hadoop-projects IBM stock project Get IBM stock dataset Clean the dataset Load dataset on the HDFS Build MapReduce program Process/ Analyse result Hadoop set up Run single node Hadoop cluster /usr/local/Celler/hadoop Check : https://www.slideshare.net/SunilkumarMohanty3/install-apache-hadoop-on-mac-os-sierra-76275019 http://zhongyaonan.com/hadoop-tutorial/setting-up-hadoop-2-6-on-mac-osx-yosemite.html Go to :http://localhost:50070/dfshealth.html#tab-overview Start : hstart Hadoop command: hadoop fs -ls hadoop fs -mkdir /hbp Upload a file in HDFS hadoop fs -put <localsrc> ... <HDFS_dest_Path> go to : http://localhost:50070/explorer.html#/hbp/ibm-stock Dataset head date - opening stock quote - high - low - traded volume - closing price Clean dataset with command : awk,sed,grep Run the program Copy jar to Hadoop Run the program on Hadoop system: hadoop jar /hbp/ibm-stock/ibm-stock-1.0-SNAPSHOT.jar /hbp/ibm-stock/ibm-stock.csv /hbp/ibm-stock/output Check output dir : hadoop fs -ls /hbp/ibm-stock/output Copy file from HDFS to local file system : hadoop fs -get /hpb/ibm-stock/output/part-r-00000 home/Users/hien/results.csv Check head home/Users/hien/results.csv Customer Analysis Collect data Customer master data : MySQL Logs : text file Twitter feeds : JSON Load data from data sources in HDFS Mug data Create table in Hive to store data in format Query and join tables Export data Set up stack: Hortonwork data platform HDP Install HDP sandbox: HDP 2.3 HDP : hive, squoop , Fraud Detection system Clean dataset Create model Using: Spark and Hadoop Problem: predict payment transaction is suspect Build model : Find relevant field: Apache Spark 2 Spark ecosystem : Spark core Spark streaming Spark SQL MLlib GraphX Spark-R Apache Spark component: + navigate to : localhost:4040 run spark-shell : $SPARK_HOME/bin/spark-shell Word count Create pairRDD : valpairRDD=stringRdd.map( s => (s,1)) Run reducebykey to count the occurency of each word : alwordCountRDD=pairRDD.reduceByKey((x,y) =>x+y) Run the collect to see the result : valwordCountList=wordCountRDD.collect Find the sum of integers Create RDD of even number from integers : valintRDD = sc.parallelize(Array(1,4,5,6,7,10,15)) Filter even numbers from RDD : valevenNumbersRDD=intRDD.filter(i => (i%2==0)) Sum the even numbers from RDD : val sum =evenNumbersRDD.sum Count the number of words in file : Read txt file : cat people.txt Read file from Apache Spark shell : val file=sc.textFile("/usr/local/spark/examples/src/main/resources/people.txt") Flaten the file, prcess and split , with each word : valflattenFile = file.flatMap(s =>s.split(", ")) Check the content of RDD : flattenFile.collect Count all words from RDD : val count = flattenFile.count Working with Data and Storage + Chua hoc 4 (RDD transformation),

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