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From Donald Szeto <don...@apache.org>
Subject Re: PIO Train error - JDBC - Oracle / Classification Template
Date Wed, 07 Mar 2018 23:27:26 GMT
Hi,

Can you provide the version of Oracle you are using? Do you have a live
event server backed by Oracle collecting these events properly? Do you have
content of your "pio.log"? Was Oracle JDBC driver in your classpath?

Regards,
Donald

On Wed, Mar 7, 2018 at 6:46 AM, Praveen Prasannakumar <
praveen2399works@gmail.com> wrote:

> Hello Team
>
> I am using classification template and using oracle jdbc as datastore. I
> am getting a error during PIO Train. I had checked the Data store and I
> have data. Copied the error , query and data exported in json below. Can
> you please help ?
>
> Exception in thread "main" java.lang.IllegalArgumentException:
> requirement failed: RDD[labeledPoints] in PreparedData cannot be empty.
> Please check if DataSource generates TrainingData and Preparator generates
> PreparedData correctly.
>
>         at scala.Predef$.require(Predef.scala:224)
>
>         at org.example.classification.NaiveBayesAlgorithm.train(
> NaiveBayesAlgorithm.scala:25)
>
>         at org.example.classification.NaiveBayesAlgorithm.train(
> NaiveBayesAlgorithm.scala:18)
>
>         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:254)
>
>         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.SparkSubmit$.org$apache$spark$
> deploy$SparkSubmit$$runMain(SparkSubmit.scala:743)
>
>         at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(
> SparkSubmit.scala:187)
>
>         at org.apache.spark.deploy.SparkSubmit$.submit(
> SparkSubmit.scala:212)
>
>         at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.
> scala:126)
>
>         at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
>
> Query  is :  select         id,         event,
> entityType,         entityId,         targetEntityType,
> targetEntityId,         properties,         eventTime,
> eventTimeZone,         tags,         prId,         creationTime,
> creationTimeZone       from pio_event_42       where         eventTime >=
> TO_DATE('20000101','yyyymmdd') and         eventTime <
> TO_DATE('20200101','yyyymmdd')       and entityType = 'user'
> and (event = '$set' or event = '$unset' or event = '$delete')
>
>
> JSON Data from oracle Database :
>
> [{"eventId":"36a4e04c6ae64bf499d80529f86c4542","event":"$set","
> entityType":"user","entityId":"u0","properties":{"attr0":0,"
> attr1":1,"attr2":0,"plan":1},"eventTime":"2018-03-06T22:27:
> 17.336Z","creationTime":"2018-03-06T22:27:17.336Z"},{"eventId":"
> f22d1b09210a4af78dfaaa846fc85296","event":"$set","
> entityType":"user","entityId":"u0","properties":{"attr0":0,"
> attr1":1,"attr2":0,"plan":1},"eventTime":"2018-03-06T22:27:
> 18.260Z","creationTime":"2018-03-06T22:27:18.260Z"},{"eventId":"
> 07ab0aacb53b48fda35283ea66520613","event":"$set","
> entityType":"user","entityId":"u0","properties":{"attr0":0,"
> attr1":1,"attr2":0,"plan":1},"eventTime":"2018-03-06T22:27:
> 18.762Z","creationTime":"2018-03-06T22:27:18.762Z"},{"eventId":"
> ed07830d82f8409ab69585319c046759","event":"$set","
> entityType":"user","entityId":"u0","properties":{"attr0":0,"
> attr1":1,"attr2":0,"plan":1},"eventTime":"2018-03-06T22:27:
> 20.149Z","creationTime":"2018-03-06T22:27:20.149Z"},{"eventId":"
> 085da152c76f40c286360d393d0afcc5","event":"$set","
> entityType":"user","entityId":"u0","properties":{"attr0":0,"
> attr1":1,"attr2":0,"plan":1},"eventTime":"2018-03-06T22:27:
> 20.681Z","creationTime":"2018-03-06T22:27:20.681Z"},{"eventId":"
> f2a070bf9f984e118f5ac224a2eb4a9c","event":"$set","
> entityType":"user","entityId":"u0","properties":{"attr0":0,"
> attr1":1,"attr2":0,"plan":1},"eventTime":"2018-03-06T22:27:
> 21.162Z","creationTime":"2018-03-06T22:27:21.162Z"},{"eventId":"
> 48d8721217974a12871eae59a5e94d58","event":"$set","
> entityType":"user","entityId":"u0","properties":{"attr0":0,"
> attr1":1,"attr2":0,"plan":1},"eventTime":"2018-03-06T22:27:
> 21.602Z","creationTime":"2018-03-06T22:27:21.602Z"},{"eventId":"
> dba190567485456ab04258260a388c9b","event":"$set","
> entityType":"user","entityId":"u0","properties":{"attr0":0,"
> attr1":1,"attr2":0,"plan":1},"eventTime":"2018-03-06T22:27:
> 22.023Z","creationTime":"2018-03-06T22:27:22.023Z"},{"eventId":"
> a6fa9afe16674d408b5f0155e33263f2","event":"$set","
> entityType":"user","entityId":"u0","properties":{"attr0":0,"
> attr1":1,"attr2":0,"plan":1},"eventTime":"2018-03-06T22:27:
> 23.383Z","creationTime":"2018-03-06T22:27:23.383Z"}]
>
> Thanks
> Praveen
>

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