Makes the following changes to the `keyword_marker` token filter docs:
* Rewrites description and adds Lucene link
* Adds detailed analyze example
* Rewrites parameter definitions
* Adds custom analyzer and filter example
Adds conceptual docs for token graphs.
These docs cover:
* How a token graph is constructed from a token stream
* How synonyms and multi-position tokens impact token graphs
* How token graphs are used during search
* Why some token filters produce invalid token graphs
Also makes the following supporting changes:
* Adds anchors to the 'Anatomy of an Analyzer' docs for cross-linking
* Adds several SVGs for token graph diagrams
Makes the following changes to the `remove_duplicates` token filter
docs:
* Rewrites description and adds Lucene link
* Adds detailed analyze example
* Adds custom analyzer example
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>
Makes the following changes to the `word_delimiter` token filter docs:
* Adds a warning admonition recommending the `word_delimiter_graph`
filter instead. This warning includes a link to the deprecated Lucene
`WordDelimiterFilter`.
* Updates the description
* Adds detailed analyze snippet
* Adds custom analyzer and custom filter snippets
* Reorganizes and updates parameter documentation
In a tip admonition, we recommend using the `keyword` tokenizer with the
`word_delimiter_graph` token filter. However, we only use the
`whitespace` tokenizer in the example snippets. This updates those
snippets to use the `keyword` tokenizer instead.
Also corrects several spacing issues for arrays in these docs.
Makes the following changes to the `word_delimiter_graph` token filter
docs:
* Updates the Lucene experimental admonition.
* Updates description
* Adds analyze snippet
* Adds custom analyzer and custom filter snippets
* Reorganizes and updates parameter list
* Expands and updates section re: differences between `word_delimiter`
and `word_delimiter_graph`
Per the [Asciidoctor docs][0], Asciidoctor replaces the following
syntax with double arrows in the rendered HTML:
* => renders as ⇒
* <= renders as ⇐
This escapes several unintended replacements, such as in the Painless
docs.
Where appropriate, it also replaces some double arrow instances with
single arrows for consistency.
[0]: https://asciidoctor.org/docs/user-manual/#replacements
Makes the following changes to the `stop` token filter docs:
* Updates description
* Adds a link to the related Lucene filter
* Adds detailed analyze snippet
* Updates custom analyzer and custom filter snippets
* Adds a list of predefined stop words by language
Co-authored-by: ScottieL <36999642+ScottieL@users.noreply.github.com>
Makes the following changes to the `trim` token filter docs:
* Updates description
* Adds a link to the related Lucene filter
* Adds tip about removing whitespace using tokenizers
* Adds detailed analyze snippets
* Adds custom analyzer snippet
* [DOCS] Rewrite analysis intro. Move index/search analysis content.
* Rewrites 'Text analysis' page intro as high-level definition.
Adds guidance on when users should configure text analysis
* Rewrites and splits index/search analysis content:
* Conceptual content -> 'Index and search analysis' under 'Concepts'
* Task-based content -> 'Specify an analyzer' under 'Configure...'
* Adds detailed examples for when to use the same index/search analyzer
and when not.
* Adds new example snippets for specifying search analyzers
* clarifications
* Add toc. Decrement headings.
* Reword 'When to configure' section
* Remove sentence from tip
Adds a 'Configure text analysis' page to house tutorial content for the
analysis topic.
Also relocates the following pages as children as this new page:
* 'Test an analyzer'
* 'Configuring built-in analyzers'
* 'Create a custom analyzer'
I plan to add a tutorial for specifying index-time and search-time
analyzers to this section as part of a future PR.
This helps the topic better match the structure of
our machine learning docs, e.g.
https://www.elastic.co/guide/en/machine-learning/7.5/ml-concepts.html
This PR only includes the 'Anatomy of an analyzer' page as a 'Concepts'
child page, but I plan to add other concepts, such as 'Index time vs.
search time', with later PRs.
* Changes titles to sentence case.
* Appends pages with 'reference' to differentiate their content from
conceptual overviews.
* Moves the 'Normalizers' page to end of the Analysis topic pages.
Adds a 'text analysis overview' page to the analysis topic docs.
The goals of this page are:
* Concisely summarize the analysis process while avoiding in-depth concepts, tutorials, or API examples
* Explain why analysis is important, largely through highlighting problems with full-text searches missing analysis
* Highlight how analysis can be used to improve search results
* Adds a title abbreviation
* Updates the description and adds a Lucene link
* Reformats the parameters section
* Adds analyze, custom analyzer, and custom filter snippets
Relates to #44726.
* Adds a title abbreviation
* Relocates the older name deprecation warning
* Updates the description and adds a Lucene link
* Adds a note to explain payloads and how to store them
* Adds analyze and custom analyzer snippets
* Adds a 'Return stored payloads' example
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.
James Rodewig
lgypro
Jim Ferenczi
rhymes
debadair
PND
Nik Everett
Christoph Büscher
gpaimla