com.netflix.atlas.core.model.MathExpr
Percentiles
Related Doc:
package MathExpr
Input data expression. The value should be a sum or group by. The group by list should
include the 'percentile' key. If using the :percentiles word to construct the instance
then other aggregate types, such as max, will automatically be converted to sum and the
percentile key will be added into the group by clause.
List of percentiles to compute. Each value should be in the range [0.0, 100.0].
The underlying data expressions that supply input for the evaluation.
The underlying data expressions that supply input for the evaluation. These are used to fetch data from the data stores. There may be some expressions types that generate data and will have an empty set. Examples are constants, random, or time.
Input data expression.
Input data expression. The value should be a sum or group by. The group by list should
include the 'percentile' key. If using the :percentiles word to construct the instance
then other aggregate types, such as max, will automatically be converted to sum and the
percentile key will be added into the group by clause.
Returns a string that can be executed with the stack interpreter to create this expression.
Returns a string that can be executed with the stack interpreter to create this expression.
Returns the final grouping for the expression.
Returns the final grouping for the expression. For non-grouped expressions this will be an empty list. If a multi-level group by is used, then this will return the grouping of the final result and ignore any intermediate groupings.
Returns the grouping key generated for a given tag map.
Returns the grouping key generated for a given tag map. All keys for the group by must be present in the map.
Returns true if the result is grouped.
Returns true if the result is grouped. See GroupBy operators.
List of percentiles to compute.
List of percentiles to compute. Each value should be in the range [0.0, 100.0].
Rewrite the expression using the specified function.
Rewrite the expression using the specified function. The default implementation will try to recursively apply the rewrite to case classes.
Apply a time shift to all underlying data expressions.
Apply a time shift to all underlying data expressions.
(Since version ) see corresponding Javadoc for more information.
Compute estimated percentile values using counts for well known buckets. See spectator PercentileBuckets for more information. The input will be grouped by the
percentilekey with each key value being the bucket index. The output will be one line per requested percentile.Input data expression. The value should be a sum or group by. The group by list should include the 'percentile' key. If using the
:percentilesword to construct the instance then other aggregate types, such as max, will automatically be converted to sum and thepercentilekey will be added into the group by clause.List of percentiles to compute. Each value should be in the range [0.0, 100.0].