ClickHouse median Function

The median function in ClickHouse calculates the median value of a numeric data set. It's commonly used in statistical analysis and data processing to find the middle value in a sorted list of numbers, providing a measure of central tendency that is less affected by outliers compared to the mean.

Syntax

median(x) or MEDIAN(x)

Official Documentation

Example usage

SELECT median(salary) AS median_salary
FROM employees
WHERE department = 'Sales';

Common issues

  • Performance can be slower compared to other aggregation functions for large datasets.
  • Results may be approximate for very large datasets due to the use of reservoir sampling.

Best practices

  • Consider using medianExact for smaller datasets where precision is critical.
  • For large datasets, medianTDigest can provide faster approximate results.
  • Use median in combination with other statistical functions like avg and percentile for a comprehensive data analysis.

Frequently Asked Questions

Q: What's the difference between median and avg in ClickHouse?
A: median returns the middle value in a sorted list of numbers, while avg calculates the arithmetic mean. median is less affected by extreme outliers compared to avg.

Q: How accurate is the median function for large datasets?
A: For large datasets, ClickHouse uses an algorithm that may provide an approximate result. For exact results on large datasets, consider using medianExact, but be aware it may be slower.

Q: Can median be used with non-numeric data types?
A: No, median is designed for numeric data types. For other data types, you may need to use different aggregation functions or convert the data to a numeric representation first.

Q: How does median handle NULL values?
A: median ignores NULL values in its calculations. If you need to include NULL values in your analysis, you should handle them explicitly in your query.

Q: Is there a way to calculate weighted median in ClickHouse?
A: ClickHouse doesn't have a built-in weighted median function. For weighted median calculations, you might need to implement a custom solution using other available functions or consider using approximate functions like medianTDigest with weights.

Pulse - Elasticsearch Operations Done Right

Pulse can solve your Elasticsearch issues

Subscribe to the Pulse Newsletter

Get early access to new Pulse features, insightful blogs & exclusive events , webinars, and workshops.

We use cookies to provide an optimized user experience and understand our traffic. To learn more, read our use of cookies; otherwise, please choose 'Accept Cookies' to continue using our website.