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Elasticsearch Training

Elasticsearch Training

Elasticsearch Training Introduction:

Elasticsearch is a search server based on Lucene. It provides a distributed, multitenant-capable full-text search engine with a Rest ful web interface and schema-free JSON documents. Elasticsearch Training is developed in Java and is released as open source under the terms of the Apache License. Elasticsearch is the second most popular enterprise search engine.

Elasticsearch is a highly scalable open-source full-text search and analytics engine. It allows you to store, search, and analyze big volumes of data quickly and in near real time. It is generally used as the underlying engine/technology that powers applications that have complex search features and requirements. It allows you to start with one machine and scale to hundreds, and supports distributed search deployed over Amazon EC2’s cloud hosting.To know more about this training contact reach at helpdesk of Global Online Trainings today.

Elasticsearch Online Training Course Content

Introduction
  • Terminology, basic concepts, implementation, setup, and basic operations
  • What is Elasticsearch Training?
  • oOverview of best practices
  • What’s in a distribution?
  • Understanding Elasticsearch cluster, shards, and replicas
  • Discussion of configuration, APIs, & local gateway
Multi-Tenancy
  • Value of multiple indices, index aliases & cross-index operations
  • Introduction to data flow
Elasticsearch Training Index
  • In-depth analysis of mappings, indexing & operations
  • Discussion of transaction logs & Lucene indexing
  • Understanding configuration options, mappings, APIs & available settings
Search
  • 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 and Mapping
  • Introduction to aggregations & nested document relations
  • Understanding nested objects & parent-child relationships
  • The importance of geolocation, mapping, indexing query percolation,relevancy, searching & morea
Advanced Distributed Model
  • Cluster state recovery, low level replication, low level recovery & shard allocation
  • How to approach data architecture
  • Index templates, features & functionality
Big Data Design Pattern
  • In-depth content on multiple indices, overallocation, shard overallocation,node types, routing, replication & aliases
Preparing for Production
  • Discussion on capacity planning & data flow
  • Performance tuning, more on data flow & memory allocation.
Running in Production
  • Installation, configuration, memory file descriptions & hardware Monitoring, alerts, thread pools, information & stats APIs

What are the requirements?

  • Beginner level knowledge in relational databases is needed

What am I going to get from this Elasticsearch Training?

  • Do create, read, update and delete operations on Elasticsearch

  • Have a good understanding of searching and sorting documents in Elasticsearch Training

  • Know how mapping and analyzers work and learn how to use them effectively

  • Become an Elasticsearch jedi

What is the target audience?

  • Elasticsearch Training in Action course is for everyone with motivation to learn Elasticsearch. The only skill you will need is a basic understanding of relational databases. No computer science degree, or a programming knowledge is needed.

Elasticsearch Training Basics:

  • ElasticSearch is able to achieve fast search responses because, instead of searching the text directly, it searches an index instead.
  • This is like retrieving pages in a book related to a keyword by scanning the index at the back of a book, as opposed to searching every word of every page of the book.
  • This type of index is called an inverted index, because it inverts a page-centric data structure to a keyword-centric data structure.
  • ElasticSearch uses Apache Lucene to create and manage this inverted index.
  • In Elasticsearch Training, a Document is the unit of search and index.
  • An index consists of one or more Documents, and a Document consists of one or more Fields.
  • In database terminology, a Document corresponds to a table row, and a Field corresponds to a table column.

Schema:

  • Unlike Solr, Elasticsearch Training is schema-free. Well, kinda.

  • Whilst you are not required to specify a schema before indexing documents, it is necessary to addmapping declarations if you require anything but the most basic fields and operations.

  • This is no different from specifying a schema!

The schema declares:

  • what fields there are

  • which field should be used as the unique/primary key

  • which fields are required

  • how to index and search each field

  • In Elasticsearch Training, an index may store documents of different mapping types. You can associate multiple mapping definitions for each mapping type. A mapping type is a way of separating the documents in an index into logical groups.

  • To create a mapping, you will need the Put Mapping API, or you can add multiple mappings when you create an index.

Query DSL:

  • The Query DSL is ElasticSearch’s way of making Lucene’s query syntax accessible to users, allowing complex queries to be composed using a JSON syntax.
  • Like Lucene, there are basic queries such as term or prefix queries and also compound queries like the boolquery.

Elasticsearch Training Overview:

 Introduction

  • Terminology, basic concepts, implementation, setup, and basic operations
  • What is Elasticsearch Training?
  • Overview of best practices
  • What’s in a distribution?
  • Understanding Elasticsearch Training 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 Training Index

  • In-depth analysis of mappings, indexing, and operations
  • Discussion of transaction logs and Lucene indexing
  • Understanding configuration options, mappings, APIs, and available settings

 Search

  • Understanding search Query DSL
  • In-depth understanding of search components: aggregations, search types, highlighting and other options.
  • Overview of bit Sets, filters and Lucene

Advanced Search and 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
  • Index templates, features, and functionality

Big Data Design Pattern

  • In-depth content on multiple indices, over allocation, shard over allocation, 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