167 lines
7.7 KiB
Markdown
167 lines
7.7 KiB
Markdown
---
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stage: Enablement
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group: Memory
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info: To determine the technical writer assigned to the Stage/Group associated with this page, see https://about.gitlab.com/handbook/engineering/ux/technical-writing/#assignments
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---
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# Cached queries guidelines
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Rails provides an [SQL query cache](https://guides.rubyonrails.org/caching_with_rails.html#sql-caching)
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which is used to cache the results of database queries for the duration of a request.
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When Rails encounters the same query again within the same request, it uses the cached
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result set instead of running the query against the database again.
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The query results are only cached for the duration of that single request, and
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don't persist across multiple requests.
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## Why cached queries are considered bad
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Cached queries help by reducing the load on the database, but they still:
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- Consume memory.
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- Require Rails to re-instantiate each `ActiveRecord` object.
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- Require Rails to re-instantiate each relation of the object.
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- Make us spend additional CPU cycles to look into a list of cached queries.
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Although cached queries are cheaper from a database perspective, they are potentially
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more expensive from a memory perspective. They could mask
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[N+1 query problems](https://guides.rubyonrails.org/active_record_querying.html#eager-loading-associations),
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so you should treat them the same way you treat regular N+1 queries.
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In cases of N+1 queries masked by cached queries, the same query is executed N times.
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It doesn't hit the database N times but instead returns the cached results N times.
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This is still expensive because you need to re-initialize objects each time at a
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greater expense to the CPU and memory resources. Instead, you should use the same
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in-memory objects whenever possible.
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When you introduce a new feature, you should:
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- Avoid N+1 queries.
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- Minimize the [query count](merge_request_performance_guidelines.md#query-counts).
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- Pay special attention to ensure
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[cached queries](merge_request_performance_guidelines.md#cached-queries) are not
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masking N+1 problems.
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## How to detect cached queries
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### Detect potential offenders by using Kibana
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GitLab.com, logs entries with the number of executed cached queries in the
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`pubsub-redis-inf-gprd*` index as
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[`db_cached_count`](https://log.gprd.gitlab.net/goto/77d18d80ad84c5df1bf1da5c2cd35b82).
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You can filter by endpoints that have a large number of executed cached queries. For
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example, an endpoint with a `db_cached_count` greater than 100 can indicate an N+1 problem which
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is masked by cached queries. You should investigate this endpoint further to determine
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if it is indeed executing duplicated cached queries.
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For more Kibana visualizations related to cached queries, read
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[issue #259007, 'Provide metrics that would help us to detect the potential N+1 CACHED SQL calls'](https://gitlab.com/gitlab-org/gitlab/-/issues/259007).
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### Inspect suspicious endpoints using the Performance Bar
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When building features, use the
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[performance bar](../administration/monitoring/performance/performance_bar.md)
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to view the list of database queries, including cached queries. The
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performance bar shows a warning when the number of total executed and cached queries is
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greater than 100.
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To learn more about the statistics available to you, read the
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[Performance Bar documentation](../administration/monitoring/performance/performance_bar.md).
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## What to look for
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Using [Kibana](#detect-potential-offenders-by-using-kibana), you can look for a large number
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of executed cached queries. Endpoints with a large `db_cached_count` could suggest a large number
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of duplicated cached queries, which often indicates a masked N+1 problem.
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When you investigate a specific endpoint, use
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the [performance bar](#inspect-suspicious-endpoints-using-the-performance-bar)
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to identify similar and cached queries, which may also indicate an N+1 query issue
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(or a similar kind of query batching problem).
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### An example
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For example, let's debug the "Group Members" page. In the left corner of the
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performance bar, **Database queries** shows the total number of database queries
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and the number of executed cached queries:
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![Performance Bar Database Queries](img/performance_bar_members_page.png)
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The page included 55 cached queries. Clicking the number displays a modal window
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with more details about queries. Cached queries are marked with the `cached` label
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below the query. You can see multiple duplicate cached queries in this modal window:
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![Performance Bar Cached Queries Modal](img/performance_bar_cached_queries.png)
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Click **...** to expand the actual stack trace:
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```ruby
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[
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"app/models/group.rb:305:in `has_owner?'",
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"ee/app/views/shared/members/ee/_license_badge.html.haml:1",
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"app/helpers/application_helper.rb:19:in `render_if_exists'",
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"app/views/shared/members/_member.html.haml:31",
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"app/views/groups/group_members/index.html.haml:75",
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"app/controllers/application_controller.rb:134:in `render'",
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"ee/lib/gitlab/ip_address_state.rb:10:in `with'",
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"ee/app/controllers/ee/application_controller.rb:44:in `set_current_ip_address'",
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"app/controllers/application_controller.rb:493:in `set_current_admin'",
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"lib/gitlab/session.rb:11:in `with_session'",
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"app/controllers/application_controller.rb:484:in `set_session_storage'",
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"app/controllers/application_controller.rb:478:in `set_locale'",
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"lib/gitlab/error_tracking.rb:52:in `with_context'",
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"app/controllers/application_controller.rb:543:in `sentry_context'",
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"app/controllers/application_controller.rb:471:in `block in set_current_context'",
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"lib/gitlab/application_context.rb:54:in `block in use'",
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"lib/gitlab/application_context.rb:54:in `use'",
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"lib/gitlab/application_context.rb:21:in `with_context'",
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"app/controllers/application_controller.rb:463:in `set_current_context'",
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"lib/gitlab/jira/middleware.rb:19:in `call'"
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]
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```
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The stack trace shows an N+1 problem, because the code repeatedly executes
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`group.has_owner?(current_user)` for each group member. To solve this issue,
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move the repeated line of code outside of the loop, passing the result to each rendered member instead:
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```erb
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- current_user_is_group_owner = @group && @group.has_owner?(current_user)
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= render partial: 'shared/members/member',
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collection: @members, as: :member,
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locals: { membership_source: @group,
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group: @group,
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current_user_is_group_owner: current_user_is_group_owner }
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```
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After [fixing the cached query](https://gitlab.com/gitlab-org/gitlab/-/merge_requests/44626/diffs#27c2761d66e496495be07d0925697f7e62b5bd14), the performance bar now shows only
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6 cached queries:
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![Performance Bar Fixed Cached Queries](img/performance_bar_fixed_cached_queries.png)
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## How to measure the impact of the change
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Use the [memory profiler](performance.md#using-memory-profiler) to profile your code.
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For [this example](#an-example), wrap the profiler around the `Groups::GroupMembersController#index` action. Before the fix, the application had
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the following statistics:
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- Total allocated: 7133601 bytes (84858 objects)
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- Total retained: 757595 bytes (6070 objects)
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- `db_count`: 144
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- `db_cached_count`: 55
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- `db_duration`: 303ms
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The fix reduced the allocated memory, and the number of cached queries. These
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factors help improve the overall execution time:
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- Total allocated: 5313899 bytes (65290 objects), 1810KB (25%) less
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- Total retained: 685593 bytes (5278 objects), 72KB (9%) less
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- `db_count`: 95 (34% less)
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- `db_cached_count`: 6 (89% less)
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- `db_duration`: 162ms (87% faster)
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## For more information
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- [Metrics that would help us detect the potential N+1 Cached SQL calls](https://gitlab.com/gitlab-org/gitlab/-/issues/259007)
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- [Merge request performance guidelines for cached queries](merge_request_performance_guidelines.md#cached-queries)
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- [Improvements for biggest offenders](https://gitlab.com/groups/gitlab-org/-/epics/4508)
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