Elasticsearch knowledge

This area is to maintain a compendium of useful information when working with elasticsearch.

Information on how to enable ElasticSearch and perform the initial indexing is kept in https://docs.gitlab.com/ee/integration/elasticsearch.html#enabling-elasticsearch

Initial installation on OS X

It is recommended to use the Docker image. After installing docker you can immediately spin up an instance with

docker run --name elastic55 -p 9200:9200 -p 9300:9300 -e "discovery.type=single-node" docker.elastic.co/elasticsearch/elasticsearch:5.5.3

and use docker stop elastic55 and docker start elastic55 to stop/start it.

Installing on the host

We currently only support Elasticsearch up to 5.5, but brew only has elasticsearch 6, 5.6, and 2.4 available. While 2.4 would work you probably want to test things out in the latest one we support.

In order to install 5.5.2, you would usually have to hunt down an old homebrew-core commit that contains the recipe for it. We've already done the work for you. Simply run:

brew install https://raw.githubusercontent.com/Homebrew/homebrew-core/f1a767645f61112762f05e68a610d89b161faa99/Formula/elasticsearch.rb

There is no need to install any plugins

Experimental indexer

If you're interested on working with the experimental indexer, all you need to do is:

  • git clone git@gitlab.com:gitlab-org/gitlab-elasticsearch-indexer.git
  • make
  • make install

this adds gitlab-elasticsearch-indexer to $GOPATH/bin, please make sure that is in your $PATH. After that GitLab will find it and you'll be able to enable it in the admin settings area.

note: make will not recompile the executable unless you do make clean beforehand

How does it work?

The ElasticSearch integration depends on an external indexer. We ship a ruby indexer by default but are also working on an indexer written in Go. The user must trigger the initial indexing via a rake task, but after this is done GitLab itself will trigger reindexing when required via after_ callbacks on create, update, and destroy that are inherited from /ee/app/models/concerns/elastic/application_search.rb.

All indexing after the initial one is done via ElasticIndexerWorker (sidekiq jobs).

Search queries are generated by the concerns found in ee/app/models/concerns/elastic. These concerns are also in charge of access control, and have been a historic source of security bugs so please pay close attention to them!

Existing Analyzers/Tokenizers/Filters

These are all defined in https://gitlab.com/gitlab-org/gitlab-ee/blob/master/ee/lib/elasticsearch/git/model.rb



Used when indexing blobs' paths. Uses the path_tokenizer and the lowercase and asciifolding filters.

Please see the path_tokenizer explanation below for an example.


Used in blobs and commits. Uses the sha_tokenizer and the lowercase and asciifolding filters.

Please see the sha_tokenizer explanation later below for an example.


Used when indexing a blob's filename and content. Uses the whitespace tokenizer and the filters: code, edgeNGram_filter, lowercase, and asciifolding

The whitespace tokenizer was selected in order to have more control over how tokens are split. For example the string Foo::bar(4) needs to generate tokens like Foo and bar(4) in order to be properly searched.

Please see the code filter for an explanation on how tokens are split.


Not directly used for indexing, but rather used to transform a search input. Uses the whitespace tokenizer and the lowercase and asciifolding filters.



This is a custom tokenizer that uses the edgeNGram tokenizer to allow SHAs to be searcheable by any sub-set of it (minimum of 5 chars).


240c29dc7e becomes:

  • 240c2
  • 240c29
  • 240c29d
  • 240c29dc
  • 240c29dc7
  • 240c29dc7e


This is a custom tokenizer that uses the path_hierarchy tokenizer with reverse: true in order to allow searches to find paths no matter how much or how little of the path is given as input.


'/some/path/application.js' becomes:

  • '/some/path/application.js'
  • 'some/path/application.js'
  • 'path/application.js'
  • 'application.js'



Uses a Pattern Capture token filter to split tokens into more easily searched versions of themselves.


  • "(\\p{Ll}+|\\p{Lu}\\p{Ll}+|\\p{Lu}+)": captures CamelCased and lowedCameCased strings as separate tokens
  • "(\\d+)": extracts digits
  • "(?=([\\p{Lu}]+[\\p{L}]+))": captures CamelCased strings recursively. Ex: ThisIsATest => [ThisIsATest, IsATest, ATest, Test]
  • '"((?:\\"|[^"]|\\")*)"': captures terms inside quotes, removing the quotes
  • "'((?:\\'|[^']|\\')*)'": same as above, for single-quotes
  • '\.([^.]+)(?=\.|\s|\Z)': separate terms with periods in-between
  • '\/?([^\/]+)(?=\/|\b)': separate path terms like/this/one


Uses an Edge NGram token filter to allow inputs with only parts of a token to find the token. For example it would turn glasses into permutations starting with gl and ending with glasses, which would allow a search for "glass" to find the original token glasses


  • Searches can have their own analyzers. Remember to check when editing analyzers
  • Character filters (as opposed to token filters) always replace the original character, so they're not a good choice as they can hinder exact searches