The sample operator in APL psuedo-randomly selects rows from the input dataset at a rate specified by a parameter. This operator is useful when you want to analyze a subset of data, reduce the dataset size for testing, or quickly explore patterns without processing the entire dataset. The sampling algorithm is not statistically rigorous but provides a way to explore and understand a dataset. For statistically rigorous analysis, use summarize instead.

You can find the sample operator useful when working with large datasets, where processing the entire dataset is resource-intensive or unnecessary. It’s ideal for scenarios like log analysis, performance monitoring, or sampling for data quality checks.

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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.

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Usage

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Syntax

| sample ProportionOfRows

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Parameters

  • ProportionOfRows: A float greater than 0 and less than 1 which specifies the proportion of rows to return from the dataset. The rows are selected randomly.

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Returns

The operator returns a table containing the specified number of rows, selected randomly from the input dataset.

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Use case examples

In this use case, you sample a small number of rows from your HTTP logs to quickly analyze trends without working through the entire dataset.

Query

['sample-http-logs']
| sample 0.05

Run in Playground

Output

_timereq_duration_msidstatusurimethodgeo.citygeo.country
2023-10-16 12:45:00234user1200/indexGETNew YorkUS
2023-10-16 12:47:00120user2404/loginPOSTParisFR
2023-10-16 12:48:00543user3500/checkoutPOSTTokyoJP

This query returns a random subset of 5 % of all rows from the HTTP logs, helping you quickly identify any potential issues or patterns without analyzing the entire dataset.

  • take: Use take when you want to return the first N rows in the dataset rather than a random subset.
  • where: Use where to filter rows based on conditions rather than sampling randomly.
  • top: Use top to return the highest N rows based on a sorting criterion.

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