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Elasticsearch 8 and The Elastic Stack: In Depth and Hands On - Printable Version +- Softwarez.Info - Software's World! (https://softwarez.info) +-- Forum: Library Zone (https://softwarez.info/Forum-Library-Zone) +--- Forum: Video Tutorials (https://softwarez.info/Forum-Video-Tutorials) +--- Thread: Elasticsearch 8 and The Elastic Stack: In Depth and Hands On (/Thread-Elasticsearch-8-and-The-Elastic-Stack-In-Depth-and-Hands-On--1139909) |
Elasticsearch 8 and The Elastic Stack: In Depth and Hands On - AD-TEAM - 10-19-2025 ![]() Elasticsearch 8 and the Elastic Stack: In Depth and Hands On Last updated 6/2022 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 4.72 GB | Duration: 15h 13m 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 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 8 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 8 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 15 hours of video.We'll show you how to set up search indices on an Elasticsearch 8 cluster (if you need Elasticsearch 6 or 7 - 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 8 and illustrate all the new syntax requirements of Elasticsearch commands, now that things deprecated through the Elasticsearch 7 have been removed. Almost every hands-on activity has been re-recorded to ensure compatibility with Elasticsearch 8.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, monitoring 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 Opensearch 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 8 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 A note on entering CURL commands. Lecture 19 Import a Single Movie via JSON / REST Lecture 20 Insert Many Movies at Once with the Bulk API Lecture 21 Updating Data in Elasticsearch Lecture 22 Deleting Data in Elasticsearch Lecture 23 [Exercise] Insert, Update and Delete a Movie Lecture 24 Dealing with Concurrency Lecture 25 Using Analyzers and Tokenizers Lecture 26 Data Modeling and Parent/Child Relationships, Part 1 Lecture 27 Data Modeling and Parent/Child Relationships, Part 2 Lecture 28 Flattened Datatype Lecture 29 Dealing with Mapping Exceptions Lecture 30 Section 2 Wrapup Section 3: Searching with Elasticsearch Lecture 31 Section 3 Intro Lecture 32 "Query Lite" interface Lecture 33 JSON Search In-Depth Lecture 34 Phrase Matching Lecture 35 [Exercise] Querying in Different Ways Lecture 36 Pagination Lecture 37 Sorting Lecture 38 More with Filters Lecture 39 [Exercise] Using Filters Lecture 40 Fuzzy Queries Lecture 41 Partial Matching Lecture 42 Query-time Search As You Type Lecture 43 N-Grams, Part 1 Lecture 44 N-Grams, Part 2 Lecture 45 "Search as you Type" Field Type Lecture 46 Section 3 Wrapup Section 4: Importing Data into your Index - Big or Small Lecture 47 Section 4 Intro Lecture 48 Importing Data with a Script Lecture 49 Importing with Client Libraries Lecture 50 [Exercise] Importing with a Script Lecture 51 Introducing Logstash Lecture 52 Installing Logstash Lecture 53 Running Logstash 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 Elasticsearch and Kafka, Part 1 Lecture 67 Elasticsearch and Kafka, Part 2 Lecture 68 Elasticsearch and Apache Spark, Part 1 Lecture 69 Elasticsearch and Apache Spark, Part 2 Lecture 70 [Exercise] Importing Data with Spark Lecture 71 Section 4 Wrapup Section 5: Aggregation Lecture 72 Section 5 Intro Lecture 73 Aggregations, Buckets, and Metrics Lecture 74 Histograms Lecture 75 Time Series Lecture 76 [Exercise] Generating Histogram Data Lecture 77 Nested Aggregations, Part 1 Lecture 78 Nested Aggregations, Part 2 Lecture 79 Section 5 Wrapup Section 6: Using Kibana Lecture 80 Section 6 Intro Lecture 81 Installing Kibana Lecture 82 Playing with Kibana Lecture 83 [Exercise] Exploring Data with Kibana Lecture 84 Kibana Lens Lecture 85 Kibana Management Lecture 86 Elasticsearch SQL Lecture 87 Using Kibana Canvas Lecture 88 Elasticsearch and Apache Hadoop Lecture 89 Section 6 Wrapup Section 7: Analyzing Log Data with the Elastic Stack Lecture 90 Section 7 Intro Lecture 91 Data Frame Transforms Lecture 92 FileBeat and the Elastic Stack Architecture Lecture 93 X-Pack Security Lecture 94 Installing FileBeat Lecture 95 Analyzing Logs with Kibana Dashboards Lecture 96 [Exercise] Log analysis with Kibana Lecture 97 Section 7 Wrapup Section 8: Elasticsearch Operations Lecture 98 Section 8 Intro Lecture 99 Choosing the Right Number of Shards Lecture 100 Adding Indices as a Scaling Strategy Lecture 101 Index Alias Rotation Lecture 102 Index Lifecycle Management Lecture 103 Choosing your Cluster's Hardware Lecture 104 Heap Sizing Lecture 105 Monitoring Lecture 106 Troubleshooting Common Issues Lecture 107 Failover in Action, Part 1 Lecture 108 Index Design Changes (Grouping, Splitting, and Shrinking Indices) Lecture 109 Snapshots Lecture 110 Snapshot Lifecycle Management Lecture 111 Rolling Restarts Lecture 112 Uptime Monitoring with Heartbeat Lecture 113 Section 8 Wrapup Section 9: Elasticsearch in the Cloud Lecture 114 Section 9 Intro Lecture 115 Amazon Opensearch Service, Part 1 Lecture 116 Amazon Opensearch Service, Part 2 Lecture 117 The Elastic Cloud Lecture 118 Section 9 Wrapup Section 10: You Made It! Lecture 119 Wrapping Up Lecture 120 Bonus Lecture: More Courses to Explore! Any technologist tasked with fast, scalable searching and analysis of big data sets. ![]() RapidGator NitroFlare DDownload |