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Exemplos de consultas query-examples

Last update: Thu Nov 20 2025 00:00:00 GMT+0000 (Coordinated Universal Time)

Criado para:

  • Experiente
  • Desenvolvedor
  • Administrador

Esta seção lista vários exemplos usados com frequência para consultar Eventos de etapa da Jornada no Data Lake.

Verifique se os campos usados em suas consultas têm valores associados no esquema correspondente.

Qual é a diferença entre id, instanceid e profileid
  • id: exclusiva para todas as entradas de evento de etapa. Dois eventos de etapa diferentes não podem ter a mesma ID.
  • instanceId: instanceID é o mesmo para todos os eventos de etapa associados a um perfil em uma execução de jornada. Se um perfil entrar novamente na jornada, uma instanceId diferente será usada. Essa nova instanceId será a mesma para todos os eventos de etapa da instância reinserida (do início ao fim).
  • profileID: a identidade do perfil correspondente ao namespace da jornada.
note note
NOTE
Para fins de solução de problemas, recomendamos usar journeyVersionID em vez de journeyVersionName ao consultar jornadas. Saiba mais sobre os atributos de propriedades de jornada nesta seção.

Casos de uso básicos/consultas comuns common-queries

Quantos perfis entraram em uma jornada em um determinado período

Esta consulta fornece o número de perfis distintos que entraram na jornada especificada no período.

Consulta do Data Lake

code language-sql 
SELECT count(distinct _experience.journeyOrchestration.stepEvents.profileID)
FROM journey_step_events WHERE _experience.journeyOrchestration.stepEvents.journeyVersionID = '<journeyVersionID>'
AND _experience.journeyOrchestration.stepEvents.nodeType='start'
AND _experience.journeyOrchestration.stepEvents.instanceType = 'unitary'
AND DATE(timestamp) > (now() - interval '<last x hours>' hour);

Saiba como solucionar problemas de tipos de eventos descartados em jornada_step_events.

Qual regra fez com que um perfil não entrasse em uma determinada jornada

Esta consulta retorna o conjunto de regras rejeitado e as informações da regra quando um perfil é impedido de inserir uma jornada devido às regras de limitação ou qualificação.

Exemplo

code language-sql 
SELECT
    _experience.journeyOrchestration.serviceEvents.dispatcher.eventType,
    _experience.journeyOrchestration.serviceEvents.dispatcher.rejectedRuleset.ID AS RULESET_ID,
    _experience.journeyOrchestration.serviceEvents.dispatcher.rejectedRuleset.name AS RULESET_NAME,
    _experience.journeyOrchestration.serviceEvents.dispatcher.rejectedRuleset.rejectedRules.ID AS RULE_ID,
    _experience.journeyOrchestration.serviceEvents.dispatcher.rejectedRuleset.rejectedRules.name AS RULE_NAME
FROM
    journey_step_events
WHERE
    _experience.journeyOrchestration.serviceEvents.dispatcher.eventCode = 'discard'
AND
    _experience.journeyOrchestration.stepEvents.journeyVersionID='3855072d-79c3-438a-a5c3-c77fd6843812'
AND
    timestamp >= to_date('2025-05-16')
Quantos erros ocorreram em cada nó de uma jornada específica por um determinado período

Essa consulta conta os perfis distintos que apresentaram erros em cada nó de uma jornada, agrupados por nome de nó. Inclui todos os tipos de erros de execução de ação e erros de busca.

Consulta do Data Lake

code language-sql 
SELECT
_experience.journeyOrchestration.stepEvents.nodeName,
count(distinct _experience.journeyOrchestration.stepEvents.profileID)
FROM journey_step_events
WHERE _experience.journeyOrchestration.stepEvents.journeyVersionID='<journeyVersionID>'
AND DATE(timestamp) > (now() - interval '<last x hours>' hour)
AND
  (_experience.journeyOrchestration.stepEvents.actionExecutionError is not NULL
    OR _experience.journeyOrchestration.stepEvents.actionExecutionErrorCode is not NULL
    OR _experience.journeyOrchestration.stepEvents.actionExecutionOriginCode is not NULL
    OR _experience.journeyOrchestration.stepEvents.actionExecutionOriginError is not NULL
    OR _experience.journeyOrchestration.stepEvents.fetchError is not NULL
    OR _experience.journeyOrchestration.stepEvents.fetchErrorCode is not NULL
  )
GROUP BY _experience.journeyOrchestration.stepEvents.nodeName;
Quantos eventos foram descartados de uma jornada específica em um determinado período

Esta consulta conta o número total de eventos que foram descartados de uma jornada. Ele filtra vários códigos de evento de descarte, incluindo erros de trabalho de exportação de segmento, descartes do Dispatcher e descartes da máquina de estado.

Consulta do Data Lake

code language-sql 
SELECT
count(_id) AS NUMBER_OF_EVENTS_DISCARDED
FROM journey_step_events
WHERE (
   _experience.journeyOrchestration.serviceEvents.segmentExportJob.eventCode = 'error'
   OR _experience.journeyOrchestration.serviceEvents.dispatcher.eventCode = 'discard'
   OR _experience.journeyOrchestration.serviceEvents.stateMachine.eventCode = 'discard'
   OR _experience.journeyOrchestration.serviceEvents.segmentExportJob.eventCode is not null
)
AND _experience.journeyOrchestration.stepEvents.journeyVersionID='<journeyVersionID>'
AND DATE(timestamp) > (now() - interval '<last x hours>' hour);
O que acontece com um perfil específico em uma jornada específica em um intervalo de tempo específico

Esta consulta retorna todos os eventos de etapa e eventos de serviço para o perfil e a jornada fornecidos pelo tempo especificado em ordem cronológica.

Consulta do Data Lake

code language-sql 
SELECT
timestamp,
_experience.journeyOrchestration.stepEvents.journeyVersionID,
_experience.journeyOrchestration.stepEvents.profileID,
_experience.journeyOrchestration.stepEvents.nodeName,
_experience.journeyOrchestration.stepEvents.journeyNodeProcessed,
_experience.journeyOrchestration.serviceType,
to_json(_experience.journeyOrchestration.profile),
to_json(_experience.journeyOrchestration.serviceEvents)
FROM journey_step_events
WHERE _experience.journeyOrchestration.stepEvents.journeyVersionID='<journeyVersionID>'
AND DATE(timestamp) > (now() - interval '<last x hours>' hour)
AND
  (
    _experience.journeyOrchestration.stepEvents.profileID='<profileID>'
    OR _experience.journeyOrchestration.profile.ID='<profileID>'
  );
ORDER BY timestamp;
Quanto tempo decorreu entre dois nós

Essas consultas podem ser usadas, por exemplo, para estimar o tempo gasto em uma atividade de espera. Isso permite verificar se a atividade de espera está configurada corretamente.

Consulta do Data Lake

code language-sql 
WITH

START_NODE_INFO AS (

    SELECT

        timestamp AS TS_START,
        _experience.journeyOrchestration.stepEvents.nodeName AS NODE_NAME,
        _experience.journeyOrchestration.stepEvents.instanceID AS INSTANCE_ID

    FROM

        journey_step_events

    WHERE

        _experience.journeyOrchestration.stepEvents.journeyVersionID = '<journey version id>' AND
        _experience.journeyOrchestration.stepEvents.nodeName = '<name of node before wait activity>' AND
        _experience.journeyOrchestration.stepEvents.journeyNodeProcessed = true

),

END_NODE_INFO AS (

    SELECT

        timestamp AS TS_END,
        _experience.journeyOrchestration.stepEvents.nodeName AS NODE_NAME,
        _experience.journeyOrchestration.stepEvents.instanceID AS INSTANCE_ID

    FROM

        journey_step_events

    WHERE

        _experience.journeyOrchestration.stepEvents.journeyVersionID = '<journey version id>' AND
        _experience.journeyOrchestration.stepEvents.nodeName = '<name of wait activity node>' AND
        _experience.journeyOrchestration.stepEvents.journeyNodeProcessed = true

)

SELECT

    T1.INSTANCE_ID AS INSTANCE_ID,
    T1.NODE_NAME AS START_NODE_NAME,
    T2.NODE_NAME AS END_NODE_NAME,
    DATEDIFF(millisecond,T1.TS_START,T2.TS_END) AS ELAPSED_TIME_MS

FROM

    START_NODE_INFO AS T1,
    END_NODE_INFO AS T2

WHERE

    T1.INSTANCE_ID = T2.INSTANCE_ID

Consulta do Data Lake

code language-sql 
WITH

START_NODE_INFO AS (

    SELECT

        timestamp AS TS_START,
        _experience.journeyOrchestration.stepEvents.nodeName AS NODE_NAME,
        _experience.journeyOrchestration.stepEvents.instanceID AS INSTANCE_ID

    FROM

        journey_step_events

    WHERE

        _experience.journeyOrchestration.stepEvents.journeyVersionID = '<journey version id>' AND
        _experience.journeyOrchestration.stepEvents.nodeName = '<name of node before wait activity>' AND
        _experience.journeyOrchestration.stepEvents.journeyNodeProcessed = true

),

END_NODE_INFO AS (

    SELECT

        timestamp AS TS_END,
        _experience.journeyOrchestration.stepEvents.nodeName AS NODE_NAME,
        _experience.journeyOrchestration.stepEvents.instanceID AS INSTANCE_ID

    FROM

        journey_step_events

    WHERE

        _experience.journeyOrchestration.stepEvents.journeyVersionID = '<journey version id>' AND
        _experience.journeyOrchestration.stepEvents.nodeName = '<name of wait activity node>' AND
        _experience.journeyOrchestration.stepEvents.journeyNodeProcessed = true

)

SELECT

    AVG(DATEDIFF(millisecond,T1.TS_START,T2.TS_END)) AS AVERAGE_ELAPSED_TIME,
    MIN(DATEDIFF(millisecond,T1.TS_START,T2.TS_END)) AS MIN_ELAPSED_TIME,
    MAX(DATEDIFF(millisecond,T1.TS_START,T2.TS_END)) AS MAX_ELAPSED_TIME

FROM

    START_NODE_INFO AS T1,
    END_NODE_INFO AS T2

WHERE

    T1.INSTANCE_ID = T2.INSTANCE_ID
Como verificar os detalhes de um serviceEvent

O conjunto de dados de Eventos de etapa de Jornada contém todos os stepEvents e serviceEvents. stepEvents são usados em relatórios, pois se relacionam a atividades (evento, ações etc.) de perfis em uma jornada. serviceEvents são armazenados no mesmo conjunto de dados e indicam informações adicionais para fins de depuração, por exemplo, o motivo para um descarte de evento de experiência.

Este é um exemplo de consulta para verificar os detalhes de um serviceEvent:

Consulta do Data Lake

code language-sql 
SELECT

     _experience.journeyOrchestration.profile.ID,
     _experience.journeyOrchestration.journey.versionID,
     to_json(_experience.journeyOrchestration.serviceEvents)

FROM journey_step_event

WHERE _experience.journeyOrchestration.serviceType is not null;

Erros de mensagem/ação message-action-errors

accordion
Lista de cada erro encontrado no jornada

Essa consulta permite listar cada erro encontrado no jornada ao executar uma mensagem/ação.

Consulta do Data Lake

code language-sql 
SELECT _experience.journeyOrchestration.stepEvents.actionExecutionError, count(distinct _id) FROM journey_step_events
WHERE _experience.journeyOrchestration.stepEvents.nodeName=<'message-name'>
AND _experience.journeyOrchestration.stepEvents.actionExecutionError IS NOT NULL
AND _experience.journeyOrchestration.stepEvents.journeyVersionID = '<journey-version-id>'
GROUP BY _experience.journeyOrchestration.stepEvents.actionExecutionError

Exemplo

code language-sql 
SELECT _experience.journeyOrchestration.stepEvents.actionExecutionError, count(distinct _id) FROM journey_step_events
WHERE _experience.journeyOrchestration.stepEvents.nodeName='Message - 100KB Email with Gateway and Kafkav2'
AND _experience.journeyOrchestration.stepEvents.actionExecutionError IS NOT NULL
AND _experience.journeyOrchestration.stepEvents.journeyVersionID = '67b14482-143e-4f83-9cf5-cfec0fca3d26'
GROUP BY _experience.journeyOrchestration.stepEvents.actionExecutionError

Esta consulta retorna todos os erros diferentes que ocorreram ao executar uma ação em uma jornada junto com a contagem de quantas vezes ela ocorreu.

Consultas baseadas em perfil profile-based-queries

Localizar se um perfil inseriu uma Jornada específica

Esta consulta verifica se um perfil específico inseriu uma jornada, contando os eventos associados a esse perfil e a combinação de jornada.

Consulta do Data Lake

code language-sql 
SELECT count(distinct _id) FROM journey_step_events
where
_experience.journeyOrchestration.stepEvents.journeyVersionID = '<journey-version-id>' AND
_experience.journeyOrchestration.stepEvents.profileID = '<profileID corresponding to the namespace used>'

Exemplo

code language-sql 
SELECT count(distinct _id) FROM journey_step_events
where
_experience.journeyOrchestration.stepEvents.journeyVersionID = 'ec9efdd0-8a7c-4d7a-a765-b2cad659fa4e' AND
_experience.journeyOrchestration.stepEvents.profileID = 'saurgarg@adobe.com'

O resultado deve ser maior que 0. Esta consulta retorna o número exato de vezes que um perfil inseriu uma jornada.

Descubra se um perfil recebeu uma mensagem específica

Método 1: se o nome da mensagem não for exclusivo na jornada (ela é usada em vários locais).

Consulta do Data Lake

code language-sql 
SELECT count(distinct _id) FROM journey_step_events WHERE
_experience.journeyOrchestration.stepEvents.nodeID='<NodeId in the UI corresponding to the message>' AND
_experience.journeyOrchestration.stepEvents.actionExecutionError IS NULL AND
_experience.journeyOrchestration.stepEvents.journeyVersionID = '<journey-version-id>' AND
_experience.journeyOrchestration.stepEvents.profileID = '<profileID corresponding to the namespace used>'

Exemplo

code language-sql 
SELECT count(distinct _id) FROM journey_step_events WHERE
_experience.journeyOrchestration.stepEvents.nodeID='17ae65a1-02dd-439d-b54e-b56a78520eba' AND
_experience.journeyOrchestration.stepEvents.actionExecutionError IS NULL AND
_experience.journeyOrchestration.stepEvents.journeyVersionID = '67b14482-143e-4f83-9cf5-cfec0fca3d26' AND
_experience.journeyOrchestration.stepEvents.profileID = 'saurgarg@adobe.com'

O resultado deve ser maior que 0. Esta consulta informa apenas se a ação de mensagem foi executada com êxito no lado da jornada.

Método 2: se o nome da mensagem for exclusivo na jornada.

Consulta do Data Lake

code language-sql 
SELECT count(distinct _id) FROM journey_step_events WHERE
_experience.journeyOrchestration.stepEvents.nodeName='<NodeName in the UI corresponding to the message>' AND
_experience.journeyOrchestration.stepEvents.actionExecutionError IS NULL AND
_experience.journeyOrchestration.stepEvents.journeyVersionID = '<journey-version-id>' AND
_experience.journeyOrchestration.stepEvents.profileID = '<profileID corresponding to the namespace used>'

Exemplo

code language-sql 
SELECT count(distinct _id) FROM journey_step_events WHERE
_experience.journeyOrchestration.stepEvents.nodeID='Message- 100KB Email' AND
_experience.journeyOrchestration.stepEvents.actionExecutionError IS NULL AND
_experience.journeyOrchestration.stepEvents.journeyVersionID = '67b14482-143e-4f83-9cf5-cfec0fca3d26' AND
_experience.journeyOrchestration.stepEvents.profileID = 'saurgarg@adobe.com'

A consulta retorna a lista de todas as mensagens juntamente com sua contagem invocada para o perfil selecionado.

Localizar todas as mensagens recebidas por um perfil nos últimos 30 dias

Esta consulta recupera todas as ações de mensagem executadas com êxito para um perfil específico nos últimos 30 dias, agrupadas por nome de mensagem.

Consulta do Data Lake

code language-sql 
SELECT _experience.journeyOrchestration.stepEvents.nodeName, count(distinct _id) FROM journey_step_events
WHERE  _experience.journeyOrchestration.stepEvents.actionExecutionError IS NULL AND
_experience.journeyOrchestration.stepEvents.nodeType = 'action' AND
_experience.journeyOrchestration.stepEvents.profileID = '<profileID corresponding to the namespace used>' AND
timestamp > (now() - interval '30' day)
GROUP BY _experience.journeyOrchestration.stepEvents.nodeName

Exemplo

code language-sql 
SELECT _experience.journeyOrchestration.stepEvents.nodeName, count(distinct _id) FROM journey_step_events
WHERE  _experience.journeyOrchestration.stepEvents.actionExecutionError IS NULL AND
_experience.journeyOrchestration.stepEvents.nodeType = 'action' AND
_experience.journeyOrchestration.stepEvents.profileID = 'saurgarg@adobe.com' AND
timestamp > (now() - interval '30' day)
GROUP BY _experience.journeyOrchestration.stepEvents.nodeName

A consulta retorna a lista de todas as mensagens juntamente com sua contagem invocada para o perfil selecionado.

Localizar todas as jornadas inseridas por um perfil nos últimos 30 dias

Esta consulta retorna todas as jornadas inseridas por um perfil específico nos últimos 30 dias, juntamente com a contagem de entradas de cada jornada.

Consulta do Data Lake

code language-sql 
SELECT _experience.journeyOrchestration.stepEvents.journeyVersionName, count(distinct _id) FROM journey_step_events
WHERE  _experience.journeyOrchestration.stepEvents.nodeType = 'start' AND
_experience.journeyOrchestration.stepEvents.profileID = '<profileID corresponding to the namespace used>' AND
timestamp > (now() - interval '30' day)
GROUP BY _experience.journeyOrchestration.stepEvents.journeyVersionName

Exemplo

code language-sql 
SELECT _experience.journeyOrchestration.stepEvents.journeyVersionName, count(distinct _id) FROM journey_step_events
WHERE  _experience.journeyOrchestration.stepEvents.nodeType = 'start' AND
_experience.journeyOrchestration.stepEvents.profileID = 'saurgarg@adobe.com' AND
timestamp > (now() - interval '30' day)
GROUP BY _experience.journeyOrchestration.stepEvents.journeyVersionName

A consulta retorna a lista de todos os nomes de jornada juntamente com o número de vezes que o perfil consultado inseriu a jornada.

Número de perfis qualificados para uma jornada diariamente

Este query fornece um detalhamento diário do número de perfis distintos que inseriram uma jornada em um período especificado.

Consulta do Data Lake

code language-sql 
SELECT DATE(timestamp), count(distinct _experience.journeyOrchestration.stepEvents.profileID) FROM journey_step_events
WHERE DATE(timestamp) > (now() - interval '<last x days>' day)
AND _experience.journeyOrchestration.stepEvents.journeyVersionID = '<journey-version-id>'
GROUP BY DATE(timestamp)
ORDER BY DATE(timestamp) desc

Exemplo

code language-sql 
SELECT DATE(timestamp), count(distinct _experience.journeyOrchestration.stepEvents.profileID) FROM journey_step_events
WHERE DATE(timestamp) > (now() - interval '100' day)
AND _experience.journeyOrchestration.stepEvents.journeyVersionID = '180ad071-d42d-42bb-8724-2a6ff0a109f1'
GROUP BY DATE(timestamp)
ORDER BY DATE(timestamp) desc

O query retorna, para o período definido, o número de perfis que entraram na jornada a cada dia. Se um perfil inserido por meio de várias identidades, ele será contado duas vezes. Se a reentrada estiver ativada, a contagem de perfis poderá ser duplicada em dias diferentes se ela entrar novamente na jornada em dias diferentes.

Saiba como solucionar problemas de tipos de eventos descartados em jornada_step_events.

Consultas relacionadas ao público-alvo de leitura read-segment-queries

Tempo necessário para concluir um trabalho de exportação de público

Esta consulta calcula a duração de um trabalho de exportação de público-alvo localizando a diferença de tempo entre o momento em que o trabalho foi enfileirado e o momento em que foi concluído.

Consulta do Data Lake

code language-sql 
select DATEDIFF (minute,
              (select timestamp
                where
_experience.journeyOrchestration.journey.versionID = '<journey-version-id>' AND
_experience.journeyOrchestration.serviceEvents.segmentExportJob.status = 'queued') ,
              (select timestamp
                where
_experience.journeyOrchestration.journey.versionID = '<journey-version-id>' AND
_experience.journeyOrchestration.serviceEvents.segmentExportJob.status = 'finished')) AS export_job_runtime;

Exemplo

code language-sql 
select DATEDIFF (minute,
              (select timestamp
                where
_experience.journeyOrchestration.journey.versionID = '180ad071-d42d-42bb-8724-2a6ff0a109f1' AND
_experience.journeyOrchestration.serviceEvents.segmentExportJob.status = 'queued') ,
              (select timestamp
                where
_experience.journeyOrchestration.journey.versionID = '180ad071-d42d-42bb-8724-2a6ff0a109f1' AND
_experience.journeyOrchestration.serviceEvents.segmentExportJob.status = 'finished')) AS export_job_runtime;

A consulta retorna a diferença de tempo, em minutos, entre o momento em que o trabalho de exportação de público-alvo foi enfileirado e o momento em que foi encerrado.

Número de perfis descartados pela jornada porque estavam duplicados

Esta consulta conta o número de perfis distintos que foram descartados devido a erros de duplicação de instância durante a atividade Ler público.

Consulta do Data Lake

code language-sql 
SELECT count(distinct _experience.journeyOrchestration.profile.ID) FROM journey_step_events
where
_experience.journeyOrchestration.journey.versionID = '<journey-version-id>' AND
_experience.journeyOrchestration.serviceEvents.segmentExportJob.eventCode = 'ERROR_INSTANCE_DUPLICATION'

Exemplo

code language-sql 
SELECT count(distinct _experience.journeyOrchestration.profile.ID) FROM journey_step_events
where
_experience.journeyOrchestration.journey.versionID = '180ad071-d42d-42bb-8724-2a6ff0a109f1' AND
_experience.journeyOrchestration.serviceEvents.segmentExportJob.eventCode = 'ERROR_INSTANCE_DUPLICATION'

A consulta retorna todas as IDs de perfil que foram descartadas pela jornada porque estavam duplicadas.

Número de perfis descartados pela jornada devido a um namespace inválido

Esta consulta retorna a contagem de perfis que foram descartados porque tinham um namespace inválido ou uma identidade ausente para o namespace necessário.

Consulta do Data Lake

code language-sql 
SELECT count(*) FROM journey_step_events
where
_experience.journeyOrchestration.journey.versionID = '<journey-version-id>' AND
_experience.journeyOrchestration.serviceEvents.segmentExportJob.eventCode = 'ERROR_INSTANCE_BAD_NAMESPACE'

Exemplo

code language-sql 
SELECT count(*) FROM journey_step_events
where
_experience.journeyOrchestration.journey.versionID = '180ad071-d42d-42bb-8724-2a6ff0a109f1' AND
_experience.journeyOrchestration.serviceEvents.segmentExportJob.eventCode = 'ERROR_INSTANCE_BAD_NAMESPACE'

A consulta retorna todas as IDs de perfil que foram descartadas pela jornada porque tinham um namespace inválido ou nenhuma identidade para esse namespace.

Número de perfis que foram descartados pela jornada devido à falta de um mapa de identidade

Essa consulta conta os perfis que foram descartados porque um mapa de identidade necessário para a execução da jornada estava ausente.

Consulta do Data Lake

code language-sql 
SELECT count(*) FROM journey_step_events
where
_experience.journeyOrchestration.journey.versionID = '<journey-version-id>' AND
_experience.journeyOrchestration.serviceEvents.segmentExportJob.eventCode = 'ERROR_INSTANCE_NO_IDENTITY_MAP'

Exemplo

code language-sql 
SELECT count(*) FROM journey_step_events
where
_experience.journeyOrchestration.journey.versionID = '180ad071-d42d-42bb-8724-2a6ff0a109f1' AND
_experience.journeyOrchestration.serviceEvents.segmentExportJob.eventCode = 'ERROR_INSTANCE_NO_IDENTITY_MAP'

A consulta retorna todas as IDs de perfil que foram descartadas pela jornada porque o mapa de identidade estava ausente.

Número de perfis que foram descartados pela jornada porque a jornada estava no nó de teste e o perfil não era um perfil de teste

Esta consulta identifica perfis que foram descartados quando a jornada estava sendo executada no modo de teste, mas o perfil não tinha o atributo testProfile definido como verdadeiro.

Consulta do Data Lake

code language-sql 
SELECT count(distinct _experience.journeyOrchestration.profile.ID) FROM journey_step_events
where
_experience.journeyOrchestration.journey.versionID = '<journey-version-id>' AND
_experience.journeyOrchestration.serviceEvents.segmentExportJob.eventCode = 'ERROR_INSTANCE_NOT_A_TEST_PROFILE'

Exemplo

code language-sql 
SELECT count(distinct _experience.journeyOrchestration.profile.ID) FROM journey_step_events
where
_experience.journeyOrchestration.journey.versionID = '180ad071-d42d-42bb-8724-2a6ff0a109f1' AND
_experience.journeyOrchestration.serviceEvents.segmentExportJob.eventCode = 'ERROR_INSTANCE_NOT_A_TEST_PROFILE'

A consulta retorna todas as IDs de perfil que foram descartadas pela jornada porque o trabalho de exportação foi executado no modo de teste, mas o perfil não tinha o atributo testProfile definido como verdadeiro.

Número de perfis descartados pela jornada devido a um erro interno

Esta consulta retorna a contagem de perfis que foram descartados devido a erros internos do sistema durante a execução da jornada.

Consulta do Data Lake

code language-sql 
SELECT count(distinct _experience.journeyOrchestration.profile.ID) FROM journey_step_events
where
_experience.journeyOrchestration.journey.versionID = '<journey-version-id>' AND
_experience.journeyOrchestration.serviceEvents.segmentExportJob.eventCode = 'ERROR_INSTANCE_INTERNAL'

Exemplo

code language-sql 
SELECT count(distinct _experience.journeyOrchestration.profile.ID) FROM journey_step_events
where
_experience.journeyOrchestration.journey.versionID = '180ad071-d42d-42bb-8724-2a6ff0a109f1' AND
_experience.journeyOrchestration.serviceEvents.segmentExportJob.eventCode = 'ERROR_INSTANCE_INTERNAL'

A consulta retorna todas as IDs de perfil que foram descartadas pela jornada devido a um erro interno.

Visão geral do público-alvo de leitura para uma determinada versão do jornada

Esta consulta fornece uma visão geral abrangente da atividade Ler público, incluindo detalhes do trabalho de exportação de segmento, códigos de evento, status e contagens de perfil para todos os estágios do processo de exportação de público-alvo.

Consulta do Data Lake

code language-sql 
SELECT
    _experience.journeyOrchestration.serviceEvents.segmentExportJob.eventCode           AS EVENT_CODE,
    _experience.journeyOrchestration.serviceEvents.segmentExportJob.exportSegmentID     AS SEGMENT_ID,
    _experience.journeyOrchestration.serviceEvents.segmentExportJob.ID                  AS EXPORTJOB_ID,
    _experience.journeyOrchestration.serviceEvents.segmentExportJob.status              AS EXPORTJOB_STATUS,
    _experience.journeyOrchestration.serviceEvents.segmentExportJob.exportCountTotal    AS TOTAL_EXPORTED_PROFILES_COUNT,
    _experience.journeyOrchestration.serviceEvents.segmentExportJob.exportCountRealized AS SUCCESS_EXPORTED_PROFILES_COUNT,
    _experience.journeyOrchestration.serviceEvents.segmentExportJob.exportCountFailed   AS FAILED_EXPORTED_PROFILES_COUNT
FROM
    journey_step_events
WHERE
    _experience.journeyOrchestration.journey.versionID = '<journey-version-id>' AND
    _experience.journeyOrchestration.serviceEvents.segmentExportJob.eventType = 'segmenttrigger-orchestrator'

Ele retornará todos os eventos de serviço relacionados à versão do jornada fornecida. Podemos acompanhar a cadeia de operações:

  • criação de tópico
  • exportar criação de trabalho
  • finalização do trabalho de exportação (com métricas em perfis exportados)
  • trabalhador processando desligamento

Também podemos detectar problemas como:

  • erros no tópico ou na criação do trabalho de exportação (incluindo tempos limite em chamadas da API de exportação de público)
  • trabalhos de exportação que podem ficar paralisados (caso em que, para uma determinada versão do jornada, não temos nenhum evento relacionado ao encerramento do trabalho de exportação)
  • problemas do trabalhador, se recebermos um evento de desligamento do trabalho de exportação, mas nenhum trabalhador estiver processando um desligamento

IMPORTANTE: se não houver nenhum evento retornado por essa consulta, talvez seja devido a um dos seguintes motivos:

  • a versão do jornada não atingiu o cronograma
  • se a versão do jornada deveria ter acionado o trabalho de exportação chamando o orchestrator, algo deu errado no fluxo upstream: problema na implantação do jornada, evento comercial ou problema com o scheduler.
Obter erros de público-alvo de leitura para uma determinada versão do jornada

Essa consulta filtra códigos de evento de erro específicos relacionados a falhas de Leitura de público, como erros de criação de tópico, erros de chamada de API, tempos limite e trabalhos de exportação com falha.

Consulta do Data Lake

code language-sql 
SELECT
    _experience.journeyOrchestration.serviceEvents.segmentExportJob.eventCode           AS EVENT_CODE,
    _experience.journeyOrchestration.serviceEvents.segmentExportJob.exportSegmentID     AS SEGMENT_ID,
    _experience.journeyOrchestration.serviceEvents.segmentExportJob.ID                  AS EXPORTJOB_ID,
    _experience.journeyOrchestration.serviceEvents.segmentExportJob.status              AS EXPORTJOB_STATUS,
    _experience.journeyOrchestration.serviceEvents.segmentExportJob.exportCountTotal    AS TOTAL_EXPORTED_PROFILES_COUNT,
    _experience.journeyOrchestration.serviceEvents.segmentExportJob.exportCountRealized AS SUCCESS_EXPORTED_PROFILES_COUNT,
    _experience.journeyOrchestration.serviceEvents.segmentExportJob.exportCountFailed   AS FAILED_EXPORTED_PROFILES_COUNT
FROM
    journey_step_events
WHERE
    _experience.journeyOrchestration.journey.versionID = '<journey-version-id>' AND
    _experience.journeyOrchestration.serviceEvents.segmentExportJob.eventType = 'segmenttrigger-orchestrator' AND
    _experience.journeyOrchestration.serviceEvents.segmentExportJob.eventCode IN (
        'ERROR_TOPIC_CREATION',
        'ERROR_EXPORTJOB_APICALL',
        'ERROR_EXPORTJOB_APICALL_TIMEOUT',
        'ERROR_EXPORTJOB_FAILED'
    )
Obter status de processamento do trabalho de exportação

Essa consulta recupera o status de processamento de trabalhos de exportação de público-alvo, mostrando se eles tiveram êxito ou falharam junto com as métricas de exportação de perfil.

Consulta do Data Lake

code language-sql 
SELECT
    _experience.journeyOrchestration.serviceEvents.segmentExportJob.eventCode           AS EVENT_CODE,
    _experience.journeyOrchestration.serviceEvents.segmentExportJob.exportSegmentID     AS SEGMENT_ID,
    _experience.journeyOrchestration.serviceEvents.segmentExportJob.ID                  AS EXPORTJOB_ID,
    _experience.journeyOrchestration.serviceEvents.segmentExportJob.status              AS EXPORTJOB_STATUS,
    _experience.journeyOrchestration.serviceEvents.segmentExportJob.exportCountTotal    AS TOTAL_EXPORTED_PROFILES_COUNT,
    _experience.journeyOrchestration.serviceEvents.segmentExportJob.exportCountRealized AS SUCCESS_EXPORTED_PROFILES_COUNT,
    _experience.journeyOrchestration.serviceEvents.segmentExportJob.exportCountFailed   AS FAILED_EXPORTED_PROFILES_COUNT
FROM
    journey_step_events
WHERE
    _experience.journeyOrchestration.journey.versionID = '<journey-version-id>' AND
    _experience.journeyOrchestration.serviceEvents.segmentExportJob.eventType = 'segmenttrigger-orchestrator' AND
    _experience.journeyOrchestration.serviceEvents.segmentExportJob.eventCode IN (
        'INFO_EXPORTJOB_SUCCEEDED',
        'ERROR_EXPORTJOB_FAILED'
    )

Se nenhum registro for retornado, significa que:

  • ocorreu um erro durante a criação do tópico ou do trabalho de exportação
  • o trabalho de exportação ainda está em execução
Obter métricas sobre perfis exportados, incluindo descartes e métricas de trabalho de exportação para cada trabalho de exportação

Esta consulta combina contagens de perfis descartados com métricas de trabalho de exportação para fornecer uma exibição completa do desempenho da exportação de público-alvo para cada trabalho de exportação individual.

Consulta do Data Lake

code language-sql 
WITH

DISCARDED_EXPORTED_PROFILES AS (

    SELECT
        _experience.journeyOrchestration.serviceEvents.segmentExportJob.ID AS EXPORTJOB_ID,
        count(distinct _experience.journeyOrchestration.profile.ID) AS DISCARDED_PROFILES_COUNT
    FROM
        journey_step_events
    WHERE
        _experience.journeyOrchestration.journey.versionID = '<journey-version-id>' AND
        _experience.journeyOrchestration.serviceEvents.segmentExportJob.eventCode IN (
            'ERROR_INSTANCE_DUPLICATION',
            'ERROR_INSTANCE_BAD_NAMESPACE',
            'ERROR_INSTANCE_NO_IDENTITY_MAP',
            'ERROR_INSTANCE_NOT_A_TEST_PROFILE',
            'ERROR_INSTANCE_INTERNAL'
        )
    GROUP BY
        _experience.journeyOrchestration.serviceEvents.segmentExportJob.ID

),

SEGMENT_EXPORT_METRICS AS (

    SELECT
        _experience.journeyOrchestration.serviceEvents.segmentExportJob.ID AS EXPORTJOB_ID,
        sum(_experience.journeyOrchestration.serviceEvents.segmentExportJob.exportCountTotal) AS TOTAL_EXPORTED_PROFILES_COUNT,
        sum(_experience.journeyOrchestration.serviceEvents.segmentExportJob.exportCountRealized) AS SUCCESS_EXPORTED_PROFILES_COUNT,
        sum(_experience.journeyOrchestration.serviceEvents.segmentExportJob.exportCountFailed) AS FAILED_EXPORTED_PROFILES_COUNT
    FROM
        journey_step_events
    WHERE
        _experience.journeyOrchestration.journey.versionID = '<journey-version-id>' AND
        _experience.journeyOrchestration.serviceEvents.segmentExportJob.eventType = 'segmenttrigger-orchestrator' AND
        _experience.journeyOrchestration.serviceEvents.segmentExportJob.eventCode IN (
            'INFO_EXPORTJOB_SUCCEEDED',
            'ERROR_EXPORTJOB_FAILED'
        )
    GROUP BY
        _experience.journeyOrchestration.serviceEvents.segmentExportJob.ID

)

SELECT
    sum(T2.TOTAL_EXPORTED_PROFILES_COUNT),
    sum(T2.SUCCESS_EXPORTED_PROFILES_COUNT),
    sum(T2.FAILED_EXPORTED_PROFILES_COUNT),
    sum(T1.DISCARDED_PROFILES_COUNT)
FROM
    DISCARDED_EXPORTED_PROFILES AS T1,
    SEGMENT_EXPORT_METRICS AS T2
WHERE T1.EXPORTJOB_ID = T2.EXPORTJOB_ID
Obter métricas agregadas (trabalhos de exportação de público-alvo e descartes) em todos os trabalhos de exportação

Essa consulta agrega métricas gerais em todos os trabalhos de exportação para uma determinada versão do jornada, útil para jornadas recorrentes ou jornadas acionadas por eventos comerciais com reutilização de tópico.

Consulta do Data Lake

code language-sql 
WITH

DISCARDED_EXPORTED_PROFILES AS (

    SELECT
        _experience.journeyOrchestration.journey.versionID AS JOURNEYVERSION_ID,
        count(distinct _experience.journeyOrchestration.profile.ID) AS DISCARDED_PROFILES_COUNT
    FROM
        journey_step_events
    WHERE
        _experience.journeyOrchestration.journey.versionID = '<journey-version-id>' AND
        _experience.journeyOrchestration.serviceEvents.segmentExportJob.eventCode IN (
            'ERROR_INSTANCE_DUPLICATION',
            'ERROR_INSTANCE_BAD_NAMESPACE',
            'ERROR_INSTANCE_NO_IDENTITY_MAP',
            'ERROR_INSTANCE_NOT_A_TEST_PROFILE',
            'ERROR_INSTANCE_INTERNAL'
        )
    GROUP BY
        _experience.journeyOrchestration.journey.versionID
),

SEGMENT_EXPORT_METRICS AS (

    SELECT
        _experience.journeyOrchestration.journey.versionID AS JOURNEYVERSION_ID,
        sum(_experience.journeyOrchestration.serviceEvents.segmentExportJob.exportCountTotal) AS TOTAL_EXPORTED_PROFILES_COUNT,
        sum(_experience.journeyOrchestration.serviceEvents.segmentExportJob.exportCountRealized) AS SUCCESS_EXPORTED_PROFILES_COUNT,
        sum(_experience.journeyOrchestration.serviceEvents.segmentExportJob.exportCountFailed) AS FAILED_EXPORTED_PROFILES_COUNT
    FROM
        journey_step_events
    WHERE
        _experience.journeyOrchestration.journey.versionID = '<journey-version-id>' AND
        _experience.journeyOrchestration.serviceEvents.segmentExportJob.eventType = 'segmenttrigger-orchestrator' AND
        _experience.journeyOrchestration.serviceEvents.segmentExportJob.eventCode IN (
            'INFO_EXPORTJOB_SUCCEEDED',
            'ERROR_EXPORTJOB_FAILED'
        )
    GROUP BY
          _experience.journeyOrchestration.journey.versionID

)

SELECT
    sum(T2.TOTAL_EXPORTED_PROFILES_COUNT),
    sum(T2.SUCCESS_EXPORTED_PROFILES_COUNT),
    sum(T2.FAILED_EXPORTED_PROFILES_COUNT),
    sum(T1.DISCARDED_PROFILES_COUNT)
FROM
    DISCARDED_EXPORTED_PROFILES AS T1,
    SEGMENT_EXPORT_METRICS AS T2
WHERE T1.JOURNEYVERSION_ID = T2.JOURNEYVERSION_ID

Esta consulta é diferente da anterior.

Ele retorna as métricas gerais de uma determinada versão do jornada, independentemente das tarefas que podem ter sido executadas para ele (no caso de jornadas recorrentes, eventos comerciais acionados por meio da reutilização de tópicos).

Consultas relacionadas à qualificação de público-alvo segment-qualification-queries

Perfil descartado devido a uma realização de público-alvo diferente da configurada

Esta consulta identifica perfis que foram descartados porque o status de realização do público-alvo não correspondia à configuração de Qualificação de público-alvo da jornada (por exemplo, configurado para "entra", mas o perfil "sai").

Consulta do Data Lake

code language-sql 
SELECT DATE(timestamp),  _experience.journeyOrchestration.profile.ID
FROM journey_step_events
where
_experience.journeyOrchestration.journey.versionID = '<journey-version id>' AND
_experience.journeyOrchestration.serviceEvents.dispatcher.eventType = 'ERROR_SEGMENT_REALISATION_CONDITION_MISMATCH'

Exemplo

code language-sql 
SELECT DATE(timestamp),  _experience.journeyOrchestration.profile.ID
FROM journey_step_events
where
_experience.journeyOrchestration.journey.versionID = 'a868f3c9-4888-46ac-a274-94cdf1c4159d' AND
_experience.journeyOrchestration.serviceEvents.dispatcher.eventType = 'ERROR_SEGMENT_REALISATION_CONDITION_MISMATCH'

Esta consulta retorna todas as IDs de perfil que foram descartadas pela versão do jornada devido à realização incorreta do público-alvo.

Eventos de qualificação de público-alvo descartados por qualquer outro motivo para um perfil específico

Esta consulta recupera todas as qualificações de público-alvo ou eventos externos que foram descartados para um perfil específico devido a erros de serviço interno.

Consulta do Data Lake

code language-sql 
SELECT DATE(timestamp),  _experience.journeyOrchestration.profile.ID, _experience.journeyOrchestration.serviceEvents.dispatcher.projectionID
FROM journey_step_events
where
_experience.journeyOrchestration.profile.ID = '<profile-id>' AND
_experience.journeyOrchestration.serviceEvents.dispatcher.eventCode = 'discard' AND
_experience.journeyOrchestration.serviceEvents.dispatcher.eventType = 'ERROR_SERVICE_INTERNAL';

Exemplo

code language-sql 
SELECT DATE(timestamp),  _experience.journeyOrchestration.profile.ID, _experience.journeyOrchestration.serviceEvents.dispatcher.projectionID
FROM journey_step_events
where
_experience.journeyOrchestration.profile.ID = 'mandee@adobe.com' AND
_experience.journeyOrchestration.serviceEvents.dispatcher.eventCode = 'discard' AND
_experience.journeyOrchestration.serviceEvents.dispatcher.eventType = 'ERROR_SERVICE_INTERNAL';

Esta consulta retorna todos os eventos (eventos externos/eventos de qualificação de público-alvo) que foram descartados por qualquer outro motivo para um perfil.

Consultas baseadas em eventos event-based-queries

Verificar se um evento comercial foi recebido para uma jornada

Essa consulta conta o número de vezes que um evento comercial foi recebido por uma jornada, agrupado por data, em um intervalo de tempo especificado.

Consulta do Data Lake

code language-sql 
SELECT DATE(timestamp), count(distinct _id)
FROM journey_step_events
where
_experience.journeyOrchestration.stepEvents.journeyVersionID = '<journey-version-id>' AND
_experience.journeyOrchestration.stepEvents.nodeName = '<node-name-corresponding-to-business-event>' AND
_experience.journeyOrchestration.stepEvents.nodeType = 'start' AND
WHERE DATE(timestamp) > (now() - interval '<last x hours>' hour)

Exemplo

code language-sql 
SELECT DATE(timestamp), count(distinct _id)
FROM journey_step_events
where
_experience.journeyOrchestration.stepEvents.journeyVersionID = 'b1093bd4-11f3-44cc-961e-33925cc58e18' AND
_experience.journeyOrchestration.stepEvents.nodeName = 'TEST_MLTrainingSession' AND
_experience.journeyOrchestration.stepEvents.nodeType = 'start' AND
WHERE DATE(timestamp) > (now() - interval '6' hour)
Verifique se um evento externo de um perfil foi descartado porque nenhuma jornada relacionada foi encontrada

Esta consulta identifica quando um evento externo para um perfil específico foi descartado porque não havia nenhuma jornada ativa ou correspondente configurada para receber esse evento.

Consulta do Data Lake

code language-sql 
SELECT _experience.journeyOrchestration.profile.ID, DATE(timestamp) FROM journey_step_events
where
_experience.journeyOrchestration.serviceEvents.dispatcher.eventID = '<eventId>' AND
_experience.journeyOrchestration.profile.ID = '<profileId>' AND
_experience.journeyOrchestration.serviceEvents.dispatcher.eventCode = 'discard' AND
_experience.journeyOrchestration.serviceEvents.dispatcher.eventType = 'EVENT_WITH_NO_JOURNEY'

Exemplo

code language-sql 
SELECT _experience.journeyOrchestration.profile.ID, DATE(timestamp) FROM journey_step_events
where
_experience.journeyOrchestration.serviceEvents.dispatcher.eventID = '515bff852185e434ca5c83bcfc4f24626b1545ca615659fc4cfff91626ce61a6' AND
_experience.journeyOrchestration.profile.ID = 'mandee@adobe.com' AND
_experience.journeyOrchestration.serviceEvents.dispatcher.eventCode = 'discard' AND
_experience.journeyOrchestration.serviceEvents.dispatcher.eventType = 'EVENT_WITH_NO_JOURNEY'

Saiba como solucionar problemas de tipos de eventos descartados em jornada_step_events.

Verifique se um evento externo de um perfil foi descartado por qualquer outro motivo

Esta consulta recupera eventos externos que foram descartados para um perfil específico devido a erros internos de serviço, juntamente com a ID do evento e o código de erro.

Consulta do Data Lake

code language-sql 
SELECT _experience.journeyOrchestration.profile.ID, DATE(timestamp), _experience.journeyOrchestration.serviceEvents.dispatcher.eventID, _experience.journeyOrchestration.serviceEvents.dispatcher.eventCode
FROM journey_step_events
where
_experience.journeyOrchestration.profile.ID='<profileID>' AND
_experience.journeyOrchestration.serviceEvents.dispatcher.eventID='<eventID>' AND
_experience.journeyOrchestration.serviceEvents.dispatcher.eventCode = 'discard' AND
_experience.journeyOrchestration.serviceEvents.dispatcher.eventType = 'ERROR_SERVICE_INTERNAL';

Exemplo

code language-sql 
SELECT _experience.journeyOrchestration.profile.ID, DATE(timestamp), _experience.journeyOrchestration.serviceEvents.dispatcher.eventID, _experience.journeyOrchestration.serviceEvents.dispatcher.eventCode
FROM journey_step_events
where
_experience.journeyOrchestration.profile.ID='mandee@adobe.com' AND
_experience.journeyOrchestration.serviceEvents.dispatcher.eventID='81c51be978d8bdf9ef497076b3e12b14533615522ecea9f5080a81c736491656' AND
_experience.journeyOrchestration.serviceEvents.dispatcher.eventCode = 'discard' AND
_experience.journeyOrchestration.serviceEvents.dispatcher.eventType = 'ERROR_SERVICE_INTERNAL';

Saiba como solucionar problemas de tipos de eventos descartados em jornada_step_events.

Verifique a contagem de todos os eventos descartados por stateMachine por errorCode

Essa consulta agrega todos os eventos descartados pela máquina de estado de jornada, agrupados por código de erro para ajudar a identificar os motivos mais comuns para descartes.

Consulta do Data Lake

code language-sql 
SELECT _experience.journeyOrchestration.serviceEvents.stateMachine.eventCode, COUNT() FROM journey_step_events
where
_experience.journeyOrchestration.serviceEvents.stateMachine.eventType = 'discard' GROUP BY _experience.journeyOrchestration.serviceEvents.stateMachine.eventCode

Exemplo

code language-sql 
SELECT _experience.journeyOrchestration.serviceEvents.stateMachine.eventCode, COUNT() FROM journey_step_events
where
_experience.journeyOrchestration.serviceEvents.stateMachine.eventType = 'discard' GROUP BY _experience.journeyOrchestration.serviceEvents.stateMachine.eventCode

Saiba como solucionar problemas de tipos de eventos descartados em jornada_step_events.

Verificar todos os eventos descartados porque a reentrada não foi permitida

Esta consulta identifica todos os eventos que foram descartados porque um perfil tentou inserir uma jornada novamente quando a reentrada não era permitida na configuração da jornada.

Consulta do Data Lake

code language-sql 
SELECT DATE(timestamp), _experience.journeyOrchestration.profile.ID,
_experience.journeyOrchestration.journey.versionID,
_experience.journeyOrchestration.serviceEvents.stateMachine.eventCode
FROM journey_step_events
where
_experience.journeyOrchestration.serviceEvents.stateMachine.eventType = 'discard' AND _experience.journeyOrchestration.serviceEvents.stateMachine.eventCode='reentranceNotAllowed'

Exemplo

code language-sql 
SELECT DATE(timestamp), _experience.journeyOrchestration.profile.ID,
_experience.journeyOrchestration.journey.versionID,
_experience.journeyOrchestration.serviceEvents.stateMachine.eventCode
FROM journey_step_events
where
_experience.journeyOrchestration.serviceEvents.stateMachine.eventType = 'discard' AND _experience.journeyOrchestration.serviceEvents.stateMachine.eventCode='reentranceNotAllowed'

Saiba como solucionar problemas de tipos de eventos descartados em jornada_step_events.

Consultas comuns baseadas em jornada journey-based-queries

Número de jornadas ativas diárias

Essa consulta retorna uma contagem diária de versões exclusivas do jornada que tinham atividade, ajudando você a entender os padrões de execução da jornada ao longo do tempo.

Consulta do Data Lake

code language-sql 
SELECT DATE(timestamp), count(distinct _experience.journeyOrchestration.stepEvents.journeyVersionID) FROM journey_step_events
WHERE DATE(timestamp) > (now() - interval '<last x days>' day)
GROUP BY DATE(timestamp)
ORDER BY DATE(timestamp) desc

Exemplo

code language-sql 
SELECT DATE(timestamp), count(distinct _experience.journeyOrchestration.stepEvents.journeyVersionID) FROM journey_step_events
WHERE DATE(timestamp) > (now() - interval '100' day)
GROUP BY DATE(timestamp)
ORDER BY DATE(timestamp) desc

A consulta retorna, para o período definido, a contagem de jornadas exclusivas que são acionadas a cada dia. Um único acionamento de jornada em vários dias será contado uma vez por dia.

Consultas em instâncias do jornada journey-instances-queries

Número de perfis em um estado específico por um tempo específico

Essa consulta usa Expressões de tabela comuns (CTEs) para identificar os perfis que estão aguardando atualmente em um nó específico de uma jornada, localizando os perfis que passaram pelo nó, mas ainda não avançaram para os próximos nós.

Consulta do Data Lake

code language-sql 
WITH

INSTANCES_PASSED_IN_ALL_NODES_WITH_DETAILS AS (

    SELECT
        STEP_EVENTS.timestamp AS TS,
        STEP_EVENTS._experience.journeyOrchestration.stepEvents.nodeName AS NODE_NAME,
        STEP_EVENTS._experience.journeyOrchestration.stepEvents.instanceID AS ID
    FROM
        journey_step_events AS STEP_EVENTS
    WHERE
        STEP_EVENTS._experience.journeyOrchestration.stepEvents.journeyVersionName = '<journey version name>'

),

INSTANCES_PASSED_IN_NODE_WITH_DETAILS AS (

    SELECT
        T1.TS AS TS,
        T1.ID AS ID
    FROM
        INSTANCES_PASSED_IN_ALL_NODES_WITH_DETAILS AS T1
    WHERE
        T1.NODE_NAME = '<specific node name>' AND
        <filter on time for profile in specific node>

),

INSTANCES_PASSED_IN_NEXT_NODES AS (

    SELECT
        T1.TS AS TS,
        T1.ID AS ID
    FROM
        INSTANCES_PASSED_IN_ALL_NODES_WITH_DETAILS AS T1
    WHERE
        T1.NODE_NAME in (<list of next node names from the specific node>)

),

INSTANCES_PASSED_IN_NODE_NOT_PASSED_IN_NODES AS (

    SELECT
        distinct T1.ID AS ID
    FROM
        INSTANCES_PASSED_IN_NODE_WITH_DETAILS AS T1

    EXCEPT

    SELECT
        distinct T1.ID AS ID
    FROM
        INSTANCES_PASSED_IN_NEXT_NODES AS T1

)

SELECT
    DATE_FORMAT(T1.TS,'<date pattern>') AS DATETIME,
    count(T1.ID) AS INSTANCES_COUNT
FROM
    INSTANCES_PASSED_IN_NODE_WITH_DETAILS AS T1,
    INSTANCES_PASSED_IN_NODE_NOT_PASSED_IN_NODES AS T2
WHERE
    T1.ID = T2.ID
GROUP BY
    DATETIME
ORDER BY
    DATETIME DESC

Exemplo

code language-sql 
WITH

INSTANCES_PASSED_IN_ALL_NODES_WITH_DETAILS AS (

    SELECT
        STEP_EVENTS.timestamp AS TS,
        STEP_EVENTS._experience.journeyOrchestration.stepEvents.nodeName AS NODE_NAME,
        STEP_EVENTS._experience.journeyOrchestration.stepEvents.instanceID AS ID
    FROM
        journey_step_events AS STEP_EVENTS
    WHERE
        STEP_EVENTS._experience.journeyOrchestration.stepEvents.journeyVersionName = 'Journey20009'

),

INSTANCES_PASSED_IN_NODE_WITH_DETAILS AS (

    SELECT
        T1.TS AS TS,
        T1.ID AS ID
    FROM
        INSTANCES_PASSED_IN_ALL_NODES_WITH_DETAILS AS T1
    WHERE
        T1.NODE_NAME = 'slack_bso_tests - test1' AND
        T1.TS > (now() - interval '18 hour')

),

INSTANCES_PASSED_IN_NEXT_NODES AS (

    SELECT
        T1.TS AS TS,
        T1.ID AS ID
    FROM
        INSTANCES_PASSED_IN_ALL_NODES_WITH_DETAILS AS T1
    WHERE
        T1.NODE_NAME in ('slack_bso_tests - test2')

),

INSTANCES_PASSED_IN_NODE_NOT_PASSED_IN_NODES AS (

    SELECT
        distinct T1.ID AS ID
    FROM
        INSTANCES_PASSED_IN_NODE_WITH_DETAILS AS T1

    EXCEPT

    SELECT
        distinct T1.ID AS ID
    FROM
        INSTANCES_PASSED_IN_NEXT_NODES AS T1

)

SELECT
    DATE_FORMAT(T1.TS,'yyyy/MM/dd HH:mm') AS DATETIME,
    count(T1.ID) AS INSTANCES_COUNT
FROM
    INSTANCES_PASSED_IN_NODE_WITH_DETAILS AS T1,
    INSTANCES_PASSED_IN_NODE_NOT_PASSED_IN_NODES AS T2
WHERE
    T1.ID = T2.ID
GROUP BY
    DATETIME
ORDER BY
    DATETIME DESC
Quantos perfis saíram da jornada no período específico

Esta consulta conta as instâncias do jornada que saíram durante um período de tempo especificado, incluindo saídas devido a erros de conclusão, erros, tempos limite ou erros de limite.

Consulta do Data Lake

code language-sql 
SELECT
    DATE_FORMAT(STEP_EVENTS.timestamp,'yyyy/MM/dd HH:mm') AS DATETIME,
    count(STEP_EVENTS._experience.journeyOrchestration.stepEvents.instanceID) AS EXITED_INSTANCES_COUNT
FROM
    journey_step_events AS STEP_EVENTS
WHERE
    STEP_EVENTS._experience.journeyOrchestration.stepEvents.journeyVersionName = '<journey version name>' AND
    STEP_EVENTS._experience.journeyOrchestration.stepEvents.stepStatus in ('endStep', 'error', 'timedOut', 'cappingError') AND
    <timestamp filter>
GROUP BY
    DATETIME
ORDER BY
    DATETIME DESC

Exemplo

code language-sql 
SELECT
    DATE_FORMAT(STEP_EVENTS.timestamp,'yyyy/MM/dd HH:mm') AS DATETIME,
    count(STEP_EVENTS._experience.journeyOrchestration.stepEvents.instanceID) AS EXITED_INSTANCES_COUNT
FROM
    journey_step_events AS STEP_EVENTS
WHERE
    STEP_EVENTS._experience.journeyOrchestration.stepEvents.journeyVersionName = 'Journey20009' AND
    STEP_EVENTS._experience.journeyOrchestration.stepEvents.stepStatus in ('endStep', 'error', 'timedOut', 'cappingError') AND
    STEP_EVENTS.timestamp > (now() - interval '22 hour')
GROUP BY
    DATETIME
ORDER BY
    DATETIME DESC
Quantos perfis saíram da jornada no período específico com nó/status

Esta consulta fornece um detalhamento das saídas do jornada, mostrando o nome do nó e o status de saída de cada instância encerrada para ajudar a identificar onde e por que os perfis saíram da jornada.

Consulta do Data Lake

code language-sql 
SELECT
    DATE_FORMAT(STEP_EVENTS.timestamp,'yyyy/MM/dd HH:mm') AS DATETIME,
    STEP_EVENTS._experience.journeyOrchestration.stepEvents.nodeName AS NODE_NAME,
    STEP_EVENTS._experience.journeyOrchestration.stepEvents.stepStatus AS EXIT_STATUS,
    count(STEP_EVENTS._experience.journeyOrchestration.stepEvents.instanceID) AS EXITED_INSTANCES_COUNT
FROM
    journey_step_events AS STEP_EVENTS
WHERE
    STEP_EVENTS._experience.journeyOrchestration.stepEvents.journeyVersionName = '<journey version name>' AND
    STEP_EVENTS._experience.journeyOrchestration.stepEvents.stepStatus in ('endStep', 'error', 'timedOut', 'cappingError') AND
    <timestamp filter>
GROUP BY
    DATETIME, NODE_NAME, EXIT_STATUS
ORDER BY
    DATETIME DESC

Exemplo

code language-sql 
SELECT
    DATE_FORMAT(STEP_EVENTS.timestamp,'yyyy/MM/dd HH:mm') AS DATETIME,
    STEP_EVENTS._experience.journeyOrchestration.stepEvents.nodeName AS NODE_NAME,
    STEP_EVENTS._experience.journeyOrchestration.stepEvents.stepStatus AS EXIT_STATUS,
    count(STEP_EVENTS._experience.journeyOrchestration.stepEvents.instanceID) AS EXITED_INSTANCES_COUNT
FROM
    journey_step_events AS STEP_EVENTS
WHERE
    STEP_EVENTS._experience.journeyOrchestration.stepEvents.journeyVersionName = 'Journey20009' AND
    STEP_EVENTS._experience.journeyOrchestration.stepEvents.stepStatus in ('endStep', 'error', 'timedOut', 'cappingError') AND
    STEP_EVENTS.timestamp > (now() - interval '22 hour')
GROUP BY
    DATETIME, NODE_NAME, EXIT_STATUS
ORDER BY
    DATETIME DESC

Consultas relacionadas às métricas de desempenho de Ação personalizada query-custom-action

Número total de chamadas, erros e solicitações bem-sucedidas por segundo de cada ponto de extremidade em um período específico

Esta consulta fornece métricas de desempenho para ações HTTP personalizadas, incluindo total de chamadas, chamadas bem-sucedidas, contagens de erros por tipo (4xx, 5xx, tempos limite, limitados) e taxa de transferência em solicitações por segundo para cada endpoint.

Consulta do Data Lake

code language-sql 
SELECT
    _experience.journeyOrchestration.stepEvents.actionOriginEndpoint AS ENDPOINT,
    COUNT(1) AS TOTAL_CALLS,
    COUNT(CASE WHEN _experience.journeyOrchestration.stepEvents.actionExecutionError IS NULL THEN 1 END) AS SUCCESSFUL_CALLS,
    COUNT(CASE WHEN _experience.journeyOrchestration.stepEvents.actionExecutionError = 'http' AND
                    _experience.journeyOrchestration.stepEvents.actionExecutionErrorCode LIKE '4%' THEN 1 END) AS "4xx_ERRORS",
    COUNT(CASE WHEN _experience.journeyOrchestration.stepEvents.actionExecutionError = 'http' AND
                    _experience.journeyOrchestration.stepEvents.actionExecutionErrorCode LIKE '5%' THEN 1 END) AS "5xx_ERRORS",
    COUNT(CASE WHEN _experience.journeyOrchestration.stepEvents.actionExecutionError = 'timedout' THEN 1 END) AS TIMEOUTS,
    COUNT(CASE WHEN _experience.journeyOrchestration.stepEvents.actionExecutionError = 'capped' THEN 1 END) AS CAPPED_CALLS,
    ROUND(COUNT(_experience.journeyOrchestration.stepEvents.actionExecutionOriginStartTime) /
        COUNT(DISTINCT DATE_TRUNC('second', _experience.journeyOrchestration.stepEvents.actionExecutionOriginStartTime)), 0) AS THROUGHPUT_RPS
FROM
    journey_step_events
WHERE
    _experience.journeyOrchestration.stepEvents.actionType = 'customHttpAction' AND
    _experience.journeyOrchestration.stepEvents.actionOriginEndpoint IS NOT NULL AND
    (<actionExecutionOriginStartTime filter> OR
        (_experience.journeyOrchestration.stepEvents.actionExecutionError = 'capped' AND <timestamp filter>))
GROUP BY
    ENDPOINT
ORDER BY
    ENDPOINT;

Exemplo

code language-sql 
SELECT
    _experience.journeyOrchestration.stepEvents.actionOriginEndpoint AS ENDPOINT,
    COUNT(1) AS TOTAL_CALLS,
    COUNT(CASE WHEN _experience.journeyOrchestration.stepEvents.actionExecutionError IS NULL THEN 1 END) AS SUCCESSFUL_CALLS,
    COUNT(CASE WHEN _experience.journeyOrchestration.stepEvents.actionExecutionError = 'http' AND
                    _experience.journeyOrchestration.stepEvents.actionExecutionErrorCode LIKE '4%' THEN 1 END) AS "4xx_ERRORS",
    COUNT(CASE WHEN _experience.journeyOrchestration.stepEvents.actionExecutionError = 'http' AND
                    _experience.journeyOrchestration.stepEvents.actionExecutionErrorCode LIKE '5%' THEN 1 END) AS "5xx_ERRORS",
    COUNT(CASE WHEN _experience.journeyOrchestration.stepEvents.actionExecutionError = 'timedout' THEN 1 END) AS TIMEOUTS,
    COUNT(CASE WHEN _experience.journeyOrchestration.stepEvents.actionExecutionError = 'capped' THEN 1 END) AS CAPPED_CALLS,
    ROUND(COUNT(_experience.journeyOrchestration.stepEvents.actionExecutionOriginStartTime) /
        COUNT(DISTINCT DATE_TRUNC('second', _experience.journeyOrchestration.stepEvents.actionExecutionOriginStartTime)), 0) AS THROUGHPUT_RPS
FROM
    journey_step_events
WHERE
    _experience.journeyOrchestration.stepEvents.actionType = 'customHttpAction' AND
    _experience.journeyOrchestration.stepEvents.actionOriginEndpoint IS NOT NULL AND
    (_experience.journeyOrchestration.stepEvents.actionExecutionOriginStartTime > (now() - interval '1' day) OR
        (_experience.journeyOrchestration.stepEvents.actionExecutionError = 'capped' AND timestamp > (now() - interval '1' day)))
GROUP BY
    ENDPOINT
ORDER BY
    ENDPOINT;
Série temporal de chamadas bem-sucedidas, erros e taxa de transferência de cada endpoint durante um período específico

Esta consulta fornece as mesmas métricas de desempenho da consulta anterior, mas organizadas como uma série de tempo, mostrando como o desempenho do endpoint varia ao longo do tempo com granularidade minuto a minuto.

Consulta do Data Lake

code language-sql 
SELECT
    _experience.journeyOrchestration.stepEvents.actionOriginEndpoint AS ENDPOINT,
    DATE_FORMAT(COALESCE(_experience.journeyOrchestration.stepEvents.actionExecutionOriginStartTime, timestamp), 'yyyy/MM/dd HH:mm') AS SPAN,
    COUNT(1) AS TOTAL_CALLS,
    COUNT(CASE WHEN _experience.journeyOrchestration.stepEvents.actionExecutionError IS NULL THEN 1 END) AS SUCCESSFUL_CALLS,
    COUNT(CASE WHEN _experience.journeyOrchestration.stepEvents.actionExecutionError = 'http' AND
                    _experience.journeyOrchestration.stepEvents.actionExecutionErrorCode LIKE '4%' THEN 1 END) AS "4xx_ERRORS",
    COUNT(CASE WHEN _experience.journeyOrchestration.stepEvents.actionExecutionError = 'http' AND
                    _experience.journeyOrchestration.stepEvents.actionExecutionErrorCode LIKE '5%' THEN 1 END) AS "5xx_ERRORS",
    COUNT(CASE WHEN _experience.journeyOrchestration.stepEvents.actionExecutionError = 'timedout' THEN 1 END) AS TIMEOUTS,
    COUNT(CASE WHEN _experience.journeyOrchestration.stepEvents.actionExecutionError = 'capped' THEN 1 END) AS CAPPED_CALLS,
    ROUND(COUNT(_experience.journeyOrchestration.stepEvents.actionExecutionOriginStartTime) /
        COUNT(DISTINCT DATE_TRUNC('second', _experience.journeyOrchestration.stepEvents.actionExecutionOriginStartTime)), 0) AS THROUGHPUT_RPS
FROM
    journey_step_events
WHERE
    _experience.journeyOrchestration.stepEvents.actionType = 'customHttpAction' AND
    _experience.journeyOrchestration.stepEvents.actionOriginEndpoint IS NOT NULL AND
    (<actionExecutionOriginStartTime filter> OR
        (_experience.journeyOrchestration.stepEvents.actionExecutionError = 'capped' AND
           <timestamp filter>))
GROUP BY
    ENDPOINT, SPAN
ORDER BY
    ENDPOINT,
    SPAN;

Exemplo

code language-sql 
SELECT
    _experience.journeyOrchestration.stepEvents.actionOriginEndpoint AS ENDPOINT,
    DATE_FORMAT(COALESCE(_experience.journeyOrchestration.stepEvents.actionExecutionOriginStartTime, timestamp), 'yyyy/MM/dd HH:mm') AS SPAN,
    COUNT(1) AS TOTAL_CALLS,
    COUNT(CASE WHEN _experience.journeyOrchestration.stepEvents.actionExecutionError IS NULL THEN 1 END) AS SUCCESSFUL_CALLS,
    COUNT(CASE WHEN _experience.journeyOrchestration.stepEvents.actionExecutionError = 'http' AND
                    _experience.journeyOrchestration.stepEvents.actionExecutionErrorCode LIKE '4%' THEN 1 END) AS "4xx_ERRORS",
    COUNT(CASE WHEN _experience.journeyOrchestration.stepEvents.actionExecutionError = 'http' AND
                    _experience.journeyOrchestration.stepEvents.actionExecutionErrorCode LIKE '5%' THEN 1 END) AS "5xx_ERRORS",
    COUNT(CASE WHEN _experience.journeyOrchestration.stepEvents.actionExecutionError = 'timedout' THEN 1 END) AS TIMEOUTS,
    COUNT(CASE WHEN _experience.journeyOrchestration.stepEvents.actionExecutionError = 'capped' THEN 1 END) AS CAPPED_CALLS,
    ROUND(COUNT(_experience.journeyOrchestration.stepEvents.actionExecutionOriginStartTime) /
        COUNT(DISTINCT DATE_TRUNC('second', _experience.journeyOrchestration.stepEvents.actionExecutionOriginStartTime)), 0) AS THROUGHPUT_RPS
FROM
    journey_step_events
WHERE
    _experience.journeyOrchestration.stepEvents.actionType = 'customHttpAction' AND
    _experience.journeyOrchestration.stepEvents.actionOriginEndpoint IS NOT NULL AND
    (_experience.journeyOrchestration.stepEvents.actionExecutionOriginStartTime > (now() - interval '1' day) OR
        (_experience.journeyOrchestration.stepEvents.actionExecutionError = 'capped' AND
           timestamp > (now() - interval '1' day)))
GROUP BY
    ENDPOINT, SPAN
ORDER BY
    ENDPOINT,
    SPAN;
Latência de resposta de cada endpoint aos percentis 50, 95, 99 e 99,9 em um período específico

Esta consulta calcula os percentis de tempo de resposta para endpoints de ação personalizados, ajudando você a entender a distribuição de latência e identificar outliers de desempenho em diferentes limites de percentil.

Consulta do Data Lake

code language-sql 
SELECT
    _experience.journeyOrchestration.stepEvents.actionOriginEndpoint AS ENDPOINT,
    COUNT(1) AS SUCCESSFUL_CALLS,
    ROUND(PERCENTILE_CONT(0.50) WITHIN GROUP (ORDER BY _experience.journeyOrchestration.stepEvents.actionExecutionOriginTime),0) AS P50_LATENCY_MS,
    ROUND(PERCENTILE_CONT(0.95) WITHIN GROUP (ORDER BY _experience.journeyOrchestration.stepEvents.actionExecutionOriginTime),0) AS P95_LATENCY_MS,
    ROUND(PERCENTILE_CONT(0.99) WITHIN GROUP (ORDER BY _experience.journeyOrchestration.stepEvents.actionExecutionOriginTime),0) AS P99_LATENCY_MS,
    ROUND(PERCENTILE_CONT(0.999) WITHIN GROUP (ORDER BY _experience.journeyOrchestration.stepEvents.actionExecutionOriginTime),0) AS P999_LATENCY_MS
FROM
    journey_step_events
WHERE
    _experience.journeyOrchestration.stepEvents.actionType = 'customHttpAction' AND
    _experience.journeyOrchestration.stepEvents.actionOriginEndpoint IS NOT NULL AND
    _experience.journeyOrchestration.stepEvents.actionExecutionError IS NULL AND
    _experience.journeyOrchestration.stepEvents.actionExecutionOriginTime IS NOT NULL
    <actionExecutionOriginStartTime filter>
GROUP BY
    ENDPOINT
ORDER BY
    ENDPOINT;

Exemplo

code language-sql 
SELECT
    _experience.journeyOrchestration.stepEvents.actionOriginEndpoint AS ENDPOINT,
    COUNT(1) AS SUCCESSFUL_CALLS,
    ROUND(PERCENTILE_CONT(0.50) WITHIN GROUP (ORDER BY _experience.journeyOrchestration.stepEvents.actionExecutionOriginTime),0) AS P50_LATENCY_MS,
    ROUND(PERCENTILE_CONT(0.95) WITHIN GROUP (ORDER BY _experience.journeyOrchestration.stepEvents.actionExecutionOriginTime),0) AS P95_LATENCY_MS,
    ROUND(PERCENTILE_CONT(0.99) WITHIN GROUP (ORDER BY _experience.journeyOrchestration.stepEvents.actionExecutionOriginTime),0) AS P99_LATENCY_MS,
    ROUND(PERCENTILE_CONT(0.999) WITHIN GROUP (ORDER BY _experience.journeyOrchestration.stepEvents.actionExecutionOriginTime),0) AS P999_LATENCY_MS
FROM
    journey_step_events
WHERE
    _experience.journeyOrchestration.stepEvents.actionType = 'customHttpAction' AND
    _experience.journeyOrchestration.stepEvents.actionOriginEndpoint IS NOT NULL AND
    _experience.journeyOrchestration.stepEvents.actionExecutionError IS NULL AND
    _experience.journeyOrchestration.stepEvents.actionExecutionOriginTime IS NOT NULL AND
    _experience.journeyOrchestration.stepEvents.actionExecutionOriginStartTime > (now() - interval '1' day)
GROUP BY
    ENDPOINT
ORDER BY
    ENDPOINT;
Série temporal de percentis de latência de resposta de cada endpoint durante um período específico

Essa consulta fornece percentis de latência organizados como uma série de tempo, permitindo rastrear como os tempos de resposta do endpoint mudam ao longo do tempo em diferentes níveis de percentil.

Consulta do Data Lake

code language-sql 
SELECT
    _experience.journeyOrchestration.stepEvents.actionOriginEndpoint AS ENDPOINT,
    COUNT(1) AS SUCCESSFUL_CALLS,
    DATE_FORMAT(_experience.journeyOrchestration.stepEvents.actionExecutionOriginStartTime, 'yyyy/MM/dd HH:mm') AS SPAN,
    ROUND(PERCENTILE_CONT(0.50) WITHIN GROUP (ORDER BY _experience.journeyOrchestration.stepEvents.actionExecutionOriginTime),0) AS P50_LATENCY_MS,
    ROUND(PERCENTILE_CONT(0.95) WITHIN GROUP (ORDER BY _experience.journeyOrchestration.stepEvents.actionExecutionOriginTime),0) AS P95_LATENCY_MS,
    ROUND(PERCENTILE_CONT(0.99) WITHIN GROUP (ORDER BY _experience.journeyOrchestration.stepEvents.actionExecutionOriginTime),0) AS P99_LATENCY_MS,
    ROUND(PERCENTILE_CONT(0.999) WITHIN GROUP (ORDER BY _experience.journeyOrchestration.stepEvents.actionExecutionOriginTime),0) AS P999_LATENCY_MS
FROM
    journey_step_events
WHERE
    _experience.journeyOrchestration.stepEvents.actionType = 'customHttpAction' AND
    _experience.journeyOrchestration.stepEvents.actionOriginEndpoint IS NOT NULL AND
    _experience.journeyOrchestration.stepEvents.actionExecutionError IS NULL AND
    _experience.journeyOrchestration.stepEvents.actionExecutionOriginTime IS NOT NULL
    <actionExecutionOriginStartTime filter>
GROUP BY
    ENDPOINT,
    SPAN
ORDER BY
    ENDPOINT,
    SPAN;

Exemplo

code language-sql 
SELECT
    _experience.journeyOrchestration.stepEvents.actionOriginEndpoint AS ENDPOINT,
    COUNT(1) AS SUCCESSFUL_CALLS,
    DATE_FORMAT(_experience.journeyOrchestration.stepEvents.actionExecutionOriginStartTime, 'yyyy/MM/dd HH:mm') AS SPAN,
    ROUND(PERCENTILE_CONT(0.50) WITHIN GROUP (ORDER BY _experience.journeyOrchestration.stepEvents.actionExecutionOriginTime),0) AS P50_LATENCY_MS,
    ROUND(PERCENTILE_CONT(0.95) WITHIN GROUP (ORDER BY _experience.journeyOrchestration.stepEvents.actionExecutionOriginTime),0) AS P95_LATENCY_MS,
    ROUND(PERCENTILE_CONT(0.99) WITHIN GROUP (ORDER BY _experience.journeyOrchestration.stepEvents.actionExecutionOriginTime),0) AS P99_LATENCY_MS,
    ROUND(PERCENTILE_CONT(0.999) WITHIN GROUP (ORDER BY _experience.journeyOrchestration.stepEvents.actionExecutionOriginTime),0) AS P999_LATENCY_MS
FROM
    journey_step_events
WHERE
    _experience.journeyOrchestration.stepEvents.actionType = 'customHttpAction' AND
    _experience.journeyOrchestration.stepEvents.actionOriginEndpoint IS NOT NULL AND
    _experience.journeyOrchestration.stepEvents.actionExecutionError IS NULL AND
    _experience.journeyOrchestration.stepEvents.actionExecutionOriginTime IS NOT NULL AND
    _experience.journeyOrchestration.stepEvents.actionExecutionOriginStartTime > (now() - interval '1' day)
GROUP BY
    ENDPOINT,
    SPAN
ORDER BY
    ENDPOINT,
    SPAN;
Tempo de espera na fila em pontos de extremidade limitados nos percentis 50 e 95 em um período específico

Esta consulta analisa os tempos de espera da fila para endpoints com limitação, mostrando os percentis de espera 50 e 95 para ajudar você a entender o impacto da limitação em suas ações personalizadas.

Consulta do Data Lake

code language-sql 
SELECT
    _experience.journeyOrchestration.stepEvents.actionOriginEndpoint AS ENDPOINT,
    COUNT(1) AS THROTTLED_CALLS,
    ROUND(PERCENTILE_CONT(0.50) WITHIN GROUP (ORDER BY _experience.journeyOrchestration.stepEvents.actionWaitTime),0) AS P50_QUEUE_TIME_MS,
    ROUND(PERCENTILE_CONT(0.95) WITHIN GROUP (ORDER BY _experience.journeyOrchestration.stepEvents.actionWaitTime),0) AS P95_QUEUE_TIME_MS
FROM
    journey_step_events
WHERE
    _experience.journeyOrchestration.stepEvents.actionType = 'customHttpAction' AND
    _experience.journeyOrchestration.stepEvents.actionOriginEndpoint IS NOT NULL AND
    _experience.journeyOrchestration.stepEvents.actionIsThrottled = 'true' AND
    _experience.journeyOrchestration.stepEvents.actionWaitTime IS NOT NULL AND
    <actionExecutionOriginStartTime filter>
GROUP BY
    ENDPOINT
ORDER BY
    ENDPOINT;

Exemplo

code language-sql 
SELECT
    _experience.journeyOrchestration.stepEvents.actionOriginEndpoint AS ENDPOINT,
    COUNT(1) AS THROTTLED_CALLS,
    ROUND(PERCENTILE_CONT(0.50) WITHIN GROUP (ORDER BY _experience.journeyOrchestration.stepEvents.actionWaitTime),0) AS P50_QUEUE_TIME_MS,
    ROUND(PERCENTILE_CONT(0.95) WITHIN GROUP (ORDER BY _experience.journeyOrchestration.stepEvents.actionWaitTime),0) AS P95_QUEUE_TIME_MS
FROM
    journey_step_events
WHERE
    _experience.journeyOrchestration.stepEvents.actionType = 'customHttpAction' AND
    _experience.journeyOrchestration.stepEvents.actionOriginEndpoint IS NOT NULL AND
    _experience.journeyOrchestration.stepEvents.actionIsThrottled = 'true' AND
    _experience.journeyOrchestration.stepEvents.actionWaitTime IS NOT NULL AND
    _experience.journeyOrchestration.stepEvents.actionExecutionOriginStartTime > (now() - interval '1' day)
GROUP BY
    ENDPOINT
ORDER BY
    ENDPOINT;
Série de tempo de percentis de tempo de espera da fila para cada ponto de extremidade limitado

Essa consulta fornece percentis de tempo de espera de fila como uma série de tempo, permitindo monitorar como a limitação afeta os tempos de espera ao longo do tempo para cada endpoint.

Consulta do Data Lake

code language-sql 
SELECT
    _experience.journeyOrchestration.stepEvents.actionOriginEndpoint AS ENDPOINT,
    DATE_FORMAT(_experience.journeyOrchestration.stepEvents.actionExecutionOriginStartTime, 'yyyy/MM/dd HH:mm') AS SPAN,
    COUNT(1) AS THROTTLED_CALLS,
    ROUND(PERCENTILE_CONT(0.50) WITHIN GROUP (ORDER BY _experience.journeyOrchestration.stepEvents.actionWaitTime),0) AS P50_QUEUE_TIME_MS,
    ROUND(PERCENTILE_CONT(0.95) WITHIN GROUP (ORDER BY _experience.journeyOrchestration.stepEvents.actionWaitTime),0) AS P95_QUEUE_TIME_MS
FROM
    journey_step_events
WHERE
    _experience.journeyOrchestration.stepEvents.actionType = 'customHttpAction' AND
    _experience.journeyOrchestration.stepEvents.actionOriginEndpoint IS NOT NULL AND
    _experience.journeyOrchestration.stepEvents.actionIsThrottled = 'true' AND
    _experience.journeyOrchestration.stepEvents.actionWaitTime IS NOT NULL AND
    <actionExecutionOriginStartTime filter>
GROUP BY
    ENDPOINT,
    SPAN
ORDER BY
    ENDPOINT,
    SPAN;

Exemplo

code language-sql 
SELECT
    _experience.journeyOrchestration.stepEvents.actionOriginEndpoint AS ENDPOINT,
    DATE_FORMAT(_experience.journeyOrchestration.stepEvents.actionExecutionOriginStartTime, 'yyyy/MM/dd HH:mm') AS SPAN,
    COUNT(1) AS THROTTLED_CALLS,
    ROUND(PERCENTILE_CONT(0.50) WITHIN GROUP (ORDER BY _experience.journeyOrchestration.stepEvents.actionWaitTime),0) AS P50_QUEUE_TIME_MS,
    ROUND(PERCENTILE_CONT(0.95) WITHIN GROUP (ORDER BY _experience.journeyOrchestration.stepEvents.actionWaitTime),0) AS P95_QUEUE_TIME_MS
FROM
    journey_step_events
WHERE
    _experience.journeyOrchestration.stepEvents.actionType = 'customHttpAction' AND
    _experience.journeyOrchestration.stepEvents.actionOriginEndpoint IS NOT NULL AND
    _experience.journeyOrchestration.stepEvents.actionIsThrottled = 'true' AND
    _experience.journeyOrchestration.stepEvents.actionWaitTime IS NOT NULL AND
    _experience.journeyOrchestration.stepEvents.actionExecutionOriginStartTime > (now() - interval '1' day)
GROUP BY
    ENDPOINT,
    SPAN
ORDER BY
    ENDPOINT,
    SPAN;
Número de erros por tipo e código para um endpoint específico durante um período específico

Esta consulta fornece um detalhamento dos erros de um endpoint específico, agrupados por tipo de erro e código de erro, incluindo informações sobre tentativas de repetição.

Consulta do Data Lake

code language-sql 
SELECT
    _experience.journeyOrchestration.stepEvents.actionExecutionError AS ERROR_TYPE,
    _experience.journeyOrchestration.stepEvents.actionExecutionErrorCode AS ERROR_CODE,
    COUNT(1) AS CALLS,
    COUNT(CASE WHEN _experience.journeyOrchestration.stepEvents.actionExecutionOriginError IS NOT NULL THEN 1 END) AS CALLS_WITH_RETRY
FROM
    journey_step_events
WHERE
    _experience.journeyOrchestration.stepEvents.actionType = 'customHttpAction' AND
    _experience.journeyOrchestration.stepEvents.actionOriginEndpoint = '<endpoint URI>' AND
    _experience.journeyOrchestration.stepEvents.actionExecutionError IS NOT NULL AND
    (<actionExecutionOriginStartTime filter>) OR
        (_experience.journeyOrchestration.stepEvents.actionExecutionError = 'capped' AND <timestamp filter>))
GROUP BY
    ERROR_TYPE, ERROR_CODE
ORDER BY
    ERROR_TYPE, ERROR_CODE;

Exemplo

code language-sql 
SELECT
    _experience.journeyOrchestration.stepEvents.actionExecutionError AS ERROR_TYPE,
    _experience.journeyOrchestration.stepEvents.actionExecutionErrorCode AS ERROR_CODE,
    COUNT(1) AS CALLS,
    COUNT(CASE WHEN _experience.journeyOrchestration.stepEvents.actionExecutionOriginError IS NOT NULL THEN 1 END) AS CALLS_WITH_RETRY
FROM
    journey_step_events
WHERE
    _experience.journeyOrchestration.stepEvents.actionType = 'customHttpAction' AND
    _experience.journeyOrchestration.stepEvents.actionOriginEndpoint = 'https://example.com/my/endpoint' AND
    _experience.journeyOrchestration.stepEvents.actionExecutionError IS NOT NULL AND
    (_experience.journeyOrchestration.stepEvents.actionExecutionOriginStartTime > (now() - interval '1' day) OR
        (_experience.journeyOrchestration.stepEvents.actionExecutionError = 'capped' AND timestamp > (now() - interval '1' day)))
GROUP BY
    ERROR_TYPE, ERROR_CODE
ORDER BY
    ERROR_TYPE, ERROR_CODE;
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