Cuando utilizáis InterSystems IRIS como motor de interoperabilidad, todos sabemos y apreciamos lo fácil que es usar el Visor de Mensajes para revisar las trazas de los mensajes y ver exactamente qué está ocurriendo en vuestra producción. Sin embargo, cuando un sistema maneja millones de mensajes al día, puede que no sepáis por dónde empezar vuestra investigación.
A lo largo de mis años apoyando producciones en IRIS, a menudo me encuentro investigando cosas como...
- ¿Qué tipo de rendimiento tiene este flujo de trabajo?
- ¿Dónde está el cuello de botella?
- ¿Cuáles son mis errores más comunes?
Uno de mis lugares favoritos para buscar pistas es la tabla de Encabezados de Mensajes, que almacena metadatos sobre cada mensaje que pasa por el sistema. Estos son los mismos mensajes que aparecen en el Visor de Mensajes y en las Trazas Visuales.
He recopilado una colección de consultas SQL útiles, y me encantaría compartirlas con vosotros. Mis ejemplos provienen principalmente de casos de uso de HealthShare o IRIS for Health, pero se pueden adaptar fácilmente a cualquier flujo de trabajo que tengáis...
-- SQL query to find the # of messages through a component per day
select {fn SUBSTRING(timeprocessed,1,10)} AS day, count(*) MessagesThisDay
FROM Ens.MessageHeader
where TargetConfigName = 'HS.Hub.Push.Evaluator'
GROUP BY {fn SUBSTRING(timeprocessed,1,10)}
ORDER BY day ASC
-- SQL query to find long-running messages through particular components
SELECT PReq.SessionID as SessionId,
PReq.TimeCreated as pReqTimeCreated,
PRes.TimeCreated as pResTimeCreated,
{fn TIMESTAMPDIFF(SQL_TSI_SECOND, PReq.TimeCreated,PRes.TimeCreated)} as TimeDelay
FROM (
SELECT ID, SessionId, TimeCreated
FROM Ens.MessageHeader
WHERE MessageBodyClassName = 'HS.Message.PatientSearchRequest'
AND SourceConfigName = 'HS.Hub.MPI.Manager'
AND TargetConfigName = 'HUB'
) as PReq
INNER JOIN (
SELECT ID, SessionId, TimeCreated
FROM Ens.MessageHeader
WHERE MessageBodyClassName = 'HS.Message.PatientSearchResponse'
AND SourceConfigName = 'HS.Hub.MPI.Manager'
AND TargetConfigName = 'HS.IHE.PIX.Manager.Process'
) as PRes on pReq.SessionId = PRes.SessionId
WHERE {fn TIMESTAMPDIFF(SQL_TSI_SECOND, PReq.TimeCreated,PRes.TimeCreated)} > 1
ORDER BY SessionId desc ----------------------------------------------------------
/*-- Query to find the bottleneck message through a particular component
-- set your threshold for "how long is too long (e.g. 20 seconds)
-- look for clusters of messages that are longer than that (e.g. the first cluster started at 3:22:00, then there was a second cluster at 5:15:30)
-- in each cluster, look at the first message in that cluster (chronologically). That is likely to be the bottleneck message, and all messages after it are victims of its bottleneck
*/
SELECT %NOLOCK req.TargetConfigName, req.MessageBodyClassName, req.SessionId, req.TimeCreated, req.TimeProcessed, {fn TIMESTAMPDIFF(SQL_TSI_SECOND, req.TimeCreated, req.TimeProcessed)} as TimeToProcess
FROM Ens.MessageHeader AS req
WHERE req.TargetConfigName = 'HS.Hub.Management.Operations'
AND req.TimeCreated BETWEEN '2021-04-21 00:00:00' AND '2021-04-21 11:00:00'
AND {fn TIMESTAMPDIFF(SQL_TSI_SECOND, req.TimeCreated, req.TimeProcessed)} > 20
/* If you have a particular error that you're investigating, try this one. It scans through the Ensemble Error Log for "Object to Load not found" entries, then returns some key fields from the relevant PatientSearchRequest message */
SELECT l.SessionId, mh.MessageBodyID, mh.TimeCreated, psr.SearchMode, psr.RequestingUser, psr.FirstName, psr.MiddleName, psr.LastName, psr.SSN, psr.Sex, psr.DOB
FROM Ens_Util.Log as l
INNER JOIN Ens.MessageHeader as mh on l.SessionId = mh.SessionId
INNER JOIN HS_Message.PatientSearchRequest as psr on mh.MessageBodyID = psr.ID
WHERE l.Type = 'Error'
AND l.ConfigName = 'HSPI.Server.APIOperation'
AND l.Text like 'ERROR #5809: Object to Load not found%'
AND mh.MessageBodyClassName = 'HS.Message.PatientSearchRequest'
AND mh.SourceConfigName = 'HSPI.Server.APIWebService'
AND mh.TargetConfigName = 'HSPI.Server.APIOperation'
-- Scan the Ensemble Error Log for a particular timeframe. Count up the different types of errors
SELECT substring(text,1,80) as AbbreviatedError, count(*) as NumTheseErrors
FROM Ens_Util.Log
WHERE Type = 'Error'
AND TimeLogged > '2022-03-03 00:00:00' -- when the last batch started
AND TimeLogged < '2022-03-03 16:00:00' -- when we estimate this batch might end
GROUP BY substring(text,1,80)
ORDER BY NumTheseErrors desc
-- Find the Gateway Processing Time for each StreameltRequest / ECRFetchResponse pair
SELECT sr.Gateway,request.sessionid, response.sessionid, request.timecreated AS starttime, response.timecreated AS stoptime,
datediff(ms,request.timecreated,response.timecreated) AS ProcessingTime,
Avg(datediff(ms,request.timecreated,response.timecreated)) AS AverageProcessingTimeAllGateways
FROM Ens.MessageHeader request
INNER JOIN Ens.MessageHeader AS response ON response.correspondingmessageid = request.id
INNER JOIN HS_Message.StreamletRequest AS sr ON sr.ID = request.MessageBodyId
WHERE request.messagebodyclassname = 'HS.Message.StreamletRequest'
AND response.messagebodyclassname = 'HS.Message.ECRFetchResponse'
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