Ali experts finally fully understand the "big data + Netty + distributed combat"

One, Hadoop actual combat

Hadoop is an open source distributed computing platform under the Apache Software Foundation. Hadoop with Hadoop Distributed Filesystem (HDFS, Hadoop Distributed Filesystem) and MapReduce (open source implementation of Google MapReduce) as its core provides users with a distributed infrastructure with transparent underlying details of the system. The high fault tolerance and high scalability of HDFS allow users to deploy Hadoop on low-cost hardware to form a distributed system;

The MapReduce distributed programming model allows users to develop parallel applications without understanding the underlying details of the distributed system. Therefore, users can use Hadoop to easily organize computer resources to build their own distributed computing platform, and can make full use of the computing and storage capabilities of the cluster to complete the processing of massive data.

And this book is a systematic and practical Hadoop reference book and reference book. Comprehensive content, a comprehensive explanation of the entire Hadoop technology system, including not only the two core contents of HDFS and MapReduce, but also the contents of Hive, HBase, Mahout, Pig, ZooKeeper, Avro, Chukwa and other Hadoop-related sub-projects . Strong practicality, a large number of classic small cases are carefully designed for each knowledge point, easy to understand, and strong maneuverability.

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table of Contents

• Introduction to Haoop
• Hadoop installation and configuration
• Haoop application case analysis
• MapReduce calculation model
• Develop MapReduce applications
• MapRe duce application case
• MapRe duce. working mechanism
• Hadoop I/0 operations
• Detailed HDFS
• Hadoop management
• Hive in detail
• HBase detailed
• Mahout explained
• Pig detailed
• Zooeeper detailed
• Avro detailed
• Chulkv a detailed explanation
• Common plug-ins and development of Hadoop

 

 

Second, Spark big data analysis actual combat

Spark big data technology is still developing in full swing, the Spark China Summit is held, and meetups are held in various places. The open source software Spark has also risen, and many companies have already implemented and applied Spark on a large scale. The needs of Spark users have gone from the initial deployment, installation, and running of examples, to the growing need to build rich data analysis applications through Spark. Writing a technical book on Spark practical cases is an idea that has lasted for a long time. Due to the tight work, I only summarized the Spark related cases that I participated in or learned at first, but as time goes on, I finally plan to abstract the general algorithms, system architecture and application scenarios and simplify them appropriately. A kind of summary and sharing.

table of Contents

• Introduction to Spark
• Spark development and environment configuration program
• Introduction to BDAS
• Lamda architecture log analysis pipeline
• Recommendation system based on cloud platform and user logs
• Twitter sentiment analysis
• Hot News Analysis System
• Build a distributed collaborative filtering recommendation system
• Social network analysis based on Sparl
• Large-scale news topic analysis based on Spark
• Build a distributed search engine

 

 

Three, Hbase

HBase is a NoSQL storage system, specifically designed to quickly and randomly read and write large-scale data. HBase runs on ordinary commercial servers and can scale smoothly to support data sets ranging from medium-scale to billions of rows and millions of columns. .

This book is a guide based on experience. It teaches readers how to use HBase to design, build and run big data application systems. The book is divided into 4 parts. The first two parts introduce the development history of distributed systems and large-scale data processing, explain the basic principle of HBase model design and how to use the advanced features of HBase; the third part uses real applications and code examples and support these practical skills Theoretical knowledge, to further explore some practical technologies of HBase; The fourth part explains how to upgrade the prototype development system to a full-fledged production system.

table of Contents

The first part of HBase basics

1. Introduction to HBase
2. getting Started
3. Distributed Base, HDFS and MapReduce

The second part of advanced concepts

1. HBase table design
2. Use coprocessor to extend iBase
3. Other HBase client options

The third part of the application system examples

1. Learn HBase through examples: OpenTSDB
2. Query geographic information system on HBase

The fourth part makes HBase work

1. Deploy IBase
2. Operation and maintenance

 

 

Fourth, the principle, design and actual combat of distributed service architecture

This book takes the current popular distributed service architecture as the main line and explains the principle, design and practice of the distributed service architecture.

This book first introduces the background and evolution of the distributed service architecture, and then elaborates on the design ideas and implementable schemes to ensure the consistency, high performance, and high availability of distributed services; then it introduces the large-scale and high-availability design ideas. The emergency process and technical tackling process of concurrent online services, and an effective and commonly used tool set for discovering and locating problems; finally, it introduces the containerized process analysis, agile development and online tools in the distributed service architecture in detail. Convenience provided by developers of high-concurrency service architecture

table of Contents

• Principles of Distributed Microservice Architecture Design
• Thoroughly solve the problem of distributed system consistency
• Servicing system capacity assessment and performance guarantee
• Construction of Big Data Logging System
• Design and Implementation of Service Management System Based on Call Chain
• Online emergency and technical research of Java services
• Service containerization process
• Automated tools for agile development 2.

 

 

Five, Netty actual combat principle

Netty is a Java framework for rapid development of high-performance network applications. It encapsulates the complexity of network programming, so that the latest developments in network programming and Web technology can be accessed by a wider range of developers than ever before. Netty is not just a collection of interfaces and classes; it also defines an architectural model and a rich set of design patterns. But until now, there is still a lack of a comprehensive and systematic user guide, which has become an obstacle to getting started with Netty. This situation is what this book aims to change. In addition to explaining the components of the framework and detailed information about the API, this book will also show how Netty can help developers write more efficient, reusable, and maintainable code.

table of Contents

The first part of the concept and architecture of Netty

1. Netty--asynchronous and event-driven
2. Your first Hetty app
3. Netty components and design
4. transmission
5. ByteBuf
6. ChannelHandler和 ChannelPipeline
7. EventLoop and thread model
8. guide
9. unit test

The second part of the codec

1. Codec framework
2. Pre-built ChannelHandler and codec

The third part of the network protocol

1. WebSocket
2. Broadcast events using VDP

Part Four Case Study

1. Case study, part one
2. Case study, part two

 

 

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