Scala - 创建IndexedDatasetSpark对象

Question

我想对从mongodb获取的数据运行Spark RowSimilarity推荐器。为此，我写了下面的代码，它从mongo获取输入，将其转换为对象的RDD。这需要传递到IndexedDataSetSpark，然后传递给SimilarityAnalysis.rowSimilarityIDS

import org.apache.hadoop.conf.Configuration 
import org.apache.mahout.math.cf.SimilarityAnalysis 
import org.apache.mahout.sparkbindings.indexeddataset.IndexedDatasetSpark 
import org.apache.spark.rdd.{NewHadoopRDD, RDD} 
import org.apache.spark.{SparkConf, SparkContext} 
import org.bson.BSONObject 
import com.mongodb.hadoop.MongoInputFormat 

object SparkExample extends App { 
    val mongoConfig = new Configuration() 
    mongoConfig.set("mongo.input.uri", "mongodb://my_mongo_ip:27017/db.collection") 

    val sparkConf = new SparkConf() 
    val sc = new SparkContext("local", "SparkExample", sparkConf) 

    val documents: RDD[(Object, BSONObject)] = sc.newAPIHadoopRDD(
    mongoConfig, 
    classOf[MongoInputFormat], 
    classOf[Object], 
    classOf[BSONObject] 
) 
    val new_doc: RDD[(String, String)] = documents.map(
    doc1 => (
    doc1._2.get("product_id").toString(), 
    doc1._2.get("product_attribute_value").toString().replace("[ \"", "").replace("\"]", "").split("\" , \"").map(value => value.toLowerCase.replace(" ", "-")).mkString(" ") 
    ) 
) 
    var myIDs = IndexedDatasetSpark(new_doc)(sc) 

    SimilarityAnalysis.rowSimilarityIDS(myIDs).dfsWrite("hdfs://myhadoop:9000/myfile", readWriteSchema) 

我无法创造出可以传递给SimilarityAnalysis.rowSimilarityIDS一个IndexedDatasetSpark。请帮助我解决这个问题。

EDIT1：

我设法创建IndexedDatasetSpark对象和代码现在编译正确。我不得不作为一个隐含参数添加(sc)到IndexedDatasetSpark的代码运行：

Error: could not find implicit value for parameter sc: org.apache.spark.SparkContext 

现在，当我运行它，它提供了以下错误：

Error: could not find implicit value for parameter sc: org.apache.mahout.math.drm.DistributedContext 

我无法弄清楚如何让DistributedContext。

这是创建RDD并将其转换为IDS以便通过rowSimilarityIDS进行处理的正确方法吗？

更多上下文：我已经从这种情况开始：Run Mahout RowSimilarity recommender on MongoDB data

我build.sbt：

name := "scala-mongo" 

version := "1.0" 

scalaVersion := "2.10.6" 

libraryDependencies += "org.mongodb" %% "casbah" % "3.1.1" 

libraryDependencies += "org.apache.spark" %% "spark-core" % "1.6.1" 
libraryDependencies += "org.mongodb.mongo-hadoop" % "mongo-hadoop-core" % "1.4.2" 

libraryDependencies ++= Seq(
    "org.apache.hadoop" % "hadoop-client" % "2.6.0" exclude("javax.servlet", "servlet-api") exclude ("com.sun.jmx", "jmxri") exclude ("com.sun.jdmk", "jmxtools") exclude ("javax.jms", "jms") exclude ("org.slf4j", "slf4j-log4j12") exclude("hsqldb","hsqldb"), 
    "org.scalatest" % "scalatest_2.10" % "1.9.2" % "test" 
) 

libraryDependencies += "org.apache.mahout" % "mahout-math-scala_2.10" % "0.11.2" 
libraryDependencies += "org.apache.mahout" % "mahout-spark_2.10" % "0.11.2" 
libraryDependencies += "org.apache.mahout" % "mahout-math" % "0.11.2" 
libraryDependencies += "org.apache.mahout" % "mahout-hdfs" % "0.11.2" 

resolvers += "typesafe repo" at "http://repo.typesafe.com/typesafe/releases/" 

resolvers += Resolver.mavenLocal 

EDIT2：我暂时去掉dfsWrite让代码执行和偶然误差以下：

java.io.NotSerializableException: org.apache.mahout.math.DenseVector 
Serialization stack: 
- object not serializable (class: org.apache.mahout.math.DenseVector, value: {3:1.0,8:1.0,10:1.0}) 
- field (class: scala.Some, name: x, type: class java.lang.Object) 
- object (class scala.Some, Some({3:1.0,8:1.0,10:1.0})) 
at org.apache.spark.serializer.SerializationDebugger$.improveException(SerializationDebugger.scala:40) 
at org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:47) 
at org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:101) 
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:240) 
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) 
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) 
at java.lang.Thread.run(Thread.java:745) 

是否有一些序列化，我可能跳过了？

Answer 1

我会放回你删除的任何东西，第二个错误是自己造成的。

原来的错误是因为你还没有创建一个SparkContext，这是可以做到：

implicit val mc = mahoutSparkContext() 

此后我觉得MC（一SparkDistributedContext）到SC的隐式转换（一SparkContext）会由包助手函数处理。如果sc仍然缺失，请尝试：

implicit val sc = sdc2sc(mc)