Elasticsearch Tutorial | Getting Started with Elasticsearch | ELK Stack Training | Edureka

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Agenda
❑ What Is Artificial Intelligence ?
❑ What Is Machine Learning ?
❑ Limitations Of Machine Learning
❑ Deep Learning To The Rescue
❑ What Is Deep Learning ?
❑ Deep Learning Applications

APIs6
Agenda
What Is Elasticsearch? 1
Advantages 3
Installation 4
API Conventions 5
Mapping8
Analysis9
Modules10
Why Elasticsearch? 2 Query DSL7

What Is Elasticsearch?
Let’s understand what is Elasticsearch.

What Is Elasticsearch?
• Real time distributed and analytics engine
• Open Source developed in Java
• Elasticsearch is based on the Lucene engine on
top of which we have a rest interface.
• Supports full-text search i.e completely
document based instead of tables and schemas
• Used for Single Page Application Projects

Why Elasticsearch?
Let’s understand why we are using Elasticsearch.

Why Elasticsearch?
Query
• Lets you perform and combine many types of searches like structured,
unstructured, geo, metric etc.
• You can ask a query “anyway you want”
• Lets you understand billions of log lines easily
• Provides aggregations which help you zoom out to explore trends and patterns
in your data
Analyze

Why Elasticsearch?
Show files where
place is Dubai
Dubai
Dubai
DubaiDubai
Dubai

Why Elasticsearch?
Dubai DubaiDubaiDubai Dubai

Why Elasticsearch?
Aggregate data by
days

Why Elasticsearch?
Aggregate posts
by geography

Advantages Of Elasticsearch
Let’s now see what all benefits Elasticsearch provides.

Really Fast
Scalability
MultilingualA

Autocompletion &
Instant Search
Document
Oriented
Schema Free
Science
Scientist
sc

Installation
Let’s now install Elasticsearch.

Installation
1
Install the latest Java version.
OR
If you already have Java Installed
then check for its version using
java –version command in cmd
NOTE: Java version must be 7 or more

Installation
2
3
Go to
https://www.elastic.co/downloads
Click on Download
to get the zip file

Installation
4 Unzip the file
5
Go to bin folder

Installation
6
Double click on
elasticsearch.bat file

Installation
6 Wait for Elasticsearch to start

Installation
6 Open a browser and type localhost:9200
7
If you can see this message on
the browser that means your
Elasticsearch is up and running

Installation
7 You need to add the Sense(beta) plugin which will act as an developers interface to Elasticsearch

Basic Concepts
Before you dive into Elasticsearch let’s see few core concepts of Elasticsearch.

Near Real Time
Elasticsearch is a near real time search platform that is there is a slight
from the time you index a document until the time it becomes searchable
Basic Concepts
Cluster
A cluster is a collection of one or more nodes that together holds the entire data. It
provides federated indexing and search capabilities across all nodes and is identified
by a unique name (by default it is ‘elasticsearch’)
Node
A node is a single server which is a part of cluster, stores data and
participates in the cluster’s indexing and search capabilities

Index
An index is a collection of documents with similar characteristics and is identified by a
name. This name is used to refer to the index while performing indexing, search,
update, and delete operations against the documents in it.
Type
A type is a logical category/ partition of an index whose semantics is completely. It is
defined for documents that have a set of common fields. You can define more than one
type in your index
Basic Concepts

Basic Concepts
Document
A document is a basic unit of information which can be indexed. It is expressed
in JSON which is an ubiquitous internet data interchange format
Shards
Elasticsearch provides the ability to subdivide the index into multiple pieces
called shards. Each shard is in itself a fully-functional and independent
"index" that can be hosted on any node within the cluster
Replicas
Elasticsearch allows you to make one or more copies of your index’s shards which are
called replica shards or replica

API Conventions
Let’s now find out the API Conventions in Elasticsearch.

API Conventions
Multiple Indices
Date Math Support
in Index Name
Common
Options
URL based
Access Control
The elasticsearch REST APIs are accessed using JSON over HTTP. Elasticsearch uses following conventions
throughout the REST API:

API Conventions
Multiple Indices
Date Math Support
in Index Name
URL based
Access Control
Common
Options
• Most APIs support execution across multiple indices
• Different notations are used to perform operations in multiple indices like:
o Comma separated notations
demo1,demo2,demo3
o Wildcard notations (*,+,-)
demo*,de*o2,+demo3,-demo3
o _all keyword for all indices
o URL Query String Parameters
a. ignore_unavailable
b. allow_no_indices
c. expand_wildcards

API Conventions
Multiple Indices
Date Math Support
in Index Name
URL based
Access Control
Common
Options
• Elasticsearch lets you to search indices according to date and time.
• You need to specify date and time in a specific format like:
<static_name{date_math_expr{date_format|time_zone}}>
static text part of the name
computes the date dynamically
optional date format
optional time zone

API Conventions
Multiple Indices
Date Math Support
in Index Name
URL based
Access Control
Common
Options
• Following are the common options for all the REST APIs:
o Pretty Result
o Human Readable Output
o Date Math
o Response Filtering
o Flat Settings
o Parameter
o No Values
o Time Units
o Byte Size Units
o Unit-less quantities
o Distance Units
o Fuzziness
o Enabling Stack Traces
o Request Body In Query String

API Conventions
Multiple Indices
Date Math Support
in Index Name
URL based
Access Control
Common
Options
• Users can also use a proxy with URL-based access control to secure
access to the Elasticsearch indices
• User has an option of specifying an index in the URL and on each
individual request within the request body for some requests like:
o multi-search
o multi-get
o bulk

Elasticsearch APIs
Let’s now find out different types of APIs in Elasticsearch.

1 532 4
Document APIs
Search APIs Index APIs
Aggregation Cluster APIs
Elasticsearch APIs

1 532 4
Search APIs Index APIs
Aggregation Cluster APIsDocument APIs
Elasticsearch APIs

Document API
Single Document API Multi-Document API
• Index API
• Get API
• Update API
• Delete API
• Multi Get API
• Bulk API
• Delete By Query API
• Update By Query API
• Reindex API

Document API – CRUD Operations
• Index API
• Get API
• Update API
• Delete API
Creating the document

• Index API
• Get API
• Update API
• Delete API
Reading the document

• Index API
• Get API
• Update API
• Delete API
Updating the document

• Index API
• Get API
• Update API
• Delete API
Deleting the document

Search API
Using a search API, you can execute a search query and get back search hits that match the query
Multi - Type
URI Search
Multi Index You can search for the documents present in all the indices or in some specific indices
You can search all the documents in an index across all types or in some specified type
Various parameters can be passed in a search operation using Uniform Resource
Identifier:
• q
• lenient
• fields
• sort
• timeout
• terminate_after
• from
• size

Search API
Using URI: q searchExample:

Aggregation
"aggregations" : {
"<aggregation_name>" : {
"<aggregation_type>" : {
<aggregation_body>
}
[,"meta" : { [<meta_data_body>] } ]?
[,"aggregations" : { [<sub_aggregation>]+ } ]?
}
[,"<aggregation_name_2>" : { ... } ]*
}
Aggregation collects all the data which is selected by the search query. This framework consists of
many building blocks called aggregators, which help in building complex summaries of the data

Aggregation - Types
Bucketing Metric
Matrix Pipeline

Index API
Index APIs are responsible for managing all the aspects of index like settings, aliases, mappings, index templates
Create Index
Delete Index
Get Index
Index Exits
Open/ Close Index API
Index Aliases
Index Settings
Analyze
Index Template
Index Stats
Flush
Refresh

Cluster API
Cluster API is used for getting information about cluster and its nodes and making changes in them
Cluster Health
Cluster State
Cluster Stats
Pending Cluster Task
Cluster Reroute
Node Stats
Nodes hot_threads

Query DSL
Let’s now find out how Query DSL is used to define queries.

Leaf Query Clauses
Query DSL
Elasticsearch provides a full Query DSL based on JSON to define queries. Query DSL is an AST of
queries, consisting of two types of clause:
1
Compound Query Clauses2

Mapping
Let’s now find out how documents are mapped in elasticsearch.

Mapping
Mapping is the process of defining how a document, and the fields that it contains, are stored and indexed
Mapping Types
Meta - fields
1 Fields or properties
2
Field Data Types
Core Data Types
1
Specialized Data Types
4
Geo Data Types
3
Complex Data Types
2

Mapping
Dynamic Mapping
Mapping Parameters
✓ Analyzer
✓ Boost
✓ Coerce
✓ copy_to
✓ doc_values
✓ Dynamic
✓ Enabled
✓ Fielddata
✓ Geohash
✓ geohash_precision
✓ geohash_prefix
✓ Format
✓ ignore_above
✓ ignore_malformed
✓ include_in_all
✓ index_options
✓ lat_lon
✓ Index
✓ Fields
✓ Norms
✓ null_value
✓ position_increment_gap
✓ Properties
✓ search_analyser
✓ Similarity
✓ Store
✓ term_vector

Analysis
Let’s now find out how data is configured.

Analysis
During a search operation when a query is processed , the content in any index is analysed by analysis module
Analyzers1
Token Filter3
Tokenizer
Character Filter
2
4

Modules
Let’s now find out modules and it’s different types in elasticsearch

Static Setting
Modules
Elasticsearch is composed of a number of modules, which are mainly responsible for its functionality
These modules have 2 types of settings:
Dynamic Setting
These settings need to be configured in the config
(elasticsearch.yml) file before starting the Elasticsearch
These settings can be set on live Elasticsearch.

Modules Types
Discovery
Gateway
HTTP
Indices
Network
Node
Client
Painless
Plug-in
Scripting
Snapshot
/Restore
Thread
pools
Transport
Tribe
nodes
Cross
Cluster
Search
Cluster-level
routing and
shard
allocation

Demo

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Elasticsearch Tutorial | Getting Started with Elasticsearch | ELK Stack Training | Edureka

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