createNarrowReactiveStateEngine

createNarrowReactiveStateEngine(name, metrics, metricNames, dummyTable, outputTable, keyColumn, [filter], [snapshotDir], [snapshotIntervalInMsgCount], [keepOrder], [keyPurgeFilter], [keyPurgeFreqInSecond=0], [raftGroup], [outputElapsedMicroseconds=false], [keyCapacity=1024], [parallelism=1], [outputHandler=NULL], [msgAsTable=false])

Create a reactive state engine that returns a table in narrow format. The only difference between createNarrowReactiveStateEngine and createReactiveStateEngine lies in the schema of the returned table, i.e., the former outputs results of multiple factors to a single column, while the latter outputs results of each factor to separate columns.

As most of the parameters of createNarrowReactiveStateEngine are identical with those of createReactiveStateEngine, only the different ones are explained here.

metrics is metacode or a tuple of metacode containing columns from the input table (excluding keyColumn, optional) or factors (formulas for calculation, required).

metricNames is a STRING scalar or vector, indicating the name for each factor specified in metrics. The number and order of names must align to that of factors specified in metrics.

outputTable is the output table for the results. It can be an in-memory table or a DFS table. Create an empty table and specify the column names and types before calling the function.

The output columns are in the following order:

(1) The first few columns must be in the same order as that of keyColumn.

(2) If the outputElapsedMicroseconds is set to true, specify two more columns: a LONG column and an INT column.

(3) The references to columns from the input table specified in metrics.

(4) A single column containing metricNames.

(5) Then followed by one result column.

Note: The following parameters are not supported currently: snapshotDir, snapshotIntervalInMsgCount, and raftGroup.

outputHandler (optional) is a unary function or a partial function with a single unfixed parameter. If set, the engine will not write the calculation results to the output table directly. Instead, the results will be passed as a parameter to the outputHandler function. The default value is NULL, which means the result will be written to the output table.

msgAsTable (optional) is a Boolean scalar indicating whether the output data is passed into function (specified by outputHandler) as a table or as a tuple. If msgAsTable=true, the subscribed data is passed into function as a table. The default value is false, which means the output data is passed into function as a tuple of columns.

Calculate the cumulative volume and the moving average and output the results of both factors to a single column.

dummy = streamTable(1:0, ["securityID1","securityID2","securityID3","createTime","updateTime","upToDatePrice","qty","value"], [STRING,STRING,STRING,TIMESTAMP,TIMESTAMP,DOUBLE,DOUBLE,INT]) 
share streamTable(1:0,["securityID1","securityID2","securityID3","createTime","updateTime","metricNames","factorValue"], [STRING,STRING,STRING, TIMESTAMP,TIMESTAMP,STRING,DOUBLE]) as outputTable
// Define two factors: cumulative volume and the moving average
factor = [<createTime>, <updateTime>,<cumsum(qty)>,<cumavg(upToDatePrice)>]
Narrowtest = createNarrowReactiveStateEngine(name="narrowtest1",metrics=factor,metricNames=["factor1","factor2"],dummyTable=dummy,outputTable=outputTable,keyColumn=["securityID1","securityID2","securityID3"])

num = 5
tmp = table(take("A" + lpad(string(1..4),4,"0"),num) as securityID1,take("CC.HH" + lpad(string(21..34),4,"0"),num) as securityID2,take("FFICE" + lpad(string(13..34),4,"0"),num) as securityID3, 2023.09.01 00:00:00+(1..num) as createTime, 2023.09.01 00:00:00+(1..num) as updateTime,100.0+(1..num) as upToDatePrice, 130.0+(1..num) as qty,take(1..3,num) as value)
Narrowtest.append!(tmp)

select * from outputTable


securityID1	securityID2	securityID3	createTime	updateTime	metricNames	factorValue
A0001	CC.HH0021	FFICE0013	2023.09.01T00:00:01.000	2023.09.01T00:00:01.000	factor1	131
A0001	CC.HH0021	FFICE0013	2023.09.01T00:00:01.000	2023.09.01T00:00:01.000	factor2	101
A0002	CC.HH0022	FFICE0014	2023.09.01T00:00:02.000	2023.09.01T00:00:02.000	factor1	132
A0002	CC.HH0022	FFICE0014	2023.09.01T00:00:02.000	2023.09.01T00:00:02.000	factor2	102
A0003	CC.HH0023	FFICE0015	2023.09.01T00:00:03.000	2023.09.01T00:00:03.000	factor1	133
A0003	CC.HH0023	FFICE0015	2023.09.01T00:00:03.000	2023.09.01T00:00:03.000	factor2	103
A0004	CC.HH0024	FFICE0016	2023.09.01T00:00:04.000	2023.09.01T00:00:04.000	factor1	134
A0004	CC.HH0024	FFICE0016	2023.09.01T00:00:04.000	2023.09.01T00:00:04.000	factor2	104
A0001	CC.HH0025	FFICE0017	2023.09.01T00:00:05.000	2023.09.01T00:00:05.000	factor1	135
A0001	CC.HH0025	FFICE0017	2023.09.01T00:00:05.000	2023.09.01T00:00:05.000	factor2	105

Related functions: addReactiveMetrics, getReactiveMetrics