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Using Elasticsearch and Kibana
You, This Course, and Us
You, This Course, and Us (2:23)
Introducing Elasticsearch
Course Outline (3:00)
Course Materials
A Brief History of Search (7:51)
Steps in Search (8:14)
Inverted Index (6:12)
Using the Inverted Index (5:19)
Lucene (7:20)
Elasticsearch Introduced (5:37)
Installing ES (8:43)
Clusters and Nodes (5:43)
Indices and Documents (8:26)
Cluster Health (7:00)
CRUD Operations in Elasticsearch
Curl (7:20)
Create Index (8:15)
Create Document (8:20)
Retrieve Documents (5:23)
Update Documents (8:18)
Script Elements (4:40)
Delete (4:34)
mGet (4:39)
The Bulk API (9:06)
Bulk Loading (9:05)
The Query DSL (Domain-Specific Language)
Search Recap (4:21)
Random Data Gen (5:19)
Contexts (5:52)
Contexts (5:56)
Query Params (7:15)
Request Body (9:03)
Source Filtering (8:32)
Full Text Search_Match (4:10)
Full Text Search_MatchPhrasePrefix (7:14)
Relevance (8:10)
TfIdf (6:06)
Common Terms (6:17)
Boolean Compound Queries (6:42)
Term Queries Boosting Terms (4:42)
Filters (6:01)
Wildcards (6:09)
Aggregations
Types Of Aggregations (3:59)
Metric Aggregations (7:12)
Cardinality Aggregations (9:07)
Bucketing Aggregations (5:31)
Bucketing Aggregations_2 (6:09)
Multilevel Nested Aggregations (5:13)
FilterBucketAggs (6:43)
Elasticsearch and Python
Pythonsetup (8:32)
Create Index (4:58)
Documents (5:07)
Search_Count (4:40)
Kibana
Kibana_elk (4:26)
Kibana_Install (2:48)
Mapping (7:51)
Loading Logs (6:37)
Discovery (6:49)
Visualize (7:00)
Timelion (8:01)
Dashboard (3:50)
Anaconda and Pip (9:00)
A Brief History of Search
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