Changes the titles for tokenizer pages to sentence case.
Also moves the 'Path hierarchy tokenizer examples' page within the
'Path hierarchy tokenizer' page and adds a related redirect.
This change removes the Lucene's experimental flag from the documentations of the following
tokenizer/filters:
* Simple Pattern Split Tokenizer
* Simple Pattern tokenizer
* Flatten Graph Token Filter
* Word Delimiter Graph Token Filter
The flag is still present in Lucene codebase but we're fully supporting these tokenizers/filters
in ES for a long time now so the docs flag is misleading.
Co-authored-by: James Rodewig <james.rodewig@elastic.co>
Reformats the edge n-gram and n-gram token filter docs. Changes include:
* Adds title abbreviations
* Updates the descriptions and adds Lucene links
* Reformats parameter definitions
* Adds analyze and custom analyzer snippets
* Adds notes explaining differences between the edge n-gram and n-gram
filters
Additional changes:
* Switches titles to use "n-gram" throughout.
* Fixes a typo in the edge n-gram tokenizer docs
* Adds an explicit anchor for the `index.max_ngram_diff` setting
Currently the `token_chars` setting in both `edgeNGram` and `ngram` tokenizers
only allows for a list of predefined character classes, which might not fit
every use case. For example, including underscore "_" in a token would currently
require the `punctuation` class which comes with a lot of other characters.
This change adds an additional "custom" option to the `token_chars` setting,
which requires an additional `custom_token_chars` setting to be present and
which will be interpreted as a set of characters to inlcude into a token.
Closes#25894
The `edge_ngram` tokenizer limits tokens to the `max_gram` character
length. Autocomplete searches for terms longer than this limit return
no results.
To prevent this, you can use the `truncate` token filter to truncate
tokens to the `max_gram` character length. However, this could return irrelevant results.
This commit adds some advisory text to make users aware of this limitation and outline the tradeoffs for each approach.
Closes#48956.
The "include_type_name" parameter was temporarily introduced in #37285 to facilitate
moving the default parameter setting to "false" in many places in the documentation
code snippets. Most of the places can simply be reverted without causing errors.
In this change I looked for asciidoc files that contained the
"include_type_name=true" addition when creating new indices but didn't look
likey they made use of the "_doc" type for mappings. This is mostly the case
e.g. in the analysis docs where index creating often only contains settings. I
manually corrected the use of types in some places where the docs still used an
explicit type name and not the dummy "_doc" type.
* Default include_type_name to false for get and put mappings.
* Default include_type_name to false for get field mappings.
* Add a constant for the default include_type_name value.
* Default include_type_name to false for get and put index templates.
* Default include_type_name to false for create index.
* Update create index calls in REST documentation to use include_type_name=true.
* Some minor clean-ups around the get index API.
* In REST tests, use include_type_name=true by default for index creation.
* Make sure to use 'expression == false'.
* Clarify the different IndexTemplateMetaData toXContent methods.
* Fix FullClusterRestartIT#testSnapshotRestore.
* Fix the ml_anomalies_default_mappings test.
* Fix GetFieldMappingsResponseTests and GetIndexTemplateResponseTests.
We make sure to specify include_type_name=true during xContent parsing,
so we continue to test the legacy typed responses. XContent generation
for the typeless responses is currently only covered by REST tests,
but we will be adding unit test coverage for these as we implement
each typeless API in the Java HLRC.
This commit also refactors GetMappingsResponse to follow the same appraoch
as the other mappings-related responses, where we read include_type_name
out of the xContent params, instead of creating a second toXContent method.
This gives better consistency in the response parsing code.
* Fix more REST tests.
* Improve some wording in the create index documentation.
* Add a note about types removal in the create index docs.
* Fix SmokeTestMonitoringWithSecurityIT#testHTTPExporterWithSSL.
* Make sure to mention include_type_name in the REST docs for affected APIs.
* Make sure to use 'expression == false' in FullClusterRestartIT.
* Mention include_type_name in the REST templates docs.
This commit changes the format of the `hits.total` in the search response to be an object with
a `value` and a `relation`. The `value` indicates the number of hits that match the query and the
`relation` indicates whether the number is accurate (in which case the relation is equals to `eq`)
or a lower bound of the total (in which case it is equals to `gte`).
This change also adds a parameter called `rest_total_hits_as_int` that can be used in the
search APIs to opt out from this change (retrieve the total hits as a number in the rest response).
Note that currently all search responses are accurate (`track_total_hits: true`) or they don't contain
`hits.total` (`track_total_hits: true`). We'll add a way to get a lower bound of the total hits in a
follow up (to allow numbers to be passed to `track_total_hits`).
Relates #33028
=== Char Group Tokenizer
The `char_group` tokenizer breaks text into terms whenever it encounters
a
character which is in a defined set. It is mostly useful for cases where
a simple
custom tokenization is desired, and the overhead of use of the
<<analysis-pattern-tokenizer, `pattern` tokenizer>>
is not acceptable.
=== Configuration
The `char_group` tokenizer accepts one parameter:
`tokenize_on_chars`::
A string containing a list of characters to tokenize the string on.
Whenever a character
from this list is encountered, a new token is started. Also supports
escaped values like `\\n` and `\\f`,
and in addition `\\s` to represent whitespace, `\\d` to represent
digits and `\\w` to represent letters.
Defaults to an empty list.
=== Example output
```The 2 QUICK Brown-Foxes jumped over the lazy dog's bone for $2```
When the configuration `\\s-:<>` is used for `tokenize_on_chars`, the
above sentence would produce the following terms:
```[ The, 2, QUICK, Brown, Foxes, jumped, over, the, lazy, dog's, bone,
for, $2 ]```
This commit changes the default out-of-the-box configuration for the
number of shards from five to one. We think this will help address a
common problem of oversharding. For users with time-based indices that
need a different default, this can be managed with index templates. For
users with non-time-based indices that find they need to re-shard with
the split API in place they no longer need to resort only to
reindexing.
Since this has the impact of changing the default number of shards used
in REST tests, we want to ensure that we still have coverage for issues
that could arise from multiple shards. As such, we randomize (rarely)
the default number of shards in REST tests to two. This is managed via a
global index template. However, some tests check the templates that are
in the cluster state during the test. Since this template is randomly
there, we need a way for tests to skip adding the template used to set
the number of shards to two. For this we add the default_shards feature
skip. To avoid having to write our docs in a complicated way because
sometimes they might be behind one shard, and sometimes they might be
behind two shards we apply the default_shards feature skip to all docs
tests. That is, these tests will always run with the default number of
shards (one).
Allowing `_doc` as a type will enable users to make the transition to 7.0
smoother since the index APIs will be `PUT index/_doc/id` and `POST index/_doc`.
This also moves most of the documentation to `_doc` as a type name.
Closes#27750Closes#27751
* Add limits for ngram and shingle settings (#27211)
Create index-level settings:
max_ngram_diff - maximum allowed difference between max_gram and min_gram in
NGramTokenFilter/NGramTokenizer. Default is 1.
max_shingle_diff - maximum allowed difference between max_shingle_size and
min_shingle_size in ShingleTokenFilter. Default is 3.
Throw an IllegalArgumentException when
trying to create NGramTokenFilter, NGramTokenizer, ShingleTokenFilter
where difference between max_size and min_size exceeds the settings value.
Closes#25887
Other tokenizers like the standard tokenizer allow overriding the default
maximum token length of 255 using the `"max_token_length` parameter. This change
enables using this parameter also with the whitespace tokenizer. The range that
is currently allowed is from 0 to StandardTokenizer.MAX_TOKEN_LENGTH_LIMIT,
which is 1024 * 1024 = 1048576 characters.
Closes#26643
Today if we search across a large amount of shards we hit every shard. Yet, it's quite
common to search across an index pattern for time based indices but filtering will exclude
all results outside a certain time range ie. `now-3d`. While the search can potentially hit
hundreds of shards the majority of the shards might yield 0 results since there is not document
that is within this date range. Kibana for instance does this regularly but used `_field_stats`
to optimize the indexes they need to query. Now with the deprecation of `_field_stats` and it's upcoming removal a single dashboard in kibana can potentially turn into searches hitting hundreds or thousands of shards and that can easily cause search rejections even though the most of the requests are very likely super cheap and only need a query rewriting to early terminate with 0 results.
This change adds a pre-filter phase for searches that can, if the number of shards are higher than a the `pre_filter_shard_size` threshold (defaults to 128 shards), fan out to the shards
and check if the query can potentially match any documents at all. While false positives are possible, a negative response means that no matches are possible. These requests are not subject to rejection and can greatly reduce the number of shards a request needs to hit. The approach here is preferable to the kibana approach with field stats since it correctly handles aliases and uses the correct threadpools to execute these requests. Further it's completely transparent to the user and improves scalability of elasticsearch in general on large clusters.
This snapshot has faster range queries on range fields (LUCENE-7828), more
accurate norms (LUCENE-7730) and the ability to use fake term frequencies
(LUCENE-7854).
Expose the experimental simplepattern and
simplepatternsplit tokenizers in the common
analysis plugin. They provide tokenization based
on regular expressions, using Lucene's
deterministic regex implementation that is usually
faster than Java's and has protections against
creating too-deep stacks during matching.
Both have a not-very-useful default pattern of the
empty string because all tokenizer factories must
be able to be instantiated at index creation time.
They should always be configured by the user
in practice.
* Docs: Improved tokenizer docs
Added descriptions and runnable examples
* Addressed Nik's comments
* Added TESTRESPONSEs for all tokenizer examples
* Added TESTRESPONSEs for all analyzer examples too
* Added docs, examples, and TESTRESPONSES for character filters
* Skipping two tests:
One interprets "$1" as a stack variable - same problem exists with the REST tests
The other because the "took" value is always different
* Fixed tests with "took"
* Fixed failing tests and removed preserve_original from fingerprint analyzer
Currently regexes in Pattern Tokenizer docs are escaped (it seems according to Java rules). I think it is better not to escape them because JSON escaping should be automatic in client libraries, and string escaping depends on a client language used. The default pattern is `\W+`, not `\\W+`.
Closes#6615
Add `irish` analyzer
Add `sorani` analyzer (Kurdish)
Add `classic` tokenizer: specific to english text and tries to recognize hostnames, companies, acronyms, etc.
Add `thai` tokenizer: segments thai text into words.
Add `classic` tokenfilter: cleans up acronyms and possessives from classic tokenizer
Add `apostrophe` tokenfilter: removes text after apostrophe and the apostrophe itself
Add `german_normalization` tokenfilter: umlaut/sharp S normalization
Add `hindi_normalization` tokenfilter: accounts for hindi spelling differences
Add `indic_normalization` tokenfilter: accounts for different unicode representations in Indian languages
Add `sorani_normalization` tokenfilter: normalizes kurdish text
Add `scandinavian_normalization` tokenfilter: normalizes Norwegian, Danish, Swedish text
Add `scandinavian_folding` tokenfilter: much more aggressive form of `scandinavian_normalization`
Add additional languages to stemmer tokenfilter: `galician`, `minimal_galician`, `irish`, `sorani`, `light_nynorsk`, `minimal_nynorsk`
Add support access to default Thai stopword set "_thai_"
Fix some bugs and broken links in documentation.
Closes#5935
James Rodewig
Andrei Balici
Jim Ferenczi
Christoph Büscher
Mayya Sharipova
Peter Dyson
Julie Tibshirani
Josh Soref
Itamar Syn-Hershko
Jason Tedor
Adrien Grand
Christoph Büscher
Clinton Gormley
Neil Rickards
Simon Willnauer
Andy Bristol
Shubham Aggarwal
Allen Torres
Pascal Borreli
Nik Everett
Mikhail Korobov
Robert Muir
Richard Boulton
Yousef