Download or read book Learning Apache Thrift written by Krzysztof Rakowski and published by Packt Publishing Ltd. This book was released on 2015-12-30 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: Make applications cross-communicate using Apache Thrift! About This Book Leverage Apache Thrift to enable applications written in different programming languages (Java, C++, Python, PHP, Ruby, and so on) to cross-communicate. Learn to make your services ready for real-world applications by using stepwise examples and modifying code from Industry giants. Be a crackerjack at solving Apache Thrift-related issues. Who This Book Is For If you have some experience of developing applications in one or more languages supported by Apache Thrift (C++, Java, PHP, Python, Ruby, and others) and want to broaden your knowledge and skills in building cross-platform, scalable applications, then this book is for you. What You Will Learn Understand the need for cross-language services and the basics of Apache Thrift. Learn how Apache Thrift works and what problems it solves. Determine when to use Apache Thrift instead of other methods (REST API), and when not to use it. Create and run an example application using Apache Thrift. Use Apache Thrift in your applications written in different languages supported by Apache Thrift (PHP, Python, Ruby, Java, and C++). Handle exceptions and deal with errors. Modify code in different languages. Use Apache Thrift in the production environments of big applications. In Detail With modern software systems being increasingly complex, providing a scalable communication architecture for applications in different languages is tedious. The Apache Thrift framework is the solution to this problem! It helps build efficient and easy-to-maintain services and offers a plethora of options matching your application type by supporting several popular programming languages, including C++, Java, Python, PHP, Ruby, Erlang, Perl, Haskell, C#, Cocoa, JavaScript, Node.js, Smalltalk, OCaml, and Delphi. This book will help you set aside the basics of service-oriented systems through your first Apache Thrift-powered app. Then, progressing to more complex examples, it will provide you with tips for running large-scale applications in production environments. You will learn how to assess when Apache Thrift is the best tool to be used. To start with, you will run a simple example application, learning the framework's structure along the way; you will quickly advance to more complex systems that will help you solve various real-life problems. Moreover, you will be able to add a communication layer to every application written in one of the popular programming languages, with support for various data types and error handling. Further, you will learn how pre-eminent companies use Apache Thrift in their popular applications. This book is a great starting point if you want to use one of the best tools available to develop cross-language applications in service-oriented architectures. Style and approach A stepwise guide to learning Apache Thrift, with ready-to-run examples explained comprehensively. Advanced topics supply the inspiration for further work.

Download or read book The Programmer s Guide to Apache Thrift written by Randy Abernethy and published by Manning Publications. This book was released on 2018-04-30 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Any distributed application includes individual components, often written in different languages and hosted in multiple locations, which must communicate quickly and efficiently. Apache Thrift is a communication framework that enables cross-language remote procedure calls and serialization. It supports embedded, mobile, web, and server environments, and a host of languages ranging from JavaScript to C++. It's perfect for back end services and embedded systems where size, scalability, and performance are mission critical. Programmer's Guide to Apache Thrift provides comprehensive coverage of the Apache Thrift framework along with a developer's-eye view of modern distributed application architecture. Packed with complete code examples and pragmatic discussion, it lays the best practices for multi-language distributed application development. Readers will get a guided tour through transports, protocols, IDL, and servers as they explore complete example programs in C++, Java, and Python. They'll also learn how to work with platforms, ranging from enterprise servers to mobile clients. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

Download or read book Programmer s Guide to Apache Thrift written by William Abernethy and published by Simon and Schuster. This book was released on 2019-03-17 with total page 878 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Programmer's Guide to Apache Thrift provides comprehensive coverage of the Apache Thrift framework along with a developer's-eye view of modern distributed application architecture. Foreword by Jens Geyer. About the Technology Thrift-based distributed software systems are built out of communicating components that use different languages, protocols, and message types. Sitting between them is Thrift, which handles data serialization, transport, and service implementation. Thrift supports many client and server environments and a host of languages ranging from PHP to JavaScript, and from C++ to Go. About the Book Programmer's Guide to Apache Thrift provides comprehensive coverage of distributed application communication using the Thrift framework. Packed with code examples and useful insight, this book presents best practices for multi-language distributed development. You'll take a guided tour through transports, protocols, IDL, and servers as you explore programs in C++, Java, and Python. You'll also learn how to work with platforms ranging from browser-based clients to enterprise servers. What's inside Complete coverage of Thrift's IDL Building and serializing complex user-defined types Plug-in protocols, transports, and data compression Creating cross-language services with RPC and messaging systems About the Reader Readers should be comfortable with a language like Python, Java, or C++ and the basics of service-oriented or microservice architectures. About the Author Randy Abernethy is an Apache Thrift Project Management Committee member and a partner at RX-M. Table of Contents Introduction to Apache Thrift Apache Thrift architecture Building, testing, and debugging Moving bytes with transports Serializing data with protocols Apache Thrift IDL User-defined types Implementing services Handling exceptions Servers Building clients and servers with C++ Building clients and servers with Java Building C# clients and servers with .NET Core and Windows Building Node.js clients and servers Apache Thrift and JavaScript Scripting Apache Thrift Thrift in the enterprise

Download or read book Programmer s Guide to Apache Thrift written by Randy Abernethy and published by Manning Publications. This book was released on 2019-04-14 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Programmer's Guide to Apache Thrift provides comprehensive coverage of the Apache Thrift framework along with a developer's-eye view of modern distributed application architecture. Foreword by Jens Geyer. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Thrift-based distributed software systems are built out of communicating components that use different languages, protocols, and message types. Sitting between them is Thrift, which handles data serialization, transport, and service implementation. Thrift supports many client and server environments and a host of languages ranging from PHP to JavaScript, and from C++ to Go. About the Book Programmer's Guide to Apache Thrift provides comprehensive coverage of distributed application communication using the Thrift framework. Packed with code examples and useful insight, this book presents best practices for multi-language distributed development. You'll take a guided tour through transports, protocols, IDL, and servers as you explore programs in C++, Java, and Python. You'll also learn how to work with platforms ranging from browser-based clients to enterprise servers. What's inside Complete coverage of Thrift's IDL Building and serializing complex user-defined types Plug-in protocols, transports, and data compression Creating cross-language services with RPC and messaging systems About the Reader Readers should be comfortable with a language like Python, Java, or C++ and the basics of service-oriented or microservice architectures. About the Author Randy Abernethy is an Apache Thrift Project Management Committee member and a partner at RX-M. Table of Contents PART 1 - APACHE THRIFT OVERVIEW Introduction to Apache Thrift Apache Thrift architecture Building, testing, and debugging PART 2 - PROGRAMMING APACHE THRIFT Moving bytes with transports Serializing data with protocols Apache Thrift IDL User-defined types Implementing services Handling exceptions Servers PART 3 - APACHE THRIFT LANGUAGES Building clients and servers with C++ Building clients and servers with Java Building C# clients and servers with .NET Core and Windows Building Node.js clients and servers Apache Thrift and JavaScript Scripting Apache Thrift Thrift in the enterprise

Download or read book Programming Hive written by Edward Capriolo and published by "O'Reilly Media, Inc.". This book was released on 2012-09-26 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: Need to move a relational database application to Hadoop? This comprehensive guide introduces you to Apache Hive, Hadoop’s data warehouse infrastructure. You’ll quickly learn how to use Hive’s SQL dialect—HiveQL—to summarize, query, and analyze large datasets stored in Hadoop’s distributed filesystem. This example-driven guide shows you how to set up and configure Hive in your environment, provides a detailed overview of Hadoop and MapReduce, and demonstrates how Hive works within the Hadoop ecosystem. You’ll also find real-world case studies that describe how companies have used Hive to solve unique problems involving petabytes of data. Use Hive to create, alter, and drop databases, tables, views, functions, and indexes Customize data formats and storage options, from files to external databases Load and extract data from tables—and use queries, grouping, filtering, joining, and other conventional query methods Gain best practices for creating user defined functions (UDFs) Learn Hive patterns you should use and anti-patterns you should avoid Integrate Hive with other data processing programs Use storage handlers for NoSQL databases and other datastores Learn the pros and cons of running Hive on Amazon’s Elastic MapReduce

Download or read book Learning Apache Cassandra written by Mat Brown and published by Packt Publishing Ltd. This book was released on 2015-02-25 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you're an application developer familiar with SQL databases such as MySQL or Postgres, and you want to explore distributed databases such as Cassandra, this is the perfect guide for you. Even if you've never worked with a distributed database before, Cassandra's intuitive programming interface coupled with the step-by-step examples in this book will have you building highly scalable persistence layers for your applications in no time.

Download or read book Spark The Definitive Guide written by Bill Chambers and published by "O'Reilly Media, Inc.". This book was released on 2018-02-08 with total page 712 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the 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. Youâ??ll explore the basic operations and common functions of Sparkâ??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, Sparkâ??s scalable machine-learning library. Get a gentle overview of big data and Spark Learn about DataFrames, SQL, and Datasetsâ??Sparkâ??s core APIsâ??through worked examples Dive into Sparkâ??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 Structured Streaming, Sparkâ??s stream-processing engine Learn how you can apply MLlib to a variety of problems, including classification or recommendation

Download or read book Learning Apache Spark 2 written by Muhammad Asif Abbasi and published by Packt Publishing Ltd. This book was released on 2017-03-28 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn about the fastest-growing open source project in the world, and find out how it revolutionizes big data analytics About This Book Exclusive guide that covers how to get up and running with fast data processing using Apache Spark Explore and exploit various possibilities with Apache Spark using real-world use cases in this book Want to perform efficient data processing at real time? This book will be your one-stop solution. Who This Book Is For This guide appeals to big data engineers, analysts, architects, software engineers, even technical managers who need to perform efficient data processing on Hadoop at real time. Basic familiarity with Java or Scala will be helpful. The assumption is that readers will be from a mixed background, but would be typically people with background in engineering/data science with no prior Spark experience and want to understand how Spark can help them on their analytics journey. What You Will Learn Get an overview of big data analytics and its importance for organizations and data professionals Delve into Spark to see how it is different from existing processing platforms Understand the intricacies of various file formats, and how to process them with Apache Spark. Realize how to deploy Spark with YARN, MESOS or a Stand-alone cluster manager. Learn the concepts of Spark SQL, SchemaRDD, Caching and working with Hive and Parquet file formats Understand the architecture of Spark MLLib while discussing some of the off-the-shelf algorithms that come with Spark. Introduce yourself to the deployment and usage of SparkR. Walk through the importance of Graph computation and the graph processing systems available in the market Check the real world example of Spark by building a recommendation engine with Spark using ALS. Use a Telco data set, to predict customer churn using Random Forests. In Detail Spark juggernaut keeps on rolling and getting more and more momentum each day. Spark provides key capabilities in the form of Spark SQL, Spark Streaming, Spark ML and Graph X all accessible via Java, Scala, Python and R. Deploying the key capabilities is crucial whether it is on a Standalone framework or as a part of existing Hadoop installation and configuring with Yarn and Mesos. The next part of the journey after installation is using key components, APIs, Clustering, machine learning APIs, data pipelines, parallel programming. It is important to understand why each framework component is key, how widely it is being used, its stability and pertinent use cases. Once we understand the individual components, we will take a couple of real life advanced analytics examples such as 'Building a Recommendation system', 'Predicting customer churn' and so on. The objective of these real life examples is to give the reader confidence of using Spark for real-world problems. Style and approach With the help of practical examples and real-world use cases, this guide will take you from scratch to building efficient data applications using Apache Spark. You will learn all about this excellent data processing engine in a step-by-step manner, taking one aspect of it at a time. This highly practical guide will include how to work with data pipelines, dataframes, clustering, SparkSQL, parallel programming, and such insightful topics with the help of real-world use cases.

Download or read book Cassandra The Definitive Guide written by Jeff Carpenter and published by "O'Reilly Media, Inc.". This book was released on 2016-06-29 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you’ll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This expanded second edition—updated for Cassandra 3.0—provides the technical details and practical examples you need to put this database to work in a production environment. Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra’s non-relational design, with special attention to data modeling. If you’re a developer, DBA, or application architect looking to solve a database scaling issue or future-proof your application, this guide helps you harness Cassandra’s speed and flexibility. Understand Cassandra’s distributed and decentralized structure Use the Cassandra Query Language (CQL) and cqlsh—the CQL shell Create a working data model and compare it with an equivalent relational model Develop sample applications using client drivers for languages including Java, Python, and Node.js Explore cluster topology and learn how nodes exchange data Maintain a high level of performance in your cluster Deploy Cassandra on site, in the Cloud, or with Docker Integrate Cassandra with Spark, Hadoop, Elasticsearch, Solr, and Lucene

Download or read book Apache Hive Cookbook written by Hanish Bansal and published by Packt Publishing Ltd. This book was released on 2016-04-29 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Easy, hands-on recipes to help you understand Hive and its integration with frameworks that are used widely in today's big data world About This Book Grasp a complete reference of different Hive topics. Get to know the latest recipes in development in Hive including CRUD operations Understand Hive internals and integration of Hive with different frameworks used in today's world. Who This Book Is For The book is intended for those who want to start in Hive or who have basic understanding of Hive framework. Prior knowledge of basic SQL command is also required What You Will Learn Learn different features and offering on the latest Hive Understand the working and structure of the Hive internals Get an insight on the latest development in Hive framework Grasp the concepts of Hive Data Model Master the key concepts like Partition, Buckets and Statistics Know how to integrate Hive with other frameworks such as Spark, Accumulo, etc In Detail Hive was developed by Facebook and later open sourced in Apache community. Hive provides SQL like interface to run queries on Big Data frameworks. Hive provides SQL like syntax also called as HiveQL that includes all SQL capabilities like analytical functions which are the need of the hour in today's Big Data world. This book provides you easy installation steps with different types of metastores supported by Hive. This book has simple and easy to learn recipes for configuring Hive clients and services. You would also learn different Hive optimizations including Partitions and Bucketing. The book also covers the source code explanation of latest Hive version. Hive Query Language is being used by other frameworks including spark. Towards the end you will cover integration of Hive with these frameworks. Style and approach Starting with the basics and covering the core concepts with the practical usage, this book is a complete guide to learn and explore Hive offerings.

Download or read book Kafka The Definitive Guide written by Neha Narkhede and published by "O'Reilly Media, Inc.". This book was released on 2017-08-31 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Every enterprise application creates data, whether it’s log messages, metrics, user activity, outgoing messages, or something else. And how to move all of this data becomes nearly as important as the data itself. If you’re an application architect, developer, or production engineer new to Apache Kafka, this practical guide shows you how to use this open source streaming platform to handle real-time data feeds. Engineers from Confluent and LinkedIn who are responsible for developing Kafka explain how to deploy production Kafka clusters, write reliable event-driven microservices, and build scalable stream-processing applications with this platform. Through detailed examples, you’ll learn Kafka’s design principles, reliability guarantees, key APIs, and architecture details, including the replication protocol, the controller, and the storage layer. Understand publish-subscribe messaging and how it fits in the big data ecosystem. Explore Kafka producers and consumers for writing and reading messages Understand Kafka patterns and use-case requirements to ensure reliable data delivery Get best practices for building data pipelines and applications with Kafka Manage Kafka in production, and learn to perform monitoring, tuning, and maintenance tasks Learn the most critical metrics among Kafka’s operational measurements Explore how Kafka’s stream delivery capabilities make it a perfect source for stream processing systems

Download or read book Apache Spark in 24 Hours Sams Teach Yourself written by Jeffrey Aven and published by Sams Publishing. This book was released on 2016-08-31 with total page 1353 pages. Available in PDF, EPUB and Kindle. Book excerpt: Apache Spark is a fast, scalable, and flexible open source distributed processing engine for big data systems and is one of the most active open source big data projects to date. In just 24 lessons of one hour or less, Sams Teach Yourself Apache Spark in 24 Hours helps you build practical Big Data solutions that leverage Spark’s amazing speed, scalability, simplicity, and versatility. This book’s straightforward, step-by-step approach shows you how to deploy, program, optimize, manage, integrate, and extend Spark–now, and for years to come. You’ll discover how to create powerful solutions encompassing cloud computing, real-time stream processing, machine learning, and more. Every lesson builds on what you’ve already learned, giving you a rock-solid foundation for real-world success. Whether you are a data analyst, data engineer, data scientist, or data steward, learning Spark will help you to advance your career or embark on a new career in the booming area of Big Data. Learn how to • Discover what Apache Spark does and how it fits into the Big Data landscape • Deploy and run Spark locally or in the cloud • Interact with Spark from the shell • Make the most of the Spark Cluster Architecture • Develop Spark applications with Scala and functional Python • Program with the Spark API, including transformations and actions • Apply practical data engineering/analysis approaches designed for Spark • Use Resilient Distributed Datasets (RDDs) for caching, persistence, and output • Optimize Spark solution performance • Use Spark with SQL (via Spark SQL) and with NoSQL (via Cassandra) • Leverage cutting-edge functional programming techniques • Extend Spark with streaming, R, and Sparkling Water • Start building Spark-based machine learning and graph-processing applications • Explore advanced messaging technologies, including Kafka • Preview and prepare for Spark’s next generation of innovations Instructions walk you through common questions, issues, and tasks; Q-and-As, Quizzes, and Exercises build and test your knowledge; "Did You Know?" tips offer insider advice and shortcuts; and "Watch Out!" alerts help you avoid pitfalls. By the time you're finished, you'll be comfortable using Apache Spark to solve a wide spectrum of Big Data problems.

Download or read book Learning Spark written by Jules S. Damji and published by O'Reilly Media. This book was released on 2020-07-16 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data is bigger, arrives faster, and comes in a variety of formats—and it all needs to be processed at scale for analytics or machine learning. But how can you process such varied workloads efficiently? Enter Apache Spark. Updated to include Spark 3.0, this second edition shows data engineers and data scientists why structure and unification in Spark matters. Specifically, this book explains how to perform simple and complex data analytics and employ machine learning algorithms. Through step-by-step walk-throughs, code snippets, and notebooks, you’ll be able to: Learn Python, SQL, Scala, or Java high-level Structured APIs Understand Spark operations and SQL Engine Inspect, tune, and debug Spark operations with Spark configurations and Spark UI Connect to data sources: JSON, Parquet, CSV, Avro, ORC, Hive, S3, or Kafka Perform analytics on batch and streaming data using Structured Streaming Build reliable data pipelines with open source Delta Lake and Spark Develop machine learning pipelines with MLlib and productionize models using MLflow

Download or read book Using Flume written by Hari Shreedharan and published by "O'Reilly Media, Inc.". This book was released on 2014-09-16 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can you get your data from frontend servers to Hadoop in near real time? With this complete reference guide, you’ll learn Flume’s rich set of features for collecting, aggregating, and writing large amounts of streaming data to the Hadoop Distributed File System (HDFS), Apache HBase, SolrCloud, Elastic Search, and other systems. Using Flume shows operations engineers how to configure, deploy, and monitor a Flume cluster, and teaches developers how to write Flume plugins and custom components for their specific use-cases. You’ll learn about Flume’s design and implementation, as well as various features that make it highly scalable, flexible, and reliable. Code examples and exercises are available on GitHub. Learn how Flume provides a steady rate of flow by acting as a buffer between data producers and consumers Dive into key Flume components, including sources that accept data and sinks that write and deliver it Write custom plugins to customize the way Flume receives, modifies, formats, and writes data Explore APIs for sending data to Flume agents from your own applications Plan and deploy Flume in a scalable and flexible way—and monitor your cluster once it’s running

Download or read book Designing Data Intensive Applications written by Martin Kleppmann and published by "O'Reilly Media, Inc.". This book was released on 2017-03-16 with total page 658 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures

Download or read book Architecting HBase Applications written by Jean-Marc Spaggiari and published by "O'Reilly Media, Inc.". This book was released on 2016-07-18 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lots of HBase books, online HBase guides, and HBase mailing lists/forums are available if you need to know how HBase works. But if you want to take a deep dive into use cases, features, and troubleshooting, Architecting HBase Applications is the right source for you. With this book, you'll learn a controlled set of APIs that coincide with use-case examples and easily deployed use-case models, as well as sizing/best practices to help jump start your enterprise application development and deployment.

Download or read book Mastering Apache Storm written by Ankit Jain and published by Packt Publishing Ltd. This book was released on 2017-08-16 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master the intricacies of Apache Storm and develop real-time stream processing applications with ease About This Book Exploit the various real-time processing functionalities offered by Apache Storm such as parallelism, data partitioning, and more Integrate Storm with other Big Data technologies like Hadoop, HBase, and Apache Kafka An easy-to-understand guide to effortlessly create distributed applications with Storm Who This Book Is For If you are a Java developer who wants to enter into the world of real-time stream processing applications using Apache Storm, then this book is for you. No previous experience in Storm is required as this book starts from the basics. After finishing this book, you will be able to develop not-so-complex Storm applications. What You Will Learn Understand the core concepts of Apache Storm and real-time processing Follow the steps to deploy multiple nodes of Storm Cluster Create Trident topologies to support various message-processing semantics Make your cluster sharing effective using Storm scheduling Integrate Apache Storm with other Big Data technologies such as Hadoop, HBase, Kafka, and more Monitor the health of your Storm cluster In Detail Apache Storm is a real-time Big Data processing framework that processes large amounts of data reliably, guaranteeing that every message will be processed. Storm allows you to scale your data as it grows, making it an excellent platform to solve your big data problems. This extensive guide will help you understand right from the basics to the advanced topics of Storm. The book begins with a detailed introduction to real-time processing and where Storm fits in to solve these problems. You'll get an understanding of deploying Storm on clusters by writing a basic Storm Hello World example. Next we'll introduce you to Trident and you'll get a clear understanding of how you can develop and deploy a trident topology. We cover topics such as monitoring, Storm Parallelism, scheduler and log processing, in a very easy to understand manner. You will also learn how to integrate Storm with other well-known Big Data technologies such as HBase, Redis, Kafka, and Hadoop to realize the full potential of Storm. With real-world examples and clear explanations, this book will ensure you will have a thorough mastery of Apache Storm. You will be able to use this knowledge to develop efficient, distributed real-time applications to cater to your business needs. Style and approach This easy-to-follow guide is full of examples and real-world applications to help you get an in-depth understanding of Apache Storm. This book covers the basics thoroughly and also delves into the intermediate and slightly advanced concepts of application development with Apache Storm.