314 lines
12 KiB
Markdown
314 lines
12 KiB
Markdown
---
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stage: Enablement
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group: Database
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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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# Adding Database Indexes
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Indexes can be used to speed up database queries, but when should you add a new
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index? Traditionally the answer to this question has been to add an index for
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every column used for filtering or joining data. For example, consider the
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following query:
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```sql
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SELECT *
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FROM projects
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WHERE user_id = 2;
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```
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Here we are filtering by the `user_id` column and as such a developer may decide
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to index this column.
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While in certain cases indexing columns using the above approach may make sense
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it can actually have a negative impact. Whenever you write data to a table any
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existing indexes need to be updated. The more indexes there are the slower this
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can potentially become. Indexes can also take up quite some disk space depending
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on the amount of data indexed and the index type. For example, PostgreSQL offers
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"GIN" indexes which can be used to index certain data types that can not be
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indexed by regular B-tree indexes. These indexes however generally take up more
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data and are slower to update compared to B-tree indexes.
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Because of all this one should not blindly add a new index for every column used
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to filter data by. Instead one should ask themselves the following questions:
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1. Can I write my query in such a way that it re-uses as many existing indexes
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as possible?
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1. Is the data going to be large enough that using an index will actually be
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faster than just iterating over the rows in the table?
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1. Is the overhead of maintaining the index worth the reduction in query
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timings?
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We'll explore every question in detail below.
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## Re-using Queries
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The first step is to make sure your query re-uses as many existing indexes as
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possible. For example, consider the following query:
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```sql
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SELECT *
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FROM todos
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WHERE user_id = 123
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AND state = 'open';
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```
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Now imagine we already have an index on the `user_id` column but not on the
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`state` column. One may think this query will perform badly due to `state` being
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unindexed. In reality the query may perform just fine given the index on
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`user_id` can filter out enough rows.
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The best way to determine if indexes are re-used is to run your query using
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`EXPLAIN ANALYZE`. Depending on any extra tables that may be joined and
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other columns being used for filtering you may find an extra index is not going
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to make much (if any) difference. On the other hand you may determine that the
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index _may_ make a difference.
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In short:
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1. Try to write your query in such a way that it re-uses as many existing
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indexes as possible.
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1. Run the query using `EXPLAIN ANALYZE` and study the output to find the most
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ideal query.
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## Data Size
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A database may decide not to use an index despite it existing in case a regular
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sequence scan (= simply iterating over all existing rows) is faster. This is
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especially the case for small tables.
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If a table is expected to grow in size and you expect your query has to filter
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out a lot of rows you may want to consider adding an index. If the table size is
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very small (for example, fewer than `1,000` records) or any existing indexes filter out
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enough rows you may _not_ want to add a new index.
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## Maintenance Overhead
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Indexes have to be updated on every table write. In case of PostgreSQL _all_
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existing indexes will be updated whenever data is written to a table. As a
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result of this having many indexes on the same table will slow down writes.
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Because of this one should ask themselves: is the reduction in query performance
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worth the overhead of maintaining an extra index?
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If adding an index reduces SELECT timings by 5 milliseconds but increases
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INSERT/UPDATE/DELETE timings by 10 milliseconds then the index may not be worth
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it. On the other hand, if SELECT timings are reduced but INSERT/UPDATE/DELETE
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timings are not affected you may want to add the index after all.
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## Finding Unused Indexes
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To see which indexes are unused you can run the following query:
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```sql
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SELECT relname as table_name, indexrelname as index_name, idx_scan, idx_tup_read, idx_tup_fetch, pg_size_pretty(pg_relation_size(indexrelname::regclass))
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FROM pg_stat_all_indexes
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WHERE schemaname = 'public'
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AND idx_scan = 0
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AND idx_tup_read = 0
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AND idx_tup_fetch = 0
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ORDER BY pg_relation_size(indexrelname::regclass) desc;
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```
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This query outputs a list containing all indexes that are never used and sorts
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them by indexes sizes in descending order. This query can be useful to
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determine if any previously indexes are useful after all. More information on
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the meaning of the various columns can be found at
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<https://www.postgresql.org/docs/current/monitoring-stats.html>.
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Because the output of this query relies on the actual usage of your database it
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may be affected by factors such as (but not limited to):
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- Certain queries never being executed, thus not being able to use certain
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indexes.
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- Certain tables having little data, resulting in PostgreSQL using sequence
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scans instead of index scans.
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In other words, this data is only reliable for a frequently used database with
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plenty of data and with as many GitLab features enabled (and being used) as
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possible.
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## Requirements for naming indexes
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Indexes with complex definitions need to be explicitly named rather than
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relying on the implicit naming behavior of migration methods. In short,
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that means you **must** provide an explicit name argument for an index
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created with one or more of the following options:
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- `where`
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- `using`
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- `order`
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- `length`
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- `type`
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- `opclass`
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### Considerations for index names
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Index names don't have any significance in the database, so they should
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attempt to communicate intent to others. The most important rule to
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remember is that generic names are more likely to conflict or be duplicated,
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and should not be used. Some other points to consider:
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- For general indexes, use a template, like: `index_{table}_{column}_{options}`.
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- For indexes added to solve a very specific problem, it may make sense
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for the name to reflect their use.
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- Identifiers in PostgreSQL have a maximum length of 63 bytes.
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- Check `db/structure.sql` for conflicts and ideas.
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### Why explicit names are required
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As Rails is database agnostic, it generates an index name only
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from the required options of all indexes: table name and column name(s).
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For example, imagine the following two indexes are created in a migration:
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```ruby
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def up
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add_index :my_table, :my_column
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add_index :my_table, :my_column, where: 'my_column IS NOT NULL'
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end
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```
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Creation of the second index would fail, because Rails would generate
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the same name for both indexes.
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This is further complicated by the behavior of the `index_exists?` method.
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It considers only the table name, column name(s) and uniqueness specification
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of the index when making a comparison. Consider:
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```ruby
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def up
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unless index_exists?(:my_table, :my_column, where: 'my_column IS NOT NULL')
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add_index :my_table, :my_column, where: 'my_column IS NOT NULL'
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end
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end
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```
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The call to `index_exists?` will return true if **any** index exists on
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`:my_table` and `:my_column`, and index creation will be bypassed.
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The `add_concurrent_index` helper is a requirement for creating indexes
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on populated tables. Since it cannot be used inside a transactional
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migration, it has a built-in check that detects if the index already
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exists. In the event a match is found, index creation is skipped.
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Without an explicit name argument, Rails can return a false positive
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for `index_exists?`, causing a required index to not be created
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properly. By always requiring a name for certain types of indexes, the
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chance of error is greatly reduced.
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## Temporary indexes
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There may be times when an index is only needed temporarily.
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For example, in a migration, a column of a table might be conditionally
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updated. To query which columns need to be updated within the
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[query performance guidelines](query_performance.md), an index is needed that would otherwise
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not be used.
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In these cases, a temporary index should be considered. To specify a
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temporary index:
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1. Prefix the index name with `tmp_` and follow the [naming conventions](database/constraint_naming_convention.md) and [requirements for naming indexes](#requirements-for-naming-indexes) for the rest of the name.
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1. Create a follow-up issue to remove the index in the next (or future) milestone.
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1. Add a comment in the migration mentioning the removal issue.
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A temporary migration would look like:
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```ruby
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INDEX_NAME = 'tmp_index_projects_on_owner_where_emails_disabled'
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def up
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# Temporary index to be removed in 13.9 https://gitlab.com/gitlab-org/gitlab/-/issues/1234
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add_concurrent_index :projects, :creator_id, where: 'emails_disabled = false', name: INDEX_NAME
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end
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def down
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remove_concurrent_index_by_name :projects, INDEX_NAME
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end
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```
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## Create indexes asynchronously
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For very large tables, index creation can be a challenge to manage.
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While `add_concurrent_index` creates indexes in a way that does not block
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normal traffic, it can still be problematic when index creation runs for
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many hours. Necessary database operations like `autovacuum` cannot run, and
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on GitLab.com, the deployment process is blocked waiting for index
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creation to finish.
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To limit impact on GitLab.com, a process exists to create indexes
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asynchronously during weekend hours. Due to generally lower levels of
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traffic and lack of regular deployments, this process allows the
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creation of indexes to proceed with a lower level of risk. The below
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sections describe the steps required to use these features:
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1. [Schedule the index to be created](#schedule-the-index-to-be-created).
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1. [Verify the MR was deployed and the index exists in production](#verify-the-mr-was-deployed-and-the-index-exists-in-production).
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1. [Add a migration to create the index synchronously](#add-a-migration-to-create-the-index-synchronously).
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### Schedule the index to be created
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Create an MR with a post-deployment migration which prepares the index
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for asynchronous creation. An example of creating an index using
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the asynchronous index helpers can be seen in the block below. This migration
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enters the index name and definition into the `postgres_async_indexes`
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table. The process that runs on weekends pulls indexes from this
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table and attempt to create them.
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```ruby
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# in db/post_migrate/
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INDEX_NAME = 'index_ci_builds_on_some_column'
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def up
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prepare_async_index :ci_builds, :some_column, name: INDEX_NAME
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end
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def down
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unprepare_async_index :ci_builds, :some_column, name: INDEX_NAME
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end
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```
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### Verify the MR was deployed and the index exists in production
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You can verify if the MR was deployed to GitLab.com by executing
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`/chatops run auto_deploy status <merge_sha>`. To verify existence of
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the index, you can:
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- Use a meta-command in #database-lab, such as: `\d <index_name>`
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- Ensure that the index is not [`invalid`](https://www.postgresql.org/docs/12/sql-createindex.html#:~:text=The%20psql%20%5Cd%20command%20will%20report%20such%20an%20index%20as%20INVALID)
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- Ask someone in #database to check if the index exists
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- With proper access, you can also verify directly on production or in a
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production clone
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### Add a migration to create the index synchronously
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After the index is verified to exist on the production database, create a second
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merge request that adds the index synchronously. The synchronous
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migration results in a no-op on GitLab.com, but you should still add the
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migration as expected for other installations. The below block
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demonstrates how to create the second migration for the previous
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asynchronous example.
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WARNING:
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The responsibility lies on the individual writing the migrations to verify
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the index exists in production before merging a second migration that
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adds the index using `add_concurrent_index`. If the second migration is
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deployed and the index has not yet been created, the index is created
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synchronously when the second migration executes.
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```ruby
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# in db/post_migrate/
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INDEX_NAME = 'index_ci_builds_on_some_column'
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disable_ddl_transaction!
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def up
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add_concurrent_index :ci_builds, :some_column, name: INDEX_NAME
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end
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def down
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remove_concurrent_index_by_name :ci_builds, INDEX_NAME
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end
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```
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