Skip to main content
The series_floor function rounds down each element in a numeric dynamic array (series) to the nearest integer that’s less than or equal to the original value. This function applies the mathematical floor operation element-wise across the entire array, which is useful for data discretization, quantization, and integer conversion in time series data. You can use series_floor when you want to convert floating-point values to integers by rounding down, discretize continuous data into bins, or prepare data for categorical analysis. This is particularly useful for creating integer-based categories, implementing quantization schemes, or when you need to ensure values don’t exceed certain thresholds. Typical applications include data binning, performance categorization, and mathematical modeling where integer values are required.

​
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.
In Splunk SPL, floor operations are typically done with the eval function and the floor() expression. To compute floor across multiple values, you usually need to expand arrays and apply the transformation row by row. In APL, series_floor works directly on dynamic arrays, making it efficient for series-wide floor operations.
... | eval floor_val=floor(duration)
In SQL, floor operations use the FLOOR() function, but this only works on single values, not arrays. To compute floor for array elements, you typically need to unnest arrays and apply FLOOR() row by row. In APL, series_floor eliminates this complexity by directly applying floor transformation to each element in an array.
SELECT FLOOR(duration) AS floor_duration
FROM requests;

​
Usage

​
Syntax

series_floor(array)

​
Parameters

ParameterTypeDescription
arraydynamicA dynamic array of numeric values.

​
Returns

A dynamic array where each element is the floor (largest integer less than or equal to) the corresponding input element.

​
Use case examples

  • Log analysis
  • OpenTelemetry traces
  • Security logs
In log analysis, you can use series_floor to discretize request durations into integer bins for categorical analysis or performance categorization.Query
['sample-http-logs']
| summarize durations = make_list(req_duration_ms) by id
| extend floor_durations = series_floor(durations)
Run in PlaygroundOutput
iddurationsfloor_durations
u123[150.7, 200.3, 250.9][150, 200, 250]
u456[100.2, 300.8, 400.1][100, 300, 400]
This query converts floating-point request durations to integers by rounding down, useful for creating discrete performance categories.
  • series_abs: Returns the absolute value of each element in an array. Use when you need to normalize values before applying floor operations.
  • series_exp: Calculates the exponential of each element in an array. Use for exponential transformations instead of floor operations.
  • series_cos: Returns the cosine of each element in an array. Use for trigonometric transformations instead of floor operations.
  • series_sin: Returns the sine of each element in an array. Use for periodic transformations instead of floor operations.
  • series_tan: Returns the tangent of each element in an array. Use for trigonometric transformations with different periodicity.