ClickHouse Troubleshooting: How NULL Values affect Query Performance


NULL values in ClickHouse can affect performance in several ways. One way is that they can increase the size of data, which can lead to slower query execution times as more data needs to be scanned. Additionally, they can also make it difficult to use indexes effectively, as the index will not contain any entries for NULL values. This can lead to more disk I/O, as the database needs to scan more data to find the relevant rows. Furthermore, they can also lead to unexpected results when performing calculations or aggregations, as NULL values are not included in these operations. To avoid these issues, it is important to understand how NULL values are used in your data and to make sure that they are handled correctly in your queries.

Troubleshooting ClickHouse Performance with NULL values

To troubleshoot ClickHouse performance issues you can follow these steps:

  1. Identify the tables and columns that have a high percentage of NULL values. You can use the following SQL query to check the NULL percentage for each column in a table:
SELECT column, 100.0 * null_values / total_values AS percentage_null 
FROM system.columns 
WHERE database = 'your_database' AND table = 'your_table' 
ORDER BY percentage_null DESC;
  1. Check the indexes on the identified columns. If the columns with a high percentage of NULL values are not indexed, adding an index can improve query performance.
  2. Analyze the queries that are causing performance issues. If the queries are using the columns with a high percentage of NULL values as filters, you can try to rewrite the queries to use other columns or indexes.
  3. Check the compression settings for the columns with a high percentage of NULL values. If the compression settings are not optimal, you can try adjusting them to reduce the size of the data on disk and improve query performance.
  4. Monitor the performance of the queries and the system as a whole. Use ClickHouse’s built-in performance monitoring tools, such as, to track query execution time, memory usage, and disk I/O.


It is important to note that NULL values do not have any performance implications in ClickHouse as the engine is designed to work with nullable columns and missing values efficiently.

To read more about ClickHouse performance, do consider reading the below articles

About Shiv Iyer 226 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.