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Expected argument extension to TS.MRANGE: GROUPBY <label> REDUCE <reducer>
TS.MRANGE 1451679382646 1451682982646 WITHLABELS
AGGREGATION MAX 60000
FILTER measurement=cpu
fieldname=usage_user
hostname=(host_9,host_3,host_5,host_1,host_7,host_2,host_8,host_4)
GROUPBY hostname REDUCE MAX
Documentation extension:
GROUPBY - Aggregate results across different time series, grouped by the provided label name.
For OSS clustered databases, RedisGears is required to be present.
When combined with AGGREGATION the groupby/reduce is applied post aggregation stage.
label - label name to group series by.
reducer - Reducer type used to aggregate series that share the same label value. Available reducers: sum, min, max.
Note: The resulting series will contain 3 labels with the following label array structure:
<label>=<groupbyvalue> : containing the label name and label value.
__reducer__=<reducer> : containing the used reducer.
__source__=key1,key2,key3 : containing the source time series used to compute the grouped serie.
Example of the above features:
Query time series with metric=cpu, group them by metric_name reduce max
Expected argument extension to
TS.MRANGE
:GROUPBY <label> REDUCE <reducer>
Documentation extension:
GROUPBY - Aggregate results across different time series, grouped by the provided label name.
For OSS clustered databases, RedisGears is required to be present.
When combined with
AGGREGATION
the groupby/reduce is applied post aggregation stage.label - label name to group series by.
reducer - Reducer type used to aggregate series that share the same label value. Available reducers: sum, min, max.
Note: The resulting series will contain 3 labels with the following label array structure:
<label>=<groupbyvalue>
: containing the label name and label value.__reducer__=<reducer>
: containing the used reducer.__source__=key1,key2,key3
: containing the source time series used to compute the grouped serie.Example of the above features:
Query time series with metric=cpu, group them by metric_name reduce max
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