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 : firstname.lastname@example.org
Phone/WhatsApp : +91-8106721223
USA Number : +1-650-993-1007
Gtalk : email@example.com
ElasticSearch Interview Questions and Answers, Recorded Video Sessions, Materials, Mock Interviews Assignments Will be provided
ELASTIC-SEARCH COURSE OUTLINE / AGENDA
(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
Value of multiple indices, index aliases, and cross-index operations
Introduction to data flow
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