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Using Elasticsearch and Kibana
Scalable Search and Analytics for Document Data
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
Get Using Elasticsearch and Kibana – Loonycorn, Only Price $11
Course Curriculum
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)t
- 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)t
- Mapping (7:51)
- Loading Logs (6:37)
- Discovery (6:49)
- Visualize (7:00)
- Timelion (8:01)
- Dashboard (3:50)
- Anaconda and Pip (9:00)
Get Using Elasticsearch and Kibana – Loonycorn, Only Price $11
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