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This page covers the steps to view new PDUSessionEstSR KPI within a given time range (a KPI that is computed by KPI MS) via UUI

Manual Configuration:

 1. UUI:

Update the images of the UUI components -

  • image: onap/usecase-ui-server: 5.1.1
  • image: onap/usecase-ui: 5.1.0

Deployment Prerequisite/dependencies for DCAE:

  1. VES, PM mapper and DataFile Collector, dcae-mongodb, Datalake Extraction Service(DES) and Datalake-feeder services should be running.

DCAE-MONGO DB:

  1. Login to dcae-mongodb container and execute following commands to check if PM data was saved in DB:
    1. mongo
    2. use datalake
    3. db.unauthenticatedperformancemeasurements.find({})

    4. to load sample data:

      sample mongodb data 
      db.unauthenticatedperformancemeasurements.insert({
  "event": {
    "commonEventHeader": {
      "domain": "perf3gpp",
      "eventId": "dfe43a5c-0868-4275-b1c9-e45945b6a38c",
      "eventName": "perf3gpp_CORE-cucpserver2_pmMeasResult",
      "lastEpochMicrosec": 1610689590387,
      "priority": "Normal",
      "reportingEntityName": "",
      "sequence": 1,
      "sourceName": "oteNB5309",
      "startEpochMicrosec": 1610689590387,
      "version": 4,
      "vesEventListenerVersion": "7.1",
      "timeZoneOffset": "UTC+05:00"
    },
    "perf3gppFields": {
      "perf3gppFieldsVersion": "1.0",
      "measDataCollection": {
        "granularityPeriod": 900,
        "measuredEntityUserName": "",
        "measuredEntityDn": "cucpserver2",
        "measuredEntitySoftwareVersion": "r0.1",
        "measInfoList": [
          {
            "measInfoId": {
              "sMeasTypesList": "SLICE"
            },
            "measTypes": {
              "sMeasTypesList": [
                "PDUSessionEstSR.00110010"
              ]
            },
            "measValuesList": [
              {
                "suspectFlag": false,
                "measResults": [
                  {
                    "p": 1,
                    "sValue": "166"
                  }
                ]
              }
            ]
          }
        ]
      }
    }
  }
})

db.unauthenticatedperformancemeasurements.insert({
  "event": {
    "commonEventHeader": {
      "domain": "perf3gpp",
      "eventId": "df069b2e-0993-4aca-9e5e-60a11c6e3399",
      "eventName": "perf3gpp_CORE-cucpserver2_pmMeasResult",
      "lastEpochMicrosec": 1606743157915,
      "priority": "Normal",
      "reportingEntityName": "",
      "sequence": 1,
      "sourceName": "oteNB5309",
      "startEpochMicrosec": 1606743157914,
      "version": 4,
      "vesEventListenerVersion": "7.1",
      "timeZoneOffset": "UTC+05:00"
    },
    "perf3gppFields": {
      "perf3gppFieldsVersion": "1.0",
      "measDataCollection": {
        "granularityPeriod": 900,
        "measuredEntityUserName": "",
        "measuredEntityDn": "cucpserver2",
        "measuredEntitySoftwareVersion": "r0.1",
        "measInfoList": [
          {
            "measInfoId": {
              "sMeasTypesList": "SLICE"
            },
            "measTypes": {
              "sMeasTypesList": [
                "PDUSessionEstSR.00110010"
              ]
            },
            "measValuesList": [
              {
                "suspectFlag": false,
                "measResults": [
                  {
                    "p": 1,
                    "sValue": "188"
                  }
                ]
              }
            ]
          }
        ]
      }
    }
  }
})

Datalake Extraction Service(DES):

  1. Build presto image and push the images to a exsting repository
    1. Download and extract presto package version v0.0.2: presto-v0.0.2.tar.gz
    2. docker build -t presto:v0.0.2 .
    3. docker tag presto:v0.0.2 registry.baidubce.com/onap/presto:v0.0.2
    4. docker push registry.baidubce.com/onap/presto:v0.0.2
    5. Note： Replace the repository path with your own repository.
  2. Install presto service
    1. kubectl -n onap run dl-presto --image=presto:v0.0.2 --env="MongoDB_IP=dcae-mongohost" --env="MongoDB_PORT=27017" --image-pull-policy=IfNotPresent
    2. kubectl expose pod dl-presto --name=dl-presto --port=9000 --target-port=9000 --type=NodePort -n onap

  3. Login to the dev-dcae-datalake-postgres-primary container and execute following sql commands:

    datalake-db init_data
    psql -Udatalake -ddatalake
\dt
delete from map_db_topic;
delete from map_db_design;
delete from db;
delete from data_exposure ;
insert into db (id, db_type_id, enabled, encrypt, name,host,port,database_name) values (2, 'MONGO', true, true, 'MongoDB 1','dcae-mongohost',27017,'datalake');
insert into map_db_topic(db_id,topic_id) select db.id, topic.id from db_type, db, topic where db.db_type_id=db_type.id and db_type.tool=false;
update kafka set secure=true, pass='admin_secret' where id=1;
insert into topic_name (id) values ('unauthenticated.PERFORMANCE_MEASUREMENTS');
insert into topic(id, topic_name_id,correlate_cleared_message,enabled, message_id_path,data_format) values (6, 'unauthenticated.PERFORMANCE_MEASUREMENTS',true,true,'/event/commonEventHeader','JSON'); insert into data_exposure(id, note,sql_template,db_id) values ('pDUSessionEstSR','pm_message', 'SELECT event.perf3gppFields.measDataCollection.measInfoList[1].measValuesList[1].measResults[1].sValue AS pDUSessionEstSR, event.commonEventHeader.startEpochMicrosec AS timeStamp FROM unauthenticatedperformancemeasurements WHERE any_match(event.perf3gppFields.measDataCollection.measInfoList[1].measTypes.sMeasTypesList, e -> e like ''${id}'') AND event.commonEventHeader.startEpochMicrosec >= ${timeStamp}',2);
  4. Execute below request to verify: 

    curl --header "Content-type: application/json" --request POST --data '{"hours":4,"id":"PDUSessionEstSR.00110010","timeStamp":"1606743157914"}' http://dl-des:1681/datalake/v1/exposure/pDUSessionEstSR -i 


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