With Early Release ebooks, you get books in their earliest form the author's raw and unedited content as he or she writes so you can take advantage of these technologies long before the official release of these titles. You ll also receive updates when significant changes are made, new chapters are available, and the final ebook bundle is released. Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of this open-source cluster-computing framework. With an emphasis on improvements and new features in Spark 2.0, authors Bill Chambers and Matei Zaharia break down Spark topics into distinct sections, each with unique goals. You ll explore the basic operations and common functions of Spark s structured APIs, as well as Structured Streaming, a new high-level API for building end-to-end streaming applications. Developers and system administrators will learn the fundamentals of monitoring, tuning, and debugging Spark, and explore machine learning techniques and scenarios for employing MLlib, Spark s scalable machine learning library. Get a gentle overview of big data and Spark Learn about DataFrames, SQL, and Datasets Spark s core APIs through worked examples Dive into Spark s low-level APIs, RDDs, and execution of SQL and DataFrames Understand how Spark runs on a cluster Debug, monitor, and tune Spark clusters and applications Learn the power of Spark s Structured Streaming and MLlib for machine learning tasks Explore the wider Spark ecosystem, including SparkR and Graph Analysis Examine Spark deployment, including coverage of Spark in the Cloud
Introduction and Motivation.- Fundamentals of Compressive Sensing.- Signal Model.- Sparsity-Based Multipath Exploitation.- Mitigating Wall Eects and Uncertainties.- Conclusions and Outlook