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As of RedisTimeseries >= 1.4 You can now add samples to a time series where the time of the sample is older than the newest sample in the series. Bundled with that, we now have a policy that will define handling of duplicate samples, and that needs to be supported on the client via the arguments [DUPLICATE_POLICY policy] on TS.CREATE and via [ON_DUPLICATE policy] on TS.ADD. The following are the possible policies:

• BLOCK - an error will occur for any out of order sample
• FIRST - ignore the new value
• LAST - override with latest value
• MIN - only override if the value is lower than the existing value
• MAX - only override if the value is higher than the existing value

Further reference: documentation link

Thanks for making this library, its been very helpful! However there are some big issues.

TimestampRange and Count are not exported correctly. They are missing in the below export:

I've made a PR I will reference soon that tries to fix many of the issues (update to the latest spec with TS.MREVRANGE, TS.REVRANGE, CHUNK_SIZE, DUPLICATE_POLICY on TS.CREATE/TS.ALTER, ON_DUPLICATE on TS.ADD). I've tried to follow the spec as much as possible so I may have missed some things. Hope you can look it over and provide input. Thanks.

Add CI build automation including nightly

The following PR RedisTimeSeries/RedisTimeSeries#617 added support for multi-series aggregations to RedisTimeSeries.

It adds GROUPBY <label> REDUCE <reducer> to TS.MRANGE/TS.MREVRANGE. It accepts SUM, MIN, MAX reducers and works with unaligned series.

Sample request:

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

Reply labels array structure

Labels:

• <label>=<groupbyvalue>
• __reducer__=<reducer>
• __source__=key1,key2,key3

Sample output:

127.0.0.1:6379> ts.add ts1 1 90 labels metric cpu name system
(integer) 1
127.0.0.1:6379> ts.add ts1 2 45 labels metric cpu name system
(integer) 2
127.0.0.1:6379> ts.add ts2 2 99 labels metric cpu name user
(integer) 2
127.0.0.1:6379> ts.add ts3 2 02 labels metric cpu name system
(integer) 2

MAX reducer sample output

127.0.0.1:6379> ts.mrange - + withlabels filter metric=cpu groupby name reduce max
1) 1) "name=system"
   2) 1) 1) "name"
         2) "system"
      2) 1) "__reducer__"
         2) "max"
      3) 1) "__source__"
         2) "ts1,ts3"
   3) 1) 1) (integer) 1
         2) 90
      2) 1) (integer) 2
         2) 45
2) 1) "name=user"
   2) 1) 1) "name"
         2) "user"
      2) 1) "__reducer__"
         2) "max"
      3) 1) "__source__"
         2) "ts2"
   3) 1) 1) (integer) 2
         2) 99

MIN reducer sample output

127.0.0.1:6379> ts.mrange - + withlabels filter metric=cpu groupby name reduce min
1) 1) "name=system"
   2) 1) 1) "name"
         2) "system"
      2) 1) "__reducer__"
         2) "min"
      3) 1) "__source__"
         2) "ts1,ts3"
   3) 1) 1) (integer) 1
         2) 90
      2) 1) (integer) 2
         2) 2
2) 1) "name=user"
   2) 1) 1) "name"
         2) "user"
      2) 1) "__reducer__"
         2) "min"
      3) 1) "__source__"
         2) "ts2"
   3) 1) 1) (integer) 2
         2) 99

I would like to pipeline multiple creates, how do I accomplish it with this library?
@averias