Elasticsearch 7 and the Elastic Stack – In Depth & Hands On!

Elasticsearch 7 and the Elastic Stack – In Depth & Hands On!
Elasticsearch 7 and the Elastic Stack – In Depth & Hands On!
English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 12 Hours | 4.47 GB

Search, analyze, and visualize big data on a cluster with Elasticsearch, Logstash, Beats, Kibana, and more.

New for 2020! We’ve teamed up with Coralogix to co-produce the most comprehensive Elastic Stack course we’ve seen. Elasticsearch 7 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 course covers it all, from installation to operations, with over 100 lectures including 11 hours of video.

We’ll cover setting up search indices on an Elasticsearch 7 cluster (if you need Elasticsearch 5 or 6 – we have other courses 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’ll explore what’s new in Elasticsearch 7 – including index lifecycle management, the deprecation of types and type mappings, and a hands-on activity with Elasticsearch SQL. We’ve also added much more depth on managing security with the Elastic Stack, and how backpressure works with Beats.

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 and Kibana Lens.

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.

What you’ll learn

  • Install and configure Elasticsearch 7 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
Table of Contents

Installing and Understanding Elasticsearch
1 Udemy 101 Getting the Most From This Course
2 How Elasticsearch Scales
3 Quiz Elasticsearch Concepts and Architecture
4 Section 1 Wrapup
5 Section 1 Intro
6 Installing Elasticsearch [Step by Step]
7 Elasticsearch Overview
8 Intro to HTTP and RESTful API’s
9 Elasticsearch Basics Logical Concepts
10 Term Frequency Inverse Document Frequency (TFIDF)
11 Using Elasticsearch
12 What’s New in Elasticsearch 7

Mapping and Indexing Data
13 Section 2 Intro
14 Dealing with Concurrency
15 Using Analyzers and Tokenizers
16 Data Modeling and ParentChild Relationships, Part 1
17 Data Modeling and ParentChild Relationships, Part 2
18 Flattened Datatype
19 Dealing with Mapping Exceptions
20 Section 2 Wrapup
21 Connecting to your Cluster
22 Introducing the MovieLens Data Set
23 Analyzers
24 Import a Single Movie via JSON REST
25 Insert Many Movies at Once with the Bulk API
26 Updating Data in Elasticsearch
27 Deleting Data in Elasticsearch
28 [Exercise] Insert, Update and Delete a Movie

Searching with Elasticsearch
29 Section 3 Intro
30 Fuzzy Queries
31 Partial Matching
32 Query-time Search As You Type
33 N-Grams, Part 1
34 N-Grams, Part 2
35 Search as you Type Field Type
36 Section 3 Wrapup
37 Query Lite interface
38 JSON Search In-Depth
39 Phrase Matching
40 [Exercise] Querying in Different Ways
41 Pagination
42 Sorting
43 More with Filters
44 [Exercise] Using Filters

Importing Data into your Index – Big or Small
45 Section 4 Intro
46 Importing JSON Data with Logstash
47 Logstash and S3
48 Parsing and Filtering Logstash with Grok
49 Elasticsearch and Kafka, Part 1
50 Elasticsearch and Kafka, Part 2
51 Elasticsearch and Apache Spark, Part 1
52 Elasticsearch and Apache Spark, Part 2
53 [Exercise] Importing Data with Spark
54 Section 4 Wrapup
55 Importing Data with a Script
56 Importing with Client Libraries
57 [Exercise] Importing with a Script
58 Introducing Logstash
59 Installing Logstash
60 Running Logstash
61 Logstash and MySQL, Part 1
62 Logstash and MySQL, Part 2

Aggregation
63 Section 5 Intro
64 Aggregations, Buckets, and Metrics
65 Histograms
66 Time Series
67 [Exercise] Generating Histogram Data
68 Nested Aggregations, Part 1
69 Nested Aggregations, Part 2
70 Section 5 Wrapup

Using Kibana
71 Section 6 Intro
72 Installing Kibana
73 Playing with Kibana
74 [Exercise] Exploring Data with Kibana
75 Kibana Lens
76 Section 6 Wrapup

Analyzing Log Data with the Elastic Stack
77 Section 7 Intro
78 FileBeat and the Elastic Stack Architecture
79 X-Pack Security
80 Installing FileBeat
81 Analyzing Logs with Kibana Dashboards
82 [Exercise] Log analysis with Kibana
83 Section 7 Wrapup

Elasticsearch Operations and SQL Support
84 Section 8 Intro
85 Troubleshooting Common Issues
86 Failover in Action, Part 1
87 Failover in Action, Part 2
88 Index Design Changes (Grouping, Splitting, and Shrinking Indices)
89 Snapshots
90 Snapshot Lifecycle Management
91 Rolling Restarts
92 Search Profiling
93 Uptime Monitoring with Heartbeat
94 Section 8 Wrapup
95 Choosing the Right Number of Shards
96 Adding Indices as a Scaling Strategy
97 Index Alias Rotation
98 Index Lifecycle Management
99 Choosing your Cluster’s Hardware
100 Heap Sizing
101 Monitoring
102 Elasticsearch SQL

Elasticsearch in the Cloud
103 Section 9 Intro
104 Amazon Elasticsearch Service, Part 1
105 Amazon Elasticsearch Service, Part 2
106 The Elastic Cloud
107 Section 9 Wrapup

You Made It!
108 Wrapping Up
109 Bonus Lecture More Courses to Explore!