Fix sort_buffer_size for Cacti: Best Solution – OrcaCore
Cacti is a powerful and widely used open-source network monitoring and graphing tool. It leverages the power of RRDTool to create insightful visualizations of network performance metrics. Cacti stores all the necessary data for generating and updating these graphs in a MySQL database and utilizes PHP for its front-end interface. This architecture allows Cacti to effectively manage graphs, data sources, and archives, while also automating the data collection process. For users familiar with MRTG, Cacti provides robust SNMP support, making it an excellent choice for creating traffic graphs and monitoring network devices.
One of the most crucial aspects of optimizing MySQL performance, especially in the context of Cacti, is understanding and configuring the sort_buffer_size
. This parameter dictates the amount of memory allocated to each process requiring local sorting operations. Improper configuration of the sort_buffer_size
can lead to performance bottlenecks and errors, as demonstrated by the issue encountered during a Cacti installation.
This guide will show you how to Fix sort_buffer_size for Cacti. If you encounter the sort_buffer_size
error during the installation or configuration of Cacti, the following steps will help you resolve the issue. This solution, as found on the Orcacore website, addresses a common problem faced by Cacti administrators.

During the install Cacti on the Ubuntu server, we faced an issue that is shown in the below image:

The root cause of the sort_buffer_size for cacti
error lies in the MySQL configuration. Specifically, the buffer sizes might be set to values that exceed the available memory or conflict with other settings.
The suggested solution is to adjust the sort_buffer_size
based on the recommendations provided during the installation process. If the recommendation indicates a negative value or an excessively large number, it’s crucial to decrease the sort_buffer_size
until it falls within acceptable memory limits.
For example, the provided solution involved setting the join_buffer_size
to 6M and the sort_buffer_size
to 4M. This configuration successfully resolved the error.
Alternative Solutions to Fix sort_buffer_size for Cacti
While adjusting the sort_buffer_size
directly is a common approach, there are alternative strategies that can address the underlying performance issues that trigger the error.
1. Optimizing MySQL Queries:
Instead of simply increasing the sort_buffer_size
, focus on optimizing the SQL queries executed by Cacti. Inefficient queries often necessitate larger sort buffers. Analyze the Cacti SQL logs (if enabled) or use MySQL’s performance schema to identify slow-running queries.
Explanation:
- Indexing: Ensure that the tables involved in frequent queries have appropriate indexes. Indexes significantly speed up data retrieval, reducing the need for sorting.
- Query Rewriting: Re-write complex queries to simplify them and reduce the amount of data that needs to be sorted. Use
EXPLAIN
to analyze query execution plans and identify potential bottlenecks. - Data Type Optimization: Verify that data types used in your queries and database schema are optimized. Using smaller integer types where appropriate or avoiding implicit type conversions can improve performance.
Example:
Let’s say Cacti is running a slow query that retrieves data for graphing purposes. After analyzing the query, you identify that it’s performing a full table scan because of a missing index on the poller_output
table.
Original Query (Hypothetical):
SELECT device_id, time, value FROM poller_output WHERE hostname = 'router1';
Solution:
Add an index to the hostname
column in the poller_output
table:
ALTER TABLE poller_output ADD INDEX idx_hostname (hostname);
This index will dramatically speed up the query, potentially eliminating the need for a large sort buffer.
2. Utilizing MySQL’s Query Cache (if applicable):
If you are using an older version of MySQL (prior to 8.0 where the query cache was removed), the query cache can dramatically improve performance by storing the results of frequently executed queries. If the exact same query is executed again, MySQL can retrieve the results from the cache instead of re-executing the query.
Explanation:
- Enable Query Cache: Ensure the query cache is enabled in your MySQL configuration file (
my.cnf
ormy.ini
). - Optimize Query Cache Settings: Adjust the
query_cache_size
andquery_cache_type
parameters to optimize the cache’s performance. Be mindful of the overhead associated with the query cache, especially in write-heavy workloads.
Code Example (MySQL Configuration – my.cnf):
[mysqld]
query_cache_type = 1 # Enable query cache
query_cache_size = 64M # Set query cache size to 64MB
Important Note: The MySQL Query Cache was deprecated in MySQL 5.7 and removed in MySQL 8.0. If you’re running a more recent version of MySQL, you’ll need to explore alternative caching mechanisms, such as using a dedicated caching layer like Redis or Memcached, or leveraging the Performance Schema for query analysis and optimization.
3. Upgrading MySQL/MariaDB Version:
Newer versions of MySQL and MariaDB often include significant performance improvements and optimized query execution engines. Upgrading your database server can improve overall performance, reducing the need for large sort buffers.
Explanation:
- Performance Enhancements: Newer versions often include algorithmic improvements in query processing and indexing.
- Bug Fixes: Upgrading can resolve bugs related to memory management and query optimization that might be contributing to the
sort_buffer_size
issue. - Feature Enhancements: Newer versions may offer features like improved indexing methods or better support for large datasets.
4. Monitoring and Resource Allocation:
- Monitor Memory Usage: Use tools like
top
,htop
, orvmstat
to monitor the overall memory usage of your server. Ensure that MySQL has sufficient memory allocated to it without starving other processes. - Optimize Other Buffer Sizes: The
sort_buffer_size
is not the only buffer size that affects performance. Review the configuration of other buffer sizes, such asinnodb_buffer_pool_size
(for InnoDB),key_buffer_size
(for MyISAM), andread_buffer_size
, to ensure they are appropriately sized for your workload.
By implementing these alternative solutions in conjunction with, or instead of, directly adjusting the sort_buffer_size
, you can achieve a more sustainable and robust solution to the performance problems that lead to the error. Remember to thoroughly test any configuration changes in a non-production environment before deploying them to your live Cacti system.
Conclusion
Cacti’s template-based design offers exceptional flexibility, simplifying network management. A solid understanding of RRDTool greatly enhances Cacti’s usability. Its organized structure facilitates quick device discovery, though re-discovery of lost devices can be challenging. Automating the addition of numerous devices is crucial, and tools like Netdot, Netdisco, IPPlan, and TIPP, along with custom scripts directly updating the Cacti MySQL database, can significantly streamline this process. The key is to Fix sort_buffer_size for Cacti by finding the best approach for your specific environment.
As demonstrated, you can Fix sort_buffer_size for Cacti by adjusting its value to fit within available memory constraints. However, remember to consider alternative optimization strategies to ensure long-term stability and performance.
We hope you found this guide helpful. You might also find these articles interesting:
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- Install Cacti Network Monitoring Tool on Debian 11
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Successfully resolving the sort_buffer_size
error will enable you to fully leverage Cacti’s capabilities for network monitoring and visualization. Remember to document your configuration changes and monitor your system’s performance to ensure continued optimal operation. The goal is to Fix sort_buffer_size for Cacti effectively, not just band-aid the problem.