I have a Postgres table that has numerous columns which frequently show up in the where clause of select queries. The table has been indexed accordingly, with indexes on all of these columns (mostly single-column indexes, but with some composite indexes thrown in). However, there is one new kind of query that this indexing isn’t fully supporting: queries with a deleted_at is null condition in the where clause (we soft-delete records using this column). Some queries with this are running very slowly despite all of the other columns they use being indexed. Naturally, I want to find a way to improve these queries with a change to our indexing.

I have a Postgres table that has numerous columns which frequently show up in the where clause of select queries. The table has been indexed accordingly, with indexes on all of these columns (mostly single-column indexes, but with some composite indexes thrown in). However, there is one new kind of query that this indexing isn’t fully supporting: queries with a deleted_at is null condition in the where clause (we soft-delete records using this column). Some queries with this are running very slowly despite all of the other columns they use being indexed. Naturally, I want to find a way to improve these queries with a change to our indexing.

I have a Postgres table that has numerous columns which frequently show up in the where clause of select queries. The table has been indexed accordingly, with indexes on all of these columns (mostly single-column indexes, but with some composite indexes thrown in). However, there is one new kind of query that this indexing isn’t fully supporting: queries with a deleted_at is null condition in the where clause (we soft-delete records using this column). Some queries with this are running very slowly despite all of the other columns they use being indexed. Naturally, I want to find a way to improve these queries with a change to our indexing.

I have a Postgres table that has numerous columns which frequently show up in the where clause of select queries. The table has been indexed accordingly, with indexes on all of these columns (mostly single-column indexes, but with some composite indexes thrown in). However, there is one new kind of query that this indexing isn’t fully supporting: queries with a deleted_at is null condition in the where clause (we soft-delete records using this column). Some queries with this are running very slowly despite all of the other columns they use being indexed. Naturally, I want to find a way to improve these queries with a change to our indexing.

I have a Postgres table that has numerous columns which frequently show up in the where clause of select queries. The table has been indexed accordingly, with indexes on all of these columns (mostly single-column indexes, but with some composite indexes thrown in). However, there is one new kind of query that this indexing isn’t fully supporting: queries with a deleted_at is null condition in the where clause (we soft-delete records using this column). Some queries with this are running very slowly despite all of the other columns they use being indexed. Naturally, I want to find a way to improve these queries with a change to our indexing.

I have a Postgres table that has numerous columns which frequently show up in the where clause of select queries. The table has been indexed accordingly, with indexes on all of these columns (mostly single-column indexes, but with some composite indexes thrown in). However, there is one new kind of query that this indexing isn’t fully supporting: queries with a deleted_at is null condition in the where clause (we soft-delete records using this column). Some queries with this are running very slowly despite all of the other columns they use being indexed. Naturally, I want to find a way to improve these queries with a change to our indexing.

I have a Postgres table that has numerous columns which frequently show up in the where clause of select queries. The table has been indexed accordingly, with indexes on all of these columns (mostly single-column indexes, but with some composite indexes thrown in). However, there is one new kind of query that this indexing isn’t fully supporting: queries with a deleted_at is null condition in the where clause (we soft-delete records using this column). Some queries with this are running very slowly despite all of the other columns they use being indexed. Naturally, I want to find a way to improve these queries with a change to our indexing.

I have a Postgres table that has numerous columns which frequently show up in the where clause of select queries. The table has been indexed accordingly, with indexes on all of these columns (mostly single-column indexes, but with some composite indexes thrown in). However, there is one new kind of query that this indexing isn’t fully supporting: queries with a deleted_at is null condition in the where clause (we soft-delete records using this column). Some queries with this are running very slowly despite all of the other columns they use being indexed. Naturally, I want to find a way to improve these queries with a change to our indexing.