Learning Path: The Road to Elasticsearch
Learning Path: The Road to Elasticsearch, available at $19.99, has an average rating of 3.2, with 60 lectures, based on 10 reviews, and has 100 subscribers.
You will learn about All about the Elastic stack, its major components, their use cases, the installation process Basic usage of each major component, and its purpose Success stories for customers by implementing the Elastic stack Develop a complete data pipeline using the Elastic stack Core fundamentals and concepts of Elasticsearch Use RESTful API to interact with data stored in Elasticsearch Learn to use the Elasticsearch domain-specific language to formulate complex queries for enabling fast searches Use Elasticsearch with Logstash and Kibana in greater detail How to perform a full analysis on Apache web logs, with Elasticsearch, Logstash, and Kibana Learn the differences between Apache Solr and Elasticsearch This course is ideal for individuals who are Any web developer interested in getting started with Elasticsearch seriously, in a big way, by first comprehensively understanding the basics, with an intention of using Elasticsearch heavily in the future. It is particularly useful for Any web developer interested in getting started with Elasticsearch seriously, in a big way, by first comprehensively understanding the basics, with an intention of using Elasticsearch heavily in the future.
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Summary
Title: Learning Path: The Road to Elasticsearch
Price: $19.99
Average Rating: 3.2
Number of Lectures: 60
Number of Published Lectures: 60
Number of Curriculum Items: 60
Number of Published Curriculum Objects: 60
Original Price: $199.99
Quality Status: approved
Status: Live
What You Will Learn
- All about the Elastic stack, its major components, their use cases, the installation process
- Basic usage of each major component, and its purpose
- Success stories for customers by implementing the Elastic stack
- Develop a complete data pipeline using the Elastic stack
- Core fundamentals and concepts of Elasticsearch
- Use RESTful API to interact with data stored in Elasticsearch
- Learn to use the Elasticsearch domain-specific language to formulate complex queries for enabling fast searches
- Use Elasticsearch with Logstash and Kibana in greater detail
- How to perform a full analysis on Apache web logs, with Elasticsearch, Logstash, and Kibana
- Learn the differences between Apache Solr and Elasticsearch
Who Should Attend
- Any web developer interested in getting started with Elasticsearch seriously, in a big way, by first comprehensively understanding the basics, with an intention of using Elasticsearch heavily in the future.
Target Audiences
- Any web developer interested in getting started with Elasticsearch seriously, in a big way, by first comprehensively understanding the basics, with an intention of using Elasticsearch heavily in the future.
Ever wanted to take your web application to a whole new level? Well then, look no further, because this Learning Path takes you on a journey to learning all about Elasticsearch, the renowned open source search engine that helps power searches within thousands of websites worldwide, and much more.
Elasticsearch is part of the Elastic family, popularly called as the Elastic stack, whose other components include Logstash, Kibana, the Beats family, and X-Pack.
Together, the Elastic stack forms an essential suite of tools that is a must for any developer wanting to embark on a path to build high-quality web applications in this day and age. Elasticsearch is a search server that can also double up as a NoSQL data store, and hence provides lightning-fast search functionality within a website. Logstash is used to collect and parse all kinds of logs. It can also be used to ferry data to and from Elasticsearch at high speeds. Kibana is an Elasticsearch data visualization tool, Beats help in gathering data from disparate sources to Elasticsearch, while X-Pack provides services such as security, monitoring, alerting, reporting, and so on.
The Road to Elasticsearch is Packt’s Video Learning Path that is a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it.
First, this learning path gets you acquainted with the new, Elastic stack. You learn all about the key components of the Elastic family, their usage and their significance. Then, we move on to a more detailed topic in which we learn in depth about the new Elasticsearch 5.0, which is the mainstay of the stack. We begin by learning about the fundamentals of Elasticsearch. Here, we learn how data is stored in Elasticsearch, specifically, concepts like index, types, and documents, and are also introduced to the Elasticsearch domain-specific language (DSL). Finally, we learn to create complex search queries that power advanced search features in top websites.
By the end of this Learning Path , you will have developed a mastery of Elasticsearch fundamentals, and would be able to seamlessly harness the power of Elasticsearch to augment the capability of your web apps.
The goal of this Learning Path is to equip you with strong fundamentals of Elasticsearch and introduce you to the Elastic stack.
This Learning Path is authored by some of the best in the field.
Ethan Anthonyis a San Francisco-based data scientist who specializes in distributed data-centric technologies, and is also the founder of XResults, a data analytics company. Ethan has over 10 combined years of experience in cloud-based technologies such as Amazon Web Services and OpenStack, as well as the data-centric technologies of Hadoop, Mahout, Spark, and Elasticsearch. He began using Elasticsearch in 2011 and has since delivered solutions based on the Elastic stack to a broad range of clientele.
Karthik Selvaraj is an integration specialist having vast experience in areas of enterprise application integration, service-oriented architecture, and API economy. He is a YouTuber and has several training videos on his YouTube channel. His technology stack includes IBM DataPower Gateway, IBM WebSphere MQ, Mule ESB, Elastic stack, Active MQ, and IBM Integration Bus.
Course Curriculum
Chapter 1: Getting Started with Elastic Stack
Lecture 1: The Course Overview
Lecture 2: The Elastic Family
Lecture 3: Making Sense of Your Data
Lecture 4: Installing and Starting Elasticsearch
Lecture 5: Installing and Starting Logstash and Kibana
Lecture 6: Basic Concepts of Elasticsearch
Lecture 7: Elasticsearch APIs
Lecture 8: Query DSL and Mapping
Lecture 9: Aggregations Using Elasticsearch
Lecture 10: Elasticsearch Analyzers
Lecture 11: Scripting in Elasticsearch
Lecture 12: Stashing with Logstash
Lecture 13: Logstash Plugins
Lecture 14: APIs for Logstash
Lecture 15: Building Kibana Interface
Lecture 16: Visualizing Data with Kibana
Lecture 17: Building Dashboards with Kibana
Lecture 18: Featuring Kibana 5
Lecture 19: Configuring Logstash Input
Lecture 20: Filtering and Processing Input
Lecture 21: Loading Data to Elasticsearch
Lecture 22: Discover Using Kibana
Lecture 23: Netflix
Lecture 24: Salesforce
Lecture 25: Orange and Tango
Chapter 2: Learning Elasticsearch 5.0
Lecture 1: The Course Overview
Lecture 2: What Is ElasticSearch?
Lecture 3: Installing ElasticSearch
Lecture 4: Goal of ElasticSearch
Lecture 5: What's New in Version 5.0?
Lecture 6: Why Use ElasticSearch?
Lecture 7: What Is an Index?
Lecture 8: Documents in ElasticSearch
Lecture 9: What Is a Cluster?
Lecture 10: Setting Shards and Replicas
Lecture 11: Adding and Deleting an Index
Lecture 12: Adding and Deleting Documents
Lecture 13: Using Bulk API
Lecture 14: Introduction to REST API
Lecture 15: Using REST API to Search
Lecture 16: Using REST API to Update
Lecture 17: Introduction to DSL
Lecture 18: Understanding DSL
Lecture 19: Term Queries and Boosting
Lecture 20: Range Query
Lecture 21: Exist Query
Lecture 22: Aggregation Based Analytics
Lecture 23: Aggregations: Implementation
Lecture 24: Myths about ElasticSearch
Lecture 25: What Is ElasticStack?
Lecture 26: Kibana
Lecture 27: Logstash
Lecture 28: X-Pack
Lecture 29: Beats
Lecture 30: Preparing for Log Analysis
Lecture 31: Running Log Analysis
Lecture 32: Sorting in ElasticSearch
Lecture 33: Geo Searching
Lecture 34: Getting into Synonyms
Lecture 35: Choosing between ElasticSearch and Apache Solr
Instructors
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Packt Publishing
Tech Knowledge in Motion
Rating Distribution
- 1 stars: 2 votes
- 2 stars: 2 votes
- 3 stars: 1 votes
- 4 stars: 3 votes
- 5 stars: 2 votes
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