Spark MLlib 贝叶斯分类算法实例具体代码及运行过程详解
import org.apache.log4j.{Level, Logger} import org.apache.spark.{SparkConf, SparkContext} import org.apache.spark.mllib.classification.{NaiveBayes, NaiveBayesModel} import org.apache.spark.mllib.linalg.Vectors import org.apache.spark.mllib.regression.LabeledPoint //数据格式:类别,特征1 特征2 特征3 //0,1 0 1 //1,0 2 0 object tmp_naive_bayes { def main(args: Array[String]){ //1、构建spark对象 val conf = new SparkConf().setAppName("naive_bayes").setMaster("local") val sc = new SparkContext(conf) Logger.getRootLogger.setLevel(Level.WARN) //2、读取数据样本 val data = sc.textFile("C://Users/wpguoc/Desktop/Spark MLlib/navie_bayes_data.txt") val parsedData = data.map{ line => val parts = line.split(',') LabeledPoint(parts(0).toDouble, Vectors.dense(parts(1).split(' ').map(_.toDouble))) } //3、样本数据划分训练样本和测试样本 val splits = parsedData.randomSplit(Array(0.6, 0.4), seed = 11L) val tran = splits(0) val test = splits(1) //4、新建贝叶斯分类模型,并训练 val model = NaiveBayes.train(tran, lambda = 1.0, modelType = "multinomial") //5、对测试样本进行测试 val predictionAndLabel = test.map(p => (model.predict(p.features), p.label)) val print_predict = predictionAndLabel.take(20) println("贝叶斯分类结果:" + "\n" + "prediction" + "\t" + "label") for(i <- 0 to print_predict.length - 1){ println(print_predict(i)._1+"\t\t\t"+print_predict(i)._2) } val accuracy = 1.0*predictionAndLabel.filter(x =>x._1 == x._2).count() / test.count() println("贝叶斯分类精度" + "\n" + "accuracy: Double = " + accuracy) //6、保存模型 val ModelPath = "C://Users/wpguoc/Desktop/Spark_MLlib/" model.save(sc, ModelPath) val sameModel = NaiveBayesModel.load(sc, ModelPath) } }
运行过程及结果
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties 18/12/19 17:32:04 INFO SparkContext: Running Spark version 1.6.3 18/12/19 17:32:04 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable 18/12/19 17:32:05 INFO SecurityManager: Changing view acls to: wpguoc 18/12/19 17:32:05 INFO SecurityManager: Changing modify acls to: wpguoc 18/12/19 17:32:05 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(wpguoc); users with modify permissions: Set(wpguoc) 18/12/19 17:32:05 INFO Utils: Successfully started service 'sparkDriver' on port 63424. 18/12/19 17:32:06 INFO Slf4jLogger: Slf4jLogger started 18/12/19 17:32:06 INFO Remoting: Starting remoting 18/12/19 17:32:06 INFO Remoting: Remoting started; listening on addresses :[akka.tcp://sparkDriverActorSystem@192.168.66.80:63437] 18/12/19 17:32:06 INFO Utils: Successfully started service 'sparkDriverActorSystem' on port 63437. 18/12/19 17:32:06 INFO SparkEnv: Registering MapOutputTracker 18/12/19 17:32:06 INFO SparkEnv: Registering BlockManagerMaster 18/12/19 17:32:06 INFO DiskBlockManager: Created local directory at C:\Users\wpguoc\AppData\Local\Temp\blockmgr-4d798e34-90b0-4ee9-a811-586a893f4818 18/12/19 17:32:06 INFO MemoryStore: MemoryStore started with capacity 1127.3 MB 18/12/19 17:32:06 INFO SparkEnv: Registering OutputCommitCoordinator 18/12/19 17:32:06 INFO Utils: Successfully started service 'SparkUI' on port 4040. 18/12/19 17:32:06 INFO SparkUI: Started SparkUI at http://192.168.66.80:4040 18/12/19 17:32:06 INFO Executor: Starting executor ID driver on host localhost 18/12/19 17:32:06 INFO Utils: Successfully started service 'org.apache.spark.network.netty.NettyBlockTransferService' on port 63444. 18/12/19 17:32:06 INFO NettyBlockTransferService: Server created on 63444 18/12/19 17:32:06 INFO BlockManagerMaster: Trying to register BlockManager 18/12/19 17:32:06 INFO BlockManagerMasterEndpoint: Registering block manager localhost:63444 with 1127.3 MB RAM, BlockManagerId(driver, localhost, 63444) 18/12/19 17:32:06 INFO BlockManagerMaster: Registered BlockManager 18/12/19 17:32:10 WARN BLAS: Failed to load implementation from: com.github.fommil.netlib.NativeSystemBLAS 18/12/19 17:32:10 WARN BLAS: Failed to load implementation from: com.github.fommil.netlib.NativeRefBLAS 贝叶斯分类结果: prediction label 0.0 0.0 0.0 0.0 2.0 2.0 2.0 2.0 2.0 2.0 贝叶斯分类精度 accuracy: Double = 1.0 SLF4J: Failed to load class "org.slf4j.impl.StaticLoggerBinder". SLF4J: Defaulting to no-operation (NOP) logger implementation SLF4J: See http://www.slf4j.org/codes.html#StaticLoggerBinder for further details. 18/12/19 17:32:14 WARN ParquetRecordReader: Can not initialize counter due to context is not a instance of TaskInputOutputContext, but is org.apache.hadoop.mapreduce.task.TaskAttemptContextImpl Process finished with exit code 0