Apache Ignite Quick Start Guide
Apache Ignite is a distributed in-memory platform designed to scale and process large volume of data. It can be integrated with microservices as well as monolithic systems, and can be used as a scalable, highly available and performant deployment platform for microservices. This book will teach you to use Apache Ignite for building a high-performance, scalable, highly available system architecture with data integrity.
The book takes you through the basics of Apache Ignite and in-memory technologies. You will learn about installation and clustering Ignite nodes, caching topologies, and various caching strategies, such as cache aside, read and write through, and write behind. Next, you will delve into detailed aspects of Ignite's data grid: web session clustering and querying data.
You will learn how to process large volumes of data using compute grid and Ignite's map-reduce and executor service. You will learn about the memory architecture of Apache Ign ...
Practical Apache Spark
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. Practical Apache Spark also covers the integration of Apache Spark with Kafka with examples. You'll follow a learn-to-do-by-yourself approach to learning - learn the concepts, practice the code snippets in Scala, and complete the assignments given to get an overall exposure.
On completion, you'll have knowledge of the functional programming aspects of Scala, and hands-on expertise in various Spark components. You'll also become familiar with machine learning algorithms with real-time usage.
Discover the functional programming features of Scala; Understand the complete architecture of Spark and its components; Integrate Apache Spark with Hive and ...
Mastering Apache Cassandra 3.x, 3rd Edition
With ever-increasing rates of data creation, the demand for storing data fast and reliably becomes a need. Apache Cassandra is the perfect choice for building fault-tolerant and scalable databases. Mastering Apache Cassandra 3.x teaches you how to build and architect your clusters, configure and work with your nodes, and program in a high-throughput environment, helping you understand the power of Cassandra as per the new features.
Once you've covered a brief recap of the basics, you'll move on to deploying and monitoring a production setup and optimizing and integrating it with other software. You'll work with the advanced features of CQL and the new storage engine in order to understand how they function on the server-side. You'll explore the integration and interaction of Cassandra components, followed by discovering features such as token allocation algorithm, CQL3, vnodes, lightweight transactions, and data modelling in detail. Last but not least you will get to g ...
Apache Hadoop 3 Quick Start Guide
Apache Hadoop is a widely used distributed data platform. It enables large datasets to be efficiently processed instead of using one large computer to store and process the data. This book will get you started with the Hadoop ecosystem, and introduce you to the main technical topics, including MapReduce, YARN, and HDFS.
The book begins with an overview of big data and Apache Hadoop. Then, you will set up a pseudo Hadoop development environment and a multi-node enterprise Hadoop cluster. You will see how the parallel programming paradigm, such as MapReduce, can solve many complex data processing problems.
The book also covers the important aspects of the big data software development lifecycle, including quality assurance and control, performance, administration, and monitoring.
You will then learn about the Hadoop ecosystem, and tools such as Kafka, Sqoop, Flume, Pig, Hive, and HBase. Finally, you will look at advanced topics, including real time streaming using ...
Big Data Processing with Apache Spark
Processing big data in real time is challenging due to scalability, information consistency, and fault-tolerance. This book teaches you how to use Spark to make your overall analytical workflow faster and more efficient. You'll explore all core concepts and tools within the Spark ecosystem, such as Spark Streaming, the Spark Streaming API, machine learning extension, and structured streaming.
You'll begin by learning data processing fundamentals using Resilient Distributed Datasets (RDDs), SQL, Datasets, and Dataframes APIs. After grasping these fundamentals, you'll move on to using Spark Streaming APIs to consume data in real time from TCP sockets, and integrate Amazon Web Services (AWS) for stream consumption.
By the end of this book, you'll not only have understood how to use machine learning extensions and structured streams but you'll also be able to apply Spark in your own upcoming big data projects. ...
Learn Apache Mesos
Apache Mesos is an open source cluster manager that provides efficient resource isolation and sharing across distributed applications or frameworks. This book will help you build a strong foundation of Mesos' capabilities along with practical examples to support the concepts explained throughout the book.
Learn Apache Mesos dives straight into how Mesos works. You will be introduced to the distributed system and its challenges and then learn how you can use Mesos and its framework to solve data problems. You will also gain a full understanding of Mesos internal mechanisms and get equipped to use Mesos and develop applications. Furthermore, this book lets you explore all the steps required to create highly available clusters and build your own Mesos frameworks. You will also cover application deployment and monitoring.
By the end of this book, you will have learned how to use Mesos to make full use of machines and how to simplify data center maintenance. ...
Beginning Apache Spark 2
Develop applications for the big data landscape with Spark and Hadoop. This book also explains the role of Spark in developing scalable machine learning and analytics applications with Cloud technologies. Beginning Apache Spark 2 gives you an introduction to Apache Spark and shows you how to work with it.
Along the way, you'll discover resilient distributed datasets (RDDs); use Spark SQL for structured data; and learn stream processing and build real-time applications with Spark Structured Streaming. Furthermore, you'll learn the fundamentals of Spark ML for machine learning and much more.
After you read this book, you will have the fundamentals to become proficient in using Apache Spark and know when and how to apply it to your big data applications.
Understand Spark unified data processing platform; How to run Spark in Spark Shell or Databricks; Use and manipulate RDDs; Deal with structured data using Spark SQL through its operations and advanced func ...
Next-Generation Big Data
Utilize this practical and easy-to-follow guide to modernize traditional enterprise data warehouse and business intelligence environments with next-generation big data technologies.
Next-Generation Big Data takes a holistic approach, covering the most important aspects of modern enterprise big data. The book covers not only the main technology stack but also the next-generation tools and applications used for big data warehousing, data warehouse optimization, real-time and batch data ingestion and processing, real-time data visualization, big data governance, data wrangling, big data cloud deployments, and distributed in-memory big data computing. Finally, the book has an extensive and detailed coverage of big data case studies from Navistar, Cerner, British Telecom, Shopzilla, Thomson Reuters, and Mastercard.
Install Apache Kudu, Impala, and Spark to modernize enterprise data warehouse and business intelligence environments, complete with real-world, easy-to-follow exampl ...
Stream Processing with Apache Flink
Get started with Apache Flink, the open source framework that enables you to process streaming data - such as user interactions, sensor data, and machine logs - as it arrives. With this practical guide, you'll learn how to use Apache Flink's stream processing APIs to implement, continuously run, and maintain real-world applications.
Authors Fabian Hueske, one of Flink's creators, and Vasia Kalavri, a core contributor to Flink's graph processing API (Gelly), explains the fundamental concepts of parallel stream processing and shows you how streaming analytics differs from traditional batch data analysis. Software engineers, data engineers, and system administrators will learn the basics of Flink's DataStream API, including the structure and components of a common Flink streaming application.Solve real-world problems with Apache Flink's DataStream API;Set up an environment for developing stream processing applications for Flink;Design stre ...
Learning Apache Drill
Apache Drill enables interactive analysis of massively large datasets, allowing you to execute SQL queries against data in many different data sources - including Hadoop and MongoDB clusters, HBase, or even your local file system - and get results quickly. With this practical guide, analysts and data scientists focused on business or research applications will learn how to incorporate Drill capabilities into complex programs, including how to use Drill queries to replace some MapReduce operations in a large-scale program.
Drill committers Charles Givre and Paul Rogers provide an introduction to Drill and its ability to handle large files containing data in flexible formats with nested data structures and tables. You'll discover how this capability fills a gap in the Hadoop ecosystem.
Additional topics show you how to:Prepare and organize data to maximize Drill performance;Set expectations for Drill performance on different data types and volumes;R ...
Expert Apache Cassandra Administration
Follow this handbook to build, configure, tune, and secure Apache Cassandra databases. Start with the installation of Cassandra and move on to the creation of a single instance, and then a cluster of Cassandra databases.
Cassandra is increasingly a key player in many big data environments, and this book shows you how to use Cassandra with Apache Spark, a popular big data processing framework. Also covered are day-to-day topics of importance such as the backup and recovery of Cassandra databases, using the right compression and compaction strategies, and loading and unloading data.
Expert Apache Cassandra Administration provides numerous step-by-step examples starting with the basics of a Cassandra database, and going all the way through backup and recovery, performance optimization, and monitoring and securing the data. The book serves as an authoritative and comprehensive guide to the building and management of simple to complex Cassandra databases.
The book: ...