1. Causes of insufficient storage space
1. Rapid growth in data volume
With the development of the business, data continues to accumulate, which may cause the amount of data in the table to exceed expectations, thereby occupying a large amount of storage space.
2. Unoptimized table structure
For example, overuse of large field types (e.g.TEXTorBLOB), excessive indexes or uncleaned indexes that are no longer used, etc.
3. Uncleaned useless data for a long time
Including historical data, transaction logs, temporary data, etc.
4. Improper configuration
For example, the storage space allocated to the database is too small, or the table space is not properly configured, etc.
2. Solution
1. Increase storage space
This is the most direct way to solve the lack of storage space.
(1) Extend physical storage
If the database is running on a local server, you can add a new hard drive or expand the capacity of an existing hard drive. If it is in a cloud environment, storage resources can be added according to the rules of the cloud service provider.
(2) Adjust the tablespace configuration
PostgreSQL supports multiple tablespaces, where different tables or indexes can be placed in different tablespaces, which can be located in different physical storage locations. For example, you can create a new tablespace and move some of the more space-consuming tables to the disk partition where the tablespace resides, which has more free space.
-- Create a new tablespace CREATE TABLESPACE new_tablespace LOCATION '/path/to/new/directory'; -- Move table to new tablespace ALTER TABLE table_name SET TABLESPACE new_tablespace;
2. Clean up useless data
(1) Delete expired or no longer used data
Regularly review tables in the database to determine if there is outdated data that can be safely deleted. For example, historical order data that has been passed for a certain period of time can be deleted.
DELETE FROM orders WHERE order_date < '2020-01-01';
(2) Clear the transaction log
PostgreSQL's transaction log (WAL) accumulates over time and may take up a lot of space if not cleaned up. You can set the appropriatewal_keep_segmentsandwal_retention_timeParameters to control the retention time and quantity of WAL.
In addition, WAL archives can be performed and archived WAL files can be cleaned regularly to free up space.
(3) Clean up temporary data
If the application uses temporary tables or temporary files, it should be cleaned up in time after use.
3. Optimize the table structure
(1) Compressed data
For some data types, compression can be used to reduce storage space usage. For example, forTEXTType, you can consider usingTOAST(The Oversized-Attribute Storage Technique) technology for compressed storage.
(2) Select the appropriate data type
Try to use the appropriate data type to store data and avoid using too large data types. For example, if a field has a value range of between 0 and 255, useSMALLINTInstead ofINTEGER 。
(3) Reduce index
Review and delete unnecessary indexes. Excessive indexing can increase the overhead of data insertion, update, and delete, and take up additional storage space.
-- View index information SELECT * FROM pg_indexes WHERE tablename = 'your_table_name'; -- Delete unnecessary indexes DROP INDEX index_name;
4. Data partitioning
Splitting the large table into multiple small partitions can be performed according to certain rules (such as time, range, etc.). This makes it easier to manage and clean data, and can only operate for specific partitions during querying, improving query efficiency.
CREATE TABLE your_table (
...
) PARTITION BY RANGE (column_name);
CREATE TABLE your_table_partition_1 PARTITION OF your_table
FOR VALUES FROM (min_value) TO (max_value);
-- Create more partitions...
3. Monitoring and early warning
1. Regularly monitor storage space usage
The following query statements can obtain the storage space usage information of each database object:
SELECT
relname,
pg_size_pretty(pg_total_relation_size(relid)) AS total_size
FROM
pg_catalog.pg_statio_all_tables
ORDER BY
pg_total_relation_size(relid) DESC;
This returns the table name and its total storage space occupied and sorts from large to small by storage space.
2. Set up an early warning mechanism
When the storage space usage reaches a certain threshold (such as 80%), send an alert to notify the administrator to handle it in time. Monitoring tools (such as Nagios, Zabbix, etc.) can be used to implement early warning functions.
4. Specific examples
Suppose we have a name calledsalestable containingorder_id、customer_id、order_date、product_idandorder_amountetc. The amount of data in this table increases sharply over time, resulting in insufficient storage space.
Analysis of the problem:
First, check the table size and index information to determine whether there is too large data type or too many indexes.
SELECT
relname,
pg_size_pretty(pg_total_relation_size(relid)) AS total_size
FROM
pg_catalog.pg_statio_all_tables
WHERE
relname ='sales';
SELECT * FROM pg_indexes WHERE tablename ='sales';
Assuming discoveryorder_amountColumns are defined asDOUBLE PRECISION, but in fact the accuracy does not need to be so high, it can be changed toNUMERIC(10, 2). And there is an index that is no longer usedidx_sales_product_id 。
Solution:
-- Modify the data type ALTER TABLE sales ALTER COLUMN order_amount TYPE NUMERIC(10, 2); -- Delete indexes that are no longer used DROP INDEX idx_sales_product_id;
Then, check if there is any historical data that can be deleted. For example, it was decided to delete order data from two years ago:
DELETE FROM sales WHERE order_date < '2021-01-01';
Next, consider the data partitioning. Suppose the order is partitioned by year:
CREATE TABLE sales_2023 (
LIKE sales INCLUDING DEFAULTS
) PARTITION OF sales
FOR VALUES FROM ('2023-01-01') TO ('2023-12-31');
CREATE TABLE sales_2022 (
LIKE sales INCLUDING DEFAULTS
) PARTITION OF sales
FOR VALUES FROM ('2022-01-01') TO ('2022-12-31');
-- Create more partitions...
Finally, set up monitoring and early warning. Use tools such as Nagios to configure monitoring of database storage usage and set alerts to send when usage exceeds 80%.
5. Summary
Insufficient storage space is a common problem in PostgreSQL databases, but it can be effectively dealt with through reasonable planning, monitoring and optimization measures. Increased storage space, cleaned useless data, optimized table structure, data partitioning, and timely monitoring and early warning are key steps to solve insufficient storage space. According to actual business needs and database environment, select the appropriate combination of methods to ensure the stable operation and good performance of the database.
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