Abstract This IBM® Redbooks® publication is intended for IBM CICS® system programmers and IBM Z architects. It describes how to deploy and manage Java EE 7 web-based applications in an IBM CICS Liberty JVM server and access data on IBM Db2® for IBM z/OS® and IBM MQ for z/OS sub systems. In this book, we describe the key steps to create and install a Liberty JVM server within a CICS region. We then describe how to best use the different deployment techniques for Java EE applications and the specific considerations when deploying applications that use JDBC, JMS, and the new CICS link to Liberty API. Finally, we describe how to secure web applications in CICS Liberty, including transport-level security and request authentication and authorization by using IBM RACF® and LDAP registries. Information is also provided about how to build a high availability infrastructure and how to use the logging and monitoring functions that are available in the CICS Liberty environment. This book is based on IBM CICS Transaction Server (CICS TS) V5.4 that uses the embedded IBM WebSphere® Application Server Liberty technology. It is also applicable to CICS TS V5.3 with the fixes for the continuous delivery APAR PI77502 applied. Sample applications are used throughout this publication and are freely available for download from the IBM CICSDev GitHub organization along with detailed deployment instructions.

In-memory data grids (IMDG) such as Pivotal GemFire, which is powered by Apache Geode, are key to making today’s modern high-speed, data-intensive applications work. By keeping data in the RAM of a horizontally scalable cluster of servers, IMDG solutions enable apps to achieve consistently low latency for data access at any scale. Many in the application development community, however, aren’t aware of IMDG’s benefits, use cases, or underlying technology. This report brings you up to speed by providing GemFire basics, including use cases and easily understood examples. You’ll determine whether GemFire can benefit your application, and learn how to install a simple test environment and build a small proof of concept. Explore GemFire use cases for Java applications—including microservices, high-speed data ingest, and transaction and event processing Get an architectural overview of GemFire, and learn installation requirements for both hardware/VM and cloud Dive into GemFire’s capabilities with continuous queries, server-side functions, and Apache Lucene integration Learn how GemFire works with the persistence model, off-heap memory, and WAN replication

Dive into the essential resource for mastering Apache Kafka with this cookbook of practical recipes. You'll explore the dynamic features of Kafka 1.0, integrate it with enterprise data solutions, and confidently manage messaging and streaming data in real-time. What this Book will help me do Effectively install and configure Apache Kafka in a professional environment. Implement Kafka producers and consumers to manage real-time data streams. Utilize Confluent platforms and Kafka streams for advanced data processing. Monitor Kafka clusters with tools like Graphite and Ganglia for optimal performance. Integrate Kafka seamlessly with tools such as Hadoop, Spark, and Elasticsearch. Author(s) None Estrada and None Zinoviev have extensive experience in enterprise data systems and have been dedicated contributors to the Apache Kafka ecosystem. Their combined expertise encompasses developing robust, real-time distributed systems and delivering insightful technical guidance. Through this book, they share their vast knowledge and practical solutions, tailored for both developers and administrators. Who is it for? This book is tailored for developers and administrators looking to enhance their expertise in Apache Kafka. Developers should be comfortable with Java or Scala to fully utilize examples, while administrators benefit from prior knowledge of Kafka operations. Ideal readers are those seeking actionable techniques to efficiently manage and integrate Kafka into their enterprise systems.

Create and run a real-time, highly-available, and high-redundancy version of the world's most popular open-source database, MySQL. You will understand the advantages and disadvantages of the MySQL NDB Cluster solution, and when MySQL NDB Cluster is the right choice. Pro MySQL NDB Cluster walks you through the full lifecycle of a MySQL Cluster installation: starting with the installation and initial configuration, moving through online configuration and schema changes, and completing with online upgrades. Along the way, you will learn to monitor your cluster, make decisions about schema design, implement geographic replication, troubleshoot and optimize performance, and much more. This book covers the many programming APIs that are supported by MySQL NDB Cluster. There's also robust coverage of connecting to MySQL NDB Cluster from Java, SQL, memcached, and even from C++. From any of these languages, you'll be able to connect and store and retrieve data as your applications demand. The book: Covers MySQL NDB Cluster concepts and architecture Takes you through the MySQL NDB Cluster lifecycle from installation to upgrades Guides you through DBA and Developer decisions when working with MySQL NDB Cluster What You'll Learn Understand the shared-nothing architecture behind MySQL NDB Cluster Plan, install, and configure a MySQL NDB Cluster environment Perform everyday tasks such as backing up, restoring, and upgrading Develop applications from Java, memcached, C++, and SQL Troubleshoot and resolve application performance problems Master enterprise-level features such the MySQL NDB Cluster Manager Who This Book Is For Database administrators and developers who are looking into deploying MySQL NDB Cluster, or who already have a cluster in production and want to increase their knowledge and ability to handle routine administrative tasks and troubleshooting. The book also is for those developers wanting to employ MySQL NDB Cluster as their chosen storage engine from Java, memcached, and C++ applications.

This book provides a comprehensive guide to real-time data processing and analytics using modern frameworks like Apache Spark, Flink, Storm, and Kafka. Through practical examples and in-depth explanations, you will learn how to implement efficient, scalable, real-time processing pipelines. What this Book will help me do Understand real-time data processing essentials and the technology stack Learn integration of components like Apache Spark and Kafka Master the concepts of stream processing with detailed case studies Gain expertise in developing monitoring and alerting solutions for real-time systems Prepare to implement production-grade real-time data solutions Author(s) Shilpi Saxena and Saurabh Gupta, the authors, are experienced professionals in distributed systems and data engineering, focusing on practical applications of real-time computing. They bring their extensive industry experience to this book, helping readers understand the complexities of real-time data solutions in an approachable and hands-on manner. Who is it for? This book is ideal for software engineers and data engineers with a background in Java who seek to develop real-time data solutions. It is suitable for readers familiar with concepts of real-time data processing, and enhances knowledge in frameworks like Spark, Flink, Storm, and Kafka. Target audience includes learners building production data solutions and those designing distributed analytics engines.

"Pentaho 8 Reporting for Java Developers" is your hands-on guide to mastering the Pentaho 8 reporting platform. Packed with practical examples and exercises, this book teaches you how to create highly functional, interactive reports for your data visualization needs. Updated for the latest version of Pentaho, it provides all the tools and techniques you need to succeed. What this Book will help me do Learn the fundamental concepts of Pentaho Reporting including setup and initial configurations. Design and customize attractive, functional reports utilizing various data sources. Integrate Pentaho reports seamlessly into Java applications with full control over their interactions and design. Explore advanced reporting features like parameterization, localization, and complex layout configurations. Incorporate Pentaho reports into the broader Pentaho suite, including the BA platform and Data Integration tools. Author(s) Jasmine Kaur and None Corti bring their extensive expertise in information technology and Java development to this comprehensive guide. With years of hands-on experience working with Pentaho Reporting tools, they have a deep understanding of the challenges and solutions in report design. Their approachable writing style and emphasis on practical examples make learning intuitive and enjoyable. Who is it for? This book is ideally suited for Information Technologists who are familiar with databases and intermediate-level Java Developers looking to integrate advanced reporting functionalities into their projects. If you are eager to build pixel-perfect, professional reports or need insights into embedding reporting tools into Java applications, this book holds the answers.

"Learning Spark SQL" takes you from data exploration to designing scalable applications with Apache Spark SQL. Through hands-on examples, you will comprehend real-world use cases and gain practical skills crucial for working with Spark SQL APIs, data frames, streaming data, and optimizing Spark applications. What this Book will help me do Understand the principles of Spark SQL and its APIs for building scalable distributed applications. Gain hands-on experience performing data wrangling and visualization using Spark SQL and real-world datasets. Learn how to design and optimize applications for performance and scalability with Spark SQL. Develop the skills to integrate Spark SQL with other frameworks like Apache Kafka for streaming analytics. Master the techniques required to architect machine learning and deep learning solutions using Spark SQL. Author(s) None Sarkar is an experienced technologist and trainer specializing in big data, streaming analytics, and scalable architectures using Apache Spark. With years of practical experience in implementing Spark solutions, Sarkar draws from real-world projects to provide readers with valuable insights. Sarkar's approachable and detailed writing style ensures readers grasp both the theory and the practice of Spark SQL. Who is it for? This book is ideal for software developers, data engineers, and architects aspiring to harness Apache Spark for robust, scalable applications. It suits readers with some SQL querying experience and a basic knowledge of programming in languages like Scala, Java, or Python. Whether you're a Spark newcomer or advancing your capabilities in scalable data processing, this resource will accelerate your learning journey.

Quickly get up to speed with Oracle's Application Development Framework (ADF). Rapidly build modern, user-friendly applications that will be easy to re-use, expand, and maintain. Oracle ADF Survival Guide covers the latest 12c version and explains all the important concepts and parts, including ADF Faces, ADF Task Flows, ADF Business Components, ADF Skins, the new Alta UI, and how to implement business logic in all layers of the application. Organizations with existing investments in Oracle database and Oracle Forms applications will be able to leverage Oracle's best practice for application development in moving those applications to the ADF framework. The book: Explains all parts of the ADF stack Shows how to integrate with databases and web services Demonstrates the best practice for ADF enterprise architecture What You Will Learn Rapidly build great-looking, user-friendly screens Build page flows visually for improved communication with business users Easily connect your user interface to databases and other back-end systems Leverage the best practice for productive team development Establish a solid enterprise architecture for maximum reuse and maintainability Automate your build and deployment process Who This Book Is For Experienced developers who want to rapidly become productive with Oracle's Application Development Framework (ADF) 12c. It is for Oracle Forms and database developers working for organizations who have followed Oracle’s strategic direction to ADF, as well as for experienced Java developers who want to learn Oracle’s highly-productive, JSF framework.

Learn how to design and build efficient real-time streaming applications using Apache Kafka, a leading distributed streaming platform. This book provides comprehensive guidance on setting up Kafka clusters, developing producers and consumers, and integrating with frameworks like Spark, Storm, and Heron. By the end, you'll master the skills needed to create enterprise-grade data streaming solutions. What this Book will help me do Grasp the core concepts and components of Apache Kafka and its ecosystem. Develop robust Kafka producers and consumers to process real-time data streams. Design and implement streaming applications using Spark, Storm, and Heron. Plan Kafka deployments with a focus on scalability, capacity, and fault tolerance. Ensure secure data streaming with best practices for securing Apache Kafka. Author(s) The authors, None Singh and None Kumar, bring years of expertise in data engineering and distributed systems. Having worked extensively with streaming technologies like Apache Kafka, they aim to share their in-depth knowledge through practical examples and real-world scenarios. Their approach to teaching focuses on making complex concepts easily understandable. Who is it for? This book is ideal for software developers and data engineers who are eager to learn Apache Kafka for building streaming applications. Some experience with programming, particularly Java, will help readers get the most out of the material. If you are working on data-processing systems or looking to enhance your skills in real-time data handling, this book caters to your needs.

Mastering Apache Storm is your step-by-step guide to mastering real-time data streaming with this robust framework. You'll learn how to process big data efficiently and integrate Apache Storm with popular technologies like Kafka, HBase, and Redis to maximize its potential. This book walks you through from basic concepts to advanced implementations of Apache Storm in real-world scenarios. What this Book will help me do Understand the core features and operation of Apache Storm for real-time data streaming. Integrate Apache Storm with other Big Data frameworks like Kafka, HBase, Redis, and Hadoop. Effectively deploy and manage multi-node Apache Storm clusters in real-world environments. Monitor and analyze your data streams and system health effectively using built-in and external tools. Learn to implement fault-tolerant, scalable, and distributed stream processing applications in Apache Storm. Author(s) None Jain is an experienced software developer and technical instructor specializing in distributed systems and real-time data processing. With years of experience working with Apache Storm and related technologies, their teachings focus on practical, hands-on learning to equip readers with actionable skills. Who is it for? This book is ideal for Java developers aspiring to build expertise in real-time data streaming and distributed processing applications using Apache Storm. Beginners can start with the fundamentals provided, while those with prior knowledge can delve into intermediate and advanced implementations.

Delve into mastering big data processing with 'Apache Spark 2.x for Java Developers.' This book provides a practical guide to implementing Apache Spark using the Java APIs, offering a unique opportunity for Java developers to leverage Spark's powerful framework without transitioning to Scala. What this Book will help me do Learn how to process data from formats like XML, JSON, CSV using Spark Core. Implement real-time analytics using Spark Streaming and third-party tools like Kafka. Understand data querying with Spark SQL and master SQL schema processing. Apply machine learning techniques with Spark MLlib to real-world scenarios. Explore graph processing and analytics using Spark GraphX. Author(s) None Kumar and None Gulati, experienced professionals in Java development and big data, bring their wealth of practical experience and passion for teaching to this book. With a clear and concise writing style, they aim to simplify Spark for Java developers, making big data approachable. Who is it for? This book is perfect for Java developers who are eager to expand their skillset into big data processing with Apache Spark. Whether you are a seasoned Spark user or first diving into big data concepts, this book meets you at your level. With practical examples and straightforward explanations, you can unlock the potential of Spark in real-world scenarios.

JSON is becoming the backbone for meaningful data interchange over the internet. This format is now supported by an entire ecosystem of standards, tools, and technologies for building truly elegant, useful, and efficient applications. With this hands-on guide, author and architect Tom Marrs shows you how to build enterprise-class applications and services by leveraging JSON tooling and message/document design. JSON at Work provides application architects and developers with guidelines, best practices, and use cases, along with lots of real-world examples and code samples. You’ll start with a comprehensive JSON overview, explore the JSON ecosystem, and then dive into JSON’s use in the enterprise. Get acquainted with JSON basics and learn how to model JSON data Learn how to use JSON with Node.js, Ruby on Rails, and Java Structure JSON documents with JSON Schema to design and test APIs Search the contents of JSON documents with JSON Search tools Convert JSON documents to other data formats with JSON Transform tools Compare JSON-based hypermedia formats, including HAL and jsonapi Leverage MongoDB to store and access JSON documents Use Apache Kafka to exchange JSON-based messages between services

Messaging is one of the more poorly understood areas of IT; most developers and architects have only a passing familiarity with how broker-based messaging technologies work. This practical report not only helps you get up to speed on the essentials of messaging, but also compares two of today’s most popular messaging technologies—Apache ActiveMQ and Apache Kafka. Author and consultant Jakub Korab describes use cases and design choices that lead developers to very different approaches for developing message-based systems. You’ll come away with a high-level understanding of both ActiveMQ and Kafka, including how they should and should not be used, how they handle concerns such as throughput and high-availability, and what to look out for when considering other messaging technologies in future. Understand the types of problems that messaging systems address Explore three primary messaging patterns: point-to-point, publish-subscribe, and a hybrid of both Dive into ActiveMQ, a classic broker-centric design implemented through Java libraries that works for a broad range of messaging use cases Examine Kafka, a distributed system that can be scaled to provide massive performance and fault tolerance through replication Learn the mechanical complexities that message-based systems need to address, and some patterns you can apply to deal with those complexities

In the second edition of this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. The authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by example. Updated for Spark 2.1, this edition acts as an introduction to these techniques and other best practices in Spark programming. You’ll start with an introduction to Spark and its ecosystem, and then dive into patterns that apply common techniques—including classification, clustering, collaborative filtering, and anomaly detection—to fields such as genomics, security, and finance. If you have an entry-level understanding of machine learning and statistics, and you program in Java, Python, or Scala, you’ll find the book’s patterns useful for working on your own data applications. With this book, you will: Familiarize yourself with the Spark programming model Become comfortable within the Spark ecosystem Learn general approaches in data science Examine complete implementations that analyze large public data sets Discover which machine learning tools make sense for particular problems Acquire code that can be adapted to many uses

Data Science is booming thanks to R and Python, but Java brings the robustness, convenience, and ability to scale critical to today’s data science applications. With this practical book, Java software engineers looking to add data science skills will take a logical journey through the data science pipeline. Author Michael Brzustowicz explains the basic math theory behind each step of the data science process, as well as how to apply these concepts with Java. You’ll learn the critical roles that data IO, linear algebra, statistics, data operations, learning and prediction, and Hadoop MapReduce play in the process. Throughout this book, you’ll find code examples you can use in your applications. Examine methods for obtaining, cleaning, and arranging data into its purest form Understand the matrix structure that your data should take Learn basic concepts for testing the origin and validity of data Transform your data into stable and usable numerical values Understand supervised and unsupervised learning algorithms, and methods for evaluating their success Get up and running with MapReduce, using customized components suitable for data science algorithms

"Data Lake for Enterprises" is a comprehensive guide to building data lakes using the Lambda Architecture. It introduces big data technologies like Hadoop, Spark, and Flume, showing how to use them effectively to manage and leverage enterprise-scale data. You'll gain the skills to design and implement data systems that handle complex data challenges. What this Book will help me do Master the use of Lambda Architecture to create scalable and effective data management systems. Understand and implement technologies like Hadoop, Spark, Kafka, and Flume in an enterprise data lake. Integrate batch and stream processing techniques using big data tools for comprehensive data analysis. Optimize data lakes for performance and reliability with practical insights and techniques. Implement real-world use cases of data lakes and machine learning for predictive data insights. Author(s) None Mishra, None John, and Pankaj Misra are recognized experts in big data systems with a strong background in designing and deploying data solutions. With a clear and methodical teaching style, they bring years of experience to this book, providing readers with the tools and knowledge required to excel in enterprise big data initiatives. Who is it for? This book is ideal for software developers, data architects, and IT professionals looking to integrate a data lake strategy into their enterprises. It caters to readers with a foundational understanding of Java and big data concepts, aiming to advance their practical knowledge of building scalable data systems. If you're eager to delve into cutting-edge technologies and transform enterprise data management, this book is for you.

Abstract Business Intelligence (BI) is a broad term that relates to applications that analyze data to understand and act on the key metrics that drive profitability in an enterprise. Key to analyzing that data is providing fast, easy access to it while delivering it in formats or tools that best fit the needs of the user. At the core of any BI solution are user query and reporting tools that provide intuitive access to data supporting a spectrum of users from executives to “power users,” from spreadsheet aficionados to the external Internet consumer. IBM® DB2® Web Query for i offers a set of modernized tools for a more robust, extensible, and productive reporting solution than the popular IBM Query for System i® tool (also known as IBM Query/400). IBM DB2 Web Query for i preserves investments in the reports that are developed with Query/400 by offering a choice of importing definitions into the new technology or continuing to run existing Query/400 reports as is. But, it also offers significant productivity and performance enhancements by leveraging the latest in DB2 for i query optimization technology. The DB2 Web Query for i product is a web-based query and report writing product that offers enhanced capabilities over the IBM Query for iSeries product (also commonly known as Query/400). IBM DB2 Web Query for i includes Query for iSeries technology to assist customers in their transition to DB2 Web Query. It offers a more modernized, Java based solution for a more robust, extensible, and productive reporting solution. DB2 Web Query provides the ability to query or build reports against data that is stored in DB2 for i (or Microsoft SQL Server) databases through browser-based user interface technologies: Build reports with ease through the web-based, ribbon-like InfoAssist tool that leverages a common look and feel that can extend the number of personnel that can generate their own reports. Simplify the management of reports by significantly reducing the number of report definitions that are required through the use of parameter driven reports. Deliver data to users in many different formats, including directly into spreadsheets, or in boardroom-quality PDF format, or viewed from the browser in HTML. Leverage advanced reporting functions, such as matrix reporting, ranking, color coding, drill-down, and font customization to enhance the visualization of DB2 data. DB2 Web Query offers features to import Query/400 definitions and enhance their look and functions. By using it, you can add OLAP-like slicing and dicing to the reports or view reports in disconnected mode for users on the go. This IBM Redbooks® publication provides a broad understanding of what can be done with the DB2 Web Query product. This publication is a companion of DB2 Web Query Tutorials, SG24-8378, which has a group of self-explanatory tutorials to help you get up to speed quickly.

Learning Apache Cassandra is an engaging and in-depth guide to understanding the concepts and practical applications of Apache Cassandra, one of the most robust distributed NoSQL databases available. By the end of this book, you will have the necessary skills to design and manage scalable, high-performance database solutions tailored for modern applications. What this Book will help me do Set up Apache Cassandra and its multi-node clusters confidently and efficiently. Master schema design principles, including the use of composite keys, collections, and user-defined types. Implement efficient query strategies with secondary indexes and materialized views. Understand data distribution strategies and tune consistency levels for different application requirements. Dive into advanced topics like user-defined functions, batch operations, and Java client optimizations for scalable database architecture. Author(s) None Yarabarla brings practical expertise and deep knowledge to the subject of Apache Cassandra. With hands-on industry experience designing scalable database solutions, the author ensures complex topics are presented through clear and actionable insights. This is coupled with real-world scenarios to help you apply your learning effectively. Who is it for? This book is ideal for developers and IT professionals interested in learning Apache Cassandra from scratch or enhancing their NoSQL database expertise. It is particularly suited for those transitioning from relational databases to NoSQL systems. Even without prior coding experience, readers can expect to follow along and achieve practical results.

Dive into the world of MQTT, the preferred protocol for IoT and M2M communication. This book provides a comprehensive guide to understanding, implementing, and securing MQTT-based systems, enabling readers to create efficient and lightweight communication networks for their connected devices. What this Book will help me do Understand the underlying principles and protocol structure of MQTT. Securely configure and deploy an MQTT broker for communication. Develop Python, Java, and JavaScript-based MQTT client applications. Utilize MQTT for real-world IoT use cases such as sensor data interchange. Optimize MQTT usage for low-latency and lightweight communication scenarios. Author(s) Gastón C. Hillar is an experienced IoT developer and author with a deep understanding of IoT protocols and technologies. With years of practical experience in designing and deploying secure IoT systems, Gastón specializes in breaking down complex topics into digestible and actionable insights. Through his books, he aims to empower developers to effectively integrate IoT technologies into their work. Who is it for? The book is tailored for software developers and engineers who are looking to integrate MQTT into their IoT solutions. It's ideal for individuals with pre-existing knowledge in IoT concepts who want to deepen their understanding of MQTT. Readers seeking to secure, optimize, and utilize MQTT for communication and automation tasks will find it especially useful. It's a perfect fit for those working with Python, Java, and web technologies in IoT contexts.

Apache Hadoop is the technology at the heart of the Big Data revolution, and Hadoop skills are in enormous demand. Now, in just 24 lessons of one hour or less, you can learn all the skills and techniques you'll need to deploy each key component of a Hadoop platform in your local environment or in the cloud, building a fully functional Hadoop cluster and using it with real programs and datasets. Each short, easy lesson builds on all that's come before, helping you master all of Hadoop's essentials, and extend it to meet your unique challenges. Apache Hadoop in 24 Hours, Sams Teach Yourself covers all this, and much more: Understanding Hadoop and the Hadoop Distributed File System (HDFS) Importing data into Hadoop, and process it there Mastering basic MapReduce Java programming, and using advanced MapReduce API concepts Making the most of Apache Pig and Apache Hive Implementing and administering YARN Taking advantage of the full Hadoop ecosystem Managing Hadoop clusters with Apache Ambari Working with the Hadoop User Environment (HUE) Scaling, securing, and troubleshooting Hadoop environments Integrating Hadoop into the enterprise Deploying Hadoop in the cloud Getting started with Apache Spark Step-by-step 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 Hadoop to solve a wide spectrum of Big Data problems.