• Get an in-depth view of the Apache Hadoop ecosystem and an overview of the architectural patterns pertaining to the popular Big Data platform
• Conquer different data...

• Create and share interactive documents with live code, text and visualizations
• Integrate popular programming languages such as Python, R, Julia, Scala...

• Use Anaconda to find solutions for clustering, classification, and linear regression
• Analyze your data efficiently with the most powerful data...

Data in all domains is getting bigger. How can you work with it efficiently? Recently updated for Spark 1.3, this book introduces Apache Spark, the open source cluster computing system that makes data analytics fast to write and fast to run. With Spark, you can tackle big datasets quickly through simple APIs in Python, Java,...

Beginning and experienced programmers will use this comprehensive guide to persistent memory programming. You will understand how persistent memory brings together several new software/hardware requirements, and offers great promise for better performance and faster application startup times?a huge leap forward in byte-addressable...

If you’re like many of Excel’s 750 million users, you want to do more with your data—like repeating similar analyses over hundreds of files, or combining data in many files for analysis at one time. This practical guide shows ambitious non-programmers how to automate and scale the processing and analysis of data in...