Sliding Time Window Aggregator¶

This stage aggregates the data of a single point by the sliding time window. The settings for this stage are as per the below.

Window type: Sliding window.
Supported aggregators: max/min/avg/count/sum/first/last.
This stage cannot guarantee idempotence of the calculation results due to failure retries caused by any reasons, such as cluster node exceptions.

Configuration¶

The configuration tabs for this stage are General, Basic, Input/Output, ExtraConfig, and CacheConfig.

Name	Required?	Description
Name	Yes	The name of the stage.
Description	No	The description of the stage.
Stage Library	Yes	The streaming operator library to which the stage belongs.
Required Fields	No	The fields that the data records must contain. If the specified fields are not included, the record will be filtered out.
Preconditions	No	The conditions that must be satisfied by the data records. Records that do not meet the conditions will be filtered out. For example, `${record:value('/value') > 0}`. For the syntax of EL expressions, see Expression Language.
On Record Error	Yes	The processing method for error data. Discard: Error data will be discarded and ignored Send to Error: Error messages will be reported Stop Pipeline: The pipeline will be stopped

Name	Required?	Description
Quality Filter	No	Filter the data according to the data quality. Only records that meet the quality conditions will be processed by this stage.

Name	Required?	Description
Input Point	Yes	Specify the input point of the records, using the format {modelId}::{pointId}.
Fixed Window Size	Yes	Specify the duration for the fixed time window, which is equal to the step length of the sliding window.
Fixed Window Unit	Yes	Select the unit for the fixed time window.
Sliding Window Size	Yes	Specify the step length of the sliding window.
Sliding Window Unit	Yes	Select the unit for the sliding window.
Aggregator Policy	Yes	Select the aggregator for data aggregation: max/min/avg/count/sum/first/last.
Output Point	Yes	Specify the output point of thr records, using the format {modelId}::{pointId}.

Name

Required?

Description

Output Data Type

Yes

Select the output data type. Options are Double and From TSL Model Service.

Double: You can select this option if the output points are all for intermediate calculation results (the output points are not defined on the model), or the data type of all the output points is Double.
From TSL Model Service: You must select this option if the output points are defined on the model and the data type of the points is not Double. Otherwise, the output data cannot be stored in TSDB correctly.

Name

Required?

Description

Cache Type

Yes

Select the storage type for cache data. Options are Redis and Local storage.

Redis: The advantage is that the cached data will not be lost after the stream processing pipeline is paused, restarted, or retried. The disadvantage is that the data processing speed is slow and that it is sensitive to network performance. It is recommended that the network delay should be less than 1ms. Otherwise, the data processing performance will be affected.
Local: The advantage is that the data processing speed is fast. The disadvantage is that the cached data will be lost after the stream processing pipeline is paused, restarted, or retried.

The output results of this stage are included in the attr struct. The description of the fields are as follows:

Name	Data Type	Description
lastOutput	Integer/Double/Float	The last output of the point (NaN for no output).
calMode	String	The output mode, which is the final output.
calType	String	The selected aggregator: max/min/avg/count/sum/first/last.
calDetail	Map	The calculation details. For example, when calType=avg, output the sum and count value of value and lastValue.