trait Distribution extends AnyRef

A distribution of values observed by an instrument. All Kamon distributions are based on the HdrHistogram and as such, they represent a distribution of values within a configured range and precision. By default, all instruments that generate distributions are configured to accept 1% error margin, meaning that all recorded values are adjusted to the bucket whose value is up to 1% away from the original value.

Distributions only expose data for non-empty buckets/percentiles.

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  1. abstract def buckets: Seq[Bucket]

    Returns an immutable list of all buckets on this distribution.

    Returns an immutable list of all buckets on this distribution. Calling this function requires allocation of new bucket instances every time it is called, if you just need to read the values to transfer them into another medium consider using a buckets iterator instead.

  2. abstract def bucketsIterator: Iterator[Bucket]

    Returns an iterator of all buckets on this distribution.

    Returns an iterator of all buckets on this distribution. This iterator uses a mutable buckets instance that gets updated as the user iterates through them to avoid allocating intermediary objects and thus, trying to copy bucket instances from the iterator into other structures might not work as you expect.

  3. abstract def count: Long

    Number of values stored in this distribution.

  4. abstract def dynamicRange: DynamicRange

    Describes the range and precision settings of the instrument from which this distribution was taken.

  5. abstract def max: Long

    Maximum value in this distribution.

  6. abstract def min: Long

    Minimum value in this distribution.

  7. abstract def percentile(rank: Double): Percentile

    Returns the percentile at the specified rank.

  8. abstract def percentiles: Seq[Percentile]

    Returns an immutable list of all percentiles on this distribution.

    Returns an immutable list of all percentiles on this distribution. Calling this function requires allocation of new percentile instances every time it is called, if you just need to read the values to transfer them into another medium consider using a percentiles iterator instead.

  9. abstract def percentilesIterator: Iterator[Percentile]

    Returns an iterator of all percentile values on this distribution.

    Returns an iterator of all percentile values on this distribution. This iterator uses a mutable percentiles instance that gets updated as the user iterates through them to avoid allocating intermediary objects and thus, trying to copy percentile instances from the iterator into other structures might not work as you expect.

  10. abstract def sum: Long

    Sum of all values in this distribution.

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