How can I optimize Postgres query performance with indexing?

By
William Rossbach
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Asked By TechExplorer92 On

I'm working with Postgres version 17 and have a crucial UI query that's currently taking over 7 seconds to run. Our goal is to reduce this response time to around 1 second. I noticed that a full table scan of the 'orders' table and a nested loop with the 'event_audit_log' table are using up significant resources, so I want to know how to address this. I'm new to indexing strategies in Postgres and have some specific questions about creating suitable indexes:

1) For the 'event_audit_log' table, should I create a composite index on the columns (request_id, created_at, event_comment_text) or just a covering index on (request_id, created_at) with an "include" clause for event_comment_text? When should covering indexes be used in Postgres?

2) Regarding the 'orders' table, should I use a covering index on (entity_id, due_date, order_type) with an include clause for (firm_dspt_case_id), or just a composite index on (entity_id, due_date, order_type)?

3) For columns used as range operators like created_at or due_date, should they be the leading column in the composite index, or can they be non-leading?

4 Answers

Answered By DataWhiz42 On

It would definitely help to share the complete table schema using `d+

`; that can give us a clearer picture of your setup. Also, you might want to consider the specific data distributions in your 'orders' table, since it seems like most of your orders are of type TYPE_A and TYPE_B, so indexing on those could be crucial. Remember, the optimizer may not always pick the existing index, so checking its selectivity is important too.

CuriousCoder07 -

Here's the table definition I pulled from DBeaver: [link to schema]. With the order_type being predominantly TYPE_A and TYPE_B, it seems like a dedicated index could help narrow down your searches effectively. Also, if the 'due_date' index isn't utilized by the optimizer, maybe consider including the 'entity_id' in that index to enhance performance further.

Answered By IndexGuru31 On

For the 'event_audit_log' table, a composite index would be beneficial if your queries frequently search on all three fields. However, if only two columns are heavily queried, a covering index might be more efficient. A general rule of thumb is to check the query plan to see how each index impacts performance. Also, range columns like created_at should typically be leading in your index; that usually offers better performance.

Answered By PGWizard22 On

You might want to consider a slightly different strategy for your indexes. Look at the query performance and consider using partial indexes if your queries often filter repeatedly on specific criteria. This could drastically reduce response times. Monitoring your table scans and adjusting indexes based on actual query usage patterns could provide further optimization!

DevOpsJoe -

Absolutely! Pay attention to the shared hits and costs in your query execution plans; that will give you context on how to tweak your indexes. Since you're dealing with heavy scans, focusing on the most queried fields will certainly help you nail down those 7+ seconds to under a second.

Answered By QueryNinja84 On

As someone who's worked with various databases, start by optimizing the core queries on your 'orders' table and ensure the filtering constraints are being enforced. If event_comment_text is being searched inefficiently first, try restructuring your query. Consider breaking it down with subqueries that leverage appropriate indexes; that'll cut down the processing time significantly!

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