Fix sort_buffer_size for Cacti: Best Solution – OrcaCore

Cacti is a powerful, open-source network monitoring and graphing tool that leverages the capabilities of RRDTool for data storage and graphing. It utilizes a MySQL database to store configuration data, graph definitions, and historical data, while its front end is built using PHP. This architecture allows Cacti to effectively manage and present network performance metrics in a visually appealing and easily digestible format.

Cacti’s flexibility extends to managing graphs, data sources, and data archives. Its automatic data collection capabilities, coupled with SNMP support, make it a favorite among network administrators familiar with tools like MRTG, especially for creating traffic graphs.

One of the most frequently discussed MySQL parameters is the sort_buffer_size. This parameter controls the amount of memory allocated to each thread that requires sorting data locally. Insufficient sort_buffer_size can lead to performance bottlenecks and errors, particularly within applications like Cacti that rely heavily on database operations.

If you encounter errors related to sort_buffer_size while using Cacti, this guide provides a solution based on our experience at OrcaCore.

During our initial setup of Cacti on an Ubuntu server, we encountered a specific error, illustrated below:

The root cause of this sort_buffer_size error in Cacti typically lies within the MySQL configuration. The recommended buffer sizes might exceed the available memory. The solution involves adjusting the buffer sizes according to the system’s resources. If the recommendation suggests a negative value, it indicates that the buffer size needs to be decreased to fit within the allowable memory constraints.

In our particular case, we configured the join_buffer_size to 6M and the sort_buffer_size to 4M, which resolved the issue and aligned with the system’s capabilities.

Alternative Solutions to Fix sort_buffer_size for Cacti

While adjusting the sort_buffer_size directly is a common approach, other strategies can mitigate the error and improve performance. Here are two alternative solutions:

1. Optimize MySQL Queries:

Inefficient SQL queries are a significant contributor to the need for large sort buffers. When queries involve complex joins, ORDER BY clauses, or GROUP BY clauses, MySQL might resort to using the sort buffer to process the data. Optimizing these queries can significantly reduce the reliance on the sort buffer.

• Indexing: Ensure that relevant columns used in WHERE, ORDER BY, and JOIN clauses are properly indexed. Indexes allow MySQL to quickly locate and retrieve data, reducing the need for full table scans and sorting.

  -- Example: Adding an index to the `hostname` column in the `devices` table
  CREATE INDEX idx_hostname ON devices (hostname);

• Rewriting Queries: Analyze slow queries using EXPLAIN and identify areas for optimization. Consider rewriting complex queries into simpler, more efficient versions. This might involve breaking down large queries into smaller, more manageable ones, or using temporary tables to pre-process data.

  -- Example: Using EXPLAIN to analyze a query
  EXPLAIN SELECT * FROM poller_output WHERE hostname LIKE '%example%' ORDER BY time DESC;

  The output of EXPLAIN will show how MySQL plans to execute the query. Look for indicators like "Using filesort" in the Extra column, which suggests that the query is relying on the sort buffer.

• Using SQL_SMALL_RESULT: If you know that a GROUP BY query will return a small result set, you can use the SQL_SMALL_RESULT modifier to instruct MySQL to use an in-memory temporary table for grouping, instead of relying on the sort buffer.

  SELECT SQL_SMALL_RESULT column1, COUNT(*) FROM table1 GROUP BY column1;

2. Using Query Cache Effectively:

The MySQL query cache can significantly reduce the load on the database by storing the results of frequently executed queries. When a query is executed, MySQL first checks the query cache to see if the result is already available. If it is, MySQL returns the cached result without having to re-execute the query.

• Enable and Configure Query Cache: Ensure that the query cache is enabled in your MySQL configuration file (my.cnf or my.ini). The relevant parameters are query_cache_type and query_cache_size.

  query_cache_type = 1  # Enable query cache
  query_cache_size = 64M # Allocate 64MB to the query cache

• Optimize Query Structure: The query cache is sensitive to even minor differences in query structure. Ensure that frequently executed queries are consistently formatted and use the same capitalization. Avoid using non-deterministic functions (e.g., NOW(), RAND()) in cached queries.

• Monitor Query Cache Performance: Use the SHOW STATUS LIKE 'Qcache%' command to monitor the performance of the query cache. Key metrics include Qcache_hits, Qcache_inserts, and Qcache_not_cached. If the hit rate is low, consider increasing the query_cache_size or optimizing your query structure.

By implementing these alternative solutions, you can reduce the reliance on the sort_buffer_size and improve the overall performance of Cacti. Focusing on query optimization and leveraging the query cache can be more effective and sustainable than simply increasing the sort_buffer_size, especially in environments with limited memory resources. Remember to test any changes thoroughly in a non-production environment before applying them to your production system. These combined efforts should help you Fix sort_buffer_size for Cacti related issues.

Conclusion

Cacti’s template-driven design provides a high degree of flexibility and ease of management. Understanding RRDTool’s underlying principles makes Cacti usage straightforward. The tool’s clear structure facilitates efficient organization and device discovery. However, rediscovering lost devices can be challenging, and automated device addition is essential for large-scale deployments. Tools like Netdot, Netdisco, IPPlan, and TIPP, along with custom scripts that directly update the Cacti MySQL database, can streamline this process. Fix sort_buffer_size for Cacti can be achieved through the methods described above.

As demonstrated, you can Fix sort_buffer_size for Cacti by adjusting its value within the allowable memory limits, or by optimizing queries and effectively utilizing the query cache.

We hope you found this guide helpful. You might also find these articles useful:

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