* Take match_phrase out of snapshot and make tech preview
* Update docs/changelog/128925.yaml
* PR feedback
* Adding regenerated test data
* Update docs/changelog/128925.yaml
Co-authored-by: Carlos Delgado <6339205+carlosdelest@users.noreply.github.com>
* [CI] Auto commit changes from spotless
* Checkstyle
* Correct docs
* Hopefully fix docs build
* Found one more bad docs link - here's hoping this now fixes the doc build
* OMG bitten by - vs _
---------
Co-authored-by: Carlos Delgado <6339205+carlosdelest@users.noreply.github.com>
Co-authored-by: elasticsearchmachine <infra-root+elasticsearchmachine@elastic.co>
Co-authored-by: Aurélien FOUCRET <aurelien.foucret@gmail.com>
* Initial commit of match_phrase
* Add MatchPhraseQueryTests
* First pass at CSV specs
* Update docs/changelog/127661.yaml
* Refactor so MatchPhrase doesn't use all fulltext test cases, just text only
* Fix tests
* Add some CSV test cases
* Fix test
* Update changelog
* Update tests
* Comment out MATCH_PHRASE in search-functions Markdown
* Minor PR feedback
* PR feedback - refactor/consolidate code
* Add some more tests
* Fix some tests
* [CI] Auto commit changes from spotless
* Fix tests
* PR feedback - add tests, support boost and numeric data
* Revert "PR feedback - add tests, support boost and numeric data"
This reverts commit 4e7a699e3e.
* Apply testing/PR feedback outside numeric support only
* Regenerate docs
* Add negative test
* Update x-pack/plugin/esql/qa/testFixtures/src/main/resources/match-phrase-function.csv-spec
Co-authored-by: Carlos Delgado <6339205+carlosdelest@users.noreply.github.com>
* Update x-pack/plugin/esql/qa/testFixtures/src/main/resources/match-phrase-function.csv-spec
Co-authored-by: Carlos Delgado <6339205+carlosdelest@users.noreply.github.com>
* Update x-pack/plugin/esql/qa/testFixtures/src/main/resources/match-phrase-function.csv-spec
Co-authored-by: Carlos Delgado <6339205+carlosdelest@users.noreply.github.com>
* PR feedback
* Fix auto-commit error
* Regenerate docs
* Update x-pack/plugin/esql/src/main/java/org/elasticsearch/xpack/esql/expression/function/fulltext/MatchPhrase.java
Co-authored-by: Liam Thompson <32779855+leemthompo@users.noreply.github.com>
* Remove non text field types
* Fake test data
* Remove tests that no longer should pass without ip/date/version support
* Put real data in score tests now that I was able to engineer a failure
* Realized the scoring test might be flakey because how it was written, updated
* PR feedback
* PR feedback
* [CI] Auto commit changes from spotless
* Add check to MatchPhrase tests
* Fix merge errors
* [CI] Auto commit changes from spotless
* Test generated docs
* Add additional verifier tests
---------
Co-authored-by: elasticsearchmachine <infra-root+elasticsearchmachine@elastic.co>
Co-authored-by: Carlos Delgado <6339205+carlosdelest@users.noreply.github.com>
Co-authored-by: Liam Thompson <32779855+leemthompo@users.noreply.github.com>
Added support for the three primary scalar grid functions:
* `ST_GEOHASH(geom, precision)`
* `ST_GEOTILE(geom, precision)`
* `ST_GEOHEX(geom, precision)`
As well as versions of these three that take an optional `geo_shape` boundary (must be a `BBOX` ie. `Rectangle`).
And also supporting conversion functions that convert the grid-id from long to string and back to long.
This work represents the core of the feature to support geo-grid aggregations in ES|QL.
* New l2 normalizer added
* L2 score normaliser is registered
* test case added to the yaml
* Documentation added
* Resolved checkstyle issues
* Update docs/changelog/128504.yaml
* Update docs/reference/elasticsearch/rest-apis/retrievers.md
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* Score 0 test case added to check for corner cases
* Edited the markdown doc description
* Pruned the comment
* Renamed the variable
* Added comment to the class
* Unit tests added
* Spotless and checkstyle fixed
* Fixed build failure
* Fixed the forbidden test
---------
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Begins adding support for running "tagged queries" to the compute
engine. Here, it's just the `LuceneSourceOperator` because that's
useful and contained.
Example time! Say you are running:
```
FROM foo
| STATS MAX(v) BY ROUND_TO(g, 0, 100, 1000, 100000)
```
It's *often* faster to run this as four queries:
* The docs that round to `0`
* The docs that round to `100`
* The docs that round to `1000`
* The docs that round to `100000`
This creates an ESQL operator that can run these queries, one after the
other and attach those tags.
Aggs uses this trick and it's *way* faster when it can push down count
queries, but it's still faster when it pushes doc loading things. This
implementation in `LuceneSourceOperator` is quite similar to the doc
loading version in _search.
I don't have performance measurements yet because I haven't plugged this
into the language. In _search we call this `filter-by-filter` and enable
it when each group averages to more than 5000 documents and when there
isn't an `_doc_count` field. It's faster in those cases not to push. I
expect we'll be pretty similar.
Creates a `ROUND_TO` function that rounds it's input to one of the
provided values. Like so:
```
ROUND_TO(v, 0, 5000, 10000, 20000, 40000, 100000)
v | ROUND_TO
0 | 0
100 | 0
6000 | 5000
45001 | 40000
999999 | 100000
```
For some sequences of numbers you could do this with the `/` operator -
but for arbitrary sequences of numbers you needed `CASE` which is quite
slow. And hard to read!
Rewriting the example above would look like:
```
CASE (
v < 5000, 0,
v < 10000, 5000,
v < 20000, 10000,
v < 40000, 20000,
v < 100000, 40000,
100000
)
```
Even better, this is *fast*:
```
(operation) Mode Cnt Score Error Units
round_to_4_via_case avgt 7 138.124 ± 0.738 ns/op
round_to_4 avgt 7 0.805 ± 0.011 ns/op
round_to_3 avgt 7 0.739 ± 0.011 ns/op
round_to_2 avgt 7 0.651 ± 0.009 ns/op
date_trunc avgt 7 2.425 ± 0.018 ns/op
```
I've included a comparison to `DATE_TRUNC` above because we should be
able to rewrite `DATE_TRUNC` into `ROUND_TO` when we know the date range
of the index. This doesn't do it now, but it should be possible.
Documents that the VALUES aggregate function returns unique documents
and points folks to the TOP aggregate function if they want to keep
dupes.
Closes#128091
---------
Co-authored-by: Liam Thompson <32779855+leemthompo@users.noreply.github.com>
Types that parse arrays directly should not need to store values in _ignored_source if synthetic_source_keep=arrays. Since they have custom handling of arrays, it provides no benefit to store in _ignored_source when there are multiple values of the type.
Initial Kibana definition files for commands, currently only providing License information. We leave the license field out if it works with BASIC, so the only two files that actually have a license line are:
* CHANGE_POINT: PLATINUM
* RRF: ENTERPRISE
Output function signature license requirements to Kibana definition files, and also test that this matches the actual licensing behaviour of the functions.
ES|QL functions that enforce license checks do so with the `LicenseAware` interface. This does not expose what that functions license level is, but only whether the current active license will be sufficient for that function and its current signature (data types passed in as fields). Rather than add to this interface, we've made the license level information test-only information. This means if a function implements LicenseAware, it also needs to add a method to its test class to specify the license level for the signature being called. All functions will be tested for compliance, so failing to add this will result in test failure. Also if the test license level does not match the enforced license, that will also cause a failure.
Apache Lucene 10.2 exposes a new search strategy for executing filtered searches over HNSW graphs.
This PR switches to utilizing that strategy by default as it generally provides a much better recall/latency pareto frontier than our regular hnsw fanout search.
Additionally, a new tech-preview setting is provided to potentially revert to the old fanout behavior if issues arise.
This erroneously claimed that the example used a `drop` processor
(which drops whole documents) when it actually uses a `remove`
processor (which removes fields).
This speeds up loading from stored fields by opting more blocks into the
"sequential" strategy. This really kicks in when loading stored fields
like `text`. And when you need less than 100% of documents, but more than,
say, 10%. This is most useful when you need 99.9% of field documents.
That sort of thing. Here's the perf numbers:
```
%100.0 {"took": 403 -> 401,"documents_found":1000000}
%099.9 {"took":3990 -> 436,"documents_found": 999000}
%099.0 {"took":4069 -> 440,"documents_found": 990000}
%090.0 {"took":3468 -> 421,"documents_found": 900000}
%030.0 {"took":1213 -> 152,"documents_found": 300000}
%020.0 {"took": 766 -> 104,"documents_found": 200000}
%010.0 {"took": 397 -> 55,"documents_found": 100000}
%009.0 {"took": 352 -> 375,"documents_found": 90000}
%008.0 {"took": 304 -> 317,"documents_found": 80000}
%007.0 {"took": 273 -> 287,"documents_found": 70000}
%005.0 {"took": 199 -> 204,"documents_found": 50000}
%001.0 {"took": 46 -> 46,"documents_found": 10000}
```
Let's explain this with an example. First, jump to `main` and load a
million documents:
```
rm -f /tmp/bulk
for a in {1..1000}; do
echo '{"index":{}}' >> /tmp/bulk
echo '{"text":"text '$(printf %04d $a)'"}' >> /tmp/bulk
done
curl -s -uelastic:password -HContent-Type:application/json -XDELETE localhost:9200/test
for a in {1..1000}; do
echo -n $a:
curl -s -uelastic:password -HContent-Type:application/json -XPOST localhost:9200/test/_bulk?pretty --data-binary @/tmp/bulk | grep errors
done
curl -s -uelastic:password -HContent-Type:application/json -XPOST localhost:9200/test/_forcemerge?max_num_segments=1
curl -s -uelastic:password -HContent-Type:application/json -XPOST localhost:9200/test/_refresh
echo
```
Now query them all. Run this a few times until it's stable:
```
echo -n "%100.0 "
curl -s -uelastic:password -HContent-Type:application/json -XPOST 'localhost:9200/_query?pretty' -d'{
"query": "FROM test | STATS SUM(LENGTH(text))",
"pragma": {
"data_partitioning": "shard"
}
}' | jq -c '{took, documents_found}'
```
Now fetch 99.9% of documents:
```
echo -n "%099.9 "
curl -s -uelastic:password -HContent-Type:application/json -XPOST 'localhost:9200/_query?pretty' -d'{
"query": "FROM test | WHERE NOT text.keyword IN (\"text 0998\") | STATS SUM(LENGTH(text))",
"pragma": {
"data_partitioning": "shard"
}
}' | jq -c '{took, documents_found}'
```
This should spit out something like:
```
%100.0 { "took":403,"documents_found":1000000}
%099.9 {"took":4098, "documents_found":999000}
```
We're loading *fewer* documents but it's slower! What in the world?!
If you dig into the profile you'll see that it's value loading:
```
$ curl -s -uelastic:password -HContent-Type:application/json -XPOST 'localhost:9200/_query?pretty' -d'{
"query": "FROM test | STATS SUM(LENGTH(text))",
"pragma": {
"data_partitioning": "shard"
},
"profile": true
}' | jq '.profile.drivers[].operators[] | select(.operator | contains("ValuesSourceReaderOperator"))'
{
"operator": "ValuesSourceReaderOperator[fields = [text]]",
"status": {
"readers_built": {
"stored_fields[requires_source:true, fields:0, sequential: true]": 222,
"text:column_at_a_time:null": 222,
"text:row_stride:BlockSourceReader.Bytes": 1
},
"values_loaded": 1000000,
"process_nanos": 370687157,
"pages_processed": 222,
"rows_received": 1000000,
"rows_emitted": 1000000
}
}
$ curl -s -uelastic:password -HContent-Type:application/json -XPOST 'localhost:9200/_query?pretty' -d'{
"query": "FROM test | WHERE NOT text.keyword IN (\"text 0998\") | STATS SUM(LENGTH(text))",
"pragma": {
"data_partitioning": "shard"
},
"profile": true
}' | jq '.profile.drivers[].operators[] | select(.operator | contains("ValuesSourceReaderOperator"))'
{
"operator": "ValuesSourceReaderOperator[fields = [text]]",
"status": {
"readers_built": {
"stored_fields[requires_source:true, fields:0, sequential: false]": 222,
"text:column_at_a_time:null": 222,
"text:row_stride:BlockSourceReader.Bytes": 1
},
"values_loaded": 999000,
"process_nanos": 3965803793,
"pages_processed": 222,
"rows_received": 999000,
"rows_emitted": 999000
}
}
```
It jumps from 370ms to almost four seconds! Loading fewer values! The
second big difference is in the `stored_fields` marker. In the second on
it's `sequential: false` and in the first `sequential: true`.
`sequential: true` uses Lucene's "merge" stored fields reader instead of
the default one. It's much more optimized at decoding sequences of
documents.
Previously we only enabled this reader when loading compact sequences of
documents - when the entire block looks like
```
1, 2, 3, 4, 5, ... 1230, 1231
```
If there are any gaps we wouldn't enable it. That was a very
conservative thing we did long ago without doing any experiments. We
knew it was faster without any gaps, but not otherwise. It turns out
it's a lot faster in a lot more cases. I've measured it as faster for
99% gaps, at least on simple documents. I'm a bit worried that this is
too aggressive, so I've set made it configurable and made the default
being to use the "merge" loader with 10% gaps. So we'd use the merge
loader with a block like:
```
1, 11, 21, 31, ..., 1231, 1241
```
This does two things:
- It describes what the `timezone` option actually does. The existing wording is misleading.
- It recommends avoiding short abbreviations for timezones such as `PST`. This has come up at least twice recently.
* [DOCS][9.0] Improve ESQL reference docs IA
- reorganized es|ql reference documentation from flat list to logical hierarchy
- created three main sections: syntax reference , special fields, advanced operations
- renamed pages with more consistent and task-oriented titles
- aligned navigation titles with page content
- improved introductory text for each section
- used parallel phrasing for similar concepts
- clarified the relationship between reference docs and conceptual docs
Co-authored-by: Alexander Spies <alexander.spies@elastic.co>
- I trimmed the KEEP query in my final iteration in https://github.com/elastic/elasticsearch/pull/127215 but neglected to update the query itself, only the response. This fixes that so the query matches the response.
- 🚘 I also updated the table response to match other ESQL response tables
* [DOCS][ESQL] Cleanup and cross-reference LOOKUP JOIN reference and landing pages
**lookup-join.md (syntax reference)**:
- removed tip formatting for simpler direct link to landing page
- improved parameter formatting and descriptions
- fixed template variable from `{esql}` to `{{esql}}`
**esql-lookup-join.md (landing page)**:
- added "compare with enrich" section header
- simplified "how the command works" with clearer parameter explanation
- added code example in how it works section
- improved image alt text for accessibility
- organized example section with better context and SQL comparison
- added dropdown for sample tables to reduce visual clutter
- added "query" subheading for clearer organization
- included reference to additional examples in command reference
- removed excessive whitespace
* Improve example, add setup code
replaced abstract employee/language example with security monitoring use case
added setup instructions for creating test indices
included sample data loading via bulk api
new practical query example joining firewall logs with threat data
simplified results output showing threat detection scenario
added note about left-join behavior
improved code comments and structure
added required index.mode: lookup setting info
* Update elasticsearch-keystore.md
Customer needs document update for handling special characters and how we can use the echo command to enter the password.
* Update docs/reference/elasticsearch/command-line-tools/elasticsearch-keystore.md
Co-authored-by: Liam Thompson <32779855+leemthompo@users.noreply.github.com>
* Update docs/reference/elasticsearch/command-line-tools/elasticsearch-keystore.md
Co-authored-by: Liam Thompson <32779855+leemthompo@users.noreply.github.com>
* Update elasticsearch-keystore.md
Moving the section out of Examples as advised.
* Update docs/reference/elasticsearch/command-line-tools/elasticsearch-keystore.md
Co-authored-by: Liam Thompson <32779855+leemthompo@users.noreply.github.com>
* Update docs/reference/elasticsearch/command-line-tools/elasticsearch-keystore.md
Co-authored-by: Liam Thompson <32779855+leemthompo@users.noreply.github.com>
---------
Co-authored-by: Liam Thompson <32779855+leemthompo@users.noreply.github.com>
While this change appears subtle at this point, I am using this in a later PR that adds a lot more spatial functions, where nesting them in related groups like this looks much better.
The main impact of this is that the On this page navigator on the right panel of the docs will show the nesting
Co-authored-by: Liam Thompson <32779855+leemthompo@users.noreply.github.com>
The docs about the queue in a `fixed` pool are a little awkwardly
worded, and there is no mention of the queue in a `scaling` pool at all.
This commit cleans this area up.
* updating documentation to remove duplicate and redundant wording from 9.x
* Update links to rerank model landing page
---------
Co-authored-by: Liam Thompson <32779855+leemthompo@users.noreply.github.com>
* Updating text_similarity_reranker documentation
* Updating docs to include urls
* remove extra THE from the text
---------
Co-authored-by: Elastic Machine <elasticmachine@users.noreply.github.com>
The current LOOKUP JOIN docs include examples that are not tested by the ES|QL tests, unlike most other examples in the documentation. This PR fixes that, changing two examples to use existing tests, and adding a new csv-spec file for the remaining four examples. These four are not required to show results, so the tests have empty data and do not require any results. This means we are testing only the syntax (parsing and semantic analysis), which is sufficient for the docs.
* ES|QL change point docs
* Move ES|QL change_point to tech preview
* Update docs/reference/query-languages/esql/esql-commands.md
Co-authored-by: Craig Taverner <craig@amanzi.com>
* different example + add it the csv tests
* Restructure change_point docs to new structure
* Added generated test examples to change_point docs
* Fixed a few README.md text mistakes and added more details
* fix grammar
* License check
* regen parser
* Update docs/reference/query-languages/esql/_snippets/commands/layout/change_point.md
Co-authored-by: Craig Taverner <craig@amanzi.com>
---------
Co-authored-by: Craig Taverner <craig@amanzi.com>
Modifies TO_IP so it can handle leading `0`s in ipv4s. Here's how it
works now:
```
ROW ip = TO_IP("192.168.0.1") // OK!
ROW ip = TO_IP("192.168.010.1") // Fails
```
This adds
```
ROW ip = TO_IP("192.168.010.1", {"leading_zeros": "octal"})
ROW ip = TO_IP("192.168.010.1", {"leading_zeros": "decimal"})
```
We do this because there isn't a consensus on how to parse leading zeros
in ipv4s. The standard unix tools like `ping` and `ftp` interpret
leading zeros as octal. Java's built in ip parsing interprets them as
decimal. Because folks are using this for security rules we need to
support all the choices.
Closes#125460
This splits the grouping functions in two: those that can be evaluated independently through the EVAL operator (`BUCKET`) and those that don't (like those that that are evaluated through an agg operator, `CATEGORIZE`).
Closes#124608
While the internal structure of the docs is already split into many (over 1000) sub-pages, the final display for the `Functions and Operators` page is a single giant page, making navigation harder. This PR splits it into separate pages, one for each group of similar functions and one for the operators. Twelve new pages.
This PR also bundles a few other related changes. In total what is done is:
* Split functions/operators into 12 pages, one for each group, maintaining the existing split of each function/operator into a snippet with dynamically generated examples
* Split esql-commands.md into source-commands.md and processing-commands.md, each of which is split into individual snippets, one for each command
* Each command snippet has it's examples split out into separate files, if they were examples that were dynamically generated in the older asciidoc system
* The examples files are overwritten by the ES|QL unit tests, using a similar mechanism to the examples written for functions and operators)
* Some additional refinements to the Kibana definition and markdown files (nicer operator headings, and display text)
In the unexpected case that Elasticsearch dies due to a segfault or
other similar native issue, a core dump is useful in diagnosing the
problem. Yet core dumps are written to the working directory, which is
read-only for most installations of Elasticsearch. This commit changes
the working directory to the logs dir which should always be writeable.
This PR adds two new REST endpoints, for listing queries and getting information on a current query.
* Resolves#124827
* Related to #124828 (initial work)
Changes from the API specified in the above issues:
* The get API is pretty initial, as we don't have a way of fetching the memory used or number of rows processed.
List queries response:
```
GET /_query/queries
// returns for each of the running queries
// query_id, start_time, running_time, query
{ "queries" : {
"abc": {
"id": "abc",
"start_time_millis": 14585858875292,
"running_time_nanos": 762794,
"query": "FROM logs* | STATS BY hostname"
},
"4321": {
"id":"4321",
"start_time_millis": 14585858823573,
"running_time_nanos": 90231,
"query": "FROM orders | LOOKUP country_code ON country"
}
}
}
```
Get query response:
```
GET /_query/queries/abc
{
"id" : "abc",
"start_time_millis": 14585858875292,
"running_time_nanos": 762794,
"query": "FROM logs* | STATS BY hostname"
"coordinating_node": "oTUltX4IQMOUUVeiohTt8A"
"data_nodes" : [ "DwrYwfytxthse49X4", "i5msnbUyWlpe86e7"]
}
```
The `elasticsearch-certutil http` command, and security auto-configuration,
generate the HTTP certificate and CA without setting the `keyUsage` extension.
This PR fixes this by setting (by default):
- `keyCertSign` and `cRLSign` for self-signed CAs
- `digitalSignature` and `keyEncipherment` for HTTP certificates and CSRs
These defaults can be overridden when running `elasticsearch-certutil http`
command. The user will be prompted to change them as they wish.
For `elasticsearch-certutil ca`, the default value can be overridden by passing
the `--keysage` option, e.g.
```
elasticsearch-certutil ca --keyusage "digitalSignature,keyCertSign,cRLSign" -pem
```
Fixes#117769
With `geo_point` fields, here is the special case of values that have a syntactically valid format, but the numerical values for `latitude` and `longitude` are out of range.
If `ignore_malformed` is `false`, an exception will be thrown as usual. But if it is `true`, the document will be indexed correctly, by normalizing the latitude and longitude values into the valid range. The special `_ignored` field will not be set. The original source document will remain as before, but indexed values, doc-values and stored fields will all be normalized.
* test
* Revert "test"
This reverts commit 9f4e2adba0.
* Refactor InferenceService to allow passing in chunking settings
* Add chunking config to inference field metadata and store in semantic_text field
* Fix test compilation errors
* Hacking around trying to get ingest to work
* Debugging
* [CI] Auto commit changes from spotless
* POC works and update TODO to fix this
* [CI] Auto commit changes from spotless
* Refactor chunking settings from model settings to field inference request
* A bit of cleanup
* Revert a bunch of changes to try to narrow down what broke CI
* test
* Revert "test"
This reverts commit 9f4e2adba0.
* Fix InferenceFieldMetadataTest
* [CI] Auto commit changes from spotless
* Add chunking settings back in
* Update builder to use new map
* Fix compilation errors after merge
* Debugging tests
* debugging
* Cleanup
* Add yaml test
* Update tests
* Add chunking to test inference service
* Trying to get tests to work
* Shard bulk inference test never specifies chunking settings
* Fix test
* Always process batches in order
* Fix chunking in test inference service and yaml tests
* [CI] Auto commit changes from spotless
* Refactor - remove convenience method with default chunking settings
* Fix ShardBulkInferenceActionFilterTests
* Fix ElasticsearchInternalServiceTests
* Fix SemanticTextFieldMapperTests
* [CI] Auto commit changes from spotless
* Fix test data to fit within bounds
* Add additional yaml test cases
* Playing with xcontent parsing
* A little cleanup
* Update docs/changelog/121041.yaml
* Fix failures introduced by merge
* [CI] Auto commit changes from spotless
* Address PR feedback
* [CI] Auto commit changes from spotless
* Fix predicate in updated test
* Better handling of null/empty ChunkingSettings
* Update parsing settings
* Fix errors post merge
* PR feedback
* [CI] Auto commit changes from spotless
* PR feedback and fix Xcontent parsing for SemanticTextField
* Remove chunking settings check to use what's passed in from sender service
* Fix some tests
* Cleanup
* Test failure whack-a-mole
* Cleanup
* Refactor to handle memory optimized bulk shard inference actions - this is ugly but at least it compiles
* [CI] Auto commit changes from spotless
* Minor cleanup
* A bit more cleanup
* Spotless
* Revert change
* Update chunking setting update logic
* Go back to serializing maps
* Revert change to model settings - source still errors on missing model_id
* Fix updating chunking settings
* Look up model if null
* Fix test
* Work around https://github.com/elastic/elasticsearch/issues/125723 in semantic text field serialization
* Add BWC tests
* Add chunking_settings to docs
* Refactor/rename
* Address minor PR feedback
* Add test case for null update
* PR feedback - adjust refactor of chunked inputs
* Refactored AbstractTestInferenceService to return offsets instead of just Strings
* [CI] Auto commit changes from spotless
* Fix tests where chunk output was of size 3
* Update mappings per PR feedback
* PR Feedback
* Fix problems related to merge
* PR optimization
* Fix test
* Delete extra file
---------
Co-authored-by: elasticsearchmachine <infra-root+elasticsearchmachine@elastic.co>
Originally, `DATE_TRUNC` only supported 1-month and 3-month intervals for months, and 1-year interval for years, while arbitrary intervals were supported for weeks and days. This PR adds support for `DATE_TRUNC` with arbitrary month and year intervals.
Closes#120094
Hides some of the "extra" lines from ESQL's documentation. These lines
are required to make the documentation into nice tests which is
important to make sure the docs don't get out of date. But readers don't
need to see them.
In particular:
* Remove all links (both asciidoc and markdown) from the JSON definition files.
* This required a two phase edit, from asciidoc links to markdown, and then removal of markdown (replace with markdown text). This is because the asciidoc does not have the display text, and because some links were already markdown.
* Split predicates into is_null and is_not_null
* We kept the old combined version because the main docs still use that, so now we have both combined and separate versions, and Kibana can select the version they want.
This primarily splits the old preview:true warning from the newer applies_to approach. Since all of our current applies_to examples are actually just behaviour modifications of current functions, we do not use the official docs {applies_to} syntax. However there is code to make use of that in the case where we have an entirely new function which will appear in a new version.
Co-authored-by: Alexander Spies <alexander.spies@elastic.co>
This allows a `rescore_vector: {oversample: 0}` to indicate bypassing
oversampling and rescoring.
This is useful for:
- Updating a quantized mapping to turn off automatic rescoring
- Bypassing oversampling at query time in an ad-hoc manner if its on by default in the mapping
closes: https://github.com/elastic/elasticsearch/issues/125157
This PR was originally focused on improving support for Kibana docs, in particular the missing operator docs, but it has expanded to cover a bunch of related things:
* Primarily the main work was to improve operators support. ESQL generated docs cover all functions and most operators for which their is a clear operator class and test class. However, some are built-in behaviour and need additional support. This PR adds more generated content for those operators.
* Various specific operators requested by Kibana: Cast & null-predicates, and in particular the addition of examples
* Two functions without examples: mv_append and to_date_nanos
* Many small visual document cleanups (spelling, grammar, capitalization, etc.)
* Initial support for `applies_to` for multi-version differentiation.
This last point requires more work, as it is not yet agreed on just how we want this to look. We'll probably need to do refinements in followup PR. Consider the version in this PR as a first step into how this could look.
Adds a new cache and setting
TransportGetAllocationStatsAction.CACHE_TTL_SETTING
"cluster.routing.allocation.stats.cache.ttl" to configure the max age
for cached NodeAllocationStats on the master. The default
value is currently 1 minute per the suggestion in issue 110716.
Closes#110716
Did a few things:
* Rewrite Kibana docs asciidoc links to be MD links
* Make kibana docs links absolute to planned publication path
* Clarify which operators are generated and which are static
* Removed the trailing .md from kibana docs links
This commit adds a conversion function from numerics (and aggregate
metric doubles) to aggregate metric doubles.
It is most useful when you have multiple indices, where one index uses
aggregate metric double (e.g. a downsampled index) and another uses a
normal numeric type like long or double (e.g. an index prior to
downsampling).
Earlier work on the ES|QL port of docs to V3 introduced an issue in the build.gradle file making it fail with --configuration-cache. This fixes that, as well as one other broken link and removes some unused files.
In addition we bring back partial support for deleting unused files. It is tricky to have full support for this due to the mix of static and generated content, particularly in the operators snippets.
In a few previous PR's we restructured the ES|QL docs to make it possible to generate them dynamically.
This PR just moves a few files around to make the query languages docs easier to work with, and a little more organized like the ES|QL docs.
A bit part of this was setting up redirects to the new locations, so other repo's could correctly link to the elasticsearch docs.
Clarify that it is expected sometimes to see inter-node connections
sending zero-window advertisements as part of the usual TCP backpressure
mechanism.
This adds a new parameter to the quantized index mapping that allows
default oversampling and rescoring to occur.
This doesn't adjust any of the defaults. It allows it to be configured.
When the user provides `rescore_vector: {oversample: <number>}` in the
query it will overwrite it.
For example, here is how to use it with bbq:
```
PUT rescored_bbq
{
"mappings": {
"properties": {
"vector": {
"type": "dense_vector",
"index_options": {
"type": "bbq_hnsw",
"rescore_vector": {"oversample": 3.0}
}
}
}
}
}
```
Then, when querying, it will auto oversample the `k` by `3x` and rerank
with the raw vectors.
```
POST _search
{
"knn": {
"query_vector": [...],
"field": "vector"
}
}
```
Building on the work started in https://github.com/elastic/elasticsearch/pull/123904, we now want to auto-generate most of the small subfiles from the ES|QL functions unit tests.
This work also investigates any remaining discrepancies between the original asciidoc version and the new markdown, and tries to minimize differences so the docs do not look too different.
The kibana json and markdown files are moved to a new location, and the operator docs are a little more generated than before (although still largely manual).
* Inline cast to date
* Update docs/changelog/123460.yaml
* New capability for `::date` casting
* More tests
* Update tests
---------
Co-authored-by: Fang Xing <155562079+fang-xing-esql@users.noreply.github.com>
Resolves#123053
This adds the thread name to the driver sleep profile output.
---------
Co-authored-by: elasticsearchmachine <infra-root+elasticsearchmachine@elastic.co>
Adds options to QSTR function.
#118619 added named function parameters. This PR uses this mechanism for allowing query string function parameters, so query string parameters can be used in ES|QL.
Closes#120933
Ioana Tagirta