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Hadoop in Practice
Summary
Hadoop in Practice collects 85 Hadoop examples and presents them in a problem/solution format. Each technique addresses a specific task you'll face, like querying big data using Pig or writing a log file loader. You'll explore each problem step by step, learning both how to build and deploy... | | Learning Spark: Lightning-Fast Big Data Analysis
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,... | | Mastering Hadoop
Go beyond the basics and master the next generation of Hadoop data processing platforms
About This Book
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Learn how to optimize Hadoop MapReduce, Pig and Hive
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Dive into YARN and learn how it can integrate Storm with Hadoop
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Understand how Hadoop can be deployed on the cloud...
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Practical Apache Spark: Using the Scala API
Work with Apache Spark using Scala to deploy and set up single-node, multi-node, and high-availability clusters. This book discusses various components of Spark such as Spark Core, DataFrames, Datasets and SQL, Spark Streaming, Spark MLib, and R on Spark with the help of practical code snippets for each topic. ... | | Talend for Big Data
If you want to start working on big data projects fast, this is the guide you've been looking for. Delve deep into Talend and discover how just how easily you can revolutionize your data handling and presentation.
Overview
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Write complex processing job codes easily with the help of clear and step by...
| | Practical Hive: A Guide to Hadoop's Data Warehouse System
Dive into the world of SQL on Hadoop and get the most out of your Hive data warehouses. This book is your go-to resource for using Hive: authors Scott Shaw, Ankur Gupta, David Kjerrumgaard, and Andreas Francois Vermeulen take you through learning HiveQL, the SQL-like language specific to Hive, to analyze, export, and massage the data stored... |
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Programming Hive
Programming Hive introduces Hive, an essential tool in the Hadoop ecosystem that
provides an SQL (Structured Query Language) dialect for querying data stored in the
Hadoop Distributed Filesystem (HDFS), other filesystems that integrate with Hadoop,
such as MapR-FS and Amazon’s S3 and databases like HBase (the ... | | Big Data Analytics with Microsoft HDInsight in 24 Hours, Sams Teach Yourself
With Microsoft HDInsight, business professionals and data analysts can rapidly leverage the power of Hadoop on a flexible, scalable cloud-based platform, using Microsoft's accessible business intelligence, visualization, and productivity tools. Now, in just 24 lessons of one hour or less, you can learn all the skills and... | | |
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Beginning Apache Cassandra Development
Beginning Apache Cassandra Development introduces you to one of the most robust and best-performing NoSQL database platforms on the planet. Apache Cassandra is a document database following the JSON document model. It is specifically designed to manage large amounts of data across many commodity servers without there being any single... | | Hadoop Cluster Deployment
Construct a modern Hadoop data platform effortlessly and gain insights into how to manage clusters efficiently
Overview
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Choose the hardware and Hadoop distribution that best suits your needs
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Get more value out of your Hadoop cluster with Hive, Impala, and Sqoop
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Learn useful...
| | Professional NoSQL
A hands-on guide to leveraging NoSQL databases
NoSQL databases are an efficient and powerful tool for storing and manipulating vast quantities of data. Most NoSQL databases scale well as data grows. In addition, they are often malleable and flexible enough to accommodate semi-structured and sparse data sets. This... |
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