Merge branch 'develop'
diff --git a/LICENSE.txt b/LICENSE.txt
new file mode 100644
index 0000000..d645695
--- /dev/null
+++ b/LICENSE.txt
@@ -0,0 +1,202 @@
+
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diff --git a/README.md b/README.md
index f824876..55efb1c 100644
--- a/README.md
+++ b/README.md
@@ -7,6 +7,13 @@
## Versions
+### v0.12.0-incubating
+
+- Bump version number to track PredictionIO version
+- Sets default build targets according to PredictionIO
+- Add checkpoint parameters
+- Fix warnings and use of case class
+
### v0.11.0-incubating
- Bump version number to track PredictionIO version
diff --git a/build.sbt b/build.sbt
index a7cb20c..7ca9a06 100644
--- a/build.sbt
+++ b/build.sbt
@@ -1,6 +1,6 @@
name := "template-scala-parallel-recommendation"
+scalaVersion := "2.11.8"
libraryDependencies ++= Seq(
- "org.apache.predictionio" %% "apache-predictionio-core" % "0.11.0-incubating" % "provided",
- "org.apache.spark" %% "spark-core" % "1.3.0" % "provided",
- "org.apache.spark" %% "spark-mllib" % "1.3.0" % "provided")
+ "org.apache.predictionio" %% "apache-predictionio-core" % "0.12.0-incubating" % "provided",
+ "org.apache.spark" %% "spark-mllib" % "2.1.1" % "provided")
diff --git a/project/assembly.sbt b/project/assembly.sbt
index e17409e..15a88b0 100644
--- a/project/assembly.sbt
+++ b/project/assembly.sbt
@@ -1 +1 @@
-addSbtPlugin("com.eed3si9n" % "sbt-assembly" % "0.14.4")
+addSbtPlugin("com.eed3si9n" % "sbt-assembly" % "0.14.5")
diff --git a/project/build.properties b/project/build.properties
index 64317fd..c091b86 100644
--- a/project/build.properties
+++ b/project/build.properties
@@ -1 +1 @@
-sbt.version=0.13.15
+sbt.version=0.13.16
diff --git a/src/main/scala/ALSAlgorithm.scala b/src/main/scala/ALSAlgorithm.scala
index b53a9af..9fa8958 100644
--- a/src/main/scala/ALSAlgorithm.scala
+++ b/src/main/scala/ALSAlgorithm.scala
@@ -5,7 +5,6 @@
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}
@@ -27,7 +26,8 @@
if (ap.numIterations > 30) {
logger.warn(
s"ALSAlgorithmParams.numIterations > 30, current: ${ap.numIterations}. " +
- s"There is a chance of running to StackOverflowException. Lower this number to remedy it")
+ s"There is a chance of running to StackOverflowException." +
+ s"To remedy it, set lower numIterations or checkpoint parameters.")
}
def train(sc: SparkContext, data: PreparedData): ALSModel = {
@@ -48,24 +48,23 @@
// seed for MLlib ALS
val seed = ap.seed.getOrElse(System.nanoTime)
- // If you only have one type of implicit event (Eg. "view" event only),
- // replace ALS.train(...) with
- //val m = ALS.trainImplicit(
- //ratings = mllibRatings,
- //rank = ap.rank,
- //iterations = ap.numIterations,
- //lambda = ap.lambda,
- //blocks = -1,
- //alpha = 1.0,
- //seed = seed)
+ // Set checkpoint directory
+ // sc.setCheckpointDir("checkpoint")
- val m = ALS.train(
- ratings = mllibRatings,
- rank = ap.rank,
- iterations = ap.numIterations,
- lambda = ap.lambda,
- blocks = -1,
- seed = seed)
+ // If you only have one type of implicit event (Eg. "view" event only),
+ // set implicitPrefs to true
+ val implicitPrefs = false
+ val als = new ALS()
+ als.setUserBlocks(-1)
+ als.setProductBlocks(-1)
+ als.setRank(ap.rank)
+ als.setIterations(ap.numIterations)
+ als.setLambda(ap.lambda)
+ als.setImplicitPrefs(implicitPrefs)
+ als.setAlpha(1.0)
+ als.setSeed(seed)
+ als.setCheckpointInterval(10)
+ val m = als.run(mllibRatings)
new ALSModel(
rank = m.rank,
@@ -84,10 +83,10 @@
// index. Convert it to String ID for returning PredictedResult
val itemScores = model.recommendProducts(userInt, query.num)
.map (r => ItemScore(itemIntStringMap(r.product), r.rating))
- new PredictedResult(itemScores)
+ PredictedResult(itemScores)
}.getOrElse{
logger.info(s"No prediction for unknown user ${query.user}.")
- new PredictedResult(Array.empty)
+ PredictedResult(Array.empty)
}
}
diff --git a/src/main/scala/ALSModel.scala b/src/main/scala/ALSModel.scala
index afec745..e0e6a9f 100644
--- a/src/main/scala/ALSModel.scala
+++ b/src/main/scala/ALSModel.scala
@@ -5,12 +5,11 @@
import org.example.recommendation.ALSAlgorithmParams
-import org.apache.predictionio.controller.IPersistentModel
-import org.apache.predictionio.controller.IPersistentModelLoader
+import org.apache.predictionio.controller.PersistentModel
+import org.apache.predictionio.controller.PersistentModelLoader
import org.apache.predictionio.data.storage.BiMap
import org.apache.spark.SparkContext
-import org.apache.spark.SparkContext._
import org.apache.spark.rdd.RDD
class ALSModel(
@@ -20,7 +19,7 @@
val userStringIntMap: BiMap[String, Int],
val itemStringIntMap: BiMap[String, Int])
extends MatrixFactorizationModel(rank, userFeatures, productFeatures)
- with IPersistentModel[ALSAlgorithmParams] {
+ with PersistentModel[ALSAlgorithmParams] {
def save(id: String, params: ALSAlgorithmParams,
sc: SparkContext): Boolean = {
@@ -48,7 +47,7 @@
}
object ALSModel
- extends IPersistentModelLoader[ALSAlgorithmParams, ALSModel] {
+ extends PersistentModelLoader[ALSAlgorithmParams, ALSModel] {
def apply(id: String, params: ALSAlgorithmParams,
sc: Option[SparkContext]) = {
new ALSModel(
diff --git a/src/main/scala/DataSource.scala b/src/main/scala/DataSource.scala
index 7f7b4a1..75bfac1 100644
--- a/src/main/scala/DataSource.scala
+++ b/src/main/scala/DataSource.scala
@@ -2,13 +2,11 @@
import org.apache.predictionio.controller.PDataSource
import org.apache.predictionio.controller.EmptyEvaluationInfo
-import org.apache.predictionio.controller.EmptyActualResult
import org.apache.predictionio.controller.Params
import org.apache.predictionio.data.storage.Event
import org.apache.predictionio.data.store.PEventStore
import org.apache.spark.SparkContext
-import org.apache.spark.SparkContext._
import org.apache.spark.rdd.RDD
import grizzled.slf4j.Logger
diff --git a/src/main/scala/Engine.scala b/src/main/scala/Engine.scala
index 20a5521..71e09bf 100644
--- a/src/main/scala/Engine.scala
+++ b/src/main/scala/Engine.scala
@@ -1,27 +1,27 @@
package org.example.recommendation
-import org.apache.predictionio.controller.IEngineFactory
+import org.apache.predictionio.controller.EngineFactory
import org.apache.predictionio.controller.Engine
case class Query(
user: String,
num: Int
-) extends Serializable
+)
case class PredictedResult(
itemScores: Array[ItemScore]
-) extends Serializable
+)
case class ActualResult(
ratings: Array[Rating]
-) extends Serializable
+)
case class ItemScore(
item: String,
score: Double
-) extends Serializable
+)
-object RecommendationEngine extends IEngineFactory {
+object RecommendationEngine extends EngineFactory {
def apply() = {
new Engine(
classOf[DataSource],
diff --git a/src/main/scala/Evaluation.scala b/src/main/scala/Evaluation.scala
index e0eebe1..acc85ff 100644
--- a/src/main/scala/Evaluation.scala
+++ b/src/main/scala/Evaluation.scala
@@ -24,12 +24,11 @@
// If there is no positive results, Precision is undefined. We don't consider this case in the
// metrics, hence we return None.
if (positives.size == 0) {
- return None
+ None
+ } else {
+ val tpCount: Int = p.itemScores.take(k).filter(is => positives(is.item)).size
+ Some(tpCount.toDouble / math.min(k, positives.size))
}
-
- val tpCount: Int = p.itemScores.take(k).filter(is => positives(is.item)).size
-
- Some(tpCount.toDouble / math.min(k, positives.size))
}
}
diff --git a/src/main/scala/Preparator.scala b/src/main/scala/Preparator.scala
index 0e20c62..5e3a653 100644
--- a/src/main/scala/Preparator.scala
+++ b/src/main/scala/Preparator.scala
@@ -3,7 +3,6 @@
import org.apache.predictionio.controller.PPreparator
import org.apache.spark.SparkContext
-import org.apache.spark.SparkContext._
import org.apache.spark.rdd.RDD
class Preparator
