Discover the definitive guide to crafting lightning-fast data processing for distributed systems with Apach Flink(Apache Flink 的權威指南，一個面向分佈式系統的閃電般數據處理框架。)
Preface (前言)
With the advent of massive computer systems, organizations in different domains generate large amounts of data at a real-time basis. The latest entrant to big data processing, Apache Flink, is designed to process continuous streams of data at a lighting fast pace.
(隨着大規模計算機系統的出現，基本上在各個領域的組織都會生成大量的實時數據。而最後進行大數據處理的Apache Flink,旨在快速地處理連續數據流。）
This book will be your definitive guide to batch and stream data processing with Apache Flink. The book begins by introducing the Apache Flink ecosystem, setting it up and using the DataSet and DataStream API for processing batch and streaming datasets. Bringing the power of SQL to Flink, this book will then explore the Table API for querying and manipulating data. In the latter half of the book. readers will get to learn the remaining ecosvstem of Apache Flink to achieve complex tasks such as event processing, machine learning, and graph processing. The final part of the book would consist of topics such as scaling Flink solutions, performance optimization, and integrating Flink with other tools such as Hadoop, ElasticSearch, Cassandra, and Kafka.
（本書可以作爲Aapache Flink的權威指南。本書開始部分將介紹Apache Flink的生態系統。安裝和使用DataSet 和DataStream API 爲處理處理批處理和流數據集。賦予Flink SQL能力，本書將爲查詢和操作數據探索 Table API 。後半部分，讀者會學習Apache Flink生態系統的其餘部分。最後會包括一些Apache Flink解決方案的擴展主題，性能優化及Flink與其他工具的集成，比如 hahddop,elastic search,cassandra 和kafka。）
Whether you want to dive deeper into Apache Flink, or investigate how to get more out of this powerful technology, you'll find everything inside. This book covers a lot of real-world.use cases, which will help you connect the dots
（無論人想深入瞭解Apache Flink的內部原理，還是想研究如何從這個強大的技術中獲取更多知識，這本書可以滿足這一切。本書覆蓋了很多現實世界中的很多應用場景，這些將幫助你連接這些點。）
What this book covers（本書包含哪些內容？）
Chapter 1 Introduction to Apache Flink, introduces you to the history, architecture, features and installation of Apache Flink on single node and multinode clusters(第一章介紹Apache Flink，介紹它的歷史，架構，功能及單機的和集羣的安裝)
Chapte 2 Data Processing Usine the DataStream API ，provides you with the details of Flink's streaming first concept. You will learn details about data sources, transformation,and data sinks available with DataStream API(第二章 介紹使用DataStream API的數據處理，介紹Flink 流處理的第一個概念。你將瞭解data source，transformation及sinks結合DataStream API使用的細節)
Chapter 3, Data Processing Usine the Batch Processing APl, enlightens you with the batch processing API that is. DataSet API You will learn about data sources, transformations.and sinks. You will also leam about the connectors available with the API.(使用Batch Processing API進行數據處理。引導你使用批處理API,那就是DataSet API,你將學到data source,transformations 和sinks。你也會學到關於鏈接器結合這些API的使用)
Chapter 4, Data Processing Usine the Table API, helps you understand how to use SQL concepts with Flink data processing frameworks. You will also learn how to apply these concepts to the real-world use case.(使用Table API 的數據處理,有助於理解Flink數據處理框架的SQL概念。你還會學到怎樣將這些概念用到現實世界的使用場景中。)
Chapter 5, Complex Event Processing, provides insights to you on how to solve complex event processing problems using Flink CEP library. You will learn details about the pattern definition, detection, and alert generation(複雜事件處理 CEP，提供給你用flink cep 包解決複雜事件處理問題見解。你也將學到關於 pattern definition,detection及alert generation的相關細節。)
Chapter 6. Machine Learning Using Flink ML. covers details on machine learning concepts and how to apply various algorithms to the real-life use cases.(第六章.機器學習 覆蓋關於機器學習的詳細概念和如何將各位機器學習算法應用到現實生活中。)
Chapte 7, Flink Graph API- Gelly, introduces you to the graph concepts and what Flink Gelly offers us to solve real-life use cases. It enlightens you on iterative graph processing.capabilities provided by Flink（第7章 Flink圖API Gelly, 介紹圖相關的概念和Flink Gelly爲解決實際問題提供了什麼功能。）
Chapter 8. Distributed Data Processing Usine Flink and Hadoop, covers details on how to use existing Hadoop-YARN clusters to submit Flink jobs. It talks about how Flink works on YARN in detail（使用Flink和hadoop進行分佈式數據處理，覆蓋如何用現有的Hadoop-YARN集羣，提交Flink jobs。本章會討論Flink如何工作在Hadoop-YARN上的細節。 ）
Chapter 9, Deploying Flink on Cloud, provides details on how to deploy Flink on Cloud, It talks in detail about how to use Flink on Google Cloud and AWS.(在雲上部署Flink,向你提供怎樣在雲上部署flink 的細節，詳細討論Flink 如何如何工作在Google雲和AWS雲)
Chapter 10, Best Practices, covers various best practices developers should follow in order to use Flink in an efficient manner. It also talks about logging, monitoring best practices to control the Flink environment(最佳實踐，覆蓋多種開發者應該學習的最佳實踐，以後可以更有效的使用Flink.也討論關於日誌，監控控制Flink環境的最佳實踐。)