How to use pg_largeobject in PostgreSQL?

The pg_largeobject system table in PostgreSQL is used to store and manage large binary objects (BLOBs) of binary data.

To use pg_largeobject, you need to perform the following steps:

  1. Create a large object: You can create a large object using the lo_create function. It returns an OID (object identifier) that you can use to reference the large object in other functions.
  2. Write to a large object: You can write binary data to a large object using the lo_open function to open a large object for writing and the lo_write function to write binary data.
  3. Read from a large object: You can read binary data from a large object using the lo_open function to open the large object for reading and the lo_read function to read binary data.
  4. Delete a large object: You can delete a large object using the lo_unlink function.

For example, the following code shows how to create a large object, write binary data to it, read binary data from it and finally delete it:

To troubleshoot pg_largeobject performance bottleneck in PostgreSQL, you can follow these steps:

  1. Monitor disk I/O performance: Check the disk I/O performance of the system where PostgreSQL is installed. A high disk I/O can result in slow pg_largeobject performance.
  2. Check disk space: Make sure that the disk has enough space for the pg_largeobject data.
  3. Monitor table size: Check the size of the pg_largeobject table. If the table is too big, it may cause performance issues.
  4. Check table fragmentation: Check the fragmentation of the pg_largeobject table. High fragmentation can lead to slow performance.
  5. Monitor indexes: Check the indexes on the pg_largeobject table. If the indexes are not properly optimized, it can cause performance issues.
  6. Monitor concurrent connections: Monitor the number of concurrent connections to the pg_largeobject table. High concurrency can lead to slow performance.
  7. Check query execution plan: Check the query execution plan of the queries that access the pg_largeobject table. Make sure that the query execution plan is optimized.
  8. Enable logging: Enable logging in PostgreSQL to capture any errors or issues that may be affecting the pg_largeobject performance.
  9. Monitor memory usage: Check the memory usage of the system where PostgreSQL is installed. High memory usage can impact pg_largeobject performance.

By following these steps, you can identify the root cause of the pg_largeobject performance bottleneck in PostgreSQL and take necessary steps to resolve the issue.

About Shiv Iyer 456 Articles
Open Source Database Systems Engineer with a deep understanding of Optimizer Internals, Performance Engineering, Scalability and Data SRE. Shiv currently is the Founder, Investor, Board Member and CEO of multiple Database Systems Infrastructure Operations companies in the Transaction Processing Computing and ColumnStores ecosystem. He is also a frequent speaker in open source software conferences globally.