This document provides an overview of Core Data including defining a data model with entities, attributes, and relationships. It also covers creating, fetching, updating, and deleting managed objects using Core Data and the managed object context. Key aspects of Core Data like the Core Data stack, persistent container, and data model editor are explained.
В докладе речь пойдет о внедрении WebSockets в масштабный проект: ~ 400 типов сущностей, высокая плотность информации (> 10K items on dashboard), и высокие требования к актуальности данных. Стек проекта: PHP, Laravel, MySQL, Redis, Beanstalkd, Ractivejs.
В докладе речь пойдет о внедрении WebSockets в масштабный проект: ~ 400 типов сущностей, высокая плотность информации (> 10K items on dashboard), и высокие требования к актуальности данных. Стек проекта: PHP, Laravel, MySQL, Redis, Beanstalkd, Ractivejs.
The agenda of the slides are to discuss some basic and in-depth details of MongoDB and NoSQL.
A snapshot of the topics discussed:
- Introduction to NoSQL and MongoDB
- Installation
- Queries
- Indexing
- Schema modeling
- Aggregation
This tutorial is an introduction to MongoDB and NoSQL. The tutorial includes an introduction to MongoDb and NoSQL, installation, queries related to MongoDB and NoSQL, aggregation framework, indexing of MongoDB and NoSQL and schema modelling. The tutorial begins with a section on introduction. This section includes an introduction to NoSQL, its data models like document model, graph model, key value etc. It also includes an introduction to MongoDB and its data model.
The introduction section is then followed by the installation section. This section includes installing MongoDB, default directory, starting MongoDB server, starting Mongo shell and more steps. It also includes adding documents. The next section is about queries related to MongoDB and NoSQL. This section includes query collection which are selecting all documents, find by example, use OR condition, use AND condition, update query. It also includes removing documents.
Then comes a section about aggregation framework. This section includes a brief about aggregation framework process and its samples. The next section is about indexing. This section involves indexing for speeding up of search and sorting, types of indexes like single field, compound field, multiple index etc. The last section of the tutorial is about schema modelling. This section includes schema design factors like rich documents, no mongo joins, no constraints, atomic operation etc.
Document databases are more flexible in many ways than relational databases and this presents both opportunities and challenges. Poorly designed document structures adversely affect performance, increase maintenance overhead, and lead to unnecessarily complex application code. This presentation describes 5 commonly used design patters in document databases: one-to-many, many-to-many, simple table inheritance, trees and lookup patterns.
NOSQL IMPLEMENTATION OF A CONCEPTUAL DATA MODEL: UML CLASS DIAGRAM TO A DOCUM...ijdms
The relational databases have shown their limits to the exponential increase in the volume of manipulated
and processed data. New NoSQL solutions have been developed to manage big data. These approaches are
an interesting way to build no-relational databases that can support large amounts of data. In this work,
we use conceptual data modeling (CDM), based on UML class diagrams, to create a logical structure of a
NoSQL database, taking account the relationships and constraints that determine how data can be stored
and accessible. The NoSQL logical data model obtained is based on the Document-Oriented Model
(DOM). to eliminate joins, a total and structured nesting is done on the collections of the documentoriented
database.
Rules of passage from the CDM to the Logical Oriented-Document Model (LODM) are also proposed in
this paper to transform the different types of associations between class. An application example of this
NoSQL BDD design method is realised to the case of an organization working in the e-commerce business
sector.
This presentation gives an overview of Elasticsearch going from the basics to complex things such as data modeling and JVM and cluster configuration and monitoring,
Query Analyzing
Introduction into indexes
Indexes In Mongo
Managing indexes in MongoDB
Using index to sort query results.
When should I use indexes.
When should we avoid using indexes.
Azure Table Storage: The Good, the Bad, the Ugly (10 min. lightning talk)Sirar Salih
The next best thing has arrived. Everyone is talking about Azure Table storage, the brand new NoSQL data service in the cloud. Schemaless and with JSON compatibility, it’s brand new, it’s simple and it does its job well. But everything great has its pitfalls.
Join me in this lightning session where we will take a look at and investigate the wonders and the mysteries, the shocks and the no-nos of using Azure Table storage. We will look at sample code setting up and using the storage in action. We will also, most notably, look at performance metrics comparing Azure Table storage to other data services. Is this truly the next best thing for you? Let’s find out!
MongoDB SoCal 2020: Best Practices for Working with IoT and Time-series DataMongoDB
Time series data is increasingly at the heart of modern applications - think IoT, stock trading, clickstreams, social media, and more. With the move from batch to real time systems, the efficient capture and analysis of time series data can enable organizations to better detect and respond to events ahead of their competitors or to improve operational efficiency to reduce cost and risk. Working with time series data is often different from regular application data, and there are best practices you should observe.
This talk covers:
Common components of an IoT solution
The challenges involved with managing time-series data in IoT applications
Different schema designs, and how these affect memory and disk utilization – two critical factors in application performance.
How to query, analyze and present IoT time-series data using MongoDB Compass and MongoDB Charts
At the end of the session, you will have a better understanding of key best practices in managing IoT time-series data with MongoDB.
The agenda of the slides are to discuss some basic and in-depth details of MongoDB and NoSQL.
A snapshot of the topics discussed:
- Introduction to NoSQL and MongoDB
- Installation
- Queries
- Indexing
- Schema modeling
- Aggregation
This tutorial is an introduction to MongoDB and NoSQL. The tutorial includes an introduction to MongoDb and NoSQL, installation, queries related to MongoDB and NoSQL, aggregation framework, indexing of MongoDB and NoSQL and schema modelling. The tutorial begins with a section on introduction. This section includes an introduction to NoSQL, its data models like document model, graph model, key value etc. It also includes an introduction to MongoDB and its data model.
The introduction section is then followed by the installation section. This section includes installing MongoDB, default directory, starting MongoDB server, starting Mongo shell and more steps. It also includes adding documents. The next section is about queries related to MongoDB and NoSQL. This section includes query collection which are selecting all documents, find by example, use OR condition, use AND condition, update query. It also includes removing documents.
Then comes a section about aggregation framework. This section includes a brief about aggregation framework process and its samples. The next section is about indexing. This section involves indexing for speeding up of search and sorting, types of indexes like single field, compound field, multiple index etc. The last section of the tutorial is about schema modelling. This section includes schema design factors like rich documents, no mongo joins, no constraints, atomic operation etc.
Document databases are more flexible in many ways than relational databases and this presents both opportunities and challenges. Poorly designed document structures adversely affect performance, increase maintenance overhead, and lead to unnecessarily complex application code. This presentation describes 5 commonly used design patters in document databases: one-to-many, many-to-many, simple table inheritance, trees and lookup patterns.
NOSQL IMPLEMENTATION OF A CONCEPTUAL DATA MODEL: UML CLASS DIAGRAM TO A DOCUM...ijdms
The relational databases have shown their limits to the exponential increase in the volume of manipulated
and processed data. New NoSQL solutions have been developed to manage big data. These approaches are
an interesting way to build no-relational databases that can support large amounts of data. In this work,
we use conceptual data modeling (CDM), based on UML class diagrams, to create a logical structure of a
NoSQL database, taking account the relationships and constraints that determine how data can be stored
and accessible. The NoSQL logical data model obtained is based on the Document-Oriented Model
(DOM). to eliminate joins, a total and structured nesting is done on the collections of the documentoriented
database.
Rules of passage from the CDM to the Logical Oriented-Document Model (LODM) are also proposed in
this paper to transform the different types of associations between class. An application example of this
NoSQL BDD design method is realised to the case of an organization working in the e-commerce business
sector.
This presentation gives an overview of Elasticsearch going from the basics to complex things such as data modeling and JVM and cluster configuration and monitoring,
Query Analyzing
Introduction into indexes
Indexes In Mongo
Managing indexes in MongoDB
Using index to sort query results.
When should I use indexes.
When should we avoid using indexes.
Azure Table Storage: The Good, the Bad, the Ugly (10 min. lightning talk)Sirar Salih
The next best thing has arrived. Everyone is talking about Azure Table storage, the brand new NoSQL data service in the cloud. Schemaless and with JSON compatibility, it’s brand new, it’s simple and it does its job well. But everything great has its pitfalls.
Join me in this lightning session where we will take a look at and investigate the wonders and the mysteries, the shocks and the no-nos of using Azure Table storage. We will look at sample code setting up and using the storage in action. We will also, most notably, look at performance metrics comparing Azure Table storage to other data services. Is this truly the next best thing for you? Let’s find out!
MongoDB SoCal 2020: Best Practices for Working with IoT and Time-series DataMongoDB
Time series data is increasingly at the heart of modern applications - think IoT, stock trading, clickstreams, social media, and more. With the move from batch to real time systems, the efficient capture and analysis of time series data can enable organizations to better detect and respond to events ahead of their competitors or to improve operational efficiency to reduce cost and risk. Working with time series data is often different from regular application data, and there are best practices you should observe.
This talk covers:
Common components of an IoT solution
The challenges involved with managing time-series data in IoT applications
Different schema designs, and how these affect memory and disk utilization – two critical factors in application performance.
How to query, analyze and present IoT time-series data using MongoDB Compass and MongoDB Charts
At the end of the session, you will have a better understanding of key best practices in managing IoT time-series data with MongoDB.
Building nTier Applications with Entity Framework Services (Part 1)David McCarter
Learn how to build real world nTier applications with the new Entity Framework and related services. With this new technology built into .NET, you can easily wrap an object model around your database and have all the data access automatically generated or use your own stored procedures and views. The session will demonstrate how to create and consume these new technologies from the ground up and focus on database modeling including views and stored procedures along with coding against the model via LINQ. Dynamic data website will also be demonstrated. Lots of code! Make sure to attend Part 2.
Building nTier Applications with Entity Framework Services (Part 1)David McCarter
Learn how to build real world nTier applications with the new Entity Framework and related services. With this new technology built into .NET, you can easily wrap an object model around your database and have all the data access automatically generated or use your own stored procedures and views. The session will demonstrate how to create and consume these new technologies from the ground up and focus on database modeling including views and stored procedures along with coding against the model via LINQ. Dynamic data website will also be demonstrated.
Being RDBMS Free -- Alternate Approaches to Data PersistenceDavid Hoerster
The general thinking is that when you create a new application, your data will be persisted into an RDBMS like SQL Server. But with the advent of NoSQL solutions, document databases, key-value stores and other options, do you really need an RDBMS for your application? In this session we’ll look at some alternatives to your persistence solution by looking at utilizing NoSQL solutions like Mongo, search services like Solr, key-value stores and other approaches to data persistence. By the end of this session, you’ll rethink how your applications will store data in the future.
WebP is an image file format created by the web performance team at Google, developed as a replacement for JPEG, PNG, and GIF, while supporting good compression, transparency, and animations.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
2. Agenda
● Overview
● Core Data stack
● Data Model Editor
○ Entity
○ Attributes
○ Relationships
● Creating and Saving Managed Objects
● Fetching Objects
● Reference
3. Core Data Overview
● Core Data is a framework that you use to manage the model layer objects
in your application.
● Core Data's focus is on objects rather than the traditional table-driven
relational database approach.
● Core Data typically decreases by 50 to 70 percent the amount of code you
write to support the model layer.
4. Different between SQLite and Core Data
● SQLite
○ SQLite is, as advertised, lightweight.
○ SQLite uses less memory and storage space.
○ SQLite can be tedious and error-prone to code.
○ SQLite is supported on Android and Microsoft Windows Phone.
● Core Data
○ Longer learning curve: it takes some study to understand.
○ Objects are easier to work with.
○ Underlying storage details are handled atomically (support for iCloud).
○ Undo and Redo features.
14. Attribute Type
Name Value Validation
Undefined - -
Integer 16 -32768 ~ 32767 Range, Default Value
Integer 32 -2147483648 ~ 2147483647 Range, Default Value
Integer 64
–9223372036854775808 ~
9223372036854775807
Range, Default Value
Decimal base-10 arithmetic Range, Default Value
Double 64-bit floating-point number Range, Default Value
15. Attribute Type
Name Value Validation
Float 32-bit floating-point number Range, Default Value
String String
String Length, Default Value,
Regular expression
Boolean true or false Default Value
Date Date Date range, Default Date
Binary Data NSData -
Transformable
NSValueTransformer to convert
to/from NSData
-
37. Saving NSManagedObject Instances
do {
try managedObjectContext.save()
} catch {
let nserror = error as NSError
NSLog("Unresolved error (nserror), (nserror.userInfo)")
abort()
}
38. Fetching NSManagedObject Instances
let fetchRequest = NSFetchRequest<Groups>(entityName: "Groups")
do {
let fetchedGroups = try
managedObjectContext.fetch(fetchRequest)
} catch {
fatalError("Failed to fetch groups: (error)")
}
39. Filtering Results
let fetchRequest = NSFetchRequest<Groups>(entityName: "Groups")
let groupName = "Figures"
fetchRequest.predicate = NSPredicate(format: "filterGroupName ==
%@", groupName)
managedObjectContext.fetch(fetchRequest)
40. Sorting Results
let fetchRequest = NSFetchRequest<Groups>(entityName: "Groups")
let sortDescriptor = NSSortDescriptor(key: "rank", ascending: true)
fetchRequest.sortDescriptors = [sortDescriptor]
managedObjectContext.fetch(fetchRequest)
41. Updating Objects
let fetchRequest = NSFetchRequest<Groups>(entityName: "Groups")
fetchRequest.predicate = NSPredicate(format: "filterGroupKey ==
%@", groupKey)
let groups = managedObjectContext.fetch(fetchRequest)
if groups.count > 0 {
groups[0].rank = 10
}
42. Deleting Objects
let fetchRequest = NSFetchRequest<Groups>(entityName: "Groups")
fetchRequest.predicate = NSPredicate(format: "filterGroupKey ==
%@", groupKey)
let groups = managedObjectContext.fetch(fetchRequest)
for group in groups {
managedObjectContext.deleteObject(group)
}
43. Reference
● The Swift Programming Language (Swift 3.0.1)
● Core Data Programming Guide
● iOS Data Storage: Core Data vs. SQLite
● Core Data Relationships and Delete Rules
● Core-data-fundamentals
● 【Swift】Core Dataの使い方。