UR is using elastic even when all the data sources are MYSQL

[yogeshExplore]

This is my pio-env.sh file

#!/usr/bin/env bash

#BASIC
SPARK_HOME=/usr/lib/spark

MYSQL_JDBC_DRIVER=/usr/share/java/mysql-connector-java.jar

PIO_FS_BASEDIR=$_LINIO_HOME/.pio_store
PIO_FS_ENGINESDIR=$PIO_FS_BASEDIR/engines
PIO_FS_TMPDIR=$PIO_FS_BASEDIR/tmp

PIO_STORAGE_REPOSITORIES_METADATA_NAME=pio_meta
PIO_STORAGE_REPOSITORIES_METADATA_SOURCE=MYSQL

PIO_STORAGE_REPOSITORIES_EVENTDATA_NAME=pio_event
PIO_STORAGE_REPOSITORIES_EVENTDATA_SOURCE=MYSQL

PIO_STORAGE_REPOSITORIES_MODELDATA_NAME=pio_model
PIO_STORAGE_REPOSITORIES_MODELDATA_SOURCE=MYSQL

#Storage Data Sources
PIO_STORAGE_SOURCES_MYSQL_TYPE=jdbc
PIO_STORAGE_SOURCES_MYSQL_URL=jdbc:mysql://10.60../pio_models
PIO_STORAGE_SOURCES_MYSQL_USERNAME=***
PIO_STORAGE_SOURCES_MYSQL_PASSWORD=***

---

VERSIONS

PIO_VERSION=0.12.1
PIO_SPARK_VERSION=2.3.1
PIO_ELASTICSEARCH_VERSION=5.6
HBASE_VERSION=1.4.6
PIO_HADOOP_VERSION=2.8.4
ZOOKEEPER=3.4.12
PYTHON_VERSION=3.6.3

ERROR WHILE RUNNING ./examples/integration-test

[INFO] [Engine$] EngineWorkflow.train
[INFO] [Engine$] DataSource: com.actionml.DataSource@175ac243
[INFO] [Engine$] Preparator: com.actionml.Preparator@1073c664
[INFO] [Engine$] AlgorithmList: List(com.actionml.URAlgorithm@152e7703)
[INFO] [Engine$] Data sanity check is on.
[INFO] [DataSource] Received events List(purchase, view, category-pref)
[INFO] [Engine$] com.actionml.TrainingData does not support data sanity check. Skipping check.
[INFO] [Preparator] EventName: purchase
[INFO] [Preparator] Downsampled users for minEventsPerUser: Some(3), eventName: purchase number of passing user-ids: 3
[INFO] [Preparator] Dimensions rows : 4 columns: 7
[INFO] [Preparator] Downsampled columns for users who pass minEventPerUser: Some(3), eventName: purchase number of user-ids: 3
[INFO] [Preparator] Dimensions rows : 3 columns: 6
[INFO] [Preparator] EventName: view
[INFO] [Preparator] Dimensions rows : 3 columns: 4
[INFO] [Preparator] Number of user-ids after creation: 3
[INFO] [Preparator] EventName: category-pref
[INFO] [Preparator] Dimensions rows : 3 columns: 2
[INFO] [Preparator] Number of user-ids after creation: 3
[INFO] [Engine$] com.actionml.PreparedData does not support data sanity check. Skipping check.
[INFO] [URAlgorithm] Actions read now creating correlators
[INFO] [PopModel] PopModel popular using end: 2018-09-18T18:54:23.466Z, and duration: 315360000, interval: 2008-09-20T18:54:23.466Z/2018-09-18T18:54:23.466Z
[INFO] [PopModel] PopModel getting eventsRDD for startTime: 2008-09-20T18:54:23.466Z and endTime 2018-09-18T18:54:23.466Z
[INFO] [URAlgorithm] Correlators created now putting into URModel
[INFO] [URAlgorithm] Index mappings for the Elasticsearch URModel: Map(expires -> (date,false), date -> (date,false), category-pref -> (keyword,true), available -> (date,false), purchase -> (keyword,true), popRank -> (float,false), view -> (keyword,true))
[INFO] [URModel] Converting cooccurrence matrices into correlators
[INFO] [URModel] Group all properties RDD
[INFO] [URModel] ES fields[11]: List(categories, countries, date, id, expires, category-pref, available, purchase, popRank, defaultRank, view)
[INFO] [EsClient$] Create new index: urindex_1537296874822, items, List(categories, countries, date, id, expires, category-pref, available, purchase, popRank, defaultRank, view), Map(expires -> (date,false), date -> (date,false), category-pref -> (keyword,true), available -> (date,false), purchase -> (keyword,true), popRank -> (float,false), view -> (keyword,true))
[INFO] [AbstractConnector] Stopped Spark@20177486{HTTP/1.1,[http/1.1]}{0.0.0.0:4040}
Exception in thread "main" java.lang.IllegalStateException: No Elasticsearch client configuration detected, check your pio-env.sh forproper configuration settings
at com.actionml.EsClient$$anonfun$client$2.apply(EsClient.scala:86)
at com.actionml.EsClient$$anonfun$client$2.apply(EsClient.scala:86)
at scala.Option.getOrElse(Option.scala:121)
at com.actionml.EsClient$.client$lzycompute(EsClient.scala:85)
at com.actionml.EsClient$.client(EsClient.scala:85)
at com.actionml.EsClient$.createIndex(EsClient.scala:174)
at com.actionml.EsClient$.hotSwap(EsClient.scala:271)
at com.actionml.URModel.save(URModel.scala:82)
at com.actionml.URAlgorithm.calcAll(URAlgorithm.scala:367)
at com.actionml.URAlgorithm.train(URAlgorithm.scala:295)
at com.actionml.URAlgorithm.train(URAlgorithm.scala:180)
at org.apache.predictionio.controller.P2LAlgorithm.trainBase(P2LAlgorithm.scala:49)
at org.apache.predictionio.controller.Engine$$anonfun$18.apply(Engine.scala:690)
at org.apache.predictionio.controller.Engine$$anonfun$18.apply(Engine.scala:690)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.immutable.List.foreach(List.scala:381)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
at scala.collection.immutable.List.map(List.scala:285)
at org.apache.predictionio.controller.Engine$.train(Engine.scala:690)
at org.apache.predictionio.controller.Engine.train(Engine.scala:176)
at org.apache.predictionio.workflow.CoreWorkflow$.runTrain(CoreWorkflow.scala:67)
at org.apache.predictionio.workflow.CreateWorkflow$.main(CreateWorkflow.scala:251)
at org.apache.predictionio.workflow.CreateWorkflow.main(CreateWorkflow.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:894)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:198)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:228)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:137)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

[musicformellons]

On actionml webpage ElasticSearch is mentioned as being a requirement. I also quote form the actionml-user maillist from an answer on a similar question:

Again I caution you that Elasticsearch is required for the Universal Recommender because of a special type of query that no other type of DB supports, this query is part of the math that defines the algorithm for the UR. So if you use Cassandra with the UR you will only be able to replace HBase in the tech stack.