Hadoop real-work solutions cookbook: over 90 hands-on recipes to help you learn and master the intricacies of Apache Hadoop 2.X, YARN, Hive, Pig, Oozie, Flume, Sqoop, Apache Spark, and Mahout

Description

Cover; Copyright; Credits; About the Author; Acknowledgements; About the Reviewer; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Getting Started with Hadoop 2.X; Chapter 2: Exploring HDFS; Chapter 3: Mastering Map Reduce Programs; Chapter 4: Data Analysis Using Hive, Pig, and Hbase; Chapter 5: Advanced Data Analysis Using Hive; Chapter 6: Data Import/Export Using Sqoop and Flume; Chapter 7: Automation of Hadoop Tasks Using Oozie; Chapter 8: Machine Learning and Predictive Analytics Using Mahout and R; Chapter 9: Integration with Apache Spark; Chapter 10: Hadoop Use Cases; Index Cover Copyright Credits About the Author Acknowledgements About the Reviewer www.PacktPub.com Table of Contents Preface Chapter 1: Getting Started with Hadoop 2.X Chapter 2: Exploring HDFS Chapter 3: Mastering Map Reduce Programs Chapter 4: Data Analysis Using Hive, Pig, and Hbase Chapter 5: Advanced Data Analysis Using Hive Chapter 6: Data Import/Export Using Sqoop and Flume Chapter 7: Automation of Hadoop Tasks Using Oozie Chapter 8: Machine Learning and Predictive Analytics Using Mahout and R Chapter 9: Integration with Apache Spark Chapter 10: Hadoop Use Cases Index IntroductionInstalling a Single Node Hadoop Cluster Installing a multi-node Hadoop cluster Adding new nodes to existing Hadoop clusters Executing balancer command for uniform data distribution Entering and exiting from the safe mode in a Hadoop cluster Decommissioning DataNodes Performing benchmarking on a Hadoop cluster Introduction Loading data from a local machine to HDFS Exporting data from HDFS to local machine Changing the replication factor of an existing file in HDFS Setting the HDFS block size for all the files in a cluster Setting the HDFS block size for a specific file in a clusterEnabling transparent encryption for HDFS Importing data from another Hadoop cluster Recycling deleted data from trash to HDFS Saving compressed data in HDFS Introduction Writing the Map Reduce program in Java to analyze web log data Executing the Map Reduce program in a Hadoop cluster Adding support for a new writable data type in Hadoop Implementing a user-defined counter in a Map Reduce program Map Reduce program to find the top X Map Reduce program to find distinct values Map Reduce program to partition data using a custom partitionerWriting Map Reduce results to multiple output files Performing Reduce side Joins using Map Reduce Unit testing the Map Reduce code using MRUnit Introduction Storing and processing Hive data in a sequential file format Storing and processing Hive data in the ORC file format Storing and processing Hive data in the ORC file format Storing and processing Hive data in the Parquet file format Performing FILTER By queries in Pig Performing Group By queries in Pig Performing Order By queries in Pig Performing JOINS in Pig Writing a user-defined function in PigAnalyzing web log data using Pig Performing the Hbase operation in CLI Performing Hbase operations in Java Executing the MapReduce programming with an Hbase Table Introduction Processing JSON data using Hive JSON SerDe Processing XML data using Hive XML SerDe Processing Hive data in AVRO format Writing User Defined functions in Hive Performing table joins in Hive Executing map side joins in Hive Performing context Ngram in Hive Call Data Record Analytics using Hive Twitter sentiment analysis using Hive