switched examples to new predict method and raised docker pio tag ver…

…sion
apache · longliveenduro · Oct 15, 2018 · Oct 15, 2018 · Oct 17, 2018 · Oct 23, 2018
commit 183c9a79b1428868d217ded1bdd70601b98f4ef4
diff --git a/docker/pio/Dockerfile b/docker/pio/Dockerfile
@@ -18,7 +18,7 @@
 FROM openjdk:8
 
 ARG PIO_GIT_URL=https://github.com/apache/predictionio.git
-ARG PIO_TAG=v0.13.0
+ARG PIO_TAG=v0.14.0
 ENV SCALA_VERSION=2.11.12
 ENV SPARK_VERSION=2.2.2
 ENV HADOOP_VERSION=2.7.7

diff --git a/examples/scala-parallel-classification/add-algorithm/build.sbt b/examples/scala-parallel-classification/add-algorithm/build.sbt
@@ -20,5 +20,5 @@ name := "template-scala-parallel-classification"
 organization := "org.apache.predictionio"
 scalaVersion := "2.11.8"
 libraryDependencies ++= Seq(
-  "org.apache.predictionio" %% "apache-predictionio-core" % "0.13.0" % "provided",
+  "org.apache.predictionio" %% "apache-predictionio-core" % "0.14.0-SNAPSHOT" % "provided",
   "org.apache.spark"        %% "spark-mllib"              % "2.1.1" % "provided")
diff --git a/...ples/scala-parallel-classification/add-algorithm/src/main/scala/NaiveBayesAlgorithm.scala b/...ples/scala-parallel-classification/add-algorithm/src/main/scala/NaiveBayesAlgorithm.scala
@@ -19,14 +19,14 @@ package org.apache.predictionio.examples.classification
 
 import org.apache.predictionio.controller.P2LAlgorithm
 import org.apache.predictionio.controller.Params
-
 import org.apache.spark.mllib.classification.NaiveBayes
 import org.apache.spark.mllib.classification.NaiveBayesModel
 import org.apache.spark.mllib.linalg.Vectors
 import org.apache.spark.SparkContext
-
 import grizzled.slf4j.Logger
 
+import scala.concurrent.{ExecutionContext, Future}
+
 case class AlgorithmParams(
   lambda: Double
 ) extends Params
@@ -47,11 +47,11 @@ class NaiveBayesAlgorithm(val ap: AlgorithmParams)
     NaiveBayes.train(data.labeledPoints, ap.lambda)
   }
 
-  def predict(model: NaiveBayesModel, query: Query): PredictedResult = {
+  def predict(model: NaiveBayesModel, query: Query)(implicit ec: ExecutionContext): Future[PredictedResult] = {
     val label = model.predict(Vectors.dense(
       Array(query.attr0, query.attr1, query.attr2)
     ))
-    PredictedResult(label)
+    Future.successful(PredictedResult(label))
   }
 
 }
diff --git a/examples/scala-parallel-classification/reading-custom-properties/build.sbt b/examples/scala-parallel-classification/reading-custom-properties/build.sbt
@@ -20,5 +20,5 @@ name := "template-scala-parallel-classification"
 organization := "org.apache.predictionio"
 scalaVersion := "2.11.8"
 libraryDependencies ++= Seq(
-  "org.apache.predictionio" %% "apache-predictionio-core" % "0.13.0" % "provided",
+  "org.apache.predictionio" %% "apache-predictionio-core" % "0.14.0-SNAPSHOT" % "provided",
   "org.apache.spark"        %% "spark-mllib"              % "2.1.1" % "provided")
diff --git a/...arallel-classification/reading-custom-properties/src/main/scala/NaiveBayesAlgorithm.scala b/...arallel-classification/reading-custom-properties/src/main/scala/NaiveBayesAlgorithm.scala
@@ -19,14 +19,14 @@ package org.apache.predictionio.examples.classification
 
 import org.apache.predictionio.controller.P2LAlgorithm
 import org.apache.predictionio.controller.Params
-
 import org.apache.spark.mllib.classification.NaiveBayes
 import org.apache.spark.mllib.classification.NaiveBayesModel
 import org.apache.spark.mllib.linalg.Vectors
 import org.apache.spark.SparkContext
-
 import grizzled.slf4j.Logger
 
+import scala.concurrent.{ExecutionContext, Future}
+
 case class AlgorithmParams(
   lambda: Double
 ) extends Params
@@ -47,12 +47,12 @@ class NaiveBayesAlgorithm(val ap: AlgorithmParams)
     NaiveBayes.train(data.labeledPoints, ap.lambda)
   }
 
-  def predict(model: NaiveBayesModel, query: Query): PredictedResult = {
+  def predict(model: NaiveBayesModel, query: Query)(implicit ec: ExecutionContext): Future[PredictedResult] = {
     val label = model.predict(Vectors.dense(
       // MODIFIED
       Array(query.featureA, query.featureB, query.featureC, query.featureD)
     ))
-    PredictedResult(label)
+    Future.successful(PredictedResult(label))
   }
 
 }
diff --git a/examples/scala-parallel-ecommercerecommendation/adjust-score/build.sbt b/examples/scala-parallel-ecommercerecommendation/adjust-score/build.sbt
@@ -20,5 +20,5 @@ name := "template-scala-parallel-ecommercerecommendation"
 organization := "org.apache.predictionio"
 scalaVersion := "2.11.8"
 libraryDependencies ++= Seq(
-  "org.apache.predictionio" %% "apache-predictionio-core" % "0.13.0" % "provided",
+  "org.apache.predictionio" %% "apache-predictionio-core" % "0.14.0-SNAPSHOT" % "provided",
   "org.apache.spark"        %% "spark-mllib"              % "2.1.1" % "provided")
diff --git a/...s/scala-parallel-ecommercerecommendation/adjust-score/src/main/scala/ECommAlgorithm.scala b/...s/scala-parallel-ecommercerecommendation/adjust-score/src/main/scala/ECommAlgorithm.scala
@@ -22,16 +22,15 @@ import org.apache.predictionio.controller.Params
 import org.apache.predictionio.data.storage.BiMap
 import org.apache.predictionio.data.storage.Event
 import org.apache.predictionio.data.store.LEventStore
-
 import org.apache.spark.SparkContext
 import org.apache.spark.SparkContext._
 import org.apache.spark.mllib.recommendation.ALS
 import org.apache.spark.mllib.recommendation.{Rating => MLlibRating}
 import org.apache.spark.rdd.RDD
-
 import grizzled.slf4j.Logger
 
 import scala.collection.mutable.PriorityQueue
+import scala.concurrent.{ExecutionContext, Future}
 import scala.concurrent.duration.Duration
 import scala.concurrent.ExecutionContext.Implicits.global
 
@@ -239,7 +238,7 @@ class ECommAlgorithm(val ap: ECommAlgorithmParams)
     buyCountsRDD.collectAsMap.toMap
   }
 
-  def predict(model: ECommModel, query: Query): PredictedResult = {
+  def predict(model: ECommModel, query: Query)(implicit ec: ExecutionContext): Future[PredictedResult] = {
 
     val userFeatures = model.userFeatures
     val productModels = model.productModels
@@ -322,7 +321,7 @@ class ECommAlgorithm(val ap: ECommAlgorithmParams)
       )
     }
 
-    new PredictedResult(itemScores)
+    Future.successful(new PredictedResult(itemScores))
   }
 
   /** Generate final blackList based on other constraints */

diff --git a/examples/scala-parallel-ecommercerecommendation/train-with-rate-event/build.sbt b/examples/scala-parallel-ecommercerecommendation/train-with-rate-event/build.sbt
@@ -20,5 +20,5 @@ name := "template-scala-parallel-ecommercerecommendation"
 organization := "org.apache.predictionio"
 scalaVersion := "2.11.8"
 libraryDependencies ++= Seq(
-  "org.apache.predictionio" %% "apache-predictionio-core" % "0.13.0" % "provided",
+  "org.apache.predictionio" %% "apache-predictionio-core" % "0.14.0-SNAPSHOT" % "provided",
   "org.apache.spark"        %% "spark-mllib"              % "2.1.1" % "provided")
diff --git a/...arallel-ecommercerecommendation/train-with-rate-event/src/main/scala/ECommAlgorithm.scala b/...arallel-ecommercerecommendation/train-with-rate-event/src/main/scala/ECommAlgorithm.scala
@@ -22,16 +22,15 @@ import org.apache.predictionio.controller.Params
 import org.apache.predictionio.data.storage.BiMap
 import org.apache.predictionio.data.storage.Event
 import org.apache.predictionio.data.store.LEventStore
-
 import org.apache.spark.SparkContext
 import org.apache.spark.SparkContext._
 import org.apache.spark.mllib.recommendation.ALS
 import org.apache.spark.mllib.recommendation.{Rating => MLlibRating}
 import org.apache.spark.rdd.RDD
-
 import grizzled.slf4j.Logger
 
 import scala.collection.mutable.PriorityQueue
+import scala.concurrent.{ExecutionContext, Future}
 import scala.concurrent.duration.Duration
 import scala.concurrent.ExecutionContext.Implicits.global
 
@@ -240,7 +239,7 @@ class ECommAlgorithm(val ap: ECommAlgorithmParams)
     buyCountsRDD.collectAsMap.toMap
   }
 
-  def predict(model: ECommModel, query: Query): PredictedResult = {
+  def predict(model: ECommModel, query: Query)(implicit ec: ExecutionContext): Future[PredictedResult] = {
 
     val userFeatures = model.userFeatures
     val productModels = model.productModels
@@ -311,7 +310,7 @@ class ECommAlgorithm(val ap: ECommAlgorithmParams)
       )
     }
 
-    new PredictedResult(itemScores)
+    Future.successful(new PredictedResult(itemScores))
   }
 
   /** Generate final blackList based on other constraints */

diff --git a/examples/scala-parallel-recommendation/blacklist-items/build.sbt b/examples/scala-parallel-recommendation/blacklist-items/build.sbt
@@ -20,5 +20,5 @@ name := "template-scala-parallel-recommendation"
 organization := "org.apache.predictionio"
 scalaVersion := "2.11.8"
 libraryDependencies ++= Seq(
-  "org.apache.predictionio" %% "apache-predictionio-core" % "0.13.0" % "provided",
+  "org.apache.predictionio" %% "apache-predictionio-core" % "0.14.0-SNAPSHOT" % "provided",
   "org.apache.spark"        %% "spark-mllib"              % "2.1.1" % "provided")
diff --git a/examples/scala-parallel-recommendation/blacklist-items/src/main/scala/ALSAlgorithm.scala b/examples/scala-parallel-recommendation/blacklist-items/src/main/scala/ALSAlgorithm.scala
@@ -20,16 +20,16 @@ package org.apache.predictionio.examples.recommendation
 import org.apache.predictionio.controller.PAlgorithm
 import org.apache.predictionio.controller.Params
 import org.apache.predictionio.data.storage.BiMap
-
 import org.apache.spark.SparkContext
 import org.apache.spark.SparkContext._
 import org.apache.spark.rdd.RDD
 import org.apache.spark.mllib.recommendation.ALS
 import org.apache.spark.mllib.recommendation.{Rating => MLlibRating}
 import org.apache.spark.mllib.recommendation.ALSModel
-
 import grizzled.slf4j.Logger
 
+import scala.concurrent.{ExecutionContext, Future}
+
 case class ALSAlgorithmParams(
   rank: Int,
   numIterations: Int,
@@ -92,7 +92,7 @@ class ALSAlgorithm(val ap: ALSAlgorithmParams)
       itemStringIntMap = itemStringIntMap)
   }
 
-  def predict(model: ALSModel, query: Query): PredictedResult = {
+  def predict(model: ALSModel, query: Query)(implicit ec: ExecutionContext): Future[PredictedResult] = {
     // Convert String ID to Int index for Mllib
     model.userStringIntMap.get(query.user).map { userInt =>
       // create inverse view of itemStringIntMap
@@ -103,10 +103,10 @@ class ALSAlgorithm(val ap: ALSAlgorithmParams)
       val itemScores = model
         .recommendProductsWithFilter(userInt, query.num, blackList) // MODIFIED
         .map (r => ItemScore(itemIntStringMap(r.product), r.rating))
-      PredictedResult(itemScores)
+      Future.successful(PredictedResult(itemScores))
     }.getOrElse{
       logger.info(s"No prediction for unknown user ${query.user}.")
-      PredictedResult(Array.empty)
+      Future.successful(PredictedResult(Array.empty))
     }
   }
 

diff --git a/examples/scala-parallel-recommendation/customize-data-prep/build.sbt b/examples/scala-parallel-recommendation/customize-data-prep/build.sbt
@@ -20,5 +20,5 @@ name := "template-scala-parallel-recommendation"
 organization := "org.apache.predictionio"
 scalaVersion := "2.11.8"
 libraryDependencies ++= Seq(
-  "org.apache.predictionio" %% "apache-predictionio-core" % "0.13.0" % "provided",
+  "org.apache.predictionio" %% "apache-predictionio-core" % "0.14.0-SNAPSHOT" % "provided",
   "org.apache.spark"        %% "spark-mllib"              % "2.1.1" % "provided")
diff --git a/examples/scala-parallel-recommendation/customize-data-prep/src/main/scala/ALSAlgorithm.scala b/examples/scala-parallel-recommendation/customize-data-prep/src/main/scala/ALSAlgorithm.scala
@@ -20,16 +20,16 @@ package org.apache.predictionio.examples.recommendation
 import org.apache.predictionio.controller.PAlgorithm
 import org.apache.predictionio.controller.Params
 import org.apache.predictionio.data.storage.BiMap
-
 import org.apache.spark.SparkContext
 import org.apache.spark.SparkContext._
 import org.apache.spark.rdd.RDD
 import org.apache.spark.mllib.recommendation.ALS
 import org.apache.spark.mllib.recommendation.{Rating => MLlibRating}
 import org.apache.spark.mllib.recommendation.ALSModel
-
 import grizzled.slf4j.Logger
 
+import scala.concurrent.{ExecutionContext, Future}
+
 case class ALSAlgorithmParams(
   rank: Int,
   numIterations: Int,
@@ -92,7 +92,7 @@ class ALSAlgorithm(val ap: ALSAlgorithmParams)
       itemStringIntMap = itemStringIntMap)
   }
 
-  def predict(model: ALSModel, query: Query): PredictedResult = {
+  def predict(model: ALSModel, query: Query)(implicit ec: ExecutionContext): Future[PredictedResult] = {
     // Convert String ID to Int index for Mllib
     model.userStringIntMap.get(query.user).map { userInt =>
       // create inverse view of itemStringIntMap
@@ -101,10 +101,10 @@ class ALSAlgorithm(val ap: ALSAlgorithmParams)
       // index. Convert it to String ID for returning PredictedResult
       val itemScores = model.recommendProducts(userInt, query.num)
         .map (r => ItemScore(itemIntStringMap(r.product), r.rating))
-      PredictedResult(itemScores)
+      Future.successful(PredictedResult(itemScores))
     }.getOrElse{
       logger.info(s"No prediction for unknown user ${query.user}.")
-      PredictedResult(Array.empty)
+      Future.successful(PredictedResult(Array.empty))
     }
   }
 

diff --git a/examples/scala-parallel-recommendation/customize-serving/build.sbt b/examples/scala-parallel-recommendation/customize-serving/build.sbt
@@ -20,5 +20,5 @@ name := "template-scala-parallel-recommendation"
 organization := "org.apache.predictionio"
 scalaVersion := "2.11.8"
 libraryDependencies ++= Seq(
-  "org.apache.predictionio" %% "apache-predictionio-core" % "0.13.0" % "provided",
+  "org.apache.predictionio" %% "apache-predictionio-core" % "0.14.0-SNAPSHOT" % "provided",
   "org.apache.spark"        %% "spark-mllib"              % "2.1.1" % "provided")
diff --git a/examples/scala-parallel-recommendation/customize-serving/src/main/scala/ALSAlgorithm.scala b/examples/scala-parallel-recommendation/customize-serving/src/main/scala/ALSAlgorithm.scala
@@ -20,16 +20,16 @@ package org.apache.predictionio.examples.recommendation
 import org.apache.predictionio.controller.PAlgorithm
 import org.apache.predictionio.controller.Params
 import org.apache.predictionio.data.storage.BiMap
-
 import org.apache.spark.SparkContext
 import org.apache.spark.SparkContext._
 import org.apache.spark.rdd.RDD
 import org.apache.spark.mllib.recommendation.ALS
 import org.apache.spark.mllib.recommendation.{Rating => MLlibRating}
 import org.apache.spark.mllib.recommendation.ALSModel
-
 import grizzled.slf4j.Logger
 
+import scala.concurrent.{ExecutionContext, Future}
+
 case class ALSAlgorithmParams(
   rank: Int,
   numIterations: Int,
@@ -92,7 +92,7 @@ class ALSAlgorithm(val ap: ALSAlgorithmParams)
       itemStringIntMap = itemStringIntMap)
   }
 
-  def predict(model: ALSModel, query: Query): PredictedResult = {
+  def predict(model: ALSModel, query: Query)(implicit ec: ExecutionContext): Future[PredictedResult] = {
     // Convert String ID to Int index for Mllib
     model.userStringIntMap.get(query.user).map { userInt =>
       // create inverse view of itemStringIntMap
@@ -101,10 +101,10 @@ class ALSAlgorithm(val ap: ALSAlgorithmParams)
       // index. Convert it to String ID for returning PredictedResult
       val itemScores = model.recommendProducts(userInt, query.num)
         .map (r => ItemScore(itemIntStringMap(r.product), r.rating))
-      PredictedResult(itemScores)
+      Future.successful(PredictedResult(itemScores))
     }.getOrElse{
       logger.info(s"No prediction for unknown user ${query.user}.")
-      PredictedResult(Array.empty)
+      Future.successful(PredictedResult(Array.empty))
     }
   }
 

diff --git a/examples/scala-parallel-recommendation/reading-custom-events/build.sbt b/examples/scala-parallel-recommendation/reading-custom-events/build.sbt
@@ -20,5 +20,5 @@ name := "template-scala-parallel-recommendation"
 organization := "org.apache.predictionio"
 scalaVersion := "2.11.8"
 libraryDependencies ++= Seq(
-  "org.apache.predictionio" %% "apache-predictionio-core" % "0.13.0" % "provided",
+  "org.apache.predictionio" %% "apache-predictionio-core" % "0.14.0-SNAPSHOT" % "provided",
   "org.apache.spark"        %% "spark-mllib"              % "2.1.1" % "provided")
diff --git a/...les/scala-parallel-recommendation/reading-custom-events/src/main/scala/ALSAlgorithm.scala b/...les/scala-parallel-recommendation/reading-custom-events/src/main/scala/ALSAlgorithm.scala
@@ -20,16 +20,16 @@ package org.apache.predictionio.examples.recommendation
 import org.apache.predictionio.controller.PAlgorithm
 import org.apache.predictionio.controller.Params
 import org.apache.predictionio.data.storage.BiMap
-
 import org.apache.spark.SparkContext
 import org.apache.spark.SparkContext._
 import org.apache.spark.rdd.RDD
 import org.apache.spark.mllib.recommendation.ALS
 import org.apache.spark.mllib.recommendation.{Rating => MLlibRating}
 import org.apache.spark.mllib.recommendation.ALSModel
-
 import grizzled.slf4j.Logger
 
+import scala.concurrent.{ExecutionContext, Future}
+
 case class ALSAlgorithmParams(
   rank: Int,
   numIterations: Int,
@@ -92,7 +92,7 @@ class ALSAlgorithm(val ap: ALSAlgorithmParams)
       itemStringIntMap = itemStringIntMap)
   }
 
-  def predict(model: ALSModel, query: Query): PredictedResult = {
+  def predict(model: ALSModel, query: Query)(implicit ec: ExecutionContext): Future[PredictedResult] = {
     // Convert String ID to Int index for Mllib
     model.userStringIntMap.get(query.user).map { userInt =>
       // create inverse view of itemStringIntMap
@@ -101,10 +101,10 @@ class ALSAlgorithm(val ap: ALSAlgorithmParams)
       // index. Convert it to String ID for returning PredictedResult
       val itemScores = model.recommendProducts(userInt, query.num)
         .map (r => ItemScore(itemIntStringMap(r.product), r.rating))
-      PredictedResult(itemScores)
+      Future.successful(PredictedResult(itemScores))
     }.getOrElse{
       logger.info(s"No prediction for unknown user ${query.user}.")
-      PredictedResult(Array.empty)
+      Future.successful(PredictedResult(Array.empty))
     }
   }
 

diff --git a/examples/scala-parallel-recommendation/train-with-view-event/build.sbt b/examples/scala-parallel-recommendation/train-with-view-event/build.sbt
@@ -20,5 +20,5 @@ name := "template-scala-parallel-recommendation"
 organization := "org.apache.predictionio"
 scalaVersion := "2.11.8"
 libraryDependencies ++= Seq(
-  "org.apache.predictionio" %% "apache-predictionio-core" % "0.13.0" % "provided",
+  "org.apache.predictionio" %% "apache-predictionio-core" % "0.14.0-SNAPSHOT" % "provided",
   "org.apache.spark"        %% "spark-mllib"              % "2.1.1" % "provided")