show size of all tables postgres with code examples

In a PostgreSQL database, it is common to have multiple tables with varying sizes. The size of a table can be important for performance tuning and optimization purposes. In this article, we will explore different methods of measuring the size of tables in PostgreSQL and provide code examples for easy adoption.

Method 1: Using the pg_total_relation_size Function
The pg_total_relation_size function is a built-in PostgreSQL function that returns the size of a table in bytes. This function takes the table name as input and returns the size of the table data and its associated indexes. Here is an example of using the pg_total_relation_size function:

SELECT pg_total_relation_size('table_name');

This query will return the size of the table named 'table_name'. The output of this query will be in bytes.

Method 2: Using the pg_table_size Function
The pg_table_size function is another built-in PostgreSQL function that returns the size of a table in bytes. This function returns the size of the table data only and does not include indexes. Here is an example of using the pg_table_size function:

SELECT pg_table_size('table_name');

This query will return the size of the table data for the table named 'table_name'. The output of this query will be in bytes.

Method 3: Using the pg_class and pg_attribute Tables

Another method of measuring table size in PostgreSQL is by using the pg_class and pg_attribute tables. The pg_class table contains information about database objects, including tables, indexes, and sequences. The pg_attribute table contains information about table columns. Here is an example of using these tables to measure the size of a table:

SELECT
relname AS table_name,
relpages::bigint * 8 * 1024 AS table_size
FROM pg_class
WHERE relkind = 'r' AND relname NOT LIKE 'pg_%' AND relname NOT LIKE 'sql_%'
ORDER BY relpages DESC;

This query displays the size of each table in the database by querying the pg_class table. The query filters out system tables and sorts the results by the size of the table. The table size is calculated by multiplying the number of pages by the page size (usually 8KB).

Method 4: Using the \d+ Command in psql

Finally, users can use the \d+ command in the psql terminal to display information about each table in the database. This command returns the same information as the previous method but includes additional details such as the number of rows in the table and the number of attributes. Here is an example of using the \d+ command in psql:

\d+ table_name

This command will display the information for the table named 'table_name'. The output of this command will include the size of the table, the number of rows, and the number of attributes.

Conclusion

Measuring the size of tables is an important task when optimizing the performance of a PostgreSQL database. There are several methods of measuring table size, including the pg_total_relation_size and pg_table_size functions, querying the pg_class and pg_attribute tables, and using the \d+ command in psql. By using these methods, database administrators can easily identify the largest tables and take appropriate actions to optimize their performance.

I'd be happy to provide more information on the previous topics.

Method 1: Using the pg_total_relation_size Function

The pg_total_relation_size function is a very useful built-in PostgreSQL function that returns the total size of a table, including its indexes. This function is particularly useful when you have tables with many indexes, as the size can add up quickly and impact performance. Using this function can help you identify these tables and optimize them accordingly.

It's important to note that the output of pg_total_relation_size is in bytes. This means that the number returned can be quite large for larger tables. It's also important to remember to divide by 1024 or 1024^2 to get the size in kilobytes or megabytes, respectively.

Method 2: Using the pg_table_size Function

The pg_table_size function is similar to pg_total_relation_size, but it only returns the size of the table data itself, and doesn't include indexes. This is useful when you want to focus specifically on the size of the table and don't want to be distracted by the indexes.

One thing to keep in mind when using pg_table_size is that it doesn't include data that's external to the table itself. For example, if your table includes large bytea or text columns that store files, the size of those files won't be included in the output of this function.

Method 3: Using the pg_class and pg_attribute Tables

Using the pg_class and pg_attribute tables to measure the size of tables can be useful when you want to get an overall picture of the sizes of all the tables in your database. This method provides more detailed information than the previous two methods, as it includes the size of indexes, number of rows, and number of attributes for each table.

It's important to filter out system tables in this method to ensure that you're only measuring your actual tables, as opposed to system-generated tables that PostgreSQL uses internally.

Method 4: Using the \d+ Command in psql

The \d+ command in psql provides a convenient way to quickly look up information about a specific table. This command includes information on the size of the table, number of rows, and number of attributes, as well as other useful details such as column names, data types, and constraints.

One downside of using the \d+ command is that you have to run it separately for each table you're interested in. This can be time-consuming if you have many tables in your database.

Conclusion

In conclusion, there are several different methods for measuring the size of tables in PostgreSQL, each with its own advantages and disadvantages. By using these methods, you can get a better understanding of the sizes of your tables and work on optimizing them for performance. It's important to remember to filter out system tables when measuring the size of all tables in the database, and to be mindful of the output units of the functions used (e.g. bytes vs kilobytes vs megabytes).

Popular questions

Sure, here are five questions with answers related to showing the size of all tables in PostgreSQL:

  1. What is the purpose of measuring the size of tables in PostgreSQL?
    Answer: Measuring the size of tables in PostgreSQL is important for optimizing performance. Understanding the size of tables can help identify tables that are too large or inefficiently designed, ultimately leading to better database performance.

  2. What is the difference between the pg_total_relation_size and pg_table_size functions?
    Answer: The pg_total_relation_size function returns the size of a table and its indexes, while the pg_table_size function returns the size of the table data only, without indexes. Depending on your needs, you may want to use one function over the other.

  3. How can the pg_class and pg_attribute tables be used to measure the size of all tables in a PostgreSQL database?
    Answer: The pg_class and pg_attribute tables can be used in combination to measure the size of all tables in your database. By querying the pg_class table for information on all tables, and the pg_attribute table for information on the number of table attributes, you can calculate the size of each table.

  4. What does the \d+ command in psql provide when measuring table size?
    Answer: The \d+ command in psql provides a quick way to look up information about a specific table, including its size, number of rows, and number of attributes, among other useful information.

  5. Why is it important to filter out system tables when measuring the size of all tables in a PostgreSQL database?
    Answer: System tables are tables that PostgreSQL uses internally, and are not part of your actual data. Measuring their size along with your actual tables can skew your results and make it difficult to get a clear understanding of your database's performance. Filtering out system tables ensures that you're only measuring your actual tables.

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As a senior DevOps Engineer, I possess extensive experience in cloud-native technologies. With my knowledge of the latest DevOps tools and technologies, I can assist your organization in growing and thriving. I am passionate about learning about modern technologies on a daily basis. My area of expertise includes, but is not limited to, Linux, Solaris, and Windows Servers, as well as Docker, K8s (AKS), Jenkins, Azure DevOps, AWS, Azure, Git, GitHub, Terraform, Ansible, Prometheus, Grafana, and Bash.

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