8.7 KiB
Elasticsearch knowledge [STARTER ONLY]
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 ../integration/elasticsearch.md#enabling-elasticsearch
Deep Dive
In June 2019, Mario de la Ossa hosted a Deep Dive on GitLab's Elasticsearch integration to share his domain specific knowledge with anyone who may work in this part of the code base in the future. You can find the recording on YouTube, and the slides on Google Slides and in PDF. Everything covered in this deep dive was accurate as of GitLab 12.0, and while specific details may have changed since then, it should still serve as a good introduction.
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 elastic56 -p 9200:9200 -p 9300:9300 -e "discovery.type=single-node" docker.elastic.co/elasticsearch/elasticsearch:5.6.12
and use docker stop elastic56
and docker start elastic56
to stop/start it.
Installing on the host
We currently only support Elasticsearch 5.6 to 6.x
Version 5.6 is available on homebrew and is the recommended version to use in order to test compatibility.
brew install elasticsearch@5.6
There is no need to install any plugins
New repo indexer (beta)
If you're interested on working with the new beta repo 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
Helpful rake tasks
gitlab:elastic:test:index_size
: Tells you how much space the current index is using, as well as how many documents are in the index.gitlab:elastic:test:index_size_change
: Outputs index size, reindexes, and outputs index size again. Useful when testing improvements to indexing size.
Additionally, if you need large repos or multiple forks for testing, please consider following these instructions
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
Analyzers
path_analyzer
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.
sha_analyzer
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.
code_analyzer
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.
code_search_analyzer
Not directly used for indexing, but rather used to transform a search input. Uses the whitespace
tokenizer and the lowercase
and asciifolding
filters.
Tokenizers
sha_tokenizer
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).
Example:
240c29dc7e
becomes:
240c2
240c29
240c29d
240c29dc
240c29dc7
240c29dc7e
path_tokenizer
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.
Example:
'/some/path/application.js'
becomes:
'/some/path/application.js'
'some/path/application.js'
'path/application.js'
'application.js'
Filters
code
Uses a Pattern Capture token filter to split tokens into more easily searched versions of themselves.
Patterns:
"(\\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 termslike/this/one
edgeNGram_filter
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
Gotchas
- 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
Troubleshooting
Getting "flood stage disk watermark [95%] exceeded"
You might get an error such as
[2018-10-31T15:54:19,762][WARN ][o.e.c.r.a.DiskThresholdMonitor] [pval5Ct]
flood stage disk watermark [95%] exceeded on
[pval5Ct7SieH90t5MykM5w][pval5Ct][/usr/local/var/lib/elasticsearch/nodes/0] free: 56.2gb[3%],
all indices on this node will be marked read-only
This is because you've exceeded the disk space threshold - it thinks you don't have enough disk space left, based on the default 95% threshold.
In addition, the read_only_allow_delete
setting will be set to true
. It will block indexing, forcemerge
, etc
curl "http://localhost:9200/gitlab-development/_settings?pretty"
Add this to your elasticsearch.yml
file:
# turn off the disk allocator
cluster.routing.allocation.disk.threshold_enabled: false
or
# set your own limits
cluster.routing.allocation.disk.threshold_enabled: true
cluster.routing.allocation.disk.watermark.flood_stage: 5gb # ES 6.x only
cluster.routing.allocation.disk.watermark.low: 15gb
cluster.routing.allocation.disk.watermark.high: 10gb
Restart Elasticsearch, and the read_only_allow_delete
will clear on it's own.
from "Disk-based Shard Allocation | Elasticsearch Reference" 5.6 and 6.x