Elasticsearch 7 and the Elastic Stack: Hands On

Frank Kane, Founder of Sundog Education, ex-Amazon

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98 Lessons (8h 33m)
    • 1. Intro: Installing and Understanding Elasticsearch

      0:44
    • 2. Installing Elasticsearch [Step by Step]

      17:35
    • 3. Please follow me on Skillshare!

      0:16
    • 4. Intro to HTTP and RESTful API's

      11:48
    • 5. Elasticsearch Basics: Logical Concepts

      1:58
    • 6. Elasticsearch Overview

      5:44
    • 7. Term Frequency / Inverse Document Frequency (TF/IDF)

      3:48
    • 8. Using Elasticsearch

      3:59
    • 9. What's New in Elasticsearch 7

      3:41
    • 10. How Elasticsearch Scales

      7:27
    • 11. Quiz: Elasticsearch Concepts and Architecture

      4:08
    • 12. Section 1 Wrapup

      0:30
    • 13. Intro: Mapping and Indexing Data

      0:36
    • 14. Connecting to your Cluster

      7:03
    • 15. Introducing the MovieLens Data Set

      3:53
    • 16. Analyzers

      8:27
    • 17. Import a Single Movie via JSON / REST

      10:25
    • 18. Insert Many Movies at Once with the Bulk API

      5:29
    • 19. Updating Data in Elasticsearch

      6:28
    • 20. Deleting Data in Elasticsearch

      2:15
    • 21. [Exercise] Insert, Update and Delete a Movie

      4:14
    • 22. Dealing with Concurrency

      10:20
    • 23. Using Analyzers and Tokenizers

      10:47
    • 24. Data Modeling and Parent/Child Relationships, Part 1

      5:24
    • 25. Data Modeling and Parent/Child Relationships, Part 2

      7:00
    • 26. Section 2 Wrapup

      0:23
    • 27. Intro: Searching with Elasticsearch

      0:29
    • 28. "Query Lite" interface

      8:05
    • 29. JSON Search In-Depth

      10:13
    • 30. Phrase Matching

      6:21
    • 31. [Exercise] Querying in Different Ways

      4:25
    • 32. Pagination

      6:18
    • 33. Sorting

      7:54
    • 34. More with Filters

      3:34
    • 35. [Exercise] Using Filters

      2:39
    • 36. Fuzzy Queries

      6:05
    • 37. Partial Matching

      5:30
    • 38. Query-time Search As You Type

      4:00
    • 39. N-Grams, Part 1

      5:16
    • 40. N-Grams, Part 2

      8:11
    • 41. Section 3 Wrapup

      0:20
    • 42. Intro: Importing Data

      0:50
    • 43. Importing Data with a Script

      8:16
    • 44. Importing with Client Libraries

      6:35
    • 45. [Exercise] Importing with a Script

      3:55
    • 46. Introducing Logstash

      4:50
    • 47. Installing Logstash

      8:57
    • 48. Running Logstash

      5:11
    • 49. Logstash and MySQL, Part 1

      7:55
    • 50. Logstash and MySQL, Part 2

      7:47
    • 51. Logstash and S3

      7:55
    • 52. Elasticsearch and Kafka, Part 1

      5:58
    • 53. Elasticsearch and Kafka, Part 2

      6:45
    • 54. Elasticsearch and Apache Spark, Part 2

      8:20
    • 55. Elasticsearch and Apache Spark, Part 2

      5:58
    • 56. [Exercise] Importing Data with Spark

      8:48
    • 57. Section 4 Wrapup

      0:36
    • 58. Intro: Aggregation

      0:59
    • 59. Aggregations, Buckets, and Metrics

      10:13
    • 60. Histograms

      7:39
    • 61. Time Series

      6:03
    • 62. [Exercise] Generating Histogram Data

      4:21
    • 63. Nested Aggregations, Part 1

      6:03
    • 64. Nested Aggregations, Part 2

      8:45
    • 65. Section 5 Wrapup

      0:23
    • 66. Intro: Using Kibana

      0:20
    • 67. Installing Kibana

      4:37
    • 68. Playing with Kibana

      10:06
    • 69. [Exercise] Log analysis with Kibana

      3:19
    • 70. Section 6 Wrapup

      0:21
    • 71. Intro: Analyzing Log Data with the Elastic Stack

      0:31
    • 72. FileBeat and the Elastic Stack Architecture

      7:33
    • 73. X-Pack Security

      3:10
    • 74. Installing FileBeat

      5:58
    • 75. Analyzing Logs with Kibana Dashboards

      9:52
    • 76. [Exercise] Log analysis with Kibana

      5:25
    • 77. Section 7 Wrapup

      0:31
    • 78. Intro: Elasticsearch Operations and SQL Support

      0:39
    • 79. Choosing the Right Number of Shards

      5:09
    • 80. Adding Indices as a Scaling Strategy

      4:02
    • 81. Index Alias Rotation

      3:52
    • 82. Index Lifecycle Management

      2:09
    • 83. Choosing your Cluster's Hardware

      3:17
    • 84. Heap Sizing

      3:14
    • 85. Monitoring

      6:25
    • 86. Elasticsearch SQL

      5:30
    • 87. Failover in Action, Part 1

      7:12
    • 88. Failover in Action, Part 2

      8:46
    • 89. Snapshots

      9:51
    • 90. Rolling Restarts

      6:39
    • 91. Section 8 Wrapup

      0:29
    • 92. Intro: Elasticsearch in the Cloud

      0:58
    • 93. Amazon Elasticsearch Service, Part 1

      7:20
    • 94. Amazon Elasticsearch Service, Part 2

      5:32
    • 95. The Elastic Cloud

      9:48
    • 96. Section 9 Wrapup

      0:11
    • 97. Wrapping Up

      3:54
    • 98. Let's Stay in Touch

      0:46
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Project Description

This class has several hands-on exercises as you work through the videos, but my favorite is toward the end when we show you how to use Kibana to visualize the data in your Elasticsearch index. Your challenge is to use the index for the complete works of William Shakespeare we set up in early in the class, and use Kibana to visualize which plays have the highest number of lines in them. 

You can extend this to explore Shakespeare in other ways, too - what words are most common in Shakespeare's plays? Which character has the most lines? There's a lot of insight Kibana can give you, and you'll see it's not just limited to analyzing web logs and time series data.

Student Projects