Learning big data with Amazon Elastic MapReduce : easily learn, build, and execute real-world big data solutions using Hadoop and AWS EMR

Cover; Copyright; Credits; About the Authors; Acknowledgments; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Amazon Web Services; What is Amazon Web Services?; Structure and Design; Regions; Availability Zones; Services provided by AWS; Compute; Amazon EC2; Auto Scaling; Elastic Load Balancing; Amazon Workspaces; Storage; Amazon S3; Amazon EBS; Amazon Glacier; AWS Storage Gateway; AWS Import/Export; Databases; Amazon RDS; Amazon DynamoDB; Amazon Redshift; Amazon ElastiCache; Networking and CDN; Amazon VPC; Amazon Route 53; Amazon CloudFront; AWS Direct Connect ; AnalyticsAmazon EMR; Amazon Kinesis; AWS Data Pipeline; Application services; Amazon CloudSearch (Beta); Amazon SQS; Amazon SNS; Amazon SES; Amazon AppStream; Amazon Elastic Transcoder; Amazon SWF; Deployment and Management; AWS Identity and Access Management; Amazon CloudWatch; AWS Elastic Beanstalk; AWS CloudFormation; AWS OpsWorks; AWS CloudHSM; AWS CloudTrail; AWS Pricing; Creating an account on AWS; Step 1 - Creating an Amazon.com account; Step 2 - Providing a payment method; Step 3 - Identity verification by telephone; Step 4 - Selecting the AWS support plan ; Launching the AWS management consoleGetting started with Amazon EC2; How to start a machine on AWS?; Step 1 - Choosing an Amazon Machine Image; Step 2 - Choosing an instance type; Step 3 - Configuring instance details; Step 4 - Adding storage; Step 5 - Tagging your instance; Step 6 - Configuring a security group; Communicating with the launched instance; EC2 instance types; General purpose; Memory optimized; Compute optimized; Getting started with Amazon S3; Creating a S3 bucket; Bucket naming; S3cmd; Summary; Chapter 2: MapReduce; The map function; The reduce function; Divide and conquer ; What is MapReduce?The map reduce function models; The map function model; The reduce function model; Data life cycle in the MapReduce framework; Creation of input data splits; Record reader; Mapper; Combiner; Partitioner; Shuffle and sort; Reducer; Real-world examples and use cases of MapReduce; Social networks ; Media and entertainment; E-commerce and websites; Fraud detection and financial analytics; Search engines and ad networks; ETL and data analytics; Software distributions built on the MapReduce framework; Apache Hadoop; MapR; Cloudera distribution; Summary; Chapter 3: Apache Hadoop ; What is Apache Hadoop?Hadoop modules; Hadoop Distributed File System; Major architectural goals of HDFS; Block replication and rack awareness; The HDFS architecture; NameNode; DataNode; Apache Hadoop MapReduce; Hadoop MapReduce 1.x; JobTracker; TaskTracker; Hadoop MapReduce 2.0; Hadoop YARN; Apache Hadoop as a platform; Apache Pig; Apache Hive; Summary; Chapter 4: Amazon EMR - Hadoop on Amazon Web Services; What is AWS EMR?; Features of EMR; Accessing Amazon EMR features; Programming on AWS EMR; The EMR architecture; Types of nodes; EMR Job Flow and Steps; Job Steps; An EMR cluster ; Hadoop filesystem on EMR - S3 and HDFS