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Advanced Elasticsearch 7.0

You're reading from  Advanced Elasticsearch 7.0

Product type Book
Published in Aug 2019
Publisher Packt
ISBN-13 9781789957754
Pages 560 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Wai Tak Wong Wai Tak Wong
Profile icon Wai Tak Wong
LinkedIn
Wai Tak Wong is a faculty member in the Department of Computer Science at Kean University, NJ, USA. He has more than 15 years professional experience in cloud software design and development. His PhD in computer science was obtained at NJIT, NJ, USA. Wai Tak has served as an associate professor in the Information Management Department of Chung Hua University, Taiwan. A co-founder of Shanghai Shellshellfish Information Technology, Wai Tak acted as the Chief Scientist of the R&D team, and he has published more than a dozen algorithms in prestigious journals and conferences. Wai Tak began his search and analytics technology career with Elasticsearch in the real estate market and later applied this to data management and FinTech data services.
See other products by Wai Tak Wong

Table of Contents (25) Chapters

Preface Section 1: Fundamentals and Core APIs
Overview of Elasticsearch 7 Index APIs Document APIs Mapping APIs Anatomy of an Analyzer Search APIs Section 2: Data Modeling, Aggregations Framework, Pipeline, and Data Analytics
Modeling Your Data in the Real World Aggregation Frameworks Preprocessing Documents in Ingest Pipelines Using Elasticsearch for Exploratory Data Analysis Section 3: Programming with the Elasticsearch Client
Elasticsearch from Java Programming Elasticsearch from Python Programming Section 4: Elastic Stack
Using Kibana, Logstash, and Beats Working with Elasticsearch SQL Working with Elasticsearch Analysis Plugins Section 5: Advanced Features
Machine Learning with Elasticsearch Spark and Elasticsearch for Real-Time Analytics Building Analytics RESTful Services Other Books You May Enjoy

Overview of ES-Hadoop

As we mentioned, the ES-Hadoop feature contains two major areas: distributed computing and distributed storage. The main goal of ES-Hadoop is to seamlessly connect Elasticsearch and Hadoop so that they can benefit each other with distributed computing, distributed storage, searching, analytics, visualization, and more. We can import Hadoop Distributed File System (HDFS) data to Elasticsearch for search and analysis, and export the Elastisearch data to HDFS for snapshot and restore. ES-Hadoop fully supports the Spark framework, including Spark, Hive, Pig, Storm, Cascading, and sure, the standard MapReduce. Let's take a look at the data flow between Elasticsearch, ES-Hadoop, and components in the Hadoop ecosystem, as shown in the following screenshot:

In short, we can think of ES-Hadoop as a data bridge between Elasticsearch and the Hadoop big data ecosystem...

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Authors (1)

Profile icon Wai Tak Wong
LinkedIn
Wai Tak Wong is a faculty member in the Department of Computer Science at Kean University, NJ, USA. He has more than 15 years professional experience in cloud software design and development. His PhD in computer science was obtained at NJIT, NJ, USA. Wai Tak has served as an associate professor in the Information Management Department of Chung Hua University, Taiwan. A co-founder of Shanghai Shellshellfish Information Technology, Wai Tak acted as the Chief Scientist of the R&D team, and he has published more than a dozen algorithms in prestigious journals and conferences. Wai Tak began his search and analytics technology career with Elasticsearch in the real estate market and later applied this to data management and FinTech data services.
Read more
See other products by Wai Tak Wong

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