Data in all domains is getting bigger How can you work with it efficiently? This book introduces Apache Spark the open source cluster computing system that makes data analytics fast to write & fast to run With Spark you can tackle big datasets quickly through simple APIs in Python Java & Scala Written by the developers of Spark this book will have data scientists & engineers up & running in no time You'll learn how to express parallel jobs with just a few lines of code & cover applications from simple batch jobs to stream processing & machine learning Quickly dive into Spark capabilities such as distributed datasets in-memory caching & the interactive shell Leverage Spark's powerful built-in libraries including Spark SQL Spark Streaming & MLlib Use one programming paradigm instead of mixing & matching tools like Hive Hadoop Mahout & Storm Learn how to deploy interactive batch & streaming applications Connect to data sources including HDFS Hive JSON & S3 Master advanced topics like data partitioning & shared variables