SparkWordCount 類原始碼 standalong 模式

import org.apache.spark.SparkConf
import org.apache.spark.SparkContext
import org.apache.spark.SparkContext._

object SparkWordCount {
 def FILE_NAME:String = "word_count_results_";
 
 def main(args:Array[String]) {
 if (args.length < 1) {
 println("Usage:SparkWordCount FileName");
 System.exit(1);
 }
 val conf = new SparkConf().setAppName("Spark Exercise: Spark Version Word Count Program");
 val sc = new SparkContext(conf);
 val textFile = sc.textFile(args(0));
 val wordCounts = textFile.flatMap(line => line.split(" ")).map(
                                        word => (word, 1)).reduceByKey((a, b) => a + b)

										
 wordCounts.saveAsTextFile(FILE_NAME+System.currentTimeMillis());
 println("Word Count program running results are successfully saved.");
 }
}


--------
./spark-submit \
--class com.ibm.spark.exercise.basic.SparkWordCount \
--master spark://hadoop036166:7077 \
--num-executors 3 \
--driver-memory 6g --executor-memory 2g \
--executor-cores 2 \
/home/fams/sparkexercise.jar \
hdfs://hadoop036166:9000/user/fams/*.txt


求平均值 

import org.apache.spark.SparkConf
import org.apache.spark.SparkContext
object AvgAgeCalculator {
 def main(args:Array[String]) {
 if (args.length < 1){
 println("Usage:AvgAgeCalculator datafile")
 System.exit(1)
 }
 val conf = new SparkConf().setAppName("Spark Exercise:Average Age Calculator")
 val sc = new SparkContext(conf)
 val dataFile = sc.textFile(args(0), 5);
 val count = dataFile.count()
 val ageData = dataFile.map(line => line.split(" ")(1))
 val totalAge = ageData.map(age => Integer.parseInt(
                                String.valueOf(age))).collect().reduce((a,b) => a+b)
 println("Total Age:" + totalAge + ";Number of People:" + count )
 val avgAge : Double = totalAge.toDouble / count.toDouble
 println("Average Age is " + avgAge)
 }
}


--------------------------
./spark-submit \
 --class com.ibm.spark.exercise.basic.AvgAgeCalculator \
 --master spark://hadoop036166:7077 \
 --num-executors 3 \
 --driver-memory 6g \
 --executor-memory 2g \
 --executor-cores 2 \
 /home/fams/sparkexercise.jar \
 hdfs://hadoop036166:9000/user/fams/inputfiles/sample_age_data.txt
 
 
 
 求男性/女性 最高 最低身高 
 -----------------------
 object PeopleInfoCalculator {
 def main(args:Array[String]) {
 if (args.length < 1){
 println("Usage:PeopleInfoCalculator datafile")
 System.exit(1)
 }
 val conf = new SparkConf().setAppName("Spark Exercise:People Info(Gender & Height) Calculator")
 val sc = new SparkContext(conf)
 val dataFile = sc.textFile(args(0), 5);
 val maleData = dataFile.filter(line => line.contains("M")).map(
                              line => (line.split(" ")(1) + " " + line.split(" ")(2)))
 val femaleData = dataFile.filter(line => line.contains("F")).map(
                              line => (line.split(" ")(1) + " " + line.split(" ")(2)))

 val maleHeightData = maleData.map(line => line.split(" ")(1).toInt)
 val femaleHeightData = femaleData.map(line => line.split(" ")(1).toInt)

 val lowestMale = maleHeightData.sortBy(x => x,true).first()
 val lowestFemale = femaleHeightData.sortBy(x => x,true).first()

 val highestMale = maleHeightData.sortBy(x => x, false).first()
 val highestFemale = femaleHeightData.sortBy(x => x, false).first()
 println("Number of Male Peole:" + maleData.count())
 println("Number of Female Peole:" + femaleData.count())
 println("Lowest Male:" + lowestMale)
 println("Lowest Female:" + lowestFemale)
 println("Highest Male:" + highestMale)
 println("Highest Female:" + highestFemale)
 }
}





./spark-submit \
 --class com.ibm.spark.exercise.basic.PeopleInfoCalculator \
 --master spark://hadoop036166:7077 \
 --num-executors 3 \
 --driver-memory 6g \
 --executor-memory 3g \
 --executor-cores 2 \
 /home/fams/sparkexercise.jar \
 hdfs://hadoop036166:9000/user/fams/inputfiles/sample_people_info.txt
 
 
 每行資料出現的次數最高的
 
 =============
import org.apache.spark.SparkConf
import org.apache.spark.SparkContext

object TopKSearchKeyWords {
 def main(args:Array[String]){
 if (args.length < 2) {
 println("Usage:TopKSearchKeyWords KeyWordsFile K");
 System.exit(1)
 }
 val conf = new SparkConf().setAppName("Spark Exercise:Top K Searching Key Words")
 val sc = new SparkContext(conf)
 val srcData = sc.textFile(args(0))
 val countedData = srcData.map(line => (line.toLowerCase(),1)).reduceByKey((a,b) => a+b)

 val sortedData = countedData.map{ case (k,v) => (v,k) }.sortByKey(false)
 val topKData = sortedData.take(args(1).toInt).map{ case (v,k) => (k,v) }
 topKData.foreach(println)
 }
}

./spark-submit \
 --class com.ibm.spark.exercise.basic.TopKSearchKeyWords \
 --master spark://hadoop036166:7077 \
 --num-executors 3 \
 --driver-memory 6g \
 --executor-memory 2g \
 --executor-cores 2 \
 /home/fams/sparkexercise.jar \
 hdfs://hadoop036166:9000/user/fams/inputfiles/search_key_words.txt