- Elasticsearch Essentials
- Bharvi Dixit
- 137字
- 2021-07-16 09:33:16
Chapter 2. Understanding Document Analysis and Creating Mappings
Search is hard, and it becomes harder when both speed and relevancy are required together. There are lots of configurable options Elasticsearch provides out-of-the-box to take control before you start putting the data into it. Elasticsearch is schemaless. I gave a brief idea in the previous chapter of why it is not completely schemaless and how it creates a schema right after indexing the very first document for all the fields existing in that document. However, the schema matters a lot for a better and more relevant search. Equally important is understanding the theory behind the phases of document indexing and search.
In this chapter, we will cover the following topics:
- Full text search and inverted indices
- Document analysis
- Introducing Lucene analyzers
- Creating custom analyzers
- Elasticsearch mappings
推薦閱讀
- AngularJS Testing Cookbook
- 控糖控脂健康餐
- Learning Data Mining with Python
- R語言數據可視化實戰
- INSTANT Weka How-to
- Access 2010數據庫基礎與應用項目式教程(第3版)
- 嚴密系統設計:方法、趨勢與挑戰
- jQuery Mobile移動應用開發實戰(第3版)
- C語言程序設計實驗指導 (第2版)
- Spring Boot+MVC實戰指南
- MINECRAFT編程:使用Python語言玩轉我的世界
- 人工智能算法(卷1):基礎算法
- PHP+MySQL動態網站開發從入門到精通(視頻教學版)
- JavaScript編程精解(原書第2版)
- FusionCharts Beginner’s Guide:The Official Guide for FusionCharts Suite