This document provides an overview of MongoDB including:
- MongoDB is a cross-platform, document-oriented NoSQL database that stores data as JSON-like documents.
- It discusses MongoDB architecture, important features like queries, indexing, replication, and auto-sharding.
- The document compares MongoDB to relational databases and covers installation, CRUD operations, and aggregation.
- Examples of queries, updates, projections and other MongoDB operations are provided.
MongoDB is a cross-platform, document-oriented NoSQL database that provides high performance and scalability. It stores data in BSON documents which are similar to JSON documents. MongoDB does not enforce a schema and documents can have dynamic schemas. It supports queries, indexing, replication and sharding. Some key features include schema-less design, document-oriented storage, queries on indexed fields and MapReduce for flexible aggregation.
MongoDB is a non-relational database that supports document-based queries, indexing of all fields, master-slave replication for high availability, automatic sharding of data across multiple servers, and MapReduce for flexible aggregation. It uses dynamic schemas and embeds documents which can store binary data. Queries in MongoDB support ad-hoc queries on documents using standard operators and indexes can be applied on any field.
Ms. Chitra Alavani, Head of the Computer Science department at Kaveri College of Arts, Science and Commerce, provides an overview of key concepts for working with MongoDB including creating databases and collections, inserting and querying documents, and performing aggregation.
This document provides an overview of MongoDB concepts and how to perform CRUD operations. It discusses how to install and set up MongoDB, create collections and schemas to store data, perform basic CRUD operations like insert, find, update, and delete records, and how to drop collections. MongoDB is an open-source, document-based database that provides high performance, high availability, and easy scalability. It uses JSON-like documents with dynamic schemas and supports distributed storage and processing of large amounts of data.
This presentation is related to nosql database and nosql database types information. this presentationa also contains discussion about, how mongodb works and mongodb security and mongodb sharding information.
MongoDB (from humongous) is a cross-platform document-oriented database. Classified as a NoSQL database, MongoDB eschews the traditional table-based relational database structure in favor of JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster. Released under a combination of the GNU Affero General Public License and the Apache License, MongoDB is free and open-source software.
MongoDB is a cross-platform, document-oriented NoSQL database that provides high performance and scalability. It stores data in BSON documents which are similar to JSON documents. MongoDB does not enforce a schema and documents can have dynamic schemas. It supports queries, indexing, replication and sharding. Some key features include schema-less design, document-oriented storage, queries on indexed fields and MapReduce for flexible aggregation.
MongoDB is a non-relational database that supports document-based queries, indexing of all fields, master-slave replication for high availability, automatic sharding of data across multiple servers, and MapReduce for flexible aggregation. It uses dynamic schemas and embeds documents which can store binary data. Queries in MongoDB support ad-hoc queries on documents using standard operators and indexes can be applied on any field.
Ms. Chitra Alavani, Head of the Computer Science department at Kaveri College of Arts, Science and Commerce, provides an overview of key concepts for working with MongoDB including creating databases and collections, inserting and querying documents, and performing aggregation.
This document provides an overview of MongoDB concepts and how to perform CRUD operations. It discusses how to install and set up MongoDB, create collections and schemas to store data, perform basic CRUD operations like insert, find, update, and delete records, and how to drop collections. MongoDB is an open-source, document-based database that provides high performance, high availability, and easy scalability. It uses JSON-like documents with dynamic schemas and supports distributed storage and processing of large amounts of data.
This presentation is related to nosql database and nosql database types information. this presentationa also contains discussion about, how mongodb works and mongodb security and mongodb sharding information.
MongoDB (from humongous) is a cross-platform document-oriented database. Classified as a NoSQL database, MongoDB eschews the traditional table-based relational database structure in favor of JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster. Released under a combination of the GNU Affero General Public License and the Apache License, MongoDB is free and open-source software.
This document discusses using document databases like CouchDB with TYPO3 Flow. It provides an overview of persistence basics in Flow and Doctrine ORM. It then covers using CouchDB as a document database, including its REST API, basics, and the TYPO3.CouchDB package. It notes limitations and introduces alternatives like Radmiraal.CouchDB that support multiple backends. Finally, it discusses future support for multiple persistence backends in Flow.
In this presentation, Raghavendra BM of Valuebound has discussed the basics of MongoDB - an open-source document database and leading NoSQL database.
----------------------------------------------------------
Get Socialistic
Our website: http://valuebound.com/
LinkedIn: http://bit.ly/2eKgdux
Facebook: https://www.facebook.com/valuebound/
Twitter: http://bit.ly/2gFPTi8
MongoDB is an open source document database, and the leading NoSQL database. MongoDB is a document oriented database that provides high performance, high availability, and easy scalability. It is Maintained and supported by 10gen.
- MongoDB is a schema-free document database that stores data in BSON format.
- It aims to bridge the gap between relational and non-relational databases by providing scalability and flexibility similar to non-relational databases while also supporting richer queries than typical key-value stores.
- MongoDB installations involve downloading the MongoDB software, setting up a data directory, starting the MongoDB process, and connecting to it using the mongo shell for basic CRUD operations on databases and collections of documents.
The document provides information about MongoDB including:
- MongoDB is an open-source, document-based NoSQL database that stores data in BSON format and collections instead of tables and rows.
- It has no schema and allows embedding of documents, dynamic queries, indexing, replication and sharding for scale and high performance.
- The core components of MongoDB are the mongod daemon and mongo shell used to connect and execute commands. Collections contain documents rather than rows/columns and support dynamic schemas.
Here are 3 key questions about MongoDB:
1. What is MongoDB? MongoDB is an open source, document-oriented, NoSQL database that provides high performance, high availability, and automatic scaling. It stores data in flexible, JSON-like documents, allowing for schema-less design.
2. How does MongoDB handle large data? MongoDB uses a concept called GridFS to break files into chunks and store metadata about the file in the database. This allows for efficient storage and retrieval of large files.
3. How does MongoDB scale? MongoDB scales horizontally by sharding data across multiple servers. It splits collections into chunks which can be distributed across shards. The balancer component monitors shard loads and migrates chunks between shards for improved distribution
This document provides an introduction to MongoDB, a non-relational NoSQL database. It discusses what NoSQL databases are and their benefits compared to SQL databases, such as being more scalable and able to handle large, changing datasets. It then describes key features of MongoDB like high performance, rich querying, and horizontal scalability. The document outlines concepts like document structure, collections, and CRUD operations in MongoDB. It also covers topics such as replication, sharding, and installing MongoDB.
This document provides information about MongoDB, including:
- MongoDB is a non-SQL database that stores data as flexible documents rather than rows and tables. It is suitable for large, unstructured datasets.
- Key features include document-oriented storage, full indexing support, replication for high availability, auto-sharding for scalability, and querying capabilities.
- CRUD operations like insert, find, update, and delete can be performed on MongoDB collections and documents using methods like db.collection.insert() and db.collection.find(). Aggregation operations allow computing results by processing documents.
This document provides an introduction and overview of MongoDB. It begins with defining what a database and NoSQL database are. MongoDB is introduced as a popular open-source document-oriented NoSQL database that stores data in BSON documents. The document outlines some key advantages of MongoDB like its flexibility and support for many programming languages. It then covers how to set up a local MongoDB server, perform basic CRUD operations, and query documents. Finally, it introduces MongoDB Atlas as a cloud database service that handles deploying and managing MongoDB in the cloud.
This document provides an overview of MongoDB including what MongoDB is, its advantages over SQL databases, different types of NoSQL databases, and basic CRUD operations in MongoDB using examples. Key points covered include MongoDB being a document-based and schema-less database, its advantages like scalability and flexibility with semi-structured data, the four main types of NoSQL databases, and examples of insert, find, update, and remove operations in MongoDB.
This document provides an overview of Database Jones, a Node.js API for highly scalable database access to MySQL Cluster. It introduces J.D. Duncan and Craig Russell, the creators of Database Jones, and describes how Database Jones provides an asynchronous JavaScript API that can be used with MySQL Cluster and other databases. It also summarizes the key features and capabilities of Database Jones, including its data modeling approaches, operations, and usage with Node.js applications.
This upload requires better support for ODP formatForest Mars
I uplopaded this version in Open Office .ODP format, which is presumably the reason slideshare messed up the formatting. Slideshare, can we get some better support for open formats, stat?
If you'd like to view these slides, I've re-uploaded this talk in .ppt format.
MongoDB - A next-generation database that lets you create applications never ...Ram Murat Sharma
MongoDB is a cross-platform document-oriented database. Classified as a NoSQL database, MongoDB eschews the traditional table-based relational database structure in favor of JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.
MongoDB is a document-oriented NoSQL database that stores data in flexible JSON-like documents. It does not enforce a schema on collections of documents and allows embedding related data. Key features include dynamic schemas, indexing, replication for high availability, and horizontal scaling through sharding of data across machines. Documents are organized into collections, databases are containers for collections, and the basic components include the _id field, collections, cursors, databases, documents, fields, and storage of data in JSON format.
MongoDB is a scalable, high-performance, open-source NoSQL database that uses documents with dynamic schemas instead of tables. It supports embedded documents and arrays, replication, and sharding. MongoDB is commonly used for web applications, content management, real-time analytics, and caching due to its fast performance for typical web operations. Some key companies using MongoDB in production include eBay, Craigslist, Foursquare, and Sourceforge.
James Johnson is the founder and president of the Inland Empire .NET User's Group. He is a three time Microsoft MVP in CAD and works as a software developer during the day and runs side projects at night. He gave a presentation on Entity Framework and code first development in .NET. He discussed Entity Framework concepts like POCO objects, the entity data model, and LINQ queries. He also covered code first development, scaffolding with MVC, and maintaining databases as the data model changes.
Entity Framework Database and Code FirstJames Johnson
James Johnson is the founder and president of the Inland Empire .NET User's Group. He is a three time Microsoft MVP in CAD and works as a software developer during the day and runs side projects at night. He gave a presentation on Entity Framework and code first development where he demonstrated how to scaffold controllers and views from classes to generate a basic web application with CRUD functionality and database access.
As lockdown restrictions eased, the survey found that:
1) More people were visiting outdoor spaces at least weekly compared to the initial lockdown period and the previous year.
2) Nearly 40% reported spending more time outdoors than the same period in 2019, with certain groups like younger people and families with children spending more.
3) Most people said they would continue spending meaningful time in nature, with around half expecting to visit outdoor spaces more after the pandemic ends.
This document presents results from surveys conducted in Scotland regarding participation in outdoor activities during COVID-19 lockdowns and easing of restrictions. Some key findings include:
- Walking, cycling, and outdoor exercise increased significantly compared to previous years. More people are traveling farther for outdoor activities as restrictions have eased.
- Participation in activities like walking, wildlife watching, and running increased the most, while activities like sightseeing and picnics remained lower.
- People report increased engagement with nature through activities like gardening and enjoying local wildlife. Many note increased benefits to mental health and well-being from outdoor time.
- Common problems encountered included issues with social distancing and inconsiderate behavior from others
This document discusses using document databases like CouchDB with TYPO3 Flow. It provides an overview of persistence basics in Flow and Doctrine ORM. It then covers using CouchDB as a document database, including its REST API, basics, and the TYPO3.CouchDB package. It notes limitations and introduces alternatives like Radmiraal.CouchDB that support multiple backends. Finally, it discusses future support for multiple persistence backends in Flow.
In this presentation, Raghavendra BM of Valuebound has discussed the basics of MongoDB - an open-source document database and leading NoSQL database.
----------------------------------------------------------
Get Socialistic
Our website: http://valuebound.com/
LinkedIn: http://bit.ly/2eKgdux
Facebook: https://www.facebook.com/valuebound/
Twitter: http://bit.ly/2gFPTi8
MongoDB is an open source document database, and the leading NoSQL database. MongoDB is a document oriented database that provides high performance, high availability, and easy scalability. It is Maintained and supported by 10gen.
- MongoDB is a schema-free document database that stores data in BSON format.
- It aims to bridge the gap between relational and non-relational databases by providing scalability and flexibility similar to non-relational databases while also supporting richer queries than typical key-value stores.
- MongoDB installations involve downloading the MongoDB software, setting up a data directory, starting the MongoDB process, and connecting to it using the mongo shell for basic CRUD operations on databases and collections of documents.
The document provides information about MongoDB including:
- MongoDB is an open-source, document-based NoSQL database that stores data in BSON format and collections instead of tables and rows.
- It has no schema and allows embedding of documents, dynamic queries, indexing, replication and sharding for scale and high performance.
- The core components of MongoDB are the mongod daemon and mongo shell used to connect and execute commands. Collections contain documents rather than rows/columns and support dynamic schemas.
Here are 3 key questions about MongoDB:
1. What is MongoDB? MongoDB is an open source, document-oriented, NoSQL database that provides high performance, high availability, and automatic scaling. It stores data in flexible, JSON-like documents, allowing for schema-less design.
2. How does MongoDB handle large data? MongoDB uses a concept called GridFS to break files into chunks and store metadata about the file in the database. This allows for efficient storage and retrieval of large files.
3. How does MongoDB scale? MongoDB scales horizontally by sharding data across multiple servers. It splits collections into chunks which can be distributed across shards. The balancer component monitors shard loads and migrates chunks between shards for improved distribution
This document provides an introduction to MongoDB, a non-relational NoSQL database. It discusses what NoSQL databases are and their benefits compared to SQL databases, such as being more scalable and able to handle large, changing datasets. It then describes key features of MongoDB like high performance, rich querying, and horizontal scalability. The document outlines concepts like document structure, collections, and CRUD operations in MongoDB. It also covers topics such as replication, sharding, and installing MongoDB.
This document provides information about MongoDB, including:
- MongoDB is a non-SQL database that stores data as flexible documents rather than rows and tables. It is suitable for large, unstructured datasets.
- Key features include document-oriented storage, full indexing support, replication for high availability, auto-sharding for scalability, and querying capabilities.
- CRUD operations like insert, find, update, and delete can be performed on MongoDB collections and documents using methods like db.collection.insert() and db.collection.find(). Aggregation operations allow computing results by processing documents.
This document provides an introduction and overview of MongoDB. It begins with defining what a database and NoSQL database are. MongoDB is introduced as a popular open-source document-oriented NoSQL database that stores data in BSON documents. The document outlines some key advantages of MongoDB like its flexibility and support for many programming languages. It then covers how to set up a local MongoDB server, perform basic CRUD operations, and query documents. Finally, it introduces MongoDB Atlas as a cloud database service that handles deploying and managing MongoDB in the cloud.
This document provides an overview of MongoDB including what MongoDB is, its advantages over SQL databases, different types of NoSQL databases, and basic CRUD operations in MongoDB using examples. Key points covered include MongoDB being a document-based and schema-less database, its advantages like scalability and flexibility with semi-structured data, the four main types of NoSQL databases, and examples of insert, find, update, and remove operations in MongoDB.
This document provides an overview of Database Jones, a Node.js API for highly scalable database access to MySQL Cluster. It introduces J.D. Duncan and Craig Russell, the creators of Database Jones, and describes how Database Jones provides an asynchronous JavaScript API that can be used with MySQL Cluster and other databases. It also summarizes the key features and capabilities of Database Jones, including its data modeling approaches, operations, and usage with Node.js applications.
This upload requires better support for ODP formatForest Mars
I uplopaded this version in Open Office .ODP format, which is presumably the reason slideshare messed up the formatting. Slideshare, can we get some better support for open formats, stat?
If you'd like to view these slides, I've re-uploaded this talk in .ppt format.
MongoDB - A next-generation database that lets you create applications never ...Ram Murat Sharma
MongoDB is a cross-platform document-oriented database. Classified as a NoSQL database, MongoDB eschews the traditional table-based relational database structure in favor of JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.
MongoDB is a document-oriented NoSQL database that stores data in flexible JSON-like documents. It does not enforce a schema on collections of documents and allows embedding related data. Key features include dynamic schemas, indexing, replication for high availability, and horizontal scaling through sharding of data across machines. Documents are organized into collections, databases are containers for collections, and the basic components include the _id field, collections, cursors, databases, documents, fields, and storage of data in JSON format.
MongoDB is a scalable, high-performance, open-source NoSQL database that uses documents with dynamic schemas instead of tables. It supports embedded documents and arrays, replication, and sharding. MongoDB is commonly used for web applications, content management, real-time analytics, and caching due to its fast performance for typical web operations. Some key companies using MongoDB in production include eBay, Craigslist, Foursquare, and Sourceforge.
James Johnson is the founder and president of the Inland Empire .NET User's Group. He is a three time Microsoft MVP in CAD and works as a software developer during the day and runs side projects at night. He gave a presentation on Entity Framework and code first development in .NET. He discussed Entity Framework concepts like POCO objects, the entity data model, and LINQ queries. He also covered code first development, scaffolding with MVC, and maintaining databases as the data model changes.
Entity Framework Database and Code FirstJames Johnson
James Johnson is the founder and president of the Inland Empire .NET User's Group. He is a three time Microsoft MVP in CAD and works as a software developer during the day and runs side projects at night. He gave a presentation on Entity Framework and code first development where he demonstrated how to scaffold controllers and views from classes to generate a basic web application with CRUD functionality and database access.
As lockdown restrictions eased, the survey found that:
1) More people were visiting outdoor spaces at least weekly compared to the initial lockdown period and the previous year.
2) Nearly 40% reported spending more time outdoors than the same period in 2019, with certain groups like younger people and families with children spending more.
3) Most people said they would continue spending meaningful time in nature, with around half expecting to visit outdoor spaces more after the pandemic ends.
This document presents results from surveys conducted in Scotland regarding participation in outdoor activities during COVID-19 lockdowns and easing of restrictions. Some key findings include:
- Walking, cycling, and outdoor exercise increased significantly compared to previous years. More people are traveling farther for outdoor activities as restrictions have eased.
- Participation in activities like walking, wildlife watching, and running increased the most, while activities like sightseeing and picnics remained lower.
- People report increased engagement with nature through activities like gardening and enjoying local wildlife. Many note increased benefits to mental health and well-being from outdoor time.
- Common problems encountered included issues with social distancing and inconsiderate behavior from others
The document discusses adaptations in animals. It explains that the Viceroy butterfly uses mimicry, a physical adaptation, to resemble the Monarch butterfly for protection. Behavioral adaptations allow animals to respond to life needs through actions and can be instinctive like finding shelter, or learned through environment interactions. Physical adaptations are body structures like the elephant's trunk, while behavioral adaptations are animals' actions that can be innate or acquired.
This document discusses physical and behavioral adaptations in animals. Physical adaptations are body structures that help animals find food, defend themselves, and reproduce, including camouflage, mimicry, body coverings, and chemical defenses. Behavioral adaptations are animals' actions, which can be instinctive behaviors that are innate or learned behaviors acquired through experience. Together, physical and behavioral adaptations allow animals to survive in their environments.
This document discusses animal adaptations, separating them into two categories: physical and behavioral. Physical adaptations are body structures that help animals survive, such as camouflage, mimicry, chemical defenses, and body coverings. Behavioral adaptations are animals' actions, either instinctive behaviors that are innate or learned behaviors acquired through experience. Examples of instinctive behaviors include finding shelter, gathering food, and raising young. Learned behaviors must be taught and cannot be passed genetically to offspring.
The document discusses different types of animal adaptations including physical and behavioral adaptations. Physical adaptations are body structures that help animals survive, such as camouflage, mimicry, body coverings, and chemical defenses. Behavioral adaptations are animals' actions, which can be instinctive behaviors that are innate or learned behaviors acquired through experience. Examples of instinctive behaviors include finding shelter and raising young, while learned adaptations must be taught.
This document provides an introduction and overview of document clustering techniques in information retrieval. It discusses motivations for clustering documents, such as improving search recall and organizing search results. It covers common clustering algorithms like K-means and hierarchical clustering, how they work, and considerations like choosing the number of clusters. The document uses examples and diagrams to illustrate clustering concepts and algorithms.
The document describes a 7 minute video field trip to Pearson Landfills and Recycling. It provides contact information for the Maine Department of Environmental Protection website for more information. The video gives a brief overview of operations at a landfill and recycling facility.
Landfills are constructed and operated to strict environmental standards to protect groundwater, with liners at the bottom. While landfilling waste is the lowest priority option, modern landfills are very different from old open dump areas as they carefully manage garbage in an engineered facility.
The document outlines Maine's waste hierarchy which prioritizes waste reduction and reuse above recycling, composting, processing and beneficial use, waste-to-energy, and landfilling as a last resort. It encourages reducing waste by avoiding unnecessary packaging and single-use items, reusing items to extend their lifespan, recycling recyclable materials, and composting organic waste to reduce landfilling. The hierarchy is designed to minimize environmental impacts and costs at each step.
The document discusses different ways that nature has been socially constructed and conceived. It outlines three fundamental meanings of nature: dualistic, monistic, and adverbial. It then describes four major ways nature has been conceived: as a collection, as a web of relationships, as a process, and as Gaia. Different constructions of nature lead to different views on environmental policy and human relationships with the natural world.
Comparative analysis between traditional aquaponics and reconstructed aquapon...bijceesjournal
The aquaponic system of planting is a method that does not require soil usage. It is a method that only needs water, fish, lava rocks (a substitute for soil), and plants. Aquaponic systems are sustainable and environmentally friendly. Its use not only helps to plant in small spaces but also helps reduce artificial chemical use and minimizes excess water use, as aquaponics consumes 90% less water than soil-based gardening. The study applied a descriptive and experimental design to assess and compare conventional and reconstructed aquaponic methods for reproducing tomatoes. The researchers created an observation checklist to determine the significant factors of the study. The study aims to determine the significant difference between traditional aquaponics and reconstructed aquaponics systems propagating tomatoes in terms of height, weight, girth, and number of fruits. The reconstructed aquaponics system’s higher growth yield results in a much more nourished crop than the traditional aquaponics system. It is superior in its number of fruits, height, weight, and girth measurement. Moreover, the reconstructed aquaponics system is proven to eliminate all the hindrances present in the traditional aquaponics system, which are overcrowding of fish, algae growth, pest problems, contaminated water, and dead fish.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMSIJNSA Journal
The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
3. Introduction
MongoDB is a cross-platform, document oriented database
It is a NoSQL database
It is open source
It provides high performance and scalability
It stores data in the form of key/value pairs (document)
It eliminates the need for Object Relational Mapping (ORM) in database development
4. MOngoDB stores data in form of BSON (binary JavaScript Object Notation) documents
{
name: “travis”,
salary: 30000,
designation: “Computer Scientist”,
teams: [ “front-end”, “database” ]
}
6. Important Features of MongoDB?
•Queries support: MongoDB supports ad-hoc and document-based queries.
•Index Support: All fields in the document are indexed.
•Replication: MongoDB possesses Master-Slave replication. It uses a native
application to preventing database downtime by maintaining multiple copies of
data.
•Multiple Servers: Duplicate data that is stored in the database is run over
multiple servers to avoid the damage caused due to hardware failure.
•Auto-sharding: The data is being distributed among several physical partitions
known as shards. MongoDB has an in-built feature called automatic load
balancing.
•MapReduce: It is a flexible aggregation tool that supports the MapReduce
function.
7. •Failure Handling: In MongoDB, works effectively in case of failures such as
multiple machine failures, data center failures by protecting data and making it
•GridFS: This feature will allow the files to divide into smaller parts and store
them in different documents without complicating the stack.
•Schema-less Database: MongoDB is a schema-less database programmed in
C++ language.
•Document-oriented Storage: It uses BSON format which is similar to JSON
•Procedures: MongoDB JavaScript works better than procedures as databases use
the language more than procedures.
8. NoSQL Database
•It is a non-relational database.
• No need to create tables, relations for storing data .
•This type of database is used to store web applications or large databases.
10. MongoDB does not have schema: We can insert the data in any order.
◦ We can see in the screenshot that the first collection (tuple) in the document (table) newdb the first tuple
has fields name and age while the second tuple had gender and name it is not mandatory to maintain a
structure in MongoDB.
13. Key Terms
Collection
◦ It is a group of MongoDB documents.
◦ It is the equivalent of an RDBMS table.
◦ A collection exists within a single database.
◦ Collections do not enforce a schema.
◦ Documents within a collection can have different fields.
Document
◦ A document is a set of key-value pairs.
◦ It have dynamic schema.
◦ Dynamic schema means that documents in the same collection do not need to have the same set of
fields or structure, and common fields in a collection's documents may hold different types of data.
14. Installation Process
Cloud : MongoDB Atlas
Stand-alone system – link
Install shell
Install compass
Install data tool (if needed)
15. Execution Process
◦ Run MongoDB’s database server from command prompt
◦ If we run the command “mongod”, it will activate the mongoDB database server which is running at port 27017.
16. ◦ Run MongoDB’s shell
◦ We run the “mongo” file, which is the MongoDB Shell, from a new command prompt window.
◦ This is where we feed the database server with commands such as creating a database or a collection and dropping collections.
17. Create Database
MongoDB uses the ‘use’ command to create a database.
If the database exists already, then it will be returned. Otherwise, a new database with the given
database name will be created.
Syntax: use <DATABASE_NAME>
Example : To create a database ‘movie’.
◦ use movie //This will create a new database called ‘movie’.
18. Drop Database
MongoDB uses the ‘db.dropDatabase()’ command to drop a database.
If the database exists already, then it will be dropped and true will be returned. Otherwise,
nothing will be dropped and 0 will be returned.
Syntax: db.dropDatabase()
Example:
◦ db.dropDatabase ()
19. Create Collection
A collection is what is referred to as a table in normal RDBMS.
It stores documents which may not be in the same structure.
A collection has various options such as setting maximum size and validating rules.
20. Syntax:
db.createCollection(name,options)
◦ Parameter :Name
This field is used to specify the name of the collection which you are creating.
◦ Parameter :Options
This field is used to specify particular configurations for the collection which you have
created.
21. Example
To create a database ‘movie’.
use movie //This will create a new database called ‘movie’.
To create collection ‘KMovies’
db.createCollection("KMovies", { capped : true, autoIndexId : true, size
:6142800, max : 10000 } )
This will now create a collection KMovies which is capped, auto indexed with specified size and
specified maximum number of documents.
22. This will now create a collection KMovies with capping, auto indexing, we will set the size to
6124800 and we will set the maximum number of documents to 10000.
23. Drop Collection
Since there are several collections in a particular database, we need to specify to MongoDB which collection we
are aiming to drop.
We use “show collections” to find out which all collections we have in our database.
Syntax: db.COLLECTION_NAME.drop()
Example : db.KMovies.drop()
24. Insert Document
This is used to insert several documents(tuples) into a collection(table)
If the collection is not available a new collection is created with the specified collection name
and documents are inserted into it.
Syntax
◦ db.collection_name.insert(document)
◦ // document parameter includes the column name and their values respectively, the rows are separated using {} and comma
operators.
29. Pretty() Command
This is used to display the contents of collection in a formatted way.
Syntax
◦ db.collection_name.find().pretty()
◦ //where collection_name(table name) is the name of the collection.
31. Update Document
This is used to modify the value of a certain column which is done using $set keyword.
Syntax
db.collection_name.update(selection_criteria,updated_value)
//where collection_name is the name of the collection, selection_criteria is which value
should be updated , updated_value is by what it should be updated.
33. Delete Document
This is used to delete the value of a certain column in a collection
Syntax
db.collection_name.remove(selection_criteria)
//where collection_name(table name) is the name of the collection, selection_criteria is which value should be deleted.
35. Projection
find() Command
This is used to display only selected columns, if there are five columns in a collection and we
want to display only three columns then this is possible using projection.
Syntax
db.collection_name.find({},{key:1})
◦ where collection_name is the name of the collection, key is the column name and 1 is specified ,
because that column should be displayed.
37. Atomic operations
FindAndModify() Command
This is used to modify certain fields of a document (tuple) in a collection (table).
Syntax
db.collection_name.FindAndModify(query,update)
◦ where collection_name is the name of the collection, query is the condition for which values
should be modified , update is updated values.
39. Limit() Method
This method is used to limit the number of records that we want to display.
Syntax
limit(number)
db.COLLECTION_NAME.find().limit(NUMBER)
Code
db.movie.find({},{“director”:1,_id:0}).limit(2) //this is used to display first two records;
40. Sort() Method
This method is used to sort the document in ascending/descending order. 1 is used for ascending
order while -1 is used for descending order.
Syntax
The basic syntax of sort() method is as follows −
db.COLLECTION_NAME.find().sort({KEY:1})
Code
db.movie.find({},{“director”:1,_id:0}).sort({“ratting”:-1}) //this is used to sort the records in
descending order ;
41. To query the document on the basis of some condition,
you can use following operations.[3]
42. MongoDB- Replication
Replication in mongoDB refers to creating and storing multiple copies of same data across
different servers.
This helps in data safety due to system failure or data loss at single server.
It also ensures redundancy and data availability at different locations
Client Application
Primary
Secondary Secondary Secondary
Replication Replication
Writes Reads
Replication
43. How replication works in MongoDB
Replication in mongoDB is achieved by replica set.
A replica is group of instances hosting the same data.
In a replica, one node is primary node that receives all write operations. All other instances,
such as secondaries, apply operations from the primary so that they have the same data set.
Replica set can have only one primary node.
44. MongoDB Aggregation
Aggregation operations group values from multiple documents together, and can perform a
variety of operations on the grouped data to return a single result.
It is similar to count(*) and group by in sql.
Syntax
Basic syntax of aggregate() method is as follows −
>db.COLLECTION_NAME.aggregate(AGGREGATE_OPERATION_TO_BE_DONE)
46. Aggregate Function
First filter on “AccType:S” and then group it on “CustID” and then compute the sum
of “AccBal” and then filter those documents wherein the “TotAccBal” is greater
than 1200, use the below syntax:
db.Customers.aggregate( { $match : {AccType : "S" } },
{ $group : { _id : "$CustID",TotAccBal : { $sum : "$AccBal" } } },
{ $match : {TotAccBal : { $gt : 1200 } }});
47. Expression Description Example
$sum Sums up the defined value from all the
documents in the collection.
db.movie.aggregate([{$group : {_id :
"$by_actor", movie_name : {$sum :
"$likes"}}}])
$avg Calculates the average of all the given
values in the documents of a
collection.
db.movie.aggregate([{$group : {_id :
"$by_actor", movie_name : {$avg :
"$likes"}}}])
$min Gets the minimum of the
corresponding values from all
documents in the collection.
db.movie.aggregate([{$group : {_id :
"$by_actor", movie_name : {$min :
"$likes"}}}])
48. Expression Description Example
$max Gets the maximum of the
corresponding values from all
documents in the collection.
db.movie.aggregate([{$group :
{_id : "$by_actor", movie_name :
{$max : "$likes"}}}])
$push Inserts the value to an array in the
resulting document.
db.movie.aggregate([{$group :
{_id : "$by_actor", movie_name :
{$push : "$likes"}}}])
$addToSet Inserts the value to an array in the
resulting document but does not
create duplicates.
db.movie.aggregate([{$group :
{_id : "$by_actor", movie_name :
{$addToSet : "$likes"}}}])
$First Gets the first document from the
source documents according to
the grouping. Typically this makes
only sense together with some
previously applied “$sort”-stage.
db.movie.aggregate([{$group :
{_id : "$by_actor", movie_name :
{$First : "$likes"}}}])
50. Insert Method
Create a collection by the name “Students” and store the following data in it.
db.Students.insert({_id:1, StudName:"Michelle Jacintha", Grade: "VII", Hobbies:
"Internet Surfing"});
51. Update Method
db.Students.update({_id:3, StudName:"Aryan David", Grade: "VII"},{$set:{Hobbies:
"Skating"}},{upsert:true});
Insert the document for “Aryan David” into the Students collection only if it does not
already exist in the collection. However, if it is already present in the collection, then
update the document with new values. (Update his Hobbies from “Skating” to
“Chess”.) Use “Update else insert” (if there is an existing document, it will attempt to
update it, if there is no existing document then it will insert it).
52. Find Method
To find those documents from the Students collection where the Hobbies is set to either
‘Chess’ or is set to ‘Skating’.
db.Students.find ({Hobbies :{ $in: ['Chess','Skating']}}).pretty ();
53. Find Method
To find documents from the Students collection where the StudName begins with “M”.
db.Students.find({StudName:/^M/}).pretty();
54. Find Method
To find documents from the Students collection where the StudName has an “e” in any
position.
db.Students.find({StudName:/e/}).pretty();
55. Find Method
To sort the documents from the Students collection in the descending order of
StudName.
db.Students.find().sort({StudName:-1}).pretty();
56. MongoDB – Help Command
To see the list of help for methods you can use on the db object, call the db.help() method:
db.help()
Example - Collection Help
db.collection.help()
57. Import csv / excel data
mongoimport –db <file name > --collection <collectionName> --type csv – <fileLocation.csv> --
headerline
mongo
Show dbs
Use <databaseNAme>
Show collection
Db.<collectionname>.findone()