Using Elasticsearch and Kibana – Loonycorn

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Purchase Using Elasticsearch and Kibana – Loonycorn Course at esyGB. You will get full content similar to salepage. Downloads are quick and at no extra cost.

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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