gitlab-org--gitlab-foss/doc/integration/elasticsearch.md

Elasticsearch integration (STARTER ONLY)

• Introduced in GitLab Starter 8.4.
• Support for Amazon Elasticsearch was introduced in GitLab Starter 9.0.

This document describes how to set up Elasticsearch with GitLab. Once enabled, you'll have the benefit of fast search response times and the advantage of two special searches:

• Advanced Global Search
• Advanced Syntax Search

Version Requirements

GitLab version	Elasticsearch version
GitLab Enterprise Edition 8.4 - 8.17	Elasticsearch 2.4 with Delete By Query Plugin installed
GitLab Enterprise Edition 9.0 - 11.4	Elasticsearch 5.1 - 5.5
GitLab Enterprise Edition 11.5 - 12.6	Elasticsearch 5.6 - 6.x
GitLab Enterprise Edition 12.7+	Elasticsearch 6.x - 7.x

Installing Elasticsearch

Elasticsearch is not included in the Omnibus packages or when you install from source. You must install it separately. Be sure to select your version. Providing detailed information on installing Elasticsearch is out of the scope of this document.

NOTE: Note: Elasticsearch should be installed on a separate server, whether you install it yourself or use a cloud hosted offering like Elastic's Elasticsearch Service (available on AWS, GCP, or Azure) or the Amazon Elasticsearch service. Running Elasticsearch on the same server as GitLab is not recommended and will likely cause a degradation in GitLab instance performance.

NOTE: Note: For a single node Elasticsearch cluster the functional cluster health status will be yellow (will never be green) because the primary shard is allocated but replicas can not be as there is no other node to which Elasticsearch can assign a replica.

Once the data is added to the database or repository and Elasticsearch is enabled in the Admin Area the search index will be updated automatically.

Elasticsearch repository indexer

For indexing Git repository data, GitLab uses an indexer written in Go.

The way you install the Go indexer depends on your version of GitLab:

• For Omnibus GitLab 11.8 and above, see Omnibus GitLab.
• For installations from source or older versions of Omnibus GitLab, install the indexer From Source.

Omnibus GitLab

Since GitLab 11.8 the Go indexer is included in Omnibus GitLab. The former Ruby-based indexer was removed in GitLab 12.3.

From source

First, we need to install some dependencies, then we'll build and install the indexer itself.

This project relies on ICU for text encoding, therefore we need to ensure the development packages for your platform are installed before running make.

Debian / Ubuntu

To install on Debian or Ubuntu, run:

sudo apt install libicu-dev

CentOS / RHEL

To install on CentOS or RHEL, run:

sudo yum install libicu-devel

Mac OSX

To install on macOS, run:

brew install icu4c
export PKG_CONFIG_PATH="/usr/local/opt/icu4c/lib/pkgconfig:$PKG_CONFIG_PATH"

Building and installing

To build and install the indexer, run:

indexer_path=/home/git/gitlab-elasticsearch-indexer

# Run the installation task for gitlab-elasticsearch-indexer:
sudo -u git -H bundle exec rake gitlab:indexer:install[$indexer_path] RAILS_ENV=production
cd $indexer_path && sudo make install

The gitlab-elasticsearch-indexer will be installed to /usr/local/bin.

You can change the installation path with the PREFIX env variable. Please remember to pass the -E flag to sudo if you do so.

Example:

PREFIX=/usr sudo -E make install

Once installed, enable it under your instance's Elasticsearch settings explained below.

System Requirements

Elasticsearch requires additional resources in excess of those documented in the GitLab system requirements.

The amount of resources (memory, CPU, storage) will vary greatly, based on the amount of data being indexed into the Elasticsearch cluster. According to Elasticsearch official guidelines, each node should have:

• RAM: 8 GiB as the bare minimum
• CPU: Modern processor with multiple cores
• Storage: Use SSD storage. As a guide you will need enough storage for 50% of the total size of your Git repositories.

A few notes on CPU and storage:

• CPU requirements for Elasticsearch tend to be light. There are specific scenarios where this isn't true, but GitLab.com isn't using Elasticsearch in an exceptionally CPU-heavy way. More cores will be more performant than faster CPUs. Extra concurrency from multiple cores will far outweigh a slightly faster clock speed in Elasticsearch.

• Storage requirements for Elasticsearch are important, especially for indexing-heavy clusters. When possible, use SSDs, Their speed is far superior to any spinning media for Elasticsearch. In testing, nodes that use SSD storage see boosts in both query and indexing performance.

Keep in mind, these are minimum requirements for Elasticsearch. Heavily-utilized Elasticsearch clusters will likely require considerably more resources.

Enabling Elasticsearch

In order to enable Elasticsearch, you need to have admin access. Navigate to Admin Area (wrench icon), then Settings > Integrations and expand the Elasticsearch section.

Click Save changes for the changes to take effect.

The following Elasticsearch settings are available:

Parameter	Description
Elasticsearch indexing	Enables/disables Elasticsearch indexing. You may want to enable indexing but disable search in order to give the index time to be fully completed, for example. Also, keep in mind that this option doesn't have any impact on existing data, this only enables/disables background indexer which tracks data changes. So by enabling this you will not get your existing data indexed, use special Rake task for that as explained in Adding GitLab's data to the Elasticsearch index.
Elasticsearch pause indexing	Enables/disables temporary indexing pause. This is useful for cluster migration/reindexing. All changes are still tracked, but they are not committed to the Elasticsearch index until unpaused.
Search with Elasticsearch enabled	Enables/disables using Elasticsearch in search.
URL	The URL to use for connecting to Elasticsearch. Use a comma-separated list to support clustering (e.g., http://host1, https://host2:9200). If your Elasticsearch instance is password protected, pass the username:password in the URL (e.g., http://<username>:<password>@<elastic_host>:9200/).
Number of Elasticsearch shards	Elasticsearch indexes are split into multiple shards for performance reasons. In general, larger indexes need to have more shards. Changes to this value do not take effect until the index is recreated. You can read more about tradeoffs in the Elasticsearch documentation.
Number of Elasticsearch replicas	Each Elasticsearch shard can have a number of replicas. These are a complete copy of the shard, and can provide increased query performance or resilience against hardware failure. Increasing this value will greatly increase total disk space required by the index.
Limit namespaces and projects that can be indexed	Enabling this will allow you to select namespaces and projects to index. All other namespaces and projects will use database search instead. Please note that if you enable this option but do not select any namespaces or projects, none will be indexed. Read more below.
Using AWS hosted Elasticsearch with IAM credentials	Sign your Elasticsearch requests using AWS IAM authorization, AWS EC2 Instance Profile Credentials, or AWS ECS Tasks Credentials. The policies must be configured to allow es:* actions.
AWS Region	The AWS region your Elasticsearch service is located in.
AWS Access Key	The AWS access key.
AWS Secret Access Key	The AWS secret access key.
Maximum file size indexed	See the explanation in instance limits..
Maximum field length	See the explanation in instance limits..
Maximum bulk request size (MiB)	The Maximum Bulk Request size is used by GitLab's Golang-based indexer processes and indicates how much data it ought to collect (and store in memory) in a given indexing process before submitting the payload to Elasticsearch’s Bulk API. This setting should be used with the Bulk request concurrency setting (see below) and needs to accommodate the resource constraints of both the Elasticsearch host(s) and the host(s) running GitLab's Golang-based indexer either from the gitlab-rake command or the Sidekiq tasks.
Bulk request concurrency	The Bulk request concurrency indicates how many of GitLab's Golang-based indexer processes (or threads) can run in parallel to collect data to subsequently submit to Elasticsearch’s Bulk API. This increases indexing performance, but fills the Elasticsearch bulk requests queue faster. This setting should be used together with the Maximum bulk request size setting (see above) and needs to accommodate the resource constraints of both the Elasticsearch host(s) and the host(s) running GitLab's Golang-based indexer either from the gitlab-rake command or the Sidekiq tasks.

Limiting namespaces and projects

If you select Limit namespaces and projects that can be indexed, more options will become available

You can select namespaces and projects to index exclusively. Please note that if the namespace is a group it will include any sub-groups and projects belonging to those sub-groups to be indexed as well.

Elasticsearch only provides cross-group code/commit search (global) if all name-spaces are indexed. In this particular scenario where only a subset of namespaces are indexed, a global search will not provide a code or commit scope. This will be possible only in the scope of an indexed namespace. Currently there is no way to code/commit search in multiple indexed namespaces (when only a subset of namespaces has been indexed). For example if two groups are indexed, there is no way to run a single code search on both. You can only run a code search on the first group and then on the second.

You can filter the selection dropdown by writing part of the namespace or project name you're interested in.

NOTE: Note: If no namespaces or projects are selected, no Elasticsearch indexing will take place.

CAUTION: Warning: If you have already indexed your instance, you will have to regenerate the index in order to delete all existing data for filtering to work correctly. To do this run the Rake tasks gitlab:elastic:recreate_index and gitlab:elastic:clear_index_status. Afterwards, removing a namespace or a project from the list will delete the data from the Elasticsearch index as expected.

Disabling Elasticsearch

To disable the Elasticsearch integration:

1. Navigate to the Admin Area (wrench icon), then Settings > Integrations.

2. Expand the Elasticsearch section and uncheck Elasticsearch indexing and Search with Elasticsearch enabled.

3. Click Save changes for the changes to take effect.

4. (Optional) Delete the existing index:

   # Omnibus installations
   sudo gitlab-rake gitlab:elastic:delete_index
   
   # Installations from source
   bundle exec rake gitlab:elastic:delete_index RAILS_ENV=production
   

Adding GitLab's data to the Elasticsearch index

While Elasticsearch indexing is enabled, new changes in your GitLab instance will be automatically indexed as they happen. To backfill existing data, you can use one of the methods below to index it in background jobs.

Indexing through the administration UI

Introduced in GitLab Starter 12.3.

To index via the Admin Area:

1. Configure your Elasticsearch host and port.

2. Create empty indexes:

   # Omnibus installations
   sudo gitlab-rake gitlab:elastic:create_empty_index
   
   # Installations from source
   bundle exec rake gitlab:elastic:create_empty_index RAILS_ENV=production
   

3. Enable Elasticsearch indexing.

4. Click Index all projects in Admin Area > Settings > Integrations > Elasticsearch.

5. Click Check progress in the confirmation message to see the status of the background jobs.

6. Personal snippets need to be indexed manually:

   # Omnibus installations
   sudo gitlab-rake gitlab:elastic:index_snippets
   
   # Installations from source
   bundle exec rake gitlab:elastic:index_snippets RAILS_ENV=production
   

7. After the indexing has completed, enable Search with Elasticsearch.

Indexing through Rake tasks

Indexing can be performed using Rake tasks.

Indexing small instances

CAUTION: Warning: This will delete your existing indexes.

If the database size is less than 500 MiB, and the size of all hosted repos is less than 5 GiB:

1. Configure your Elasticsearch host and port.

2. Index your data:

   # Omnibus installations
   sudo gitlab-rake gitlab:elastic:index
   
   # Installations from source
   bundle exec rake gitlab:elastic:index RAILS_ENV=production
   

3. After the indexing has completed, enable Search with Elasticsearch.

Indexing large instances

CAUTION: Warning: Performing asynchronous indexing will generate a lot of Sidekiq jobs. Make sure to prepare for this task by having a Scalable and Highly Available Setup or creating extra Sidekiq processes

1. Configure your Elasticsearch host and port.

2. Create empty indexes:

   # Omnibus installations
   sudo gitlab-rake gitlab:elastic:create_empty_index
   
   # Installations from source
   bundle exec rake gitlab:elastic:create_empty_index RAILS_ENV=production
   

3. If this is a re-index of your GitLab instance, clear the index status:

   # Omnibus installations
   sudo gitlab-rake gitlab:elastic:clear_index_status
   
   # Installations from source
   bundle exec rake gitlab:elastic:clear_index_status RAILS_ENV=production
   

4. Enable Elasticsearch indexing.

5. Indexing large Git repositories can take a while. To speed up the process, you can tune for indexing speed:

   • You can temporarily disable refresh, the operation responsible for making changes to an index available to search.

   • You can set the number of replicas to 0. This setting controls the number of copies each primary shard of an index will have. Thus, having 0 replicas effectively disables the replication of shards across nodes, which should increase the indexing performance. This is an important trade-off in terms of reliability and query performance. It is important to remember to set the replicas to a considered value after the initial indexing is complete.

   In our experience, you can expect a 20% decrease in indexing time. After completing indexing in a later step, you can return refresh and number_of_replicas to their desired settings.

   NOTE: Note: This step is optional but may help significantly speed up large indexing operations.

   curl --request PUT localhost:9200/gitlab-production/_settings --header 'Content-Type: application/json' --data '{
       "index" : {
           "refresh_interval" : "-1",
           "number_of_replicas" : 0
       } }'
   

6. Index projects and their associated data:

   # Omnibus installations
   sudo gitlab-rake gitlab:elastic:index_projects
   
   # Installations from source
   bundle exec rake gitlab:elastic:index_projects RAILS_ENV=production
   

   This enqueues a Sidekiq job for each project that needs to be indexed. You can view the jobs in Admin Area > Monitoring > Background Jobs > Queues Tab and click elastic_indexer, or you can query indexing status using a Rake task:

   # Omnibus installations
   sudo gitlab-rake gitlab:elastic:index_projects_status
   
   # Installations from source
   bundle exec rake gitlab:elastic:index_projects_status RAILS_ENV=production
   
   Indexing is 65.55% complete (6555/10000 projects)
   

   If you want to limit the index to a range of projects you can provide the ID_FROM and ID_TO parameters:

   # Omnibus installations
   sudo gitlab-rake gitlab:elastic:index_projects ID_FROM=1001 ID_TO=2000
   
   # Installations from source
   bundle exec rake gitlab:elastic:index_projects ID_FROM=1001 ID_TO=2000 RAILS_ENV=production
   

   Where ID_FROM and ID_TO are project IDs. Both parameters are optional. The above example will index all projects from ID 1001 up to (and including) ID 2000.

   TIP: Troubleshooting: Sometimes the project indexing jobs queued by gitlab:elastic:index_projects can get interrupted. This may happen for many reasons, but it's always safe to run the indexing task again. It will skip repositories that have already been indexed.

   As the indexer stores the last commit SHA of every indexed repository in the database, you can run the indexer with the special parameter UPDATE_INDEX and it will check every project repository again to make sure that every commit in a repository is indexed, which can be useful in case if your index is outdated:

   # Omnibus installations
   sudo gitlab-rake gitlab:elastic:index_projects UPDATE_INDEX=true ID_TO=1000
   
   # Installations from source
   bundle exec rake gitlab:elastic:index_projects UPDATE_INDEX=true ID_TO=1000 RAILS_ENV=production
   

   You can also use the gitlab:elastic:clear_index_status Rake task to force the indexer to "forget" all progress, so it will retry the indexing process from the start.

7. Personal snippets are not associated with a project and need to be indexed separately:

   # Omnibus installations
   sudo gitlab-rake gitlab:elastic:index_snippets
   
   # Installations from source
   bundle exec rake gitlab:elastic:index_snippets RAILS_ENV=production
   

8. Enable replication and refreshing again after indexing (only if you previously disabled it):

   curl --request PUT localhost:9200/gitlab-production/_settings --header 'Content-Type: application/json' --data '{
       "index" : {
           "number_of_replicas" : 1,
           "refresh_interval" : "1s"
       } }'
   

   A force merge should be called after enabling the refreshing above.

   For Elasticsearch 6.x, the index should be in read-only mode before proceeding with the force merge:

   curl --request PUT localhost:9200/gitlab-production/_settings --header 'Content-Type: application/json' --data '{
     "settings": {
       "index.blocks.write": true
     } }'
   

   Then, initiate the force merge:

   curl --request POST 'localhost:9200/gitlab-production/_forcemerge?max_num_segments=5'
   

   After this, if your index is in read-only mode, switch back to read-write:

   curl --request PUT localhost:9200/gitlab-production/_settings --header 'Content-Type: application/json' --data '{
     "settings": {
       "index.blocks.write": false
     } }'
   

9. After the indexing has completed, enable Search with Elasticsearch.

Indexing limitations

For repository and snippet files, GitLab will only index up to 1 MiB of content, in order to avoid indexing timeouts.

GitLab Elasticsearch Rake tasks

Rake tasks are available to:

• Build and install the indexer.
• Delete indexes when disabling Elasticsearch.
• Add GitLab data to an index.

The following are some available Rake tasks:

Task	Description
sudo gitlab-rake gitlab:elastic:index	Enables Elasticsearch Indexing and run gitlab:elastic:create_empty_index, gitlab:elastic:clear_index_status, gitlab:elastic:index_projects, and gitlab:elastic:index_snippets.
sudo gitlab-rake gitlab:elastic:index_projects	Iterates over all projects and queues Sidekiq jobs to index them in the background.
sudo gitlab-rake gitlab:elastic:index_projects_status	Determines the overall status of the indexing. It is done by counting the total number of indexed projects, dividing by a count of the total number of projects, then multiplying by 100.
sudo gitlab-rake gitlab:elastic:clear_index_status	Deletes all instances of IndexStatus for all projects.
sudo gitlab-rake gitlab:elastic:create_empty_index[<TARGET_NAME>]	Generates an empty index and assigns an alias for it on the Elasticsearch side only if it doesn't already exist.
sudo gitlab-rake gitlab:elastic:delete_index[<TARGET_NAME>]	Removes the GitLab index and alias (if exists) on the Elasticsearch instance.
sudo gitlab-rake gitlab:elastic:recreate_index[<TARGET_NAME>]	Wrapper task for gitlab:elastic:delete_index[<TARGET_NAME>] and gitlab:elastic:create_empty_index[<TARGET_NAME>].
sudo gitlab-rake gitlab:elastic:index_snippets	Performs an Elasticsearch import that indexes the snippets data.
sudo gitlab-rake gitlab:elastic:projects_not_indexed	Displays which projects are not indexed.
sudo gitlab-rake gitlab:elastic:reindex_cluster	Schedules a zero-downtime cluster reindexing task. This feature should be used with an index that was created after GitLab 13.0.

NOTE: Note: The TARGET_NAME parameter is optional and will use the default index/alias name from the current RAILS_ENV if not set.

Environment variables

In addition to the Rake tasks, there are some environment variables that can be used to modify the process:

Environment Variable	Data Type	What it does
UPDATE_INDEX	Boolean	Tells the indexer to overwrite any existing index data (true/false).
ID_TO	Integer	Tells the indexer to only index projects less than or equal to the value.
ID_FROM	Integer	Tells the indexer to only index projects greater than or equal to the value.

Indexing a specific project

Because the ID_TO and ID_FROM environment variables use the or equal to comparison, you can index only one project by using both these variables with the same project ID number:

root@git:~# sudo gitlab-rake gitlab:elastic:index_projects ID_TO=5 ID_FROM=5
Indexing project repositories...I, [2019-03-04T21:27:03.083410 #3384]  INFO -- : Indexing GitLab User / test (ID=33)...
I, [2019-03-04T21:27:05.215266 #3384]  INFO -- : Indexing GitLab User / test (ID=33) is done!

Elasticsearch index scopes

When performing a search, the GitLab index will use the following scopes:

Scope Name	What it searches
commits	Commit data
projects	Project data (default)
blobs	Code
issues	Issue data
merge_requests	Merge Request data
milestones	Milestone data
notes	Note data
snippets	Snippet data
wiki_blobs	Wiki contents

Tuning

Guidance on choosing optimal cluster configuration

For basic guidance on choosing a cluster configuration you may refer to Elastic Cloud Calculator. You can find more information below.

• Generally, you will want to use at least a 2-node cluster configuration with one replica, which will allow you to have resilience. If your storage usage is growing quickly, you may want to plan horizontal scaling (adding more nodes) beforehand.
• It's not recommended to use HDD storage with the search cluster, because it will take a hit on performance. It's better to use SSD storage (NVMe or SATA SSD drives for example).
• You can use the GitLab Performance Tool to benchmark search performance with different search cluster sizes and configurations.
• Heap size should be set to no more than 50% of your physical RAM. Additionally, it shouldn't be set to more than the threshold for zero-based compressed oops. The exact threshold varies, but 26 GB is safe on most systems, but can also be as large as 30 GB on some systems. See Setting the heap size for more details.
• Number of CPUs (CPU cores) per node usually corresponds to the Number of Elasticsearch shards setting described below.
• A good guideline is to ensure you keep the number of shards per node below 20 per GB heap it has configured. A node with a 30GB heap should therefore have a maximum of 600 shards, but the further below this limit you can keep it the better. This will generally help the cluster stay in good health.
• Small shards result in small segments, which increases overhead. Aim to keep the average shard size between at least a few GB and a few tens of GB. Another consideration is the number of documents, you should aim for this simple formula for the number of shards: number of expected documents / 5M +1.
• refresh_interval is a per index setting. You may want to adjust that from default 1s to a bigger value if you don't need data in realtime. This will change how soon you will see fresh results. If that's important for you, you should leave it as close as possible to the default value.
• You might want to raise indices.memory.index_buffer_size to 30% or 40% if you have a lot of heavy indexing operations.

Elasticsearch integration settings guidance

• The Number of Elasticsearch shards setting usually corresponds with the number of CPUs available in your cluster. For example, if you have a 3-node cluster with 4 cores each, this means you will benefit from having at least 3*4=12 shards in the cluster. Please note, it's only possible to change the shards number by using Split index API or by reindexing to a different index with a changed number of shards.
• The Number of Elasticsearch replicas setting should most of the time be equal to 1 (each shard will have 1 replica). Using 0 is not recommended, because losing one node will corrupt the index.

Deleted documents

Whenever a change or deletion is made to an indexed GitLab object (a merge request description is changed, a file is deleted from the master branch in a repository, a project is deleted, etc), a document in the index is deleted. However, since these are "soft" deletes, the overall number of "deleted documents", and therefore wasted space, increases. Elasticsearch does intelligent merging of segments in order to remove these deleted documents. However, depending on the amount and type of activity in your GitLab installation, it's possible to see as much as 50% wasted space in the index.

In general, we recommend simply letting Elasticsearch merge and reclaim space automatically, with the default settings. From Lucene's Handling of Deleted Documents, "Overall, besides perhaps decreasing the maximum segment size, it is best to leave Lucene's defaults as-is and not fret too much about when deletes are reclaimed."

However, some larger installations may wish to tune the merge policy settings:

• Consider reducing the index.merge.policy.max_merged_segment size from the default 5 GB to maybe 2 GB or 3 GB. Merging only happens when a segment has at least 50% deletions. Smaller segment sizes will allow merging to happen more frequently.

  curl --request PUT localhost:9200/gitlab-production/_settings ---header 'Content-Type: application/json' --data '{
    "index" : {
      "merge.policy.max_merged_segment": "2gb"
    }
  }'
  

• You can also adjust index.merge.policy.reclaim_deletes_weight, which controls how aggressively deletions are targeted. But this can lead to costly merge decisions, so we recommend not changing this unless you understand the tradeoffs.

  curl --request PUT localhost:9200/gitlab-production/_settings ---header 'Content-Type: application/json' --data '{
    "index" : {
      "merge.policy.reclaim_deletes_weight": "3.0"
    }
  }'
  

• Do not do a force merge to remove deleted documents. A warning in the documentation states that this can lead to very large segments that may never get reclaimed, and can also cause significant performance or availability issues.

Troubleshooting

Common issues

Here are some common pitfalls and how to overcome them:

• How can I verify my GitLab instance is using Elasticsearch?

  The easiest method is via the rails console (sudo gitlab-rails console) by running the following:

  u = User.find_by_username('your-username')
  s = SearchService.new(u, {:search => 'search_term'})
  pp s.search_objects.class.name
  

  If you see "ActiveRecord::Relation", you are not using Elasticsearch.

  If you see "Kaminari::PaginatableArray" you are using Elasticsearch.

  NOTE: Note: The above instructions are used to verify that GitLab is using Elasticsearch only when indexing all namespaces. This is not to be used for scenarios that only index a subset of namespaces.

• I updated GitLab and now I can't find anything

  We continuously make updates to our indexing strategies and aim to support newer versions of Elasticsearch. When indexing changes are made, it may be necessary for you to reindex after updating GitLab.

• I indexed all the repositories but I can't find anything

  Make sure you indexed all the database data as stated above.

  Beyond that, check via the Elasticsearch Search API to see if the data shows up on the Elasticsearch side.

  If it shows up via the Elasticsearch Search API, check that it shows up via the rails console (sudo gitlab-rails console):

  u = User.find_by_username('your-username')
  s = SearchService.new(u, {:search => 'search_term', :scope => 'blobs'})
  pp s.search_objects.to_a
  

  NOTE: Note: The above instructions are not to be used for scenarios that only index a subset of namespaces.

  See Elasticsearch Index Scopes for more information on searching for specific types of data.

• I indexed all the repositories but then switched Elasticsearch servers and now I can't find anything

  You will need to re-run all the Rake tasks to re-index the database, repositories, and wikis.

• The indexing process is taking a very long time

  The more data present in your GitLab instance, the longer the indexing process takes.

• There are some projects that weren't indexed, but we don't know which ones

  You can run sudo gitlab-rake gitlab:elastic:projects_not_indexed to display projects that aren't indexed.

• "Can't specify parent if no parent field has been configured"

  If you enabled Elasticsearch before GitLab 8.12 and have not rebuilt indexes you will get exception in lots of different cases:

  Elasticsearch::Transport::Transport::Errors::BadRequest([400] {
      "error": {
          "root_cause": [{
              "type": "illegal_argument_exception",
              "reason": "Can't specify parent if no parent field has been configured"
          }],
          "type": "illegal_argument_exception",
          "reason": "Can't specify parent if no parent field has been configured"
      },
      "status": 400
  }):
  

  This is because we changed the index mapping in GitLab 8.12 and the old indexes should be removed and built from scratch again, see details in the update guide.

• Exception Elasticsearch::Transport::Transport::Errors::BadRequest

  If you have this exception (just like in the case above but the actual message is different) please check if you have the correct Elasticsearch version and you met the other requirements. There is also an easy way to check it automatically with sudo gitlab-rake gitlab:check command.

• Exception Elasticsearch::Transport::Transport::Errors::RequestEntityTooLarge

  [413] {"Message":"Request size exceeded 10485760 bytes"}
  

  This exception is seen when your Elasticsearch cluster is configured to reject requests above a certain size (10MiB in this case). This corresponds to the http.max_content_length setting in elasticsearch.yml. Increase it to a larger size and restart your Elasticsearch cluster.

  AWS has fixed limits for this setting ("Maximum Size of HTTP Request Payloads"), based on the size of the underlying instance.

• My single node Elasticsearch cluster status never goes from yellow to green even though everything seems to be running properly

  For a single node Elasticsearch cluster the functional cluster health status will be yellow (will never be green) because the primary shard is allocated but replicas can not be as there is no other node to which Elasticsearch can assign a replica. This also applies if you are using the Amazon Elasticsearch service.

  CAUTION: Warning: Setting the number of replicas to 0 is not something that we recommend (this is not allowed in the GitLab Elasticsearch Integration menu). If you are planning to add more Elasticsearch nodes (for a total of more than 1 Elasticsearch) the number of replicas will need to be set to an integer value larger than 0. Failure to do so will result in lack of redundancy (losing one node will corrupt the index).

  If you have a hard requirement to have a green status for your single node Elasticsearch cluster, please make sure you understand the risks outlined in the previous paragraph and then simply run the following query to set the number of replicas to 0(the cluster will no longer try to create any shard replicas):

  curl --request PUT localhost:9200/gitlab-production/_settings --header 'Content-Type: application/json' --data '{
  "index" : {
     "number_of_replicas" : 0
    }
  }'
  

• I'm getting a health check timeout: no Elasticsearch node available error in Sidekiq during the indexing process

  Gitlab::Elastic::Indexer::Error: time="2020-01-23T09:13:00Z" level=fatal msg="health check timeout: no Elasticsearch node available"
  

  You probably have not used either http:// or https:// as part of your value in the "URL" field of the Elasticsearch Integration Menu. Please make sure you are using either http:// or https:// in this field as the Elasticsearch client for Go that we are using needs the prefix for the URL to be accepted as valid. Once you have corrected the formatting of the URL, delete the index (via the dedicated Rake task) and reindex the content of your instance.

Low-level troubleshooting

There is a more structured, lower-level troubleshooting document for when you experience other issues, including poor performance.

Known Issues

• Elasticsearch code_analyzer doesn't account for all code cases

  The code_analyzer pattern and filter configuration is being evaluated for improvement. We have noticed several edge cases that are not returning expected search results due to our pattern and filter configuration.

  An improved strategy for the code_analyzer pattern and filters are being discussed in issue 29443.

Reverting to basic search

Sometimes there may be issues with your Elasticsearch index data and as such GitLab will allow you to revert to "basic search" when there are no search results and assuming that basic search is supported in that scope. This "basic search" will behave as though you don't have Elasticsearch enabled at all for your instance and search using other data sources (ie. PostgreSQL data and Git data).