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Managing Indexes in PostgreSQL

An index makes your Postgres queries faster. The index is like a "table of contents" for your data - a reference list which allows queries to quickly locate a row in a given table without needing to scan the entire table (which in large tables can take a long time).

Indexes can be structured in a few different ways. The type of index chosen depends on the values you are indexing. By far the most common index type, and the default in Postgres, is the B-Tree. A B-Tree is the generalized form of a binary search tree, where nodes can have more than two children.

Even though indexes improve query performance, the Postgres query planner may not always make use of a given index when choosing which optimizations to make. Additionally indexes come with some overhead - additional writes and increased storage - so it's useful to understand how and when to use indexes, if at all.

Create an index#

Let's take an example table:


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create table persons (
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id bigint generated by default as identity primary key,
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age int,
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height int,
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weight int,
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name text,
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deceased boolean
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);

We might want to frequently query users based on their age:


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select name from persons where age = 32;

Without an index, Postgres will scan every row in the table to find equality matches on age.

You can verify this by doing an explain on the query:


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explain select name from persons where age = 32;

Outputs:


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Seq Scan on persons (cost=0.00..22.75 rows=x width=y)
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Filter: (age = 32)

To add a simple B-Tree index you can run:


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create index idx_persons_age on persons (age);

Here is a simplified diagram of the index we just created (note that in practice, nodes actually have more than two children).

B-Tree index example in Postgres

You can see that in any large data set, traversing the index to locate a given value can be done in much less operations (O(log n)) than compared to scanning the table one value at a time from top to bottom (O(n)).

Partial indexes#

If you are frequently querying a subset of rows then it may be more efficient to build a partial index. In our example, perhaps we only want to match on age where deceased is false. We could build a partial index:


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create index idx_living_persons_age on persons (age)
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where deceased is false;

Ordering indexes#

By default B-Tree indexes are sorted in ascending order, but sometimes you may want to provide a different ordering. Perhaps our application has a page featuring the top 10 oldest people. Here we would want to sort in descending order, and include NULL values last. For this we can use:


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create index idx_persons_age_desc on persons (age desc nulls last);

Reindexing#

After a while indexes can become stale and may need rebuilding. Postgres provides a reindex command for this, but due to Postgres locks being placed on the index during this process, you may want to make use of the concurrent keyword.


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reindex index concurrently idx_persons_age;

Alternatively you can reindex all indexes on a particular table:


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reindex table concurrently persons;

Take note that reindex can be used inside a transaction, but reindex [index/table] concurrently cannot.