Presentation about Components.js, a semantic dependency injection framework, at The Web Conference 2018 (Developers Track).
https://github.com/LinkedSoftwareDependencies/Components.js
The document provides instructions on how to install and use ElasticSearch, an open-source search and analytics engine. It demonstrates how to index and query sample data, perform aggregations, and configure analyzers. Bulk insertion of sample car transaction data is also shown from a GitHub dataset for running queries.
This document provides a summary of Elasticsearch by Tom Chen. It discusses that Elasticsearch is a powerful open source search and analytics engine that is distributed, scalable and real-time. It can be used for storing, searching and analyzing large volumes of data. The document then highlights some of Elasticsearch's key features, including its powerful search capabilities using Lucene queries, and aggregations that allow faceted searches and results. Code examples are provided to demonstrate indexing data and running searches and aggregations. Finally, the document mentions a code example on GitHub that uses Elasticsearch to build a search function for a WordPress site.
For the following questions, you will implement the data structure to.pdfarjunhassan8
For the following questions, you will implement the data structure to store information used by a
local car dealer. Each car has some information and stored in a text files called cars: Write a
main program for all questions to let the user enter, delete, search for information, and print
current cars stored in the data structure. Cars formatted so car records separated by a blank line.
Each record contains (in order, each in a single line): Make (manufacturer). Model, Year,
Mileage, Price. Implement a double linked-list to store cars data. Write a double linked-list class
including search, delete, append (to the head and tail), and remove (from the head and tail).
Implement a FIFO queue of car data using the double linked-list. You can use the double linked
list you wrote in Q1. Implement a max-heap of cars data that can extract the car with the highest
price. Write a max-heap class including heapify, build heap, extract, and insertion. Implement a
binary search tree of car data. Write a BST class including search, insertion, and deletion.
Solution
Cars.java
package pacages;
public class Cars {
String make;
String model;
int year;
double mileage;
double price;
// Setters and getters for the Cars member variables
public String getMake() {
return make;
}
public void setMake(String make) {
this.make = make;
}
public String getModel() {
return model;
}
public void setModel(String model) {
this.model = model;
}
public int getYear() {
return year;
}
public void setYear(int year) {
this.year = year;
}
public double getMileage() {
return mileage;
}
public void setMileage(double mileage) {
this.mileage = mileage;
}
public double getPrice() {
return price;
}
public void setPrice(double price) {
this.price = price;
}
public String toString()
{
return \"Make: \"+getMake()+ \" Model: \"+getModel()+ \" Year: \"+getYear() + \"
Mileage: \"+getMileage() + \" Price: \"+getPrice();
}
}
DoublyLinkedList.java
package pacages;
class Node
{
protected Cars data;
protected Node next, prev;
/* Constructor */
public Node()
{
next = null;
prev = null;
data = null;
}
/* Constructor */
public Node(Cars d, Node n, Node p)
{
data = d;
next = n;
prev = p;
}
/* Function to set link to next node */
public void setLinkNext(Node n)
{
next = n;
}
/* Function to set link to previous node */
public void setLinkPrev(Node p)
{
prev = p;
}
/* Funtion to get link to next node */
public Node getLinkNext()
{
return next;
}
/* Function to get link to previous node */
public Node getLinkPrev()
{
return prev;
}
/* Function to set data to node */
public void setData(Cars d)
{
data = d;
}
/* Function to get data from node */
public Cars getData()
{
return data;
}
}
/* Class linkedList */
public class DoublyLinkedList
{
protected Node start;
protected Node end ;
public int size;
/* Constructor */
public DoublyLinkedList()
{
start = null;
end = null;
size = 0;
}
/* Function to check if list is empty */
public boolean isEmpty()
{
return start == null;
}
/* Function to get size of list */
public.
The document discusses search engine optimization (SEO) techniques for Symfony developers. It covers technical SEO best practices like using valid HTML structure, secure pages, and meta tags. It also discusses how Symfony frameworks like Sonata and CMF handle SEO through bundles that generate meta tags and sitemaps. Structured data is another topic covered, with examples of markup for events and television channels.
Experience Mazda Zoom Zoom Lifestyle and Culture by Visiting and joining the Official Mazda Community at http://www.MazdaCommunity.org for additional insight into the Zoom Zoom Lifestyle and special offers for Mazda Community Members. If you live in Arizona, check out CardinaleWay Mazda's eCommerce website at http://www.Cardinale-Way-Mazda.com
Micronaut provides out-of-the-box integrations with a lot of tools and third-party libraries: Consul, Eureka, Hibernate, Kafka, Mongo, Micrometer, Zipkin, Hystrix, Swagger,... But sometimes this is not enough and you need to integrate with a new one.
In this talk, we will discuss the different options that we have to create a new configuration for Micronaut: bean factories, conditional beans, configuration properties,... and you will learn how to make the most out of it.
Streams or Loops? Java 8 Stream API by Niki Petkov - Proxiad BulgariaHackBulgaria
Presentation from the visit of Proxiad Bulgaria - partner for the Java Course in Hack Bulgaria.
The topic is the new Stream API in Java 8 and the presenter - Nikolay Petkov from Proxiad Bulgaria
The document discusses protocol-oriented programming in Swift. It begins by comparing protocols in Swift vs Objective-C, noting key differences like protocol inheritance, extensions, default implementations, and associated types in Swift. It then defines protocol-oriented programming as separating public interfaces from implementations using protocols that components communicate through. Examples are provided of using protocols for data types, dependency injection, testing, and real-world UIKit views. Protocol-oriented programming is said to improve reusability, extensibility, and maintainability over inheritance-based approaches.
The document provides instructions on how to install and use ElasticSearch, an open-source search and analytics engine. It demonstrates how to index and query sample data, perform aggregations, and configure analyzers. Bulk insertion of sample car transaction data is also shown from a GitHub dataset for running queries.
This document provides a summary of Elasticsearch by Tom Chen. It discusses that Elasticsearch is a powerful open source search and analytics engine that is distributed, scalable and real-time. It can be used for storing, searching and analyzing large volumes of data. The document then highlights some of Elasticsearch's key features, including its powerful search capabilities using Lucene queries, and aggregations that allow faceted searches and results. Code examples are provided to demonstrate indexing data and running searches and aggregations. Finally, the document mentions a code example on GitHub that uses Elasticsearch to build a search function for a WordPress site.
For the following questions, you will implement the data structure to.pdfarjunhassan8
For the following questions, you will implement the data structure to store information used by a
local car dealer. Each car has some information and stored in a text files called cars: Write a
main program for all questions to let the user enter, delete, search for information, and print
current cars stored in the data structure. Cars formatted so car records separated by a blank line.
Each record contains (in order, each in a single line): Make (manufacturer). Model, Year,
Mileage, Price. Implement a double linked-list to store cars data. Write a double linked-list class
including search, delete, append (to the head and tail), and remove (from the head and tail).
Implement a FIFO queue of car data using the double linked-list. You can use the double linked
list you wrote in Q1. Implement a max-heap of cars data that can extract the car with the highest
price. Write a max-heap class including heapify, build heap, extract, and insertion. Implement a
binary search tree of car data. Write a BST class including search, insertion, and deletion.
Solution
Cars.java
package pacages;
public class Cars {
String make;
String model;
int year;
double mileage;
double price;
// Setters and getters for the Cars member variables
public String getMake() {
return make;
}
public void setMake(String make) {
this.make = make;
}
public String getModel() {
return model;
}
public void setModel(String model) {
this.model = model;
}
public int getYear() {
return year;
}
public void setYear(int year) {
this.year = year;
}
public double getMileage() {
return mileage;
}
public void setMileage(double mileage) {
this.mileage = mileage;
}
public double getPrice() {
return price;
}
public void setPrice(double price) {
this.price = price;
}
public String toString()
{
return \"Make: \"+getMake()+ \" Model: \"+getModel()+ \" Year: \"+getYear() + \"
Mileage: \"+getMileage() + \" Price: \"+getPrice();
}
}
DoublyLinkedList.java
package pacages;
class Node
{
protected Cars data;
protected Node next, prev;
/* Constructor */
public Node()
{
next = null;
prev = null;
data = null;
}
/* Constructor */
public Node(Cars d, Node n, Node p)
{
data = d;
next = n;
prev = p;
}
/* Function to set link to next node */
public void setLinkNext(Node n)
{
next = n;
}
/* Function to set link to previous node */
public void setLinkPrev(Node p)
{
prev = p;
}
/* Funtion to get link to next node */
public Node getLinkNext()
{
return next;
}
/* Function to get link to previous node */
public Node getLinkPrev()
{
return prev;
}
/* Function to set data to node */
public void setData(Cars d)
{
data = d;
}
/* Function to get data from node */
public Cars getData()
{
return data;
}
}
/* Class linkedList */
public class DoublyLinkedList
{
protected Node start;
protected Node end ;
public int size;
/* Constructor */
public DoublyLinkedList()
{
start = null;
end = null;
size = 0;
}
/* Function to check if list is empty */
public boolean isEmpty()
{
return start == null;
}
/* Function to get size of list */
public.
The document discusses search engine optimization (SEO) techniques for Symfony developers. It covers technical SEO best practices like using valid HTML structure, secure pages, and meta tags. It also discusses how Symfony frameworks like Sonata and CMF handle SEO through bundles that generate meta tags and sitemaps. Structured data is another topic covered, with examples of markup for events and television channels.
Experience Mazda Zoom Zoom Lifestyle and Culture by Visiting and joining the Official Mazda Community at http://www.MazdaCommunity.org for additional insight into the Zoom Zoom Lifestyle and special offers for Mazda Community Members. If you live in Arizona, check out CardinaleWay Mazda's eCommerce website at http://www.Cardinale-Way-Mazda.com
Micronaut provides out-of-the-box integrations with a lot of tools and third-party libraries: Consul, Eureka, Hibernate, Kafka, Mongo, Micrometer, Zipkin, Hystrix, Swagger,... But sometimes this is not enough and you need to integrate with a new one.
In this talk, we will discuss the different options that we have to create a new configuration for Micronaut: bean factories, conditional beans, configuration properties,... and you will learn how to make the most out of it.
Streams or Loops? Java 8 Stream API by Niki Petkov - Proxiad BulgariaHackBulgaria
Presentation from the visit of Proxiad Bulgaria - partner for the Java Course in Hack Bulgaria.
The topic is the new Stream API in Java 8 and the presenter - Nikolay Petkov from Proxiad Bulgaria
The document discusses protocol-oriented programming in Swift. It begins by comparing protocols in Swift vs Objective-C, noting key differences like protocol inheritance, extensions, default implementations, and associated types in Swift. It then defines protocol-oriented programming as separating public interfaces from implementations using protocols that components communicate through. Examples are provided of using protocols for data types, dependency injection, testing, and real-world UIKit views. Protocol-oriented programming is said to improve reusability, extensibility, and maintainability over inheritance-based approaches.
Back to Basics Webinar 5: Introduction to the Aggregation FrameworkMongoDB
The document provides information about an upcoming webinar on the MongoDB aggregation framework. Key details include:
- The webinar will introduce the aggregation framework and provide an overview of its capabilities for analytics.
- Examples will use a real-world vehicle testing dataset to demonstrate aggregation pipeline stages like $match, $project, and $group.
- Attendees will learn how the aggregation framework provides a simpler way to perform analytics compared to other tools like Spark and Hadoop.
Webinar: Schema Patterns and Your Storage EngineMongoDB
How do MongoDB’s different storage options change the way you model your data?
Each storage engine, WiredTiger, the In-Memory Storage engine, MMAP V1 and other community supported drivers, persists data differently, writes data to disk in different formats and handles memory resources in different ways.
This webinar will go through how to design applications around different storage engines based on your use case and data access patterns. We will be looking into concrete examples of schema design practices that were previously applied on MMAPv1 and whether those practices still apply, to other storage engines like WiredTiger.
Topics for review: Schema design patterns and strategies, real-world examples, sizing and resource allocation of infrastructure.
R, Scikit-Learn and Apache Spark ML - What difference does it make?Villu Ruusmann
This document discusses different machine learning frameworks like R, Scikit-Learn, LightGBM, XGBoost, and Apache Spark ML and compares their capabilities for predictive modeling tasks. It highlights differences in how each framework handles data formats, parameter tuning, model serialization, and execution. It also presents a case study predicting car prices using gradient boosted trees in various frameworks and discusses lessons learned, emphasizing that ease-of-use and integration often outweigh raw performance.
Refresh Tallahassee: The RE/MAX Front End StoryRachael L Moore
Come join us downstairs at the Proof Brewing Company for another excellent evening of inspiration! Rachael Moore, the front-end lead on the new remax.com, has kindly agreed to share the story and take a peek under the hood of this massive (and really nicely done) site. Among the likely topics of discussion are: Object-oriented CSS, CSS preprocessors, JavaScript frameworks, and the ins and outs of working with a distributed team.
Attend this session if you want to get insight on some inner workings of the search engine within Jahia. Knowing the nuts and bolts will help you understand possibilities and limitations and help you to tune your queries. You will also learn about the improvements available with Jahia 7.
Webinar: MongoDB and Polyglot Persistence ArchitectureMongoDB
Polyglot persistence is about using multiple databases in concert with one another as part of a larger datastore ecosystem. The advantage is that your database layer uses a set of specialized tools to deliver overall value and functionality while simplifying data modeling by separating command and query responsibilities. The arrival of MongoDB and it’s flexible schemas further increases the possibilities of polyglot architectures.
The document discusses Entity Framework Code First concepts including entities, DbContext, DbSet, and navigation properties. It provides examples of how to map existing database tables to Code First classes using data annotations. It also demonstrates how to perform basic CRUD operations using Code First including adding, querying, updating and deleting records. The document shows how to generate a Code First model from an existing database as well as how to create an empty Code First model and map classes using data annotations and navigation properties.
Vortrag: Tobias Meier (ca. 90 Minuten) - „TypeScript”
JavaScript, früher lediglich zur Anreicherung von Webseiten verwendet, dient inzwischen als Programmiersprache für umfangreiche Applikationen. Allerdings sind viele Entwickler nicht ganz glücklich mit der Sprache und vermissen Features wie statische Typprüfungen oder Vererbung.
Auch die großen Konzerne haben mit diesen “Herausforderungen” zu kämpfen. Im Oktober 2012 hat Anders Hejlsberg, (Mit-)Erfinder von Delphi und .Net, TypeScript vorgestellt. Bei TypeScript handelt es sich um ein Superset von JavaScript, welches dieses um Klassen, Module, Interfaces, Datentypen u.ä. ergänzt.
Inzwischen hat auch das AngularJS-Team bekanntgegeben dass sie zukünftig auf TypeScript aufsetzen.
Tobias Meier stellt die aktuelle Version von TypeScript vor und zeigt, wie TypeScript uns sowohl bei der Entwicklung von Singe Page Applications als auch herkömmlichen Webapplikationen unterstützt.
Tobias Meier ist Lead Softwarearchitekt Microsoft bei der BridgingIT GmbH und setzt TypeScript bereits seit der ersten verfügbaren Preview erfolgreich in Kundenprojekten ein.
Full-Text Search Explained - Philipp Krenn - Codemotion Rome 2017Codemotion
Today’s applications are expected to provide powerful full-text search. But how does that work in general and how do I implement it on my site or in my application? Actually, this is not as hard as it sounds at first. This talk covers: * How full-text search works in general and what the differences to databases are. * How the score or quality of a search result is calculated. * How to implement this with Elasticsearch. Attendees will learn how to add common search patterns to their applications without breaking a sweat.
The document discusses SAP HANA, an in-memory database developed by SAP. It provides an overview of SAP HANA's hardware and software innovations, including its use of main memory and columnar storage. It also describes how SAP HANA uses analytical and calculation views to enable real-time analytics on large volumes of live transactional data.
The document provides specifications for the Comprehensive Auto Report (CAR) V2.0, including sections for the header, navigation bar, footer, brochure, inspection report, vehicle history report, and auto biography. It defines the data points and XML nodes needed to generate each section of the CAR from the CAR XML file. Implementation details like XSL templates and processes for reading the XML data are also provided.
This document provides an introduction to Apache Camel, an open source integration framework. It discusses how Camel hides integration complexity and focuses on business logic. It provides examples of content-based routing in XML and Java DSL. It also outlines the various components, data formats, languages and deployment options supported by Camel.
This document discusses DocumentDB, a NoSQL database offered by Microsoft Azure. It provides an overview of DocumentDB's data model, which uses JSON-like documents with a RESTful API. It also covers best practices for modeling data relations in DocumentDB through embedding or referencing other documents. The document also explores indexing and querying capabilities in DocumentDB, as well as consistency models and techniques for scaling collections in the database.
Design Patterns with Kotlin
This document discusses several design patterns and their implementations in Kotlin, including Creational patterns like Singleton, Factory Method, Abstract Factory, and Builder. Structural patterns covered include Facade, Decorator, and Adapter. For each pattern, examples are given in Java and converted to Kotlin. Benefits and drawbacks of the patterns are also summarized. The goal is to explain how to effectively apply common design patterns when programming in Kotlin.
Building Robust ETL Pipelines with Apache SparkDatabricks
Stable and robust ETL pipelines are a critical component of the data infrastructure of modern enterprises. ETL pipelines ingest data from a variety of sources and must handle incorrect, incomplete or inconsistent records and produce curated, consistent data for consumption by downstream applications. In this talk, we’ll take a deep dive into the technical details of how Apache Spark “reads” data and discuss how Spark 2.2’s flexible APIs; support for a wide variety of datasources; state of art Tungsten execution engine; and the ability to provide diagnostic feedback to users, making it a robust framework for building end-to-end ETL pipelines.
Inheritance - the myth of code reuse | Andrei Raifura | CodeWay 2015YOPESO
Watch this presentation if you want to know why inheritance is not always the most appropriate method for code reuse - and what to do instead.
Watch the video here:
https://www.youtube.com/watch?v=H6m0W-eDyAk
The code used for the demo:
https://github.com/yopeso/Inheritance
Poster Demonstration of Comunica, a Web framework for querying heterogeneous ...Ruben Taelman
This 3 sentence summary provides the high-level and essential information from the given document:
The document is a URL for http comunica.linkeddatafragments.org. It appears to be a website related to Linked Data Fragments, which is a technique for publishing and consuming subsets of RDF datasets on the web. However, without accessing the actual website content, no further conclusions can be drawn from the given document alone.
Poster GraphQL-LD: Linked Data Querying with GraphQLRuben Taelman
GraphQL is a popular JSON-like query language for graph-based data that can now be used to query Linked Data by converting GraphQL queries to SPARQL queries using a JSON-LD context. This allows GraphQL developers to query any SPARQL engine but GraphQL queries only have semantics over a single interface, whereas GraphQL queries combined with JSON-LD have universal semantics that enable federated querying over multiple Linked Data sources.
Back to Basics Webinar 5: Introduction to the Aggregation FrameworkMongoDB
The document provides information about an upcoming webinar on the MongoDB aggregation framework. Key details include:
- The webinar will introduce the aggregation framework and provide an overview of its capabilities for analytics.
- Examples will use a real-world vehicle testing dataset to demonstrate aggregation pipeline stages like $match, $project, and $group.
- Attendees will learn how the aggregation framework provides a simpler way to perform analytics compared to other tools like Spark and Hadoop.
Webinar: Schema Patterns and Your Storage EngineMongoDB
How do MongoDB’s different storage options change the way you model your data?
Each storage engine, WiredTiger, the In-Memory Storage engine, MMAP V1 and other community supported drivers, persists data differently, writes data to disk in different formats and handles memory resources in different ways.
This webinar will go through how to design applications around different storage engines based on your use case and data access patterns. We will be looking into concrete examples of schema design practices that were previously applied on MMAPv1 and whether those practices still apply, to other storage engines like WiredTiger.
Topics for review: Schema design patterns and strategies, real-world examples, sizing and resource allocation of infrastructure.
R, Scikit-Learn and Apache Spark ML - What difference does it make?Villu Ruusmann
This document discusses different machine learning frameworks like R, Scikit-Learn, LightGBM, XGBoost, and Apache Spark ML and compares their capabilities for predictive modeling tasks. It highlights differences in how each framework handles data formats, parameter tuning, model serialization, and execution. It also presents a case study predicting car prices using gradient boosted trees in various frameworks and discusses lessons learned, emphasizing that ease-of-use and integration often outweigh raw performance.
Refresh Tallahassee: The RE/MAX Front End StoryRachael L Moore
Come join us downstairs at the Proof Brewing Company for another excellent evening of inspiration! Rachael Moore, the front-end lead on the new remax.com, has kindly agreed to share the story and take a peek under the hood of this massive (and really nicely done) site. Among the likely topics of discussion are: Object-oriented CSS, CSS preprocessors, JavaScript frameworks, and the ins and outs of working with a distributed team.
Attend this session if you want to get insight on some inner workings of the search engine within Jahia. Knowing the nuts and bolts will help you understand possibilities and limitations and help you to tune your queries. You will also learn about the improvements available with Jahia 7.
Webinar: MongoDB and Polyglot Persistence ArchitectureMongoDB
Polyglot persistence is about using multiple databases in concert with one another as part of a larger datastore ecosystem. The advantage is that your database layer uses a set of specialized tools to deliver overall value and functionality while simplifying data modeling by separating command and query responsibilities. The arrival of MongoDB and it’s flexible schemas further increases the possibilities of polyglot architectures.
The document discusses Entity Framework Code First concepts including entities, DbContext, DbSet, and navigation properties. It provides examples of how to map existing database tables to Code First classes using data annotations. It also demonstrates how to perform basic CRUD operations using Code First including adding, querying, updating and deleting records. The document shows how to generate a Code First model from an existing database as well as how to create an empty Code First model and map classes using data annotations and navigation properties.
Vortrag: Tobias Meier (ca. 90 Minuten) - „TypeScript”
JavaScript, früher lediglich zur Anreicherung von Webseiten verwendet, dient inzwischen als Programmiersprache für umfangreiche Applikationen. Allerdings sind viele Entwickler nicht ganz glücklich mit der Sprache und vermissen Features wie statische Typprüfungen oder Vererbung.
Auch die großen Konzerne haben mit diesen “Herausforderungen” zu kämpfen. Im Oktober 2012 hat Anders Hejlsberg, (Mit-)Erfinder von Delphi und .Net, TypeScript vorgestellt. Bei TypeScript handelt es sich um ein Superset von JavaScript, welches dieses um Klassen, Module, Interfaces, Datentypen u.ä. ergänzt.
Inzwischen hat auch das AngularJS-Team bekanntgegeben dass sie zukünftig auf TypeScript aufsetzen.
Tobias Meier stellt die aktuelle Version von TypeScript vor und zeigt, wie TypeScript uns sowohl bei der Entwicklung von Singe Page Applications als auch herkömmlichen Webapplikationen unterstützt.
Tobias Meier ist Lead Softwarearchitekt Microsoft bei der BridgingIT GmbH und setzt TypeScript bereits seit der ersten verfügbaren Preview erfolgreich in Kundenprojekten ein.
Full-Text Search Explained - Philipp Krenn - Codemotion Rome 2017Codemotion
Today’s applications are expected to provide powerful full-text search. But how does that work in general and how do I implement it on my site or in my application? Actually, this is not as hard as it sounds at first. This talk covers: * How full-text search works in general and what the differences to databases are. * How the score or quality of a search result is calculated. * How to implement this with Elasticsearch. Attendees will learn how to add common search patterns to their applications without breaking a sweat.
The document discusses SAP HANA, an in-memory database developed by SAP. It provides an overview of SAP HANA's hardware and software innovations, including its use of main memory and columnar storage. It also describes how SAP HANA uses analytical and calculation views to enable real-time analytics on large volumes of live transactional data.
The document provides specifications for the Comprehensive Auto Report (CAR) V2.0, including sections for the header, navigation bar, footer, brochure, inspection report, vehicle history report, and auto biography. It defines the data points and XML nodes needed to generate each section of the CAR from the CAR XML file. Implementation details like XSL templates and processes for reading the XML data are also provided.
This document provides an introduction to Apache Camel, an open source integration framework. It discusses how Camel hides integration complexity and focuses on business logic. It provides examples of content-based routing in XML and Java DSL. It also outlines the various components, data formats, languages and deployment options supported by Camel.
This document discusses DocumentDB, a NoSQL database offered by Microsoft Azure. It provides an overview of DocumentDB's data model, which uses JSON-like documents with a RESTful API. It also covers best practices for modeling data relations in DocumentDB through embedding or referencing other documents. The document also explores indexing and querying capabilities in DocumentDB, as well as consistency models and techniques for scaling collections in the database.
Design Patterns with Kotlin
This document discusses several design patterns and their implementations in Kotlin, including Creational patterns like Singleton, Factory Method, Abstract Factory, and Builder. Structural patterns covered include Facade, Decorator, and Adapter. For each pattern, examples are given in Java and converted to Kotlin. Benefits and drawbacks of the patterns are also summarized. The goal is to explain how to effectively apply common design patterns when programming in Kotlin.
Building Robust ETL Pipelines with Apache SparkDatabricks
Stable and robust ETL pipelines are a critical component of the data infrastructure of modern enterprises. ETL pipelines ingest data from a variety of sources and must handle incorrect, incomplete or inconsistent records and produce curated, consistent data for consumption by downstream applications. In this talk, we’ll take a deep dive into the technical details of how Apache Spark “reads” data and discuss how Spark 2.2’s flexible APIs; support for a wide variety of datasources; state of art Tungsten execution engine; and the ability to provide diagnostic feedback to users, making it a robust framework for building end-to-end ETL pipelines.
Inheritance - the myth of code reuse | Andrei Raifura | CodeWay 2015YOPESO
Watch this presentation if you want to know why inheritance is not always the most appropriate method for code reuse - and what to do instead.
Watch the video here:
https://www.youtube.com/watch?v=H6m0W-eDyAk
The code used for the demo:
https://github.com/yopeso/Inheritance
Poster Demonstration of Comunica, a Web framework for querying heterogeneous ...Ruben Taelman
This 3 sentence summary provides the high-level and essential information from the given document:
The document is a URL for http comunica.linkeddatafragments.org. It appears to be a website related to Linked Data Fragments, which is a technique for publishing and consuming subsets of RDF datasets on the web. However, without accessing the actual website content, no further conclusions can be drawn from the given document alone.
Poster GraphQL-LD: Linked Data Querying with GraphQLRuben Taelman
GraphQL is a popular JSON-like query language for graph-based data that can now be used to query Linked Data by converting GraphQL queries to SPARQL queries using a JSON-LD context. This allows GraphQL developers to query any SPARQL engine but GraphQL queries only have semantics over a single interface, whereas GraphQL queries combined with JSON-LD have universal semantics that enable federated querying over multiple Linked Data sources.
Poster Declaratively Describing Responses of Hypermedia-Driven Web APIsRuben Taelman
The document discusses how hypermedia-driven web APIs can declaratively describe responses using vocabularies like Hydra and SHACL. While Hydra allows declaring input parameters, it does not specify the output or response from an API call. The document proposes some solutions like using custom types, SHACL shapes, or SPIN SPARQL queries to declaratively represent both the input and output of API calls in a standard or non-standard vocabulary. This would allow machines to understand and predict the responses from following hypermedia controls.
VTPF is a feature for the Triple Pattern Fragments interface that allows for low-cost querying of RDF archives at specific versions, between versions, and for versions without requiring separate, costly interfaces per version. It introduces hypermedia controls for versioned queries and represents changesets and versionsets in RDF/HTML. The interface supports three types of triple pattern queries for versioning information.
This document discusses versioned triple pattern fragments (VTPF), a proposed interface for querying RDF archives at web scale using triple pattern fragments. VTPF adds versioning features to TPF to support version materialization, delta materialization, and version queries over archived RDF data. It introduces a "version" vocabulary to represent versions as separate datasets and includes human-readable and machine-readable hypermedia controls for the different query types. While progress has been made, an open challenge remains to standardize the mapping to RDF archive query languages and appropriate backend storage solutions.
PoDiGG: Public Transport Dataset Generator based on Population DistributionsRuben Taelman
PoDiGG is a public transport dataset generator that creates synthetic public transport networks based on population distributions. It positions stops, connects them with edges, creates synthetic routes, instantiates timely trips, and serializes the data to GTFS or RDF formats. The generator allows flexibility in dataset size, network density, number of stops, and other properties for benchmarking and testing purposes.
Exposing RDF Archives using Triple Pattern FragmentsRuben Taelman
This document discusses using the Triple Pattern Fragments (TPF) framework to expose RDF archives and support querying historical data in order to make large knowledge bases more discoverable. It proposes extending the TPF interface to support different query types about temporal data, using storage solutions that balance client load, server load, and storage cost for the various query types and versions of data, and developing client-side methods for handling different data versions.
EKAW - Publishing with Triple Pattern FragmentsRuben Taelman
Slides for the presentation on Publishing with Triple Pattern Fragments in the Modeling, Generating and Publishing knowledge as Linked Data tutorial at EKAW 2016.
This document provides an introduction to Docker. It describes Docker as a platform for running software in isolated containers. It discusses how Docker allows running multiple software versions simultaneously and makes software easily installable and disposable. It covers Docker concepts like images, containers, Dockerfiles for building images, and running containers from images. It also discusses Docker networking, Docker Compose for defining multi-container apps, and tools for monitoring Docker performance and usage.
Multidimensional Interfaces for Selecting Data with OrderRuben Taelman
This document discusses a multidimensional interface for querying linked data with low server cost. It proposes moving the data index to the client by exposing it through an HTTP interface, similar to Memento's time gate but supporting multiple dimensions. This would allow clients to navigate the index and retrieve range fragments to perform custom searches locally. Some examples are provided to illustrate querying points within ranges in a 2D index. While client-side indexing may be useful for types with many instances, trade-offs exist between client and server costs that depend on factors like index and range fragment sizes. The authors plan to experiment with different methods for exposing multidimensional data indexes.
Scalable Dynamic Data Consumption on the WebRuben Taelman
The document discusses reducing server load for dynamic web data by moving continuous query evaluation from servers to clients. It proposes doing this through three steps: scalable data storage and publication, efficient data transmission using compression and caching, and continuous evaluation on clients. Several research questions are posed around how to combine publication of real-time and historical data to make it queryable efficiently while storing it in a way that allows efficient data transfer and enabling client-side query evaluation over both static and dynamic data. Hypotheses are made that new data can be stored and retrieved linearly based on amounts, and that server costs will be lower than alternatives with data transfer being the main factor influencing query times.
Moving RDF Stream Processing to the ClientRuben Taelman
Stream-processing SPARQL endpoints hosted on web servers are expensive due to an unknown number of clients, unbounded query complexity, and the server doing all the work while clients wait for results. Publishing dynamic data with Triple Pattern Fragments and making clients contribute more to the processing addresses this by annotating triples with timestamps, having clients re-evaluate queries as needed based on the timestamps, and designing the server interface to handle simple requests while putting most of the work on clients.
Querying Dynamic Datasources with Continuously Mapped Sensor DataRuben Taelman
Triple Pattern Fragments and continuous ETL processes are used to publish raw sensor data as RDF on the web and allow clients to query current temperature and humidity readings through a lightweight query interface. Sensor measurements are extracted, transformed by adding metadata on measurement time, and loaded as RDF which is then queried using SPARQL to retrieve live temperature and humidity values from a sensor.
Continuous Self-Updating Query Results over Dynamic Linked DataRuben Taelman
This document discusses continuously updating query results over dynamic linked data. It proposes moving continuous query evaluation from the server to the client to lower server load. Key points:
- Dynamic linked data streams, like sensor data, add new triples over time and typically query the current value.
- Existing approaches have servers continuously evaluate queries, causing low availability due to high load.
- The document proposes storing dynamic data efficiently, transmitting it to clients, and having clients evaluate queries to reduce server load.
- A preliminary test showed the proposed approach moves more load to clients but scales server load better than existing solutions that rely on continuous server-side query evaluation.
Continuously Updating Query Results over Real-Time Linked DataRuben Taelman
This document discusses continuously updating query results over real-time linked data. It proposes moving continuous query evaluation from the server to the client to lower server load. Dynamic data is represented in RDF and annotated with time validity using methods like reification, graphs or implicit graphs. A query streamer engine exposes dynamic data through a Triple Pattern Fragments interface and sends query results to clients, offloading work from the server. An evaluation compares annotation methods, measures query execution times and server CPU usage, finding the query streamer approach has better scalability by distributing load to clients.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
OpenID AuthZEN Interop Read Out - AuthorizationDavid Brossard
During Identiverse 2024 and EIC 2024, members of the OpenID AuthZEN WG got together and demoed their authorization endpoints conforming to the AuthZEN API
AI-Powered Food Delivery Transforming App Development in Saudi Arabia.pdfTechgropse Pvt.Ltd.
In this blog post, we'll delve into the intersection of AI and app development in Saudi Arabia, focusing on the food delivery sector. We'll explore how AI is revolutionizing the way Saudi consumers order food, how restaurants manage their operations, and how delivery partners navigate the bustling streets of cities like Riyadh, Jeddah, and Dammam. Through real-world case studies, we'll showcase how leading Saudi food delivery apps are leveraging AI to redefine convenience, personalization, and efficiency.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceIndexBug
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
5. Hard-wiring: Instantiate programmatically
let myCar = new Porsche356B({
color: 'ruby red',
engine: new V8Engine(),
tireFrontLeft: new MichelinLTXMS2(),
tireFrontRight: new MichelinLTXMS2(),
tireBackLeft: new MichelinLTXMS2(),
tireBackRight: new MichelinLTXMS2(),
});
myCar.drive();
+ Easy
- Less flexible swapping of components
6. Dependency Injection to the rescue!
let myCar = new Porsche356B({
color: 'ruby red',
engine: new V8Engine(),
tireFrontLeft: new MichelinLTXMS2(),
tireFrontRight: new MichelinLTXMS2(),
tireBackLeft: new MichelinLTXMS2(),
tireBackRight: new MichelinLTXMS2(),
});
myCar.drive();
7. Soft-wiring with declarative instantiation
let myCar = Loader.load('myCar-config.json');
myCar.drive();
+ Flexible swapping of components
- Extra layer of complexity
10. Components.js Terminology
Collection of components (e.g., a software package)
Something that can be instantiated (e.g., a class)
An instantiated Component
Module
Component
Instance
16. Get your hands on Components.js
https://www.npmjs.com/package/componentsjs
https://github.com/LinkedSoftwareDependencies/Components.js
https://componentsjs.readthedocs.io/
17. Ruben Taelman - @rubensworks
imec - Ghent University
Components.js
A semantic dependency injection framework
20. Why semantic configuration files?
Unique identification of components and instances via URIs
Split up config files, combine over the Web
Config files are meaningful as they use standard vocabularies
All of the benefits of Linked Data
Any RDF-enabled application can work with these config files
Visualize the instance graph
Reasoners can check if parameter values are valid
Reasoners can generate a config file best suited for a given situation
SPARQL querying over your config file