ClickHouse Troubleshooting: How to Monitor I/O Subsystem Reads

Introduction

If the I/O subsystem reads in ClickHouse are struggling, it can lead to slower query performance and longer query execution times. Here are a few ways to tell if the I/O subsystem reads in ClickHouse are struggling:

  1. Increased disk I/O wait time: One way to tell if the I/O subsystem reads in ClickHouse are struggling is to monitor the disk I/O wait time. If the wait time is consistently high, it may indicate that the disk is not able to keep up with the rate of data being read from it.
  2. High disk usage: Another way to tell if the I/O subsystem reads in ClickHouse are struggling is to monitor the disk usage. If the disk usage is consistently high, it may indicate that the disk is not able to keep up with the rate of data being read from it.
  3. Slow query performance: If the I/O subsystem reads in ClickHouse are struggling, it can lead to slower query performance and longer query execution times. If you notice that queries are taking longer than usual to complete, it may be a sign that the I/O subsystem reads are struggling.
  4. High CPU usage: In some cases, high CPU usage can indicate that the I/O subsystem reads in ClickHouse are struggling. This is because when the disk is unable to keep up with the rate of data being read from it, the CPU may be forced to wait for data, leading to higher CPU usage.
  5. Error messages: ClickHouse may log error messages if the I/O subsystem reads are struggling. Check the logs for any error messages related to disk I/O or read performance.

If you notice any of these signs, it may be a sign that the I/O subsystem reads in ClickHouse are struggling. You may need to optimize your hardware, adjust ClickHouse configuration parameters, or adjust your data model to improve read performance.

Monitoring IO Subsystem Reads in ClickHouse

Here’s an SQL script to monitor the I/O subsystem reads in ClickHouse:

SELECT
SUM(read_bytes) AS total_read_bytes,
SUM(read_latency) AS total_read_latency,
SUM(read_backoff_latency) AS total_read_backoff_latency,
SUM(read_retries) AS total_read_retries
FROM system.metrics
WHERE metric LIKE 'io.%read.%';

This script queries the system.metrics table in ClickHouse and aggregates the I/O read statistics for all tables in the database. It returns the total number of bytes read, the total read latency, the total backoff latency, and the total number of read retries.

Conclusion

You can run this script periodically to monitor the I/O subsystem reads in ClickHouse and track any changes over time. If you notice any significant increases in read latency, backoff latency, or read retries, it may indicate that the I/O subsystem reads in ClickHouse are struggling and you may need to optimize your hardware or adjust your ClickHouse configuration parameters.

To know more about Troubleshooting ClickHouse I/O, do consider reading the following articles:

About Shiv Iyer 215 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.