Elasticsearch 7 And The Elastic Stack Training 2022

Published 6/2022
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 4.52 GB | Duration: 16h 29m

Complete Elastic search tutorial – search, analyze, and visualize big data with Elasticsearch, Kibana, Logstash, & Beats
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 various 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
Requirements
You need access to a Windows, Mac, or Ubuntu PC with 20GB of free disk space
You should have some familiarity with web services and REST
Some familiarity with Linux will be helpful
Exposure to JSON-formatted data will help
Description
THERE IS AN UPDATED VERSION OF THIS COURSE AVAILABLE! Please search for "Elasticsearch 8 and the Elastic Stack" unless you specifically need to learn Elasticsearch 7.——————–Elasticsearch and the Elastic Stack are important tools for managing massive data. You need to know the problems it solves and how it works to design the best systems, and be the most valuable engineer you can be.Elasticsearch 7 is a powerful tool for analyzing big data sets in a matter of milliseconds! It’s increasingly popular technology for powering search and analytics on big websites, and a valuable skill to have in today’s job market. This course covers it all, from installation to operations. Learn how to use Elasticsearch 7 and implement it in your work within the next few days.We’ve teamed up with Coralogix to co-produce the most comprehensive Elastic Stack course we’ve seen- with over 100 lectures including 16 hours of video.We’ll show you how to set up search indices on an Elasticsearch 7 cluster (if you need Elasticsearch 6 or 8 – we have other courses on that), and query 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, which allows you to glean new insights from your indexed 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.
Overview
Section 1: Installing and Understanding Elasticsearch
Lecture 1 Udemy 101: Getting the Most From This Course
Lecture 2 Section 1 Intro
Lecture 3 Installing Elasticsearch[Step by Step]
Lecture 4 Elasticsearch Overview
Lecture 5 Intro to HTTP and RESTful API’s
Lecture 6 Elasticsearch Basics: Logical Concepts
Lecture 7 Term Frequency / Inverse Document Frequency (TF/IDF)
Lecture 8 Using Elasticsearch
Lecture 9 What’s New in Elasticsearch 7
Lecture 10 How Elasticsearch Scales
Lecture 11 Quiz: Elasticsearch Concepts and Architecture
Lecture 12 Section 1 Wrapup
Section 2: Mapping and Indexing Data
Lecture 13 Section 2 Intro
Lecture 14 Connecting to your Cluster
Lecture 15 Note: alternate download location for the MovieLens data set
Lecture 16 Introducing the MovieLens Data Set
Lecture 17 Analyzers
Lecture 18 Import a Single Movie via JSON / REST
Lecture 19 Insert Many Movies at Once with the Bulk API
Lecture 20 Updating Data in Elasticsearch
Lecture 21 Deleting Data in Elasticsearch
Lecture 22[Exercise] Insert, Update and Delete a Movie
Lecture 23 Dealing with Concurrency
Lecture 24 Using Analyzers and Tokenizers
Lecture 25 Data Modeling and Parent/Child Relationships, Part 1
Lecture 26 Data Modeling and Parent/Child Relationships, Part 2
Lecture 27 Flattened Datatype
Lecture 28 Dealing with Mapping Exceptions
Lecture 29 Section 2 Wrapup
Section 3: Searching with Elasticsearch
Lecture 30 Section 3 Intro
Lecture 31 "Query Lite" interface
Lecture 32 JSON Search In-Depth
Lecture 33 Phrase Matching
Lecture 34[Exercise] Querying in Different Ways
Lecture 35 Pagination
Lecture 36 Sorting
Lecture 37 More with Filters
Lecture 38[Exercise] Using Filters
Lecture 39 Fuzzy Queries
Lecture 40 Partial Matching
Lecture 41 Query-time Search As You Type
Lecture 42 N-Grams, Part 1
Lecture 43 N-Grams, Part 2
Lecture 44 "Search as you Type" Field Type
Lecture 45 Section 3 Wrapup
Section 4: Importing Data into your Index – Big or Small
Lecture 46 Section 4 Intro
Lecture 47 Importing Data with a Script
Lecture 48 Importing with Client Libraries
Lecture 49[Exercise] Importing with a Script
Lecture 50 Introducing Logstash
Lecture 51 Installing Logstash
Lecture 52 Running Logstash
Lecture 53 ERRATA for following lecture
Lecture 54 Logstash and MySQL, Part 1
Lecture 55 Logstash and MySQL, Part 2
Lecture 56 Importing CSV Data with Logstash
Lecture 57 Importing JSON Data with Logstash
Lecture 58 Logstash and S3
Lecture 59 Parsing and Filtering Logstash with Grok
Lecture 60 Logstash Grok Examples for Common Log Formats
Lecture 61 Logstash Input Plugins, Part 1: Heartbeat
Lecture 62 Logstash Input Plugins, Part 2: Generator Input and Dead Letter Queue
Lecture 63 Logstash Input Plugins, Part 3: HTTP Poller
Lecture 64 Logstash Input Plugins, Part 4: Twitter
Lecture 65 Syslog with Logstash Deep Dive
Lecture 66 If you run into trouble at the end of the next exercise…
Lecture 67 Elasticsearch and Kafka, Part 1
Lecture 68 Elasticsearch and Kafka, Part 2
Lecture 69 Elasticsearch and Apache Spark, Part 1
Lecture 70 Elasticsearch and Apache Spark, Part 2
Lecture 71[Exercise] Importing Data with Spark
Lecture 72 Section 4 Wrapup
Section 5: Aggregation
Lecture 73 Section 5 Intro
Lecture 74 Aggregations, Buckets, and Metrics
Lecture 75 Histograms
Lecture 76 Time Series
Lecture 77[Exercise] Generating Histogram Data
Lecture 78 Nested Aggregations, Part 1
Lecture 79 Nested Aggregations, Part 2
Lecture 80 Section 5 Wrapup
Section 6: Using Kibana
Lecture 81 Section 6 Intro
Lecture 82 Installing Kibana
Lecture 83 Playing with Kibana
Lecture 84[Exercise] Exploring Data with Kibana
Lecture 85 Kibana Lens
Lecture 86 Kibana Management
Lecture 87 Elasticsearch SQL
Lecture 88 Using Kibana Canvas
Lecture 89 Elasticsearch and Apache Hadoop
Lecture 90 Section 6 Wrapup
Section 7: Analyzing Log Data with the Elastic Stack
Lecture 91 Section 7 Intro
Lecture 92 Data Frame Transforms
Lecture 93 FileBeat and the Elastic Stack Architecture
Lecture 94 X-Pack Security
Lecture 95 Installing FileBeat
Lecture 96 Analyzing Logs with Kibana Dashboards
Lecture 97[Exercise] Log analysis with Kibana
Lecture 98 Section 7 Wrapup
Section 8: Elasticsearch Operations
Lecture 99 Section 8 Intro
Lecture 100 Choosing the Right Number of Shards
Lecture 101 Adding Indices as a Scaling Strategy
Lecture 102 Index Alias Rotation
Lecture 103 Index Lifecycle Management
Lecture 104 Choosing your Cluster’s Hardware
Lecture 105 Heap Sizing
Lecture 106 Monitoring
Lecture 107 Troubleshooting Common Issues
Lecture 108 Failover in Action, Part 1
Lecture 109 Failover in Action, Part 2
Lecture 110 Index Design Changes (Grouping, Splitting, and Shrinking Indices)
Lecture 111 Snapshots
Lecture 112 Snapshot Lifecycle Management
Lecture 113 Rolling Restarts
Lecture 114 Search Profiling
Lecture 115 Uptime Monitoring with Heartbeat
Lecture 116 Section 8 Wrapup
Section 9: Elasticsearch in the Cloud
Lecture 117 Section 9 Intro
Lecture 118 Amazon Elasticsearch Service is now Amazon OpenSearch Service
Lecture 119 Amazon Elasticsearch Service, Part 1
Lecture 120 Amazon Elasticsearch Service, Part 2
Lecture 121 The Elastic Cloud
Lecture 122 Section 9 Wrapup
Section 10: ELK on Kubernetes with Elastic Cloud on Kubernetes (ECK)
Lecture 123 Introducing Elastic Cloud on Kubernetes (ECK), and setting up our cluster
Lecture 124 Setting up Elasticsearch and Kibana on Kubernetes, and installing plugins
Lecture 125 Using ECK Persistent Volumes and Setting Up a Multi-Node Elasticsearch Cluster
Section 11: You Made It!
Lecture 126 Wrapping Up
Lecture 127 Bonus Lecture: More Courses to Explore!
Any technologist tasked with fast, scalable searching and analysis of big data sets.

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