back to
BigDecimal usage which causes them to be 2500x slower.
While most hardware in the last 10 years may have the support, out of
box both VirtualBox and QEMU don't pass thru FMA support (for the latter
at least you can tweak it with e.g. -cpu host or similar to fix this).
This creates a terrible undocumented performance trap. Prevent it from
sneaking into our codebase.
Drop 3.x compatibility (which was pickier at compile-time and prevented slow things from happening). Instead add paranoia to runtime tests, so that they fail if antlr would do something slow in the parsing. This is needed because antlrv4 is a big performance trap: https://github.com/antlr/antlr4/blob/master/doc/faq/general.md
"Q: What are the main design decisions in ANTLR4?
Ease-of-use over performance. I will worry about performance later."
It allows us to move forward with newer antlr but hopefully prevent the associated headaches.
Signed-off-by: Andriy Redko <andriy.redko@aiven.io>
Co-authored-by: Robert Muir <rmuir@apache.org>
Add new stored fields and termvectors interfaces: IndexReader.storedFields()
and IndexReader.termVectors(). Deprecate IndexReader.document() and IndexReader.getTermVector().
The new APIs do not rely upon ThreadLocal storage for each index segment, which can greatly
reduce RAM requirements when there are many threads and/or segments.
Co-authored-by: Adrien Grand <jpountz@gmail.com>
* Leverage DISI static factory methods more over custom DISI impl where possible.
* Assert points field is a single-dim.
* Bound cost estimate by the cost of the doc values field (for sparse fields).
Luca Cavanna
Lu Xugang
Adrien Grand
Benjamin Trent
Patrick Zhai
Erik Pellizzon
Uwe Schindler
twosom
Greg Miller
Marc D'Mello
Zach Chen
Egor Potemkin
Francisco Fernández Castaño
Robert Muir
Andriy Redko
Craig Taverner
Ignacio Vera
Dawid Weiss
gf2121
Alan Woodward