Using Elasticsearch and Kibana
1,551 students enrolled
Using Elasticsearch and Kibana
Scalable Search and Analytics for Document Data
1,551 students enrolled
Current price: $69.99
Original price: $99.99
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This course includes
- 6 hours on-demand video
- 1 article
- 1 downloadable resource
- Full lifetime access
- Access on mobile and TV
- Certificate of Completion
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What you'll learn
- Construct robust, scalable search for production use in web and enterprise apps
- Query ES using the ES Domain Specific Language
- Perform aggregations to extract insights and run analytics on ES
- Interface with ES using Python
Course content
Expand all
59 lectures
06:08:32
+
–
Introducing Elasticsearch
12 lectures
01:13:27
Preview
03:00
Course Materials
00:02
A Brief History of Search
07:51
Steps in Search
08:14
Inverted Index
06:12
Using the Inverted Index
05:19
Lucene
07:20
Elasticsearch Introduced
05:37
Installing ES
08:43
Clusters and Nodes
05:43
Indices and Documents
08:26
Cluster Health
07:00
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CRUD Operations in Elasticsearch
10 lectures
01:07:20
Curl
07:20
Create Index
08:15
Create Document
08:20
Retrieve Documents
05:23
Update Documents
08:18
Script Elements
04:40
Delete
04:34
mGet
04:39
Preview
09:06
Bulk Loading
06:45
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The Query DSL (Domain-Specific Language)
16 lectures
01:41:49
Preview
04:21
Random Data Gen
05:19
Contexts
05:52
Contexts
05:56
Query Params
07:15
Request Body
09:03
Source Filtering
08:32
Full Text Search_Match
04:10
Full Text Search_MatchPhrasePrefix
07:14
Relevance
08:10
TfIdf
06:06
Common Terms
06:17
Boolean Compound Queries
06:42
Term Queries Boosting Terms
04:42
Filters
06:01
Wildcards
06:09
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–
Aggregations
7 lectures
43:54
Types Of Aggregations
03:59
Metric Aggregations
07:12
Cardinality Aggregations
09:07
Bucketing Aggregations
05:31
Bucketing Aggregations_2
06:09
Multilevel Nested Aggregations
05:13
FilterBucketAggs
06:43
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–
Elasticsearch and Python
4 lectures
23:17
Pythonsetup
08:32
Create Index
04:58
Documents
05:07
Search_Count
04:40
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Kibana
9 lectures
56:22
Kibana_elk
04:26
Kibana_Install
02:48
Mapping
07:51
Loading Logs
06:37
Discovery
06:49
Visualize
07:00
Timelion
08:01
Dashboard
03:50
Anaconda and Pip
09:00
Requirements
- A basic understanding of HTTP and JSON (Javascript Object Notation)
- Python is helpful for the portions of the course that deal with the ES Python client
Description
Elasticsearch wears two hats: It is both a powerful search engine built atop Apache Lucene, as well as a serious data warehousing/BI technology.
This course will help you use the power of ES in both contexts
ES as search engine technology:
- How search works, and the role that inverted indices and relevance scoring play
- The tf-idf algorithm and the intuition behind term frequency, inverse document frequency and field length
- Horizontal scaling using sharding and replication
- Powerful querying functionality including a query-DSL
- Using REST APIs - from browser as well as from cURL
ES as data warehouse/OLAP technology:
- Kibana for exploring data and finding insights
- Support for CRUD operations - Create, Retrieve, Update and Delete
- Aggregations - metrics, bucketing and nested aggs
- Python client usage
Who this course is for:
- Developers looking to add robust enterprise search functionality
- Business analysts looking to use ES and Kibana for business intelligence
- Data professionals looking to use the ElasticSearch search engine