Elasticsearch 6 and Elastic Stack – In Depth and Hands On!

Elasticsearch 6 and Elastic Stack – In Depth and Hands On!, available at $44.99, has an average rating of 4.2, with 65 lectures, based on 2317 reviews, and has 12997 subscribers.

You will learn about Install and configure Elasticsearch 6 on a cluster Create search indices and mappings Search full-text and structured data in several different ways Import data into Elasticsearch using several different techniques Integrate Elasticsearch with other systems, such as Spark, Kafka, relational databases, S3, and more Aggregate structured data using buckets and metrics Use Logstash and the "ELK stack" to import streaming log data into Elasticsearch Use Filebeats and the Elastic Stack to import streaming data at scale Analyze and visualize data in Elasticsearch using Kibana Manage operations on production Elasticsearch clusters Use cloud-based solutions including Amazon's Elasticsearch Service and Elastic Cloud This course is ideal for individuals who are Any technologist who wants to add Elasticsearch to their toolchest for searching and analyzing big data sets. It is particularly useful for Any technologist who wants to add Elasticsearch to their toolchest for searching and analyzing big data sets.

Enroll now: Elasticsearch 6 and Elastic Stack – In Depth and Hands On!

Summary

Title: Elasticsearch 6 and Elastic Stack – In Depth and Hands On!

Price: $44.99

Average Rating: 4.2

Number of Lectures: 65

Number of Published Lectures: 64

Number of Curriculum Items: 65

Number of Published Curriculum Objects: 64

Original Price: $129.99

Quality Status: approved

Status: Live

What You Will Learn

Install and configure Elasticsearch 6 on a cluster
Create search indices and mappings
Search full-text and structured data in several different ways
Import data into Elasticsearch using several different techniques
Integrate Elasticsearch with other systems, such as Spark, Kafka, relational databases, S3, and more
Aggregate structured data using buckets and metrics
Use Logstash and the "ELK stack" to import streaming log data into Elasticsearch
Use Filebeats and the Elastic Stack to import streaming data at scale
Analyze and visualize data in Elasticsearch using Kibana
Manage operations on production Elasticsearch clusters
Use cloud-based solutions including Amazon's Elasticsearch Service and Elastic Cloud

Who Should Attend

Any technologist who wants to add Elasticsearch to their toolchest for searching and analyzing big data sets.

Target Audiences

Any technologist who wants to add Elasticsearch to their toolchest for searching and analyzing big data sets.

NOTE: A NEW VERSION OF THIS COURSE FOR ELASTICSEARCH 7 IS AVAILABLE. You should only enroll in this if you need to learn Elasticsearch 6 specifically. If that’s you, read on!

Elasticsearch�is a powerful tool not only for powering search on big websites, but also for analyzing big data sets in a matter of milliseconds! It’s an increasingly popular technology, and a valuable skill to have in today’s job market. This comprehensive course covers it all, from installation to operations, with 60 lectures including 8 hours of video.

We’ll cover setting up search indices on an Elasticsearch 6 cluster (if you need Elasticsearch 5 – we have another course on that), and querying that data in many different ways. Fuzzy searches, partial matches, search-as-you-type, pagination, sorting – you name it. And it’s not just theory, every lesson has hands-on examples where you’ll practice each skill using a virtual machine running Elasticsearch on your own PC.

We cover, in depth, the often-overlooked problem of importing data into an Elasticsearch index. Whether it’s via raw RESTful queries, scripts using Elasticsearch API’s, or integration with other “big data” systems like Spark and Kafka – you’ll see many ways to get Elasticsearch started from large, existing data sets at scale. We’ll also stream data into Elasticsearch using Logstash�and Filebeat – commonly referred to as the “ELK Stack” (Elasticsearch / Logstash / Kibana) or the “Elastic Stack“.

Elasticsearch isn’t just for search anymore – it has powerful aggregation�capabilities for structured data. We’ll bucket and analyze data using Elasticsearch, and visualize it using the Elastic Stack’s web UI, Kibana.

You’ll learn how to manage operations on your Elastic Stack, using X-Pack to monitor your cluster’s health, and how to perform operational tasks like scaling up your cluster, and doing rolling restarts. We’ll also spin up Elasticsearch clusters in the cloud using Amazon Elasticsearch Service and the Elastic Cloud.

Elasticsearch is positioning itself to be a much faster alternative to Hadoop, Spark, and Flink for many common data analysis requirements. It’s an important tool to understand, and it’s easy to use! Dive in with me and I’ll show you what it’s all about.

Course Curriculum

Chapter 1: Installing and Understanding Elasticsearch

Lecture 1: Udemy 101: Getting the Most From This Course

Lecture 2: Installing Elasticsearch [Step by Step]

Lecture 3: Elasticsearch Overview

Lecture 4: Intro to HTTP and RESTful API's

Lecture 5: Using Elasticsearch

Lecture 6: Elasticsearch Architecture

Lecture 7: Quiz: Elasticsearch Concepts and Architecture

Chapter 2: Mapping and Indexing Data

Lecture 1: Connecting to your Cluster

Lecture 2: Getting to Know the Movielens Data Set

Lecture 3: Create a Mapping for MovieLens

Lecture 4: Hacking CURL (Don't Skip This!)

Lecture 5: Import a Single Movie via JSON / REST

Lecture 6: Insert Many Movies at Once

Lecture 7: Updating Data in Elasticsearch

Lecture 8: Deleting Data in Elasticsearch

Lecture 9: [Exercise] Insert, Update, and Delete a Fictitious Movie

Lecture 10: Dealing with Concurrency

Lecture 11: Using Analyzers and Tokenizers

Lecture 12: Data Modeling with Elasticsearch

Chapter 3: Searching with Elasticsearch

Lecture 1: Using Query-String Search

Lecture 2: Using JSON Search

Lecture 3: Full-Text vs. Phrase Search

Lecture 4: [Exercise] Search for New Star Wars Films Two Different Ways

Lecture 5: Pagination

Lecture 6: Sorting

Lecture 7: Using Filters

Lecture 8: [Exercise] Search for Science Fiction Movies Before 1960, Sorted by Title

Lecture 9: Fuzzy Queries

Lecture 10: Partial Matching

Lecture 11: N-Grams, and Search as you Type

Chapter 4: Importing Data into Your Index – Big or Small

Lecture 1: Importing Data from Scripts

Lecture 2: [Exercise] Import Movie Tags Into a New Index with a Python Script.

Lecture 3: Logstash Overview

Lecture 4: Installing Logstash

Lecture 5: Importing Apache Access Logs with Logstash

Lecture 6: Importing Data from MySQL using Logstash

Lecture 7: Importing Data from AWS S3 using Logstash

Lecture 8: Integrating Kafka with Elasticsearch

Lecture 9: Integrating Spark and Hadoop with Elasticsearch

Lecture 10: [Exercise] Import Movie Ratings from Spark to Elasticsearch

Chapter 5: Aggregation

Lecture 1: Buckets and Metrics

Lecture 2: Histograms

Lecture 3: Aggregating Time Series Data

Lecture 4: [Exercise] When Did my Site Go Down?

Lecture 5: Nested Aggregations

Chapter 6: Using Kibana

Lecture 1: Installing Kibana

Lecture 2: Analyzing Shakespeare with Kibana

Lecture 3: [Exercise] Find the Shakespeare Plays with the Most Lines

Chapter 7: Analyzing Log Data with the Elastic Stack

Lecture 1: The ELK Stack and Elastic Stack

Lecture 2: Install, Configure, and Use Filebeat

Lecture 3: Analyzing Server Logs with Kibana

Lecture 4: [Exercise] Narrow Down the Source of 404 Errors

Chapter 8: Elasticsearch Operations

Lecture 1: How Many Shards Should I Use?

Lecture 2: Scaling with New Indices

Lecture 3: Choosing Your Hardware

Lecture 4: Heap Sizing

Lecture 5: Monitoring with X-Pack

Lecture 6: Practicing Failover

Lecture 7: Snapshots

Lecture 8: Rolling Restarts

Chapter 9: Elasticsearch in the Cloud

Lecture 1: Using Amazon Elasticsearch Service

Lecture 2: Using Elastic Cloud

Chapter 10: You Made It!

Lecture 1: I Made It! Now What?

Lecture 2: Bonus Lecture: Discounts to continue your journey!

Instructors

Sundog Education by Frank Kane
Join over 800K students learning ML, AI, AWS, and Data Eng.
Frank Kane
Ex-Amazon Sr. Engineer and Sr. Manager, CEO Sundog Education

Rating Distribution

1 stars: 29 votes
2 stars: 45 votes
3 stars: 204 votes
4 stars: 853 votes
5 stars: 1186 votes

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