图灵程序设计丛书:大规模数据处理入门与实战(套装全10册 Kafka权威指南 Flink基础教程 数据科学实战 SQL反模式 SQL必知必会(第4版) Spark快速大数据分析 数据科学入门 Python数据挖掘入门与实践 Hadoop安全:大数据平台隐私保护 Hadoop数据分析)

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 Meet Kafka -- Installing Kafka -- Kafka Producers : Writing Messages To Kafka -- Kafka Consumers : Reading Data From Kafka -- Kafka Internals -- Reliable Data Delivery -- Building Data Pipelines -- Cross-cluster Data Mirroring -- Administering Kafka -- Monitoring Kafka -- Stream Processing. Neha Narkhede, Gwen Shapira, Todd Palino. Includes Index. Ben shu fen wei 6 zhang,Ce zhong yu jie shao Flink de he xin she ji li nian,Gong neng he yong tu,Nei rong she ji shi jian shi jian he chu li shi jian,Chuang kou he shui yin ji zhi,Jian cha dian ji zhi,Xing neng ce ping,Yi ji Flink ru he shi xian pi chu li 作为新一代的开源流处理器,Flink是众多大数据处理框架中一颗冉冉升起的新星。它以同一种技术支持流处理和批处理,并能同时满足高吞吐、低延迟和容错的需求。本书由Flink项目核心成员执笔,系统阐释Flink的适用场景、设计理念、功能、用途和性能优势。 Flink的适用场景 流处理架构相较于批处理架构的优势 Flink中的时间概念 Flink的检查点机制 Flink的性能优势 **Revision History for the First Edition** - 2017-07-07: First Release - 2017-10-13: Second Release - 2018-03-30: Third Release - 2019-08-09: Fourth Release