Organizations use tons of data! On traditional PCs from the past, processing such vast amount of information will literally blow it up. Luckily Nowadays, CPUs have a vast amount of cores available. Applications are now able to send queries in parallel to databases.
When it comes to reporting queries that work with a vast number of table rows and data, the ability of a query to utilize multiple CPU threads/cores can significantly improve the speed of its execution. Hence, parallel query execution is a powerful tool that enables faster processing of large data sets.
How is this achieved in PostgreSQL?
Well, it is implemented by utilization of more then one CPUs to process a single query. It is analogous to making more than one person to work on single task to speed it up.
To make use of Parallel Query processing in PostgreSQL, you need to use the SET max_parallel_workers_per_gather=4 command.
The above command sets the maximum number of parallel workers that can be used by a single Gather or Gather Merge node in a query plan.
Benefits of using Parallel Query Processing
It is quite understandable and easy to figure it out by now that parallel query processing is extremely beneficial, especially for large databases.
Following are some of the most prominent advantages you can get:
Faster Query Execution
Increased Efficiency
Easy of working with large databases and complex queries.
Conclusion
PostgreSQL aids developers and database managers working with huge databases by providing the option to process queries in parallel. This can enhance work productivity and make queries faster. You can learn more about this through Postgres documentation on Parallel Query
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