count

This page explains how to use the count aggregation function in APL.

The count aggregation in APL returns the total number of records in a dataset or the total number of records that match specific criteria. This function is useful when you need to quantify occurrences, such as counting log entries, user actions, or security events.

When to use count:

• To count the total number of events in log analysis, such as the number of HTTP requests or errors.
• To monitor system usage, such as the number of transactions or API calls.
• To identify security incidents by counting failed login attempts or suspicious activities.

For users of other query languages

If you come from other query languages, this section explains how to adjust your existing queries to achieve the same results in APL.

Splunk SPL users

In Splunk SPL, the count function works similarly to APL, but the syntax differs slightly.

Splunk example

| stats count by status

ANSI SQL users

In ANSI SQL, the count function works similarly, but APL uses different syntax for querying.

SQL example

SELECT status, COUNT(*)
FROM sample_http_logs
GROUP BY status

Usage

Syntax

summarize count() [by GroupingColumn]

Parameters

• GroupingColumn (optional): A column to group the count results by. If not specified, the total number of records across the dataset is returned.

Returns

• A table with the count of records for the entire dataset or grouped by the specified column.

Use case examples

Log analysis

In log analysis, you can count the number of HTTP requests by status to get a sense of how many requests result in different HTTP status codes.

Query

['sample-http-logs']
| summarize count() by status

Run in Playground

Output

status	count
200	1500
404	200

This query counts the total number of HTTP requests for each status code in the logs.

List of related aggregations

• sum: Use sum to calculate the total sum of a numeric field, as opposed to counting the number of records.
• avg: The avg function calculates the average of a numeric field. Use it when you want to determine the mean value of data instead of the count.
• min: The min function returns the minimum value of a numeric field, helping to identify the smallest value in a dataset.
• max: The max function returns the maximum value of a numeric field, useful for identifying the largest value.
• countif: The countif function allows you to count only records that meet specific conditions, giving you more flexibility in your count queries.