Azure Stream Analytics: How to use two Azure Machine Learning Function - tsql

Question

I am using two Azure Machine Learning Function in Stream Analytics but it seems like only one can be used per query. How can I split it into two queries?
The streaming job failed: Stream Analytics job has validation errors: Multiple AML web service functions used in subquery. A query step can contain no more than one AML function. Please split the step into multiple steps.
WITH subquery as (
SELECT
id as id,
deviceId as deviceId,
username as username,
try_cast(localtime as datetime) as localtime,
AC as AC, FM as FM, UC as UC,
DL as DL, DS as DS, DP as DP,
LB as LB, ASTV as ASTV, MSTV as MSTV,
ALTV as ALTV, MLTV as MLTV, Width as Width,
Min as Min, Max as Max, Nmax as Nmax,
Nzeros as Nzeros, Mode as Mode, Mean as Mean,
Median as Median, Variance as Variance, Tendency as Tendency,
rms,fmed,fpeak,sample_entropy,
EventProcessedUtcTime as EventProcessedUtcTime,
Distress(AC,FM,UC,DL,DS,DP,1,LB,ASTV,MSTV,ALTV,MLTV,
Width,Min,Max,Nmax,Nzeros,Mode,Mean,Median,Variance,
Tendency,1,1,1,1,1,1,1,1,1,1,1,1) as resultFHR,
Labour("",1,1,1,"",rms,fmed,fpeak,sample_entropy,"","") as resultUC
FROM
iot
)
SELECT
id as id,
deviceId as deviceId,
username as username,
localtime as localtime,
AC as AC, FM as FM, UC as UC,
DL as DL, DS as DS, DP as DP,
LB as LB, ASTV as ASTV, MSTV as MSTV,
ALTV as ALTV, MLTV as MLTV, Width as Width,
Min as Min, Max as Max, Nmax as Nmax,
Nzeros as Nzeros, Mode as Mode, Mean as Mean,
Median as Median, Variance as Variance, Tendency as Tendency,
EventProcessedUtcTime as EventProcessedUtcTime,
resultFHR.[classes] as distress,
resultFHR.[probabilities] as distressProbability,
resultUC.[classes] as labour,
resultUC.[probabilities] as labourProbability
INTO
sql
FROM
subquery
SELECT
*
INTO
c2d
FROM
subquery

Answer 1

You just need to split it up into 2 separate steps. Eg:
WITH subquery1 as ( SELECT id as id, deviceId as deviceId, username as username, try_cast(localtime as datetime) as localtime, AC as AC, FM as FM, UC as UC, DL as DL, DS as DS, DP as DP, LB as LB, ASTV as ASTV, MSTV as MSTV, ALTV as ALTV, MLTV as MLTV, Width as Width, Min as Min, Max as Max, Nmax as Nmax, Nzeros as Nzeros, Mode as Mode, Mean as Mean, Median as Median, Variance as Variance, Tendency as Tendency, rms,fmed,fpeak,sample_entropy, EventProcessedUtcTime as EventProcessedUtcTime, Distress(AC,FM,UC,DL,DS,DP,1,LB,ASTV,MSTV,ALTV,MLTV, Width,Min,Max,Nmax,Nzeros,Mode,Mean,Median,Variance, Tendency,1,1,1,1,1,1,1,1,1,1,1,1) as resultFHR FROM iot )
WITH subquery as ( SELECT id as id, deviceId as deviceId, username as username, try_cast(localtime as datetime) as localtime, AC as AC, FM as FM, UC as UC, DL as DL, DS as DS, DP as DP, LB as LB, ASTV as ASTV, MSTV as MSTV, ALTV as ALTV, MLTV as MLTV, Width as Width, Min as Min, Max as Max, Nmax as Nmax, Nzeros as Nzeros, Mode as Mode, Mean as Mean, Median as Median, Variance as Variance, Tendency as Tendency, rms,fmed,fpeak,sample_entropy, EventProcessedUtcTime as EventProcessedUtcTime, Labour("",1,1,1,"",rms,fmed,fpeak,sample_entropy,"","") as resultUC FROM iot )
SELECT id as id, deviceId as deviceId, username as username, localtime as localtime, AC as AC, FM as FM, UC as UC, DL as DL, DS as DS, DP as DP, LB as LB, ASTV as ASTV, MSTV as MSTV, ALTV as ALTV, MLTV as MLTV, Width as Width, Min as Min, Max as Max, Nmax as Nmax, Nzeros as Nzeros, Mode as Mode, Mean as Mean, Median as Median, Variance as Variance, Tendency as Tendency, EventProcessedUtcTime as EventProcessedUtcTime, resultFHR.[classes] as distress, resultFHR.[probabilities] as distressProbability INTO sql FROM subquery1
SELECT id as id, deviceId as deviceId, username as username, localtime as localtime, AC as AC, FM as FM, UC as UC, DL as DL, DS as DS, DP as DP, LB as LB, ASTV as ASTV, MSTV as MSTV, ALTV as ALTV, MLTV as MLTV, Width as Width, Min as Min, Max as Max, Nmax as Nmax, Nzeros as Nzeros, Mode as Mode, Mean as Mean, Median as Median, Variance as Variance, Tendency as Tendency, EventProcessedUtcTime as EventProcessedUtcTime, resultUC.[classes] as labour, resultUC.[probabilities] as labourProbability INTO sql FROM subquery2