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ElasticSearch Online Training Course Content by Corporate Trainers


Elasticsearch Training helps you to learn RESTful search, distributed, multi-tenant capable full-text search engine with an HTTP web interface and schema-free JSON documents, Explore different features of search Query DSL, capacity planning and data flow. This course also covers Advanced Distributed Model, Big Data Design Pattern, Understanding nested objects and parent-child relationships, filters and Lucene and etc. At the end of the training you will have a deep understanding of how Elasticsearch works, you will be able to reliably analyze, understand and solve common problems and ready to build state of the art search applications.


FOR FREE DEMO contact :

Email : info@ibasetraining.com

Phone/WhatsApp : +91-8106721223

USA Number : +1-650-993-1007

Gtalk : ibasetraining@gmail.com



ElasticSearch Interview Questions and Answers, Recorded Video Sessions, Materials, Mock Interviews Assignments Will be provided



(the course content can be modified as per your requirements):



Terminology, basic concepts, implementation, setup, and basic operations

What is Elasticsearch?

Overview of best practices

What’s in a distribution?

Understanding Elasticsearch cluster, shards, and replicas

Discussion of configuration, APIs, and local gateway


Multi Tenancy:

Value of multiple indices, index aliases, and cross-index operations

Introduction to data flow


Elasticsearch Index:

In-depth analysis of mappings, indexing, and operations

Discussion of transaction logs and Lucene indexing

Understanding configuration options, mappings, APIs, and available settings



Understanding search Query DSL

In-depth understanding of search components: aggregations, search types, highlighting and other options.

Overview of bitSets, filters and Lucene


Advanced Search & Mapping:

Introduction to aggregations and nested document relations

Understanding nested objects and parent-child relationships

The importance of geolocation, mapping, indexing query percolation, relevancy, searching, and more


Advanced Distributed Model:

Cluster state recovery, low level replication, low level recovery, and shard allocation

How to approach data architecture

ndex templates, features, and functionality


Bigdata Design Pattern:

In-depth content on multiple indices, overallocation, shard overallocation, node types, routing, replication, and aliases


Preparing For Production:

Discussion on capacity planning and data flow

Performance tuning, more on data flow, and memory allocation.


Running In Production:

Installation, configuration, memory file descriptions, and hardware Monitoring, alerts, thread pools, information and stats APIs


Practice tests & Interview Questions




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