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KSQL Aggregate Functions | All About

KSQL, is short for Kafka SQL. It is a streaming SQL engine for Apache Kafka that lets us query and process streaming data with SQL-like syntax.

KSQL offers a range of aggregate functions that we can use to carry out computations and aggregations on streaming data.

These aggregate functions let us analyze and summarize data as it flows through a Kafka topic.

Let’s take a look at some of the common aggregate functions available in KSQL:

• COUNT:

  The COUNT function counts the number of records in a stream or table. Additionally, we can count all records or use it with a GROUP BY clause to count records by a specific column.
• SUM:

  The SUM function calculates the sum of numeric values in a stream or table.
• AVG:

  The AVG function calculates the average of numeric values in a stream or table. It can also be used with a GROUP BY clause.
• MIN and MAX:

  These functions find the minimum and maximum values in a stream or table, respectively. Like other aggregate functions, they can be used with a GROUP BY clause.
• SUM DISTINCT:

  The SUM DISTINCT function calculates the sum of distinct values in a stream or table.
• TOPK:

  This function returns the top K values in a stream or table. This is useful for finding the most common values in a dataset.
• TOPKWITHKEY:

  This function is similar to TOPK, but it also returns the keys (or IDs) associated with the top K values.
• HISTOGRAM:

  The HISTOGRAM function creates a histogram of values in a stream or table. It counts the occurrences of values within specific ranges.

We can use the above functions in our KSQL queries to perform different computations and aggregations on streaming data from Kafka topics.

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Conclusion

In brief, our Support Experts introduced us to different KSQL aggregate functions.