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 Anthony?is 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: Whats 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

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

Frequently Asked Questions

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