debian-mirror-gitlab/doc/development/adding_database_indexes.md

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Adding Database Indexes

Indexes can be used to speed up database queries, but when should you add a new index? Traditionally the answer to this question has been to add an index for every column used for filtering or joining data. For example, consider the following query:

SELECT *
FROM projects
WHERE user_id = 2;

Here we are filtering by the user_id column and as such a developer may decide to index this column.

While in certain cases indexing columns using the above approach may make sense it can actually have a negative impact. Whenever you write data to a table any existing indexes need to be updated. The more indexes there are the slower this can potentially become. Indexes can also take up quite some disk space depending on the amount of data indexed and the index type. For example, PostgreSQL offers "GIN" indexes which can be used to index certain data types that can not be indexed by regular B-tree indexes. These indexes however generally take up more data and are slower to update compared to B-tree indexes.

Because of all this one should not blindly add a new index for every column used to filter data by. Instead one should ask themselves the following questions:

1. Can I write my query in such a way that it re-uses as many existing indexes as possible?
2. Is the data going to be large enough that using an index will actually be faster than just iterating over the rows in the table?
3. Is the overhead of maintaining the index worth the reduction in query timings?

We'll explore every question in detail below.

Re-using Queries

The first step is to make sure your query re-uses as many existing indexes as possible. For example, consider the following query:

SELECT *
FROM todos
WHERE user_id = 123
AND state = 'open';

Now imagine we already have an index on the user_id column but not on the state column. One may think this query will perform badly due to state being unindexed. In reality the query may perform just fine given the index on user_id can filter out enough rows.

The best way to determine if indexes are re-used is to run your query using EXPLAIN ANALYZE. Depending on any extra tables that may be joined and other columns being used for filtering you may find an extra index is not going to make much (if any) difference. On the other hand you may determine that the index may make a difference.

In short:

1. Try to write your query in such a way that it re-uses as many existing indexes as possible.
2. Run the query using EXPLAIN ANALYZE and study the output to find the most ideal query.

Data Size

A database may decide not to use an index despite it existing in case a regular sequence scan (= simply iterating over all existing rows) is faster. This is especially the case for small tables.

If a table is expected to grow in size and you expect your query has to filter out a lot of rows you may want to consider adding an index. If the table size is very small (e.g. less than 1,000 records) or any existing indexes filter out enough rows you may not want to add a new index.

Maintenance Overhead

Indexes have to be updated on every table write. In case of PostgreSQL all existing indexes will be updated whenever data is written to a table. As a result of this having many indexes on the same table will slow down writes.

Because of this one should ask themselves: is the reduction in query performance worth the overhead of maintaining an extra index?

If adding an index reduces SELECT timings by 5 milliseconds but increases INSERT/UPDATE/DELETE timings by 10 milliseconds then the index may not be worth it. On the other hand, if SELECT timings are reduced but INSERT/UPDATE/DELETE timings are not affected you may want to add the index after all.

Finding Unused Indexes

To see which indexes are unused you can run the following query:

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))
FROM pg_stat_all_indexes
WHERE schemaname = 'public'
AND idx_scan = 0
AND idx_tup_read = 0
AND idx_tup_fetch = 0
ORDER BY pg_relation_size(indexrelname::regclass) desc;

This query outputs a list containing all indexes that are never used and sorts them by indexes sizes in descending order. This query can be useful to determine if any previously indexes are useful after all. More information on the meaning of the various columns can be found at https://www.postgresql.org/docs/current/monitoring-stats.html.

Because the output of this query relies on the actual usage of your database it may be affected by factors such as (but not limited to):

• Certain queries never being executed, thus not being able to use certain indexes.
• Certain tables having little data, resulting in PostgreSQL using sequence scans instead of index scans.

In other words, this data is only reliable for a frequently used database with plenty of data and with as many GitLab features enabled (and being used) as possible.

Requirements for naming indexes

Indexes with complex definitions need to be explicitly named rather than relying on the implicit naming behavior of migration methods. In short, that means you must provide an explicit name argument for an index created with one or more of the following options:

• where
• using
• order
• length
• type
• opclass

Considerations for index names

Index names don't have any significance in the database, so they should attempt to communicate intent to others. The most important rule to remember is that generic names are more likely to conflict or be duplicated, and should not be used. Some other points to consider:

• For general indexes, use a template, like: index_{table}_{column}_{options}.
• For indexes added to solve a very specific problem, it may make sense for the name to reflect their use.
• Identifiers in PostgreSQL have a maximum length of 63 bytes.
• Check db/structure.sql for conflicts and ideas.

Why explicit names are required

As Rails is database agnostic, it generates an index name only from the required options of all indexes: table name and column name(s). For example, imagine the following two indexes are created in a migration:

def up
  add_index :my_table, :my_column

  add_index :my_table, :my_column, where: 'my_column IS NOT NULL'
end

Creation of the second index would fail, because Rails would generate the same name for both indexes.

This is further complicated by the behavior of the index_exists? method. It considers only the table name, column name(s) and uniqueness specification of the index when making a comparison. Consider:

def up
  unless index_exists?(:my_table, :my_column, where: 'my_column IS NOT NULL')
    add_index :my_table, :my_column, where: 'my_column IS NOT NULL'
  end
end

The call to index_exists? will return true if any index exists on :my_table and :my_column, and index creation will be bypassed.

The add_concurrent_index helper is a requirement for creating indexes on populated tables. Since it cannot be used inside a transactional migration, it has a built-in check that detects if the index already exists. In the event a match is found, index creation is skipped. Without an explicit name argument, Rails can return a false positive for index_exists?, causing a required index to not be created properly. By always requiring a name for certain types of indexes, the chance of error is greatly reduced.