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Spark 2.x ecosystem, followed by explaining how to install and configure Spark, and refreshes the Java concepts that will be useful to you when;
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Learning library Who This Book Is For Programmers and developers active in big data, Hadoop, and Java but who are new to the Apache Spark;
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hassle. This Learning Path includes content from the following Packt products: Mastering Apache Spark 2.x by Romeo Kienzler Scala and Spark for;
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/Docker for cloud-based Spark. During the course of the book, you will learn about the latest enhancements to Apache Spark 2.x, such as;
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, Spark 2.x delivers notable improvements in the areas of API, schema awareness, Performance, Structured Streaming, and simplifying building;
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Apache Tomcat is the most popular open-source de-facto Java Web application server, standard for today's Web developers using JSP/Servlets;
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infrastructure investment, and Spark's core abstractions are intuitive for most Scala, Java, and Python developers. Spark in Action;
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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;
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Stanbol How-to is for Java developers who would like to extend Stanbol or would just like to use Stanbol without caring about its internals. A few;
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optimized for Java and XML development. * Is ideal for most professional level Java developers who typically need and use build tools;
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Struts 2 Web Framework, an essentially new and improved Struts platform that should meet today's more agile Java development needs. Apache Struts;
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is forMastering Apache Cassandra 3.x is for you if you are a big data administrator, database administrator, architect, or developer who wants to build a;
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you if you are a Python developer looking for hands-on recipes for using the Apache Spark 2.x ecosystem in the best possible way. A thorough;
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for Java developers who are new to Apache Camel and message- oriented applications.;
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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;
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As the majority of Java developers are only Web-tier developers; Java technologies like JavaServer Pages (JSP), JavaServer Faces (JSF), and;
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efficient distributed data processing engine inside of Apache Spark; its user-friendly, comprehensive, and flexible programming model for processing;
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in comparison to Java, and how Scala is related to Apache Spark for big data analytics. Next, you'll set up the Scala environment ready for examining;
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A practical guide for solving complex data processing challenges by applying the best optimizations techniques in Apache Spark. Key;
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This book will save Java developers countless hours of development time by providing seven complete Ajax applications to learn from and;
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a 3-tiered, Model-View-Controller architecture by using Hibernate, JSPs, and Java Servlets. This book uses existing powerful technologies;
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in Python, Java, and Scala. Written by the developers of Spark, this book will have data scientists and engineers up and running in no time. You'll;
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book provides recipes that are based on the latest versions of Apache Hadoop 2.X, YARN, Hive, Pig, Sqoop, Flume, Apache Spark, Mahout and many;
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simple applications. This book is a good starting point for Java developers who have to work on an application dealing with various systems and;
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express train to productivity for every Java developer who has dreamed of developing for Mac OS X or iPhone, but felt that Objective-C was too;
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This volume delivers a complete and detailed look at the Mac OS X platform, geared specifically at Java developers. Programmers using the;
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workloads and even near real-time processing of streaming data. Spark fits well as a central foundation for any data engineering workload. This book;
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