* 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.
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>
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>
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)
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.
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 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.
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).
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.
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).
