В этой книге рассказывается о разных темах, в том числе о сетях данных в памяти, высокодоступной сетке сервисов, потоковой передаче (обработка событий для IoT и быстрых данных) и использования высокопроизводительных вычислений для повышения производительности с помощью Apache Ignite в вычислительной памяти.
This book covers a verity of topics, including in-memory data grid, highly available service grid, streaming (event processing for IoT and fast data) and in-memory computing use cases from high-performance computing to get performance gains. The book will be particularly useful for those, who have the following use cases:
You have a high volume of ACID transactions in your system. You have database bottleneck in your application and want to solve the problem. You want to develop and deploy Microservices in a distributed fashion. You have an existing Hadoop ecosystem (OLAP) and want to improve the performance of map/reduce jobs without making any changes in your existing map/reduce jobs. You want to share Spark RDD directly in-memory (without storing the state into the disk) You are planning to process continuous never-ending streams and complex events of data. You want to use distributed computations in parallel fashion to gain high performance.
What you will learn:
In-memory data fabrics use-cases and how it can help you to develop near real-time applications. In-memory data fabrics detail architecture. Caching strategies and how to use In-memory caching to improve the performance of the applications. SQL grid for in-memory caches. How to accelerates the performance of your existing Hadoop ecosystem without changing any code. Sharing Spark RDD states between different Spark applications for improving performance. Processing events & streaming data, integrate Apache Ignite with other frameworks like Storm, Camel, etc. Using distributed computing for building low-latency software. Developing distributed Microservices in fault-tolerant fashion.
For every topic, a complete application is delivered, which will help the audience to quick start with the topic. The book is a project-based guide, where each chapter focuses on the complete implementation of a real-world scenario, the commonly occurring challenges in each scenario have also discussed, along with tips and tricks and best practices on how to overcome them. Every chapter is independent and a complete project.
The target audience of this book will be IT architect, team leaders, a programmer with minimum programming knowledge, who want to get the maximum performance from their applications.
No excessive knowledge is required, though it would be good to be familiar with JAVA and Spring framework. The book is also useful for any reader, who already familiar with Oracle Coherence, Hazelcast, Infinispan or memcached.
Key FeaturesSet up real-time streaming and batch data intensive infrastructure using Spark and PythonDeliver insightful visualizations in a web app using Spark (PySpark)Inject live data using Spark Streaming with real-time eventsBook Description
In this fast-paced book on the Docker open standards platform for developing, packaging and running portable distributed applications, Deepak Vorhadiscusses how to build, ship and run applications on any platform such as a PC, the cloud, data center or a virtual machine. He describes how to install and create Docker images. and the advantages off ...
Starting with the basics of parallel programming, you will proceed to learn about how to build parallel algorithms and their implementation. You will then gain the expertise to evaluate problem domains, identify if a particular problem can be parallelized, and how to use the Threading and Multiprocessor modules in Python.
Powerful smart applications using deep learning algorithms to dominate numerical computing, deep learning, and functional programming. Machine learning has had a huge impact on academia and industry by turning data into actionable information. Scala has seen a steady rise in adoption over the past few years, especially in the fields of data science ...
Данный материал НЕ НАРУШАЕТ авторские права никаких физических или юридических лиц. Если это не так - свяжитесь с администрацией сайта. Материал будет немедленно удален. Электронная версия этой публикации предоставляется только в ознакомительных целях. Для дальнейшего её использования Вам необходимо будет приобрести бумажный (электронный, аудио) вариант у правообладателей.
Название: 
Распечатать
