Elastic Stack from entry to practice
Chapter 1 Course Overview
Introduce the course as a whole and give relevant study instructions and suggestions
Chapter 2 Getting Started with Elasticsearch
This chapter will give a general introduction to the Elasticsearch chapter, so that you can have a preliminary understanding of the content to be explained in each chapter of this chapter. Then I will explain the common terms and apis in Elasticsearch, and then run Elasticsearch and actually feel how the api is called to prepare for the next course.
Chapter 3: Inverted Index and Word Segmentation in Elasticsearch
This chapter will explain the basic inverted index of search engines, so that everyone can have an intuitive understanding of the inverted index and master its composition. Then I will explain the relevant knowledge of word segmentation for you, introduce the built-in word segmentation device of es, and also introduce the common solutions of Chinese word segmentation.
Chapter 4 Mapping Settings in Elasticsearch
This chapter will explain the basis of data modeling in Elasticsearch - Mapping, that is, how to define data fields and types. Let everyone be familiar with the common configuration items in mapping, and also explain the related knowledge of dynamic mapping and template.
Chapter 5: Introduction to the Search API in Elasticsearch
This chapter will explain the search features, explain the composition and classification of the Search API in detail, and lead you to understand and master the usage methods and skills of the API one by one.
Chapter 6 Introduction to Distributed Features of Elasticsearch
This chapter will explain how to build an Elasticsearch cluster step by step, let you understand the role of different node types, the meaning of shard design, and how documents are stored on shards. It will also introduce you to problems such as split brain.
Chapter 7 Elasticsearch: Deep Understanding of the Operation Mechanism of Search
This chapter will explain in depth the operation mechanism of Search, such as the specific tasks of the Query and Fetch stages, and the problems that sharding brings to the correlation score. Solutions and related issues for sorting, paging, and traversal are also covered.
Chapter 8: Introduction to Aggregation Analysis in Elasticsearch
This chapter will introduce the functions of Elasticsearch aggregation analysis, let you understand its classification and composition, and lead you to understand and master the usage methods and skills of each aggregation API one by one, so as to lay a solid foundation for the subsequent use of Kibana.
Chapter 9 Data Modeling in Elasticsearch
This chapter will introduce the common problems of data modeling and optimization ideas and solutions that should be paid attention to when using Elasticsearch, so that you can set the most reasonable model according to your own business scenarios.
Chapter 10 Cluster Tuning Suggestions for Elasticsearch
This chapter will introduce the precautions for the construction and configuration of Elasticsearch cluster, and also explain the read and write performance optimization scheme and tuning method.
Chapter 11. Getting Started and Running Mechanism of Logstash
This chapter will introduce the role and usage of Logstash, let you understand its composition and operating mechanism, and lead you to actually operate Logstash to collect a log file.
Chapter 12: Logstash Plug-in Details
This chapter will introduce the functions and related configurations of Input, Filter, Ouput, and Codec plug-ins in detail, so that you can understand the usage scenarios and effects of common related plug-ins, and how to choose each plug-in reasonably to achieve your business needs.
Chapter 13 Example Analysis of Logstash
This chapter will demonstrate how to use Logstash to collect various types of data, such as log files, databases, tcp/udp, etc., in the form of examples.
Filebeat Chapter 14 Beats
This chapter will introduce the function and composition of Beats, and then introduce the functions and common configurations of Filebeat in detail. At the same time, it will explain in detail how to use the Module module to quickly complete the log collection and analysis.
Chapter 15 Beats - Metricbeat
This chapter will introduce the functions and usage skills of Metricbeat, so that you can have an intuitive feeling about the use of Metricbeat.
Chapter 16: Packetbeat of Beats
This chapter will introduce the functions and usage skills of Packetbeat, and lead you to use Packetbeat to collect and analyze network data, so that you can have an intuitive feeling about Packetbeat.
Chapter 17 Beats, Other Beats
This chapter will introduce the functions and application scenarios of many other beats, and lead you to discover a variety of beats provided by the community to meet the needs of daily business development.
Chapter 18 Introduction and Management of Kibana
This chapter will introduce the introductory knowledge of Kibana, so that everyone can have an overall understanding of Kibana, and will also introduce the functions of Management in detail, and be familiar with the configuration of Kibana.
Chapter 19: Data Exploration Discovery in Kibana
This chapter will introduce the data exploration function of Kibana, so that you can understand the functions and usage skills of Discovery.
Chapter 20 Visual Analysis of Kibana
This chapter will introduce the visual analysis function of Kibana. First, it will lead you to operate each chart provided by Kibana one by one, and will introduce the time series analysis tool Timelion, and then introduce how to use the Dashboard function to integrate the charts and then tell stories or make reports. Problems and skills to pay attention to when using Dashboard. ...
Chapter 21 Search Items in Practice
This chapter will explain a practical project related to search engines, and guide you to quickly build a system with common search functions based on the Elastic Stack by writing a small amount of code, such as the Airbnb-like SouFun system, Douban Movies, etc.
Chapter 22 Log Analysis Project in Practice
This chapter will show you how to use the Elastic Stack to quickly analyze log data based on the logs of MOOC, and lead you to complete the steps of data collection, processing, storage and visual analysis step by step, and finally create your own Dashboard.
Chapter 23 Data Analysis Projects in Practice
This chapter will show you how to use the Elastic Stack to analyze the data around you, such as air quality analysis, order data analysis, etc., so that you can quickly apply the Elastic Stack to real life through the learning in this chapter.
Chapter 24 Course Summary
This chapter will summarize the content of this course for you, sort out the knowledge points of Elastic Stack again, and provide some suggestions and ideas for your next advanced study.
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