How to speed up PG restore in PostgreSQL?

How to speed up PG restore in PostgreSQL?

If you are using PostgreSQL 8.4.x you can potentially speed up the restore from a -Fc backup with the new pg_restore command-line option “-j n” where n=number of parallel connections to use for the restore. This will allow pg_restore to load more than one table’s data or generate more than one index at the same time.

When to use PG _ dump instead of PG _ restore?

For backup of large databases you should setup continuous archiving instead of pg_dump. Set up WAL archiving. A restore would be as simple as restoring database and WAL logs not older than pg_start_backup time from backup location and starting Postgres.

Can you load more than one table in PG _ restore?

This will allow pg_restore to load more than one table’s data or generate more than one index at the same time. I assume you need backup, not a major upgrade of database.

How to improve PostgreSQL parallel restore in 8.4?

If you are on 8.4 also experiment with parallel restore, the –jobs option for pg_restore. PG_RESTORE | always use tuning for postgres.conf and format-directory and -j options

How to take a backup and restore a PostgreSQL table?

1. Take backup of table using pg_dump. 2. SCP the backup file from source to target (copy backup file from source to target) 3. Restore the table using psql tool

When to force PG _ restore to prompt for password?

Force pg_restore to prompt for a password before connecting to a database. This option is never essential, since pg_restore will automatically prompt for a password if the server demands password authentication. However, pg_restore will waste a connection attempt finding out that the server wants a password.

Which is the best way to load PostgreSQL database?

The usage of pg_dump is generally recommended to be paired with pg_restore, instead of psql. This method can be split among cores to speed up the loading process by passing the –jobs flag as such: $ pg_restore –jobs=8 dump.sql Postgres themselves have a guide on bulk loading of data.