TS.INCRBY

Syntax
TS.INCRBY key value 
  [TIMESTAMP timestamp] 
  [RETENTION retentionPeriod] 
  [UNCOMPRESSED] 
  [CHUNK_SIZE size] 
  [LABELS {label value}...]
Available in:
Redis Stack / Time series 1.0.0
Time complexity:
O(M) when M is the amount of compaction rules or O(1) with no compaction

Increase the value of the sample with the maximum existing timestamp, or create a new sample with a value equal to the value of the sample with the maximum existing timestamp with a given increment

Examples

Required arguments

key

is key name for the time series.

value

is numeric data value of the sample (double)

Notes

  • If the time series does not exist, it is automatically created.
  • You can use this command as a counter or gauge that automatically gets history as a time series.
  • Explicitly adding samples to a compacted time series (using TS.ADD, TS.MADD, TS.INCRBY, or TS.DECRBY) may result in inconsistencies between the raw and the compacted data. The compaction process may override such samples.

Optional arguments

TIMESTAMP timestamp

is (integer) UNIX sample timestamp in milliseconds or * to set the timestamp according to the server clock.

timestamp must be equal to or higher than the maximum existing timestamp. When equal, the value of the sample with the maximum existing timestamp is increased. If it is higher, a new sample with a timestamp set to timestamp is created, and its value is set to the value of the sample with the maximum existing timestamp plus value.

If the time series is empty, the value is set to value. When not specified, set the timestamp according to the server clock.

RETENTION retentionPeriod

is maximum retention period, compared to the maximum existing timestamp, in milliseconds. Use it only if you are creating a new time series. It is ignored if you are adding samples to an existing time series. See RETENTION in TS.CREATE.

UNCOMPRESSED

changes data storage from compressed (default) to uncompressed. Use it only if you are creating a new time series. It is ignored if you are adding samples to an existing time series. See ENCODING in TS.CREATE.

CHUNK_SIZE size

is memory size, in bytes, allocated for each data chunk. Use it only if you are creating a new time series. It is ignored if you are adding samples to an existing time series. See CHUNK_SIZE in TS.CREATE.

LABELS [{label value}...]

is set of label-value pairs that represent metadata labels of the key and serve as a secondary index. Use it only if you are creating a new time series. It is ignored if you are adding samples to an existing time series. See LABELS in TS.CREATE.

Notes

  • You can use this command to add data to a nonexisting time series in a single command. This is why RETENTION, UNCOMPRESSED, CHUNK_SIZE, and LABELS are optional arguments.
  • When specified and the key doesn't exist, a new time series is created. Setting the RETENTION and LABELS introduces additional time complexity.

Examples

Store sum of data from several sources

Suppose you are getting number of orders or total income per minute from several points of sale, and you want to store only the combined value. Call TS.INCRBY for each point-of-sale report.

127.0.0.1:6379> TS.INCRBY a 232 TIMESTAMP 1657811829000		// point-of-sale #1
(integer) 1657811829000
127.0.0.1:6379> TS.INCRBY a 157 TIMESTAMP 1657811829000		// point-of-sale #2
(integer) 1657811829000
127.0.0.1:6379> TS.INCRBY a 432 TIMESTAMP 1657811829000		// point-of-sale #3
(integer) 1657811829000

Note that the timestamps must arrive in non-decreasing order.

127.0.0.1:6379> ts.incrby a 100 TIMESTAMP 50
(error) TSDB: for incrby/decrby, timestamp should be newer than the lastest one

You can achieve similar results without such protection using TS.ADD key timestamp value ON_DUPLICATE sum.

Count sensor captures

Supose a sensor ticks whenever a car is passed on a road, and you want to count occurrences. Whenever you get a tick from the sensor you can simply call:

127.0.0.1:6379> TS.INCRBY a 1
(integer) 1658431553109

The timestamp is filled automatically.

See also

TS.DECRBY | TS.CREATE

RedisTimeSeries

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