BPB Online LLP
Learning Elasticsearch 7.x
Learning Elasticsearch 7.x
US$ 19.95
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Description
Contents
Reviews

Based on NIELIT 'O' Level Revised Syllabus for the Year 2020 for Module 1 (M1-R5)
मॉड्यूल 1 (M1-R5) वर्ष 2020 के लिए NIELIT 'O' लेवल सिलेबस पर आधारित

Key Features
Set of review questions with answers are added at the end of each chapter.
प्रश्न के साथ उत्तर का सेट प्रत्येक अध्याय के अंत में दिया गया है|.
Sample papers are also included to enable the readers to know the questions likely to be asked in the examination.
परीक्षा में पूछे जाने वाले प्रश्नों के लिए पाठकों को सक्षम करने के लिए साल्व्ड और अनसॉल्व्ड पेपर का सेट भी शामिल है।

Description
Book covers the entire syllabus for Module -1, IT TOOLS and Network Basics, in a clear and straightforward style. It describes the detailed explanations of computers, Windows Operating systems. MS office, Libre office in an easy-to-understand language.पुस्तक स्पष्ट और सरल शैली में, मॉड्यूल 1, आईटी टूल और नेटवर्क बेसिक्स के पूरे पाठ्यक्रम को कवर करती है। पुस्तक कंप्यूटर, विंडोज ऑपरेटिंग सिस्टम, एमएस ऑफिस, लिब्रे ऑफिस को वर्णित करती है।

Detailed explanations of Social Networking and e-Governance Services will help the reader to develop the communication through social media sites.

सोशल नेटवर्किंग और ई-गवर्नेंस सेवाओं की विस्तृत व्याख्या पाठक को संचार को विकसित करने में मदद करेगी ।
Digital Financial Tools and Applications, Future Skills & Cyber Security will enable you to understand the various financial services, latest trends and technologies in upcoming fields in IECT.

डिजिटल वित्तीय उपकरण और अनुप्रयोग, फ्यूचर स्किल्स और साइबर सिक्योरिटी शामिल हैं जो विभिन्न वित्तीय सेवाओं, नवीनतम रुझानों और IECT में आगामी क्षेत्रों में तकनीकों को समझने में सक्षम हैं।

What will you learn
Computer, Operating System, Internet, WWW and Web
कंप्यूटर, ऑपरेटिंग सिस्टम, इंटरनेट, डब्ल्यूडब्ल्यूडब्ल्यू और वेब
Email, Social Networking and e-Governance Services
नेटवर्क, ईमेल, सोशल नेटवर्किंग और ई-गवर्नेंस

Who this book is for
Book aims at imparting a basic level of IT literacy to computer novices and will help them to learn the practical applications of the concepts.
पुस्तक का उद्देश्य कंप्यूटर नौसिखियों को आईटी साक्षरता का एक बुनियादी स्तर प्रदान करना है और उन्हें अवधारणाओं के व्यावहारिक अनुप्रयोगों को सीखने में मदद करेगा।.br/>
Table of Contents
Introduction to Computer (कंप्यूटर का परिचय)
Operating System Windows (ऑपरेटिंग सिस्टम: विंडोज)
Ubuntu/Edubuntu ( उबुन्टु / एडुबुन्टु)
MS-Word (मस –वर्ड)
LibreOffice Writer (लिब्रे ऑफिस राइटर)
MS-Excel (मस -एक्सेल)
LibreOffice Calc (लिब्रे ऑफिस कैलक)
MS-PowerPoint (मस - पॉवरपॉइंट)
LibreOffice Impress(लिब्रे ऑफिस इम्प्रेस)
Internet, WWW and Web (इंटरनेट, डब्ल्यू डब्ल्यू डब्ल्यू और वेब)
Email, Social Networking & e-Governance Services (ईमेल, सोशल नेटवर्किंग और ई-गवर्नेंस सेवाएं)
Digital Financial Tools and Applications (डिजिटल वित्तीय उपकरण और अनुप्रयोग)
Futuristic IT Technology and Cyber Security (फ्यूचरिस्टिक आईटी प्रौद्योगिकी और साइबर सुरक्षा )

About the Authors
Prof. Satish Jain has obtained B.Sc. degree from Agra University in First Division and is a gold medal winner. He obtained B.E. (Electronics) degree from Indian Institute of Science (I.I.Sc.), Bangalore with Distinction. He joined Indian Airforce as a Signal officer and held different technical appointments during 21 years of service. He was specially selected by the IAF to undergo Masters of Engineering course in Aerospace science at I.I.Sc., Bangalore and M.Tech in Computer Science Engineering at IIT Kanpur. After taking retirement from the IAF, he set up Computer Science Department in different organisations and educational institutes.
.

प्रो. सतीश जैन ने आगरा विश्वविद्यालय से प्रथम श्रेणी में बी.एससी. की डिग्री ली है और वह स्वर्ण पदक विजेता है । उन्होंने बी.ई. (इलेक्ट्रॉनिक्स) इंडियन इंस्टीट्यूट ऑफ साइंस (आई. आई. अस सी.), बैंगलोर से की है । वह सिग्नल अधिकारी के रूप में भारतीय एयरफोर्स में शामिल हुए और 21 वर्षों की सेवा के दौरान विभिन्न तकनीकी नियुक्तियां कीं। आईआईटी, बैंगलोर में उन्होंने एयरोस्पेस साइंस में मास्टर्स ऑफ इंजीनियरिंग कोर्स करने के लिए IAF द्वारा विशेष रूप से चयन हुआ था और आईआईटी कानपुर में कंप्यूटर साइंस से ऍम टेक की थी। भारतीय वायुसेना से सेवानिवृत्ति लेने के बाद, उन्होंने विभिन्न संगठनों और शैक्षणिक संस्थानों में कंप्यूटर विज्ञान विभाग की स्थापना की थी ।.

Language
English
ISBN
9789389898309
Cover Page
Title Page
Copyright Page
Dedication Page
About the Author
About the Reviewer
Acknowledgement
Preface
Errata
Table of Contents
1. Getting Started with Elasticsearch
Introduction
Structure
Objectives
Introduction to Elasticsearch
What is Elasticsearch
The basic concepts of Elasticsearch
Node
Master node
Data node
Ingest node
Machine learning node
Cluster
Documents
Index
Shard
Use cases of Elasticsearch
Data search
Data logging and analysis
Application performance monitoring
System performance monitoring
Data Visualization
Different clients for Elasticsearch
Java
PHP
Perl
Python
.NET
Ruby
JavaScript
How to use Elasticsearch
Elasticsearch as a primary data source
Elasticsearch as a secondary data source for searching
Elasticsearch as a standalone system
Conclusion
Questions
2. Installing Elasticsearch
Introduction
Structure
Objectives
What’s new in Elasticsearch 7.x
Adaptive replica selection
Skip shard refreshes
One shard per index by default
Support for small heap
Installing Elasticsearch
Installing Elasticsearch on Linux or macOS
Installing Elasticsearch on Linux
Installing Elasticsearch on macOS
Installing Elasticsearch using the Debian package
Installing the Debian package manually
Installing Elasticsearch using the RPM package
Installing the RPM package manually
Start the Elasticsearch service and verify
Elasticsearch REST APIs
cat APIs
cat API parameters
Verbose
Help
Headers
Response formats
Sort
cat count API
cat health API
cat indices API
cat master API
cat nodes API
cat shards API
Cluster APIs
Cluster health API
Cluster stats API
Conclusion
Questions
3. Working with Elastic Stack
Introduction
Structure
Objectives
What is Elastic Stack
Elasticsearch
Logstash
Logstash input plugin
Logstash filter plugin
Logstash output plugin
Fetch Apache logs using logstash
Kibana
Beats
Filebeat
Configure input
Configure output
Metricbeat
Configure Metricbeat
Enabling the required modules
Output configuration
Packetbeat
Configuring Packetbeat
Winlogbeat
Configure Winlogbeat
Auditbeat
Configuring Auditbeat
Heartbeat
Configuring Heartbeat
Functionbeat
Configuring Functionbeat
Conclusion
Questions
4. Preparing Your Data
Introduction
Structure
Objectives
Why it is important to prepare the data before indexing
An introduction to Elasticsearch analyzers
Built-in analyzer
Standard analyzer
Simple analyzer
Whitespace analyzer
Stop analyzer
Keyword analyzer
Pattern analyzer
Language analyzers
Fingerprint analyzer
Custom analyzer
Tokenizers
Word oriented tokenizers
Standard tokenizer
Letter tokenizer
Lowercase tokenizer
Whitespace tokenizer
UAX URL email tokenizer
Classic tokenizer
Partial word tokenizers
N-gram tokenizer
Edge n-gram tokenizer
Structured text tokenizers
Keyword tokenizer
Pattern tokenizer
Token filters
Character filters
HTML strip character filter
Mapping the char filter
Pattern replace character filter
Normalizers
Conclusion
Questions
5. Importing Data into Elasticsearch
Introduction
Structure
Objectives
Why is data so important for business
Data shipping
Data ingestion
Data storage
Data visualization
Importing data into Elasticsearch using different Beats
Pull Apache logs using Filebeat
Pull server metrics using Metricbeat
Pulling network data using Packetbeat
Pulling CSV data using logstash
Conclusion
Questions
6. Managing Your Index
Introduction
Structure
Objectives
Creating index along with mapping
Creating an index without any document
Creating index along with the documents
Get mapping of the index
Create a mapping of the index
Index management
Performing index-level operations
Close index
Delete index
Freeze index
Refresh index
Force merge index
Clear index cache
Flush index
Add lifecycle policy
Index APIs
Index management
Creating an index
Delete index
Get index
Close index
Open index
Index Exist API
Shrink index
Freeze index
Unfreeze index
Split index
Clone index
Rollover index
Index settings
Update index settings
Get index settings
Manage index templates
Creating an index template
Get index template
Delete index template
Index lifecycle management
Conclusion
Questions
7. Applying Search on Your Data
Introduction
Structure
Objective
URI search
Empty search
Field search
Request body search
Query versus filter
Query
Query types
Full-text search
Term-level queries
Compound queries
Multi-search
Multi-search API
Multi search template
Explain API
Profile API
Conclusion
Questions
8. Handling Geo with Elasticsearch
Introduction
Structure
Objective
Geodata type
Geo point data
Creating mapping
Saving geo point data
Geo shape data
Creating mapping
Saving geo point data
Point
LineString
Polygon
MultiPoint
MultiLineString
MultiPolygon
Geometry collection
Envelope
Circle
Geo queries
Geo-distance queries
Geo-polygon queries
Geo-bounding box queries
Geo-shape queries
Use case
Restaurant search
Aggregate restaurant based on the distance
Conclusion
Questions
9. Aggregating Your Data
Introduction
Structure
Objective
Introduction to Elasticsearch aggregation
Bucket aggregation
Range aggregation
Composite aggregation
Terms
Histogram
Date histogram
Terms aggregation
Filter aggregation
Filters aggregation
Geo distance aggregation
Metrics aggregation
Min aggregation
Max aggregation
Avg aggregation
Sum aggregation
Value count aggregation
Stats aggregation
Extended stats aggregation
Percentiles aggregation
Matrix aggregation
Matrix stats aggregation
Pipeline aggregation
Avg bucket aggregation
Max bucket aggregation
Sum bucket aggregation
Conclusion
Questions
10. Improving the Performance
Introduction
Structure
Objectives
Introduction
Tuning Elasticsearch indexing speed
Bulk R equests instead of a single request
Smart use of the Elasticsearch Cluster
Increasing the refresh interval
Disable replicas
Using auto-generated ids
Tweaking the indexing buffer size
Use of faster hardware
Allocating memory to the filesystem cache
Tuning Elasticsearch search speed
Document modelling
Search a few fields if possible
Pre-index data
Mapping of identifiers as keyword
We should force merge the read-only indices
Use filter instead of the query
Increase the replica count
Fetch only the required fields
Use of faster hardware
Allocate memory to the filesystem cache
Avoid including stop words in the search
Avoid the script in the query
Tuning Elasticsearch for disk usage
Shrink index
Force merge
Disable the unrequired features
Avoid dynamic string mappings
Disable_source
Use the smallest numeric type
Elasticsearch best practices
Always define the mapping
Do your capacity planning
Avoid split-brain problem
Enable the slow query log
Conclusion
Questions
11. Administering Elasticsearch
Structure
Objectives
Elasticsearch security
Configuring TLS
Elasticsearch cluster passwords
Configuring role-based access using Kibana
Creating users
Creating roles
Index aliases
Repository and snapshot
Creating the repository
Taking the snapshot
Restoring a snapshot
Elastic common schema
Why do we need a common schema
Introduction to Elastic common schema
ECS general guidelines
ECS field name guidelines
Getting started with ECS
Conclusion
Questions
Index

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