Add GROUPBY and REDUCE support

[Guy Korland]

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

127.0.0.1:6379> TS.ADD ts1 1 90 labels metric cpu metric_name system
(integer) 1
127.0.0.1:6379> TS.ADD ts1 2 45
(integer) 2
127.0.0.1:6379> TS.ADD ts2 2 99 labels metric cpu metric_name user
(integer) 2
127.0.0.1:6379> TS.MRANGE - + WITHLABELS FILTER metric=cpu GROUPBY metric_name REDUCE max
1) 1) "metric_name=system"
   2) 1) 1) "metric_name"
         2) "system"
      2) 1) "__reducer__"
         2) "max"
      3) 1) "__source__"
         2) "ts1"
   3) 1) 1) (integer) 1
         2) 90
      2) 1) (integer) 2
         2) 45
2) 1) "metric_name=user"
   2) 1) 1) "metric_name"
         2) "user"
      2) 1) "__reducer__"
         2) "max"
      3) 1) "__source__"
         2) "ts2"
   3) 1) 1) (integer) 2
         2) 99