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

Frank Kane, Founder of Sundog Education, ex-Amazon

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62 Videos (7h 60m)
    • Introduction, and Installing Elasticsearch

      19:54
    • Elasticsearch Overview

      5:44
    • Intro to HTTP and RESTful API's

      11:48
    • Using Elasticsearch

      9:01
    • Elasticsearch Architecture

      6:46
    • Quiz: Elasticsearch Concepts and Architecture

      4:24
    • Quiz: Elasticsearch Concepts and Architecture

      6:54
    • Getting to Know the Movielens Data Set

      4:16
    • Create a Mapping for MovieLens

      14:25
    • Hacking CURL (Don't Skip This!)

      6:04
    • Import a Single Movie via JSON / REST

      5:00
    • Insert Many Movies at Once

      5:32
    • Updating Data in Elasticsearch

      6:13
    • Deleting Data in Elasticsearch

      2:43
    • [Exercise] Insert, Update, and Delete a Fictitious Movie

      4:27
    • Dealing with Concurrency

      8:45
    • Using Analyzers and Tokenizers

      11:38
    • Data Modeling with Elasticsearch

      13:17
    • Using Query-String Search

      9:13
    • Using JSON Search

      9:54
    • Full-Text vs. Phrase Search

      6:04
    • [Exercise] Search for New Star Wars Films Two Different Ways

      3:49
    • Pagination

      6:14
    • Sorting

      7:51
    • Using Filters

      4:24
    • [Exercise] Search for Science Fiction Movies Before 1960, Sorted by Title

      3:09
    • Fuzzy Queries

      6:16
    • Partial Matching

      5:22
    • N-Grams, and Search as you Type

      12:54
    • Importing Data from Scripts

      15:09
    • [Exercise] Import Movie Tags Into a New Index with a Python Script.

      3:32
    • Logstash Overview

      4:31
    • Installing Logstash

      7:49
    • Importing Apache Access Logs with Logstash

      4:51
    • Importing Data from MySQL using Logstash

      14:34
    • Importing Data from AWS S3 using Logstash

      8:14
    • Integrating Kafka with Elasticsearch

      9:00
    • Integrating Spark and Hadoop with Elasticsearch

      12:16
    • [Exercise] Import Movie Ratings from Spark to Elasticsearch

      9:30
    • Buckets and Metrics

      12:04
    • Histograms

      7:36
    • Aggregating Time Series Data

      6:58
    • [Exercise] When Did my Site Go Down?

      4:50
    • Nested Aggregations

      12:58
    • Installing Kibana

      5:32
    • Analyzing Shakespeare with Kibana

      8:44
    • [Exercise] Find the Shakespeare Plays with the Most Lines

      3:14
    • The ELK Stack and Elastic Stack

      4:12
    • Install, Configure, and Use Filebeat

      5:31
    • Analyzing Server Logs with Kibana

      7:05
    • [Exercise] Narrow Down the Source of 404 Errors

      4:19
    • How Many Shards Should I Use?

      5:48
    • Scaling with New Indices

      7:41
    • Choosing Your Hardware

      3:04
    • Heap Sizing

      3:16
    • Monitoring with X-Pack

      11:55
    • Practicing Failover

      12:23
    • Snapshots

      9:30
    • Rolling Restarts

      8:06
    • Using Amazon Elasticsearch Service

      10:19
    • Using Elastic Cloud

      9:36
    • I Made It! Now What?

      3:45

About This Class

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.

We'll cover setting up search indices on an Elasticsearch 6 cluster 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.

3 of 3 students recommendSee All

Frank your quality of training is FIRST CLASS!! Thanks so much and look forward to learn more from you. A++++

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Frank Kane

Founder of Sundog Education, ex-Amazon

Frank spent 9 years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to hundreds of millions of customers, all the time. Frank holds 17 issued patents in the fields of distributed computing, data mining, and machine learning. In 2012, Frank left to start his own successful company, Sundog Software, which focuses on virtual reality environment technology, and teaching others about big data analysis.

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