Java 8 supports lambdas. It's API also comes with Streams support.
But Knowing some concepts on Functional Programming may help you get a lot more from what this new version of Java has to offer.
Stacks have several application areas including:
1) When functions are called to save return addresses and local variables.
2) To convert infix expressions to postfix form by acting as a placeholder.
3) To evaluate postfix expressions by holding operands and intermediate results.
The document discusses stacks and their properties. It defines a stack as a linear data structure where items are inserted and deleted from one end, following the LIFO (last in, first out) principle. Stacks are commonly used in computer systems for tasks like compiler operations and process scheduling. The key stack operations are push to insert an item and pop to remove the top item.
This document provides an introduction to basic concepts in R including how to download and install R, get started with the R console, define variables and functions, perform vector and matrix operations, and import/export data. Key points covered include using R for statistics and math operations, creating vectors through functions like c(), :, and seq(), and creating matrices from vectors using functions like matrix(), cbind(), and rbind(). Common functions for summarizing vectors and matrices are also outlined.
This document summarizes a lecture on stacks from a data structures course. It defines stacks as ordered groups where elements are added and removed from the top in LIFO order. It describes basic stack operations like push, pop, and status checks. Stacks can be represented using arrays or linked lists. Array representations require tracking the top index, while linked lists use nodes connected by pointers. Pushing adds an element to the top, while popping removes from the top.
Presented at the Second openCypher Implementers Meeting in London, UK, May 2017 @ http://www.opencypher.org/blog/2017/06/13/ocim2-blog/
A stack is a linear data structure that follows the LIFO (last-in, first-out) principle. Elements can only be inserted or removed from one end, called the top. The basic stack operations are push to insert, pop to remove, peek to examine without removing, and functions to check if the stack is empty or full. Stacks have applications in undo/redo functions, function calls, expression conversions, the Tower of Hanoi problem, and reversing strings or lists.
A humble introduction to ROP chaining basics. The ppt deals with what is ROP. It builds the basics by introducing basics of buffer overflow and then talks about ROPs and why they are needed. It also has animated videos to help understand the layout of the stack clearly.
The Compatibility Challenge:Examining R and Developing TERRLou Bajuk
Slides from Michael Sannella, architect for TIBCO Enterprise Runtime for R (TERR), on the the Compatibility Challenge: Examining R and Developing TERR. Presented at useR 2014
The document summarizes Scala, a functional programming language that runs on the Java Virtual Machine (JVM). It discusses Scala's core features like being object-oriented, type inference, and support for functional programming with immutable data structures and passing functions as parameters. It also provides examples of using Scala collections like List and Array, and functions like map, filter, flatMap, and foldLeft/reduceLeft. Finally, it demonstrates using Scala for domain-specific languages and shows examples of defining DSLs for querying and generating JavaScript.
String matching with finite state automataAnmol Hamid
The document discusses the string matching algorithm that builds a finite automaton to scan a text string for occurrences of a pattern string. It explains the suffix function and transition function that are used to specify the string matching automaton corresponding to a given pattern. It then provides an example of computing the transition function for a given text and pattern string through multiple iterations.
This presentation was made for CSE student to understand easily quick sort algorithm to implement quick algorithm. So if u want to learn quick sort than watch it.
Ao longo da história muito se falou sobre o Java ME, essa plataforma ficou muito famosa, principalmente na era do “celular tijolão”. Após o grande boom dos smartphones surgiu a grande dúvida: Para onde foi parar o JavaME? Ele morreu? O objetivo dessa palestra é falar sobre estratégias com o Java ME e das primeiras especificações que estão sendo trabalhadas no dos embarcados e internet das coisas.
Correctness and Performance of Apache Spark SQLNicolas Poggi
1) The document discusses ensuring correctness and performance of Apache Spark SQL through extensive testing that goes beyond unit and integration testing to include techniques like random query generation, failure testing, and micro and macro benchmarks.
2) It describes Databricks' continuous integration pipeline for Spark that classifies issues, analyzes regressions, and alerts on problems to minimize impacts.
3) As an example, it details an investigation that found a 18% regression in query performance between Spark 2.3 and 2.4 due to changes in hashing functions, and the steps taken like profiling and bisection to root cause and address the issue.
Perl 6 is here today ... for some uses, like writing parsing scripts, that would be too complicated for a single Perl 5 regex. This is an overview what has changed.
Stack is an abstract data type that serves as a linear collection of elements. It has two main operations: push, which adds an element to the top of the stack, and pop, which removes the top element. A stack follows last-in, first-out (LIFO) order, meaning the last element added is the first removed. Common real-world examples of stacks include piles of plates and books.
Kotlin For Android - Collections APIs (part 6 of 7)Gesh Markov
This document discusses various collection APIs in Kotlin including functions for filtering collections like filter, transforming collections like map, reducing collections to a single value using fold, and other common collection operations like sorting, joining, finding min/max. It provides examples of how to use functions like filter, map, fold, joinToString and others to manipulate and work with collections in Kotlin.
A stack is a data structure that follows the LIFO (last-in, first-out) principle, where elements can only be inserted or removed from one end called the top. The postfix notation of an expression is evaluated by pushing operands onto a stack and applying operators to pop the top two elements and push the result back on the stack, until a single value remains. The example shows evaluating the postfix expression 6 2 3 + - 3 8 2 / + * 2 ↑ 3 + step-by-step using a stack.
Hands-on Java 8 with examples and open discussion about the more relevant new feature of Java 8: lambdas, streams, CompletableFeature, new Date & Time API.
The document provides an overview of key differences between Python and Scala. Some key points summarized:
1. Python is a dynamically typed, interpreted language while Scala is statically typed and compiles to bytecode. Scala supports both object-oriented and functional programming paradigms.
2. Scala has features like case classes, traits, and pattern matching that Python lacks. Scala also has features like type parameters, implicit conversions, and tail call optimization that Python does not support natively.
3. Common data structures like lists and maps are implemented differently between the languages - Scala uses immutable Lists while Python uses mutable lists. Scala also has features like lazy vals.
4. Control
Heap is a complete binary tree represented as an array. There are two main types: min heap and max heap. A max heap has the largest element at the root and each parent is greater than or equal to its children. Heap sort uses the heap property to sort an array in O(n log n) time. It first builds a max heap from the array. Then it repeatedly removes the maximum element from the heap, adding it to the sorted portion of the array.
Regular expressions, Alex Perry, Google, PyCon2014alex_perry
This document discusses using regular expressions (RE) in Python. It introduces the re module for basic REs and parsing strings. The sre module allows examining the internal representation of REs. The sre_yield module iterates over all matching strings of a RE. While Python REs are built-in, the RE2 library provides more predictable performance without backtracking. The document demonstrates various uses of REs including parsing, formatting, counting matches, and representing large sets of strings compactly.
This document is a log file from a student submission for a lab assignment on scripting. It documents the creation and testing of 5 scripts (q01.sh through q05.sh) to generate reports on car sales data. It provides output from each script and checks that they complete required tasks. In the end, it confirms that all needed files were found and the submission is complete.
渡邊 紘太朗 (LINE株式会社 開発支援室)
LINEデリマでのElasticsearchの運用と監視の話
LINE Developer Meetup in Tokyo #27 -Elastic-の発表資料です
https://line.connpass.com/event/76226/
SAP Inside Track Vienna 2018 #sitVIE - Back to the Future by adopting OO in A...t.eazzy
Back to the Future by adopting OO in ABAP Objects
Back to the Future by adopting OO in ABAP Objects. Ten Best practices that influenced my Programming in ABAP Objects.
This document discusses pointers in C programming. It covers:
- Pointers store memory addresses of variables rather than the variable's value. For example, int *p stores the address of an integer variable.
- Arrays are passed by reference in C, so changing an array element inside a function modifies the original array in the calling function.
- Multidimensional arrays can be passed to functions using pointers to the array and its dimensions. This allows the function to modify the original multidimensional array.
This document contains the slides for a presentation on Java 8 Lambdas and Streams. The presentation will cover lambdas, including their concept, syntax, functional interfaces, variable capture, method references, and default methods. It will also cover streams. The slides provide some incomplete definitions that will be completed during the presentation. Questions from attendees are welcome. A quick survey asks about past experience with lambdas and streams.
Database structure Structures Link list and trees and Recurison complete Adnan abid
Database structure Structures Link list and trees and Recurison complete Database structure Structures Link list and trees and Recurison complete Database structure Structures Link list and trees and Recurison complete Database structure Structures Link list and trees and Recurison complete Database structure Structures Link list and trees and Recurison complete
Database structure Structures Link list and trees and Recurison complete Database structure Structures Link list and trees and Recurison complete Database structure Structures Link list and trees and Recurison complete
The Compatibility Challenge:Examining R and Developing TERRLou Bajuk
Slides from Michael Sannella, architect for TIBCO Enterprise Runtime for R (TERR), on the the Compatibility Challenge: Examining R and Developing TERR. Presented at useR 2014
The document summarizes Scala, a functional programming language that runs on the Java Virtual Machine (JVM). It discusses Scala's core features like being object-oriented, type inference, and support for functional programming with immutable data structures and passing functions as parameters. It also provides examples of using Scala collections like List and Array, and functions like map, filter, flatMap, and foldLeft/reduceLeft. Finally, it demonstrates using Scala for domain-specific languages and shows examples of defining DSLs for querying and generating JavaScript.
String matching with finite state automataAnmol Hamid
The document discusses the string matching algorithm that builds a finite automaton to scan a text string for occurrences of a pattern string. It explains the suffix function and transition function that are used to specify the string matching automaton corresponding to a given pattern. It then provides an example of computing the transition function for a given text and pattern string through multiple iterations.
This presentation was made for CSE student to understand easily quick sort algorithm to implement quick algorithm. So if u want to learn quick sort than watch it.
Ao longo da história muito se falou sobre o Java ME, essa plataforma ficou muito famosa, principalmente na era do “celular tijolão”. Após o grande boom dos smartphones surgiu a grande dúvida: Para onde foi parar o JavaME? Ele morreu? O objetivo dessa palestra é falar sobre estratégias com o Java ME e das primeiras especificações que estão sendo trabalhadas no dos embarcados e internet das coisas.
Correctness and Performance of Apache Spark SQLNicolas Poggi
1) The document discusses ensuring correctness and performance of Apache Spark SQL through extensive testing that goes beyond unit and integration testing to include techniques like random query generation, failure testing, and micro and macro benchmarks.
2) It describes Databricks' continuous integration pipeline for Spark that classifies issues, analyzes regressions, and alerts on problems to minimize impacts.
3) As an example, it details an investigation that found a 18% regression in query performance between Spark 2.3 and 2.4 due to changes in hashing functions, and the steps taken like profiling and bisection to root cause and address the issue.
Perl 6 is here today ... for some uses, like writing parsing scripts, that would be too complicated for a single Perl 5 regex. This is an overview what has changed.
Stack is an abstract data type that serves as a linear collection of elements. It has two main operations: push, which adds an element to the top of the stack, and pop, which removes the top element. A stack follows last-in, first-out (LIFO) order, meaning the last element added is the first removed. Common real-world examples of stacks include piles of plates and books.
Kotlin For Android - Collections APIs (part 6 of 7)Gesh Markov
This document discusses various collection APIs in Kotlin including functions for filtering collections like filter, transforming collections like map, reducing collections to a single value using fold, and other common collection operations like sorting, joining, finding min/max. It provides examples of how to use functions like filter, map, fold, joinToString and others to manipulate and work with collections in Kotlin.
A stack is a data structure that follows the LIFO (last-in, first-out) principle, where elements can only be inserted or removed from one end called the top. The postfix notation of an expression is evaluated by pushing operands onto a stack and applying operators to pop the top two elements and push the result back on the stack, until a single value remains. The example shows evaluating the postfix expression 6 2 3 + - 3 8 2 / + * 2 ↑ 3 + step-by-step using a stack.
Hands-on Java 8 with examples and open discussion about the more relevant new feature of Java 8: lambdas, streams, CompletableFeature, new Date & Time API.
The document provides an overview of key differences between Python and Scala. Some key points summarized:
1. Python is a dynamically typed, interpreted language while Scala is statically typed and compiles to bytecode. Scala supports both object-oriented and functional programming paradigms.
2. Scala has features like case classes, traits, and pattern matching that Python lacks. Scala also has features like type parameters, implicit conversions, and tail call optimization that Python does not support natively.
3. Common data structures like lists and maps are implemented differently between the languages - Scala uses immutable Lists while Python uses mutable lists. Scala also has features like lazy vals.
4. Control
Heap is a complete binary tree represented as an array. There are two main types: min heap and max heap. A max heap has the largest element at the root and each parent is greater than or equal to its children. Heap sort uses the heap property to sort an array in O(n log n) time. It first builds a max heap from the array. Then it repeatedly removes the maximum element from the heap, adding it to the sorted portion of the array.
Regular expressions, Alex Perry, Google, PyCon2014alex_perry
This document discusses using regular expressions (RE) in Python. It introduces the re module for basic REs and parsing strings. The sre module allows examining the internal representation of REs. The sre_yield module iterates over all matching strings of a RE. While Python REs are built-in, the RE2 library provides more predictable performance without backtracking. The document demonstrates various uses of REs including parsing, formatting, counting matches, and representing large sets of strings compactly.
This document is a log file from a student submission for a lab assignment on scripting. It documents the creation and testing of 5 scripts (q01.sh through q05.sh) to generate reports on car sales data. It provides output from each script and checks that they complete required tasks. In the end, it confirms that all needed files were found and the submission is complete.
渡邊 紘太朗 (LINE株式会社 開発支援室)
LINEデリマでのElasticsearchの運用と監視の話
LINE Developer Meetup in Tokyo #27 -Elastic-の発表資料です
https://line.connpass.com/event/76226/
SAP Inside Track Vienna 2018 #sitVIE - Back to the Future by adopting OO in A...t.eazzy
Back to the Future by adopting OO in ABAP Objects
Back to the Future by adopting OO in ABAP Objects. Ten Best practices that influenced my Programming in ABAP Objects.
This document discusses pointers in C programming. It covers:
- Pointers store memory addresses of variables rather than the variable's value. For example, int *p stores the address of an integer variable.
- Arrays are passed by reference in C, so changing an array element inside a function modifies the original array in the calling function.
- Multidimensional arrays can be passed to functions using pointers to the array and its dimensions. This allows the function to modify the original multidimensional array.
This document contains the slides for a presentation on Java 8 Lambdas and Streams. The presentation will cover lambdas, including their concept, syntax, functional interfaces, variable capture, method references, and default methods. It will also cover streams. The slides provide some incomplete definitions that will be completed during the presentation. Questions from attendees are welcome. A quick survey asks about past experience with lambdas and streams.
Database structure Structures Link list and trees and Recurison complete Adnan abid
Database structure Structures Link list and trees and Recurison complete Database structure Structures Link list and trees and Recurison complete Database structure Structures Link list and trees and Recurison complete Database structure Structures Link list and trees and Recurison complete Database structure Structures Link list and trees and Recurison complete
Database structure Structures Link list and trees and Recurison complete Database structure Structures Link list and trees and Recurison complete Database structure Structures Link list and trees and Recurison complete
Java 8 Stream API and RxJava ComparisonJosé Paumard
The slides of my JavaOne talk: Java 8 Stream API and RxJava Comparison: Patterns and Performances.
The spliterators patterns can be found here: https://github.com/JosePaumard/jdk8-spliterators.
Functional programming in Java 8 allows for:
1) The use of lambda expressions and streams for a more declarative programming style without iteration.
2) Functional interfaces like Function, Predicate, and Consumer along with lambda expressions enable function composition and chaining.
3) Features like immutable collections help reduce mutability and side effects, important aspects of functional programming.
Functional programming has started (re)gaining prominence in recent years, and with good reason too. Functional programs lend an elegant solution to the concurrency problem, result in more modular systems, are more concise and are easier to test. While modern languages like Scala and Clojure have embraced the functional style whole-heartedly, Java has lagged a bit behind in its treatment of functions as first-class citizens. With the advent of Java 8 and its support for lambdas, however, Java programmers can finally start reaping the power of functional programs as well. Even without Java 8, it is possible to adopt a functional style with the aid of excellent libraries such as Guava.
A notification is a short message briefly displayed on the status line to announce an event. Notifications can take different forms like icons in the status bar or alerts. The NotificationManager class notifies users of background events. An example shows creating a notification with the NotificationBuilder, displaying it, and canceling it. When clicked, a PendingIntent launches an activity to attend to the notification.
Functional programming is all the rage. It can undoubtedly produce cleaner and more expressive code, but why switch to Scala or wait for Java 8? In fact, there are many ways to dramatically improve your Java code quality by using a more functional style today. This presentation discusses how techniques such as functional programming, using fluent APIs, and other clean coding practices can make your code more concise, more readable, and much easier to maintain. But more importantly, you will learn about libraries such as LambdaJ and Google Guava that make this possible today with your existing Java code base.
This document is a dissertation that describes a case study of a virtual language learning community called Writing Through the Internet (WTI). The study was conducted through participant observation of the online class, interviews with selected students, and analysis of publicly available documents.
Key findings included insights about the importance of multiple means of interaction in virtual classes, the inevitability of change in virtual communities, the effort required to develop and maintain language learning communities, challenges of virtual interviews related to context and time, and the need to adjust plans based on students' varying technological capabilities.
Recommendations for online teachers and researchers centered around having backup plans, establishing clear rules, allowing sufficient time, considering time zone differences, providing multiple but optional means of
L'API la plus utilisée du JDK est sans aucun doute l'API Collection. Brillamment conçue il y a un peu plus de 15 ans, elle est encore aujourd'hui au coeur de toutes les applications Java. En 2004, elle a subi son premier lifting, avec l'introduction des génériques. Cette mise à jour, bien qu'importante, n'a cependant pas modifié ses patterns d'utilisation. Avec l'introduction des lambdas en Java 8, l'API Collection est à nouveau réécrite, mais cette fois la situation est différente : ses patterns d'utilisation sont complètement changés.
La première partie de cette conférence introduit les lambda expressions, comment les écrire, et ce qu'elle nous apportent en tant que développeurs. La deuxième partir présente en détail les nouveaux patterns introduits par les API Stream et Collector. Ces nouvelles API vont changer la façon dont nous allons pouvoir traiter les collections de grande taille, y compris en parallèle, avec un modèle de programmation très simple, et des patterns très puissants. Cette puissance sera montrée dans des exemples réels, qui monteront comment Java 8 va pouvoir nous aider à écrire simplement du code efficace et performant.
Java 8, Streams & Collectors, patterns, performances and parallelizationJosé Paumard
This document discusses Java 8 streams and collectors. It provides an overview of streams, operations on streams like forEach(), filter(), and peek(), and functional interfaces like Consumer and Predicate. It notes that streams efficiently process data in a parallel and pipelined manner without storing intermediate data. Key points covered include what streams are, how to create them from collections, common stream operations, and issues around concurrency with mutable operations.
In this Meetup Victor Perepelitsky - R&D Technical Leader at LivePerson leading the 'Real Time Event Processing Platform' team , will talk about Java 8', 'Stream API', 'Lambda', and 'Method reference'.
Victor will clarify what functional programming is and how can you use java 8 in order to create better software.
Victor will also cover some pain points that Java 8 did not solve regarding functionality and see how you can work around it.
Alphorm.com Formation Autodesk Revit 2018 : Les nouveautésAlphorm
Formation complète ici:
http://www.alphorm.com/tutoriel/formation-en-ligne-autodesk-revit-2018-les-nouveautes
Autodesk Revit fait sans doute partie des logiciels d’architecture 3D les plus performants actuellement. Il dispose d'une large gamme de fonctionnalités permettant de produire des images 3D de qualité.
Autodesk Revit est un puissant logiciel de traitement d'images 3D. Plus précisément, le programme permet de concevoir, de visualiser, et bien entendu de modifier des créations en architecture 3D. Il a été conçu pour être bien précis dans ses œuvres, de l'esquisse au crayon à la vitesse et la flexibilité de l'application.
Cette formation Revit 2018 vous permettra de maîtriser les nouveautés de Revit 2018, le logiciel d'architecture 3D, utilisé par de nombreux passionnés et professionnels.
Au cours de cette formation Revit 2018, vous aborderez les nouveautés concernant les améliorations de textes, la création des escaliers multi-étages, l’hébergement des garde-corps sur une topographie, la fonctionnalité de liaison d’un fichier Navisworks sur Revit, les améliorations concernant la création des garde-corps par esquisse.
Avec cette formation Revit 2018 les nouveautés, vous apprendrez à utiliser les nouveautés du logiciel de manière optimale afin de devenir un Spécialiste sur Revit 2018.
Formation complète ici:
http://www.alphorm.com/tutoriel/formation-en-ligne-java-server-faces
Nous rappelons tout d’abord les technologies JSP et Servlet, qui servent de base à JSF. Avec JSP et Servlet, nous créons des applications Web dynamiques. Puis, en nous appuyant sur les Servlets, nous abordons JSF. Ce qui caractérise les pages JSF, c’est l’absence totale de code Java et la présence de balises spécifiques, les facelets. Pour faire le lien entre les pages HTML et les composants Java, nous présentons Expression Language, qui permet d’écrire des expressions qui lisent ou écrivent les données.
Ensuite, nous détaillons certains composants essentiels à la construction des pages Web, et après ce chapitre, vous êtes capable de créer une interface riche et agréable à l’utilisateur. Ces composants ont ou pas un équivalent HTML. Ces composants graphiques sont ensuite accompagnés de convertisseurs, listeners et de validateurs qui permettront d’éviter de coder les règles élémentaires liées à la saisie et à la modification des données.
Nous n’oublions pas le code Java, car les beans managés ont leur chapitre, afin de préciser les règles à suivre pour qu’ils s’intègrent parfaitement dans l’application. Plusieurs choix s’offrent à nous, nous choisissons le plus pertinent.
Pour améliorer le rendu et la fluidité de l’interface, nous utiliserons Ajax, et nous montrerons comment il est simple d’introduire cette technologie dans les pages JSF. Avec Ajax, qui utilise donc du JavaScript, nous obtiendrons des mises à jour plus discrètes et plus rapides.
Enfin, nous finirons par décrire les détails de configuration concernant les beans, l’internationalisation, les flux et la sécurité. La configuration repose pour une bonne part sur l’écriture de fichiers XML, et par ailleurs beaucoup sur le respect de règles et de conventions. Le paramétrage sera abordé en prenant comme exemple GlassFish.
Map, Flatmap and Reduce are Your New Best Friends: Simpler Collections, Concu...Chris Richardson
Higher-order functions such as map(), flatmap(), filter() and reduce() have their origins in mathematics and ancient functional programming languages such as Lisp. But today they have entered the mainstream and are available in languages such as JavaScript, Scala and Java 8. They are well on their way to becoming an essential part of every developer’s toolbox.
In this talk you will learn how these and other higher-order functions enable you to write simple, expressive and concise code that solve problems in a diverse set of domains. We will describe how you use them to process collections in Java and Scala. You will learn how functional Futures and Rx (Reactive Extensions) Observables simplify concurrent code. We will even talk about how to write big data applications in a functional style using libraries such as Scalding.
Map, flatmap and reduce are your new best friends (javaone, svcc)Chris Richardson
Higher-order functions such as map(), flatmap(), filter() and reduce() have their origins in mathematics and ancient functional programming languages such as Lisp. But today they have entered the mainstream and are available in languages such as JavaScript, Scala and Java 8. They are well on their way to becoming an essential part of every developer’s toolbox. In this talk you will learn how these and other higher-order functions enable you to write simple, expressive and concise code that solve problems in a diverse set of domains. We will describe how you use them to process collections in Java and Scala. You will learn how functional Futures and Rx (Reactive Extensions) Observables simplify concurrent code. We will even talk about how to write big data applications in a functional style using libraries such as Scalding.
Java 8 Stream API. A different way to process collections.David Gómez García
A look on one of the features of Java 8 hidden behind the lambdas. A different way to iterate Collections. You'll never see the Collecions the same way.
These are the slides I used on my talk at the "Tech Thursday" by Oracle in June in Madrid.
Introduction to Functional Programming and usage of basic constructs in Java 7 using Guava.
Further, the session introduces Reactive Systems architecture and design.
Map(), flatmap() and reduce() are your new best friends: simpler collections,...Chris Richardson
This document summarizes a presentation about functional programming and how functions like map(), flatMap(), and reduce() can simplify collection processing, concurrency, and big data problems. The presentation introduces functional programming concepts and how languages like Java 8 have adopted these with features like lambda expressions and streams. It provides examples of how to use streams to map, filter, and reduce collections in a more declarative way compared to imperative for loops. It also discusses how functions and futures can help simplify concurrent operations by allowing asynchronous work to be expressed more clearly.
This document provides an overview of Java's collections framework. It introduces common data structures like lists, sets, maps and their implementations including ArrayList, LinkedList, HashSet, TreeSet and HashMap. It explains how iterators work and how to traverse collections. The key interfaces like Collection, List, Set and Map are described along with their common methods. Examples of using different collections and their performance characteristics are also provided.
OOP and FP: become a better programmer - Simone Bordet, Mario Fusco - Codemot...Codemotion
The document discusses examples of applying object-oriented programming (OOP) and functional programming (FP) paradigms to programming tasks in Java. It provides multiple versions of examples using OOP vs FP styles. The goals are to show that both paradigms are useful and that programmers should understand both to write better code. Certain problems are better solved with one paradigm over the other, and guidelines can help decide which to apply. The conclusion advocates learning both OOP and FP to practice "poly-paradigm programming" rather than just using multiple languages.
OOP and FP - Become a Better ProgrammerMario Fusco
The story of Simon, an experienced OOP Java developer, exposed to the new lambda features of JDK 8. His friend Mario, a long-bearded FP geek, will try to convince him that FP can help him develop more readable and maintainable code. A journey into the discovery of the main new feature - lambda expressions - of JDK 8
These are Java ways of functional style; pragmatic ways of understanding and introducing Lambda/Functional API.
你可以在以下找到中文說明:
http://www.codedata.com.tw/java/jdk8-functional-api/
This document provides an overview of functional programming patterns and abstractions in Java 8. It introduces common functional concepts like functors, applicative functors, monads, and type classes. It then describes implementations of these concepts for option, either, stream, future, and completable future in Java. The document explains how functional patterns allow for simpler composition and avoidance of null checks compared to imperative programming with conditionals.
This document is a beginner's guide to Java Collections Framework. It introduces common data structures like lists, sets, queues and maps. It explains basic concepts like algorithms, collection types and implementations. It also covers operations on collections like iteration, sorting and filtering. The guide demonstrates how to select the appropriate data structure based on usage and provides examples of bulk operations using streams.
This document is a beginner's guide to Java Collections Framework. It introduces common data structures like lists, sets, queues and maps. It explains basic concepts like algorithms, collection types and implementations. It also covers operations on collections like iteration, sorting and filtering. The guide demonstrates how to select the appropriate data structure and implementation based on requirements. It provides examples of using collections and streams to perform bulk operations on data.
The document discusses Java's Collections framework, which provides a unified approach to store, retrieve, and manipulate groups of data. It describes the core interfaces like Collection, Set, List, Queue, and Map. It explains the benefits of the framework and common operations supported. It also covers iteration, implementations of interfaces, usage examples, and thread safety considerations.
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These are the slides I presented during Eclipse Con 2011
http://www.eclipsecon.org/2011/sessions/?page=sessions&id=2164
This document provides an overview of Java 8 lambdas and functional programming concepts in Java. It discusses key lambda features such as functional interfaces, streams API, and method references. It also covers stream operations like filter, map, reduce, and collect, and how to parallelize stream operations. The document uses examples to illustrate how lambdas can concisely represent logic and simplify traditional iterative approaches to processing collections.
The emergence of support of functions and lambda expressions as first-class citizens in Java 8 gives us a tremendous opportunity to adapt the concepts of functional programming to the Java language.
The document discusses various collection types in Java including arrays, iterators, and common collection interfaces like Collection, Set, List, and Map. It describes the key characteristics of arrays, iterators, and common implementations of collection interfaces like ArrayList, LinkedList, HashSet, and TreeMap. The interfaces define common operations while classes implement the interfaces, providing different performance characteristics depending on the underlying data structure used.
Software, like board games, needs instructions. Should I draw a card or play my card first? Will the connection be reused, or should I use a connection pool? In heroic tales, a protagonist needs directions from elder scrolls to user magical artifacts and complete their mission.
In this talk, Ignasi will explain his journey from neglecting docs to considering them an important step on the software delivery cycle. Ignasi will share tips ant tricks he’s been collecting over the years and focus on which habits he adopted to make sure he doesn’t forget docs. Ignasi will also share the types of audience and cases where documentation can save time and money to your organization.
After discussing the importance of documentation within several teams, Ignasi will try to counter the usual arguments and excuses those who don’t document often use. No, the code is not the documentation, the code doesn’t tell the whole story. You can have a strong type system restricting how to call an API and still be an unusable API: “Hmm, I need a Token here, where do I get it?”.
Join Ignasi for a talk about board games, child tales, and embarrassing PRs.
This talk targets beginner/daily user/experts alike.
En Junio 2021 entró en vigor la tarifa 2.0TD que introduce el modelo de 3 tramos. Qué significa esto? Qué otros cambios se introdujeron? Cómo se lee una factura de la luz?
Pero el cambio de tarifa es solamente una excusa para investigar en detalle cómo se lee una factura, cómo se convierte el consumo en nuestra casa en esos números, investigar qué compañía nos conviene más o qué tarifa nos conviene más. Para! Para! Pero me acabas de decir que solo hay una tarifa?!
Entraremos en el laberinto que es el mundo del mercado eléctrico en España enfocados en el caso específico de Cataluña (porque hay variaciones).
Veremos poco código, pero aprenderemos bastante como para que cada uno pueda empezar a codificar como si no hubiera un mañana.
The document discusses how to contribute to open source software projects. It recommends getting a GitHub account, registering for Hacktoberfest, and provides tips for making contributions such as starting with small changes, communicating expectations through pull requests, and choosing projects that are familiar or have requested help. The overall message is that contributing to open source can help overcome fears of making mistakes and that maintainers are generally receptive to contributions.
This document contains slides from a presentation by Ignasi Marimon-Clos on contributing to open source software projects. It discusses various ways to contribute including code, documentation, forums, and more. It also covers impediments to contributing like lack of confidence and provides tips such as starting with small issues, writing good commit messages, and using tools like GitHub and hub to facilitate the contribution process.
This document summarizes Ignasi Marimon-Clos' presentation on reactive microsystems. It begins with an agenda that includes a glossary of terms like reactive, message passing versus event driven. It then discusses moving from monoliths to microliths to microsystems by separating concerns like stateful and stateless services, denormalizing data, and using an event log as the source of truth. The presentation concludes by discussing how the microsystems approach can be applied within a monolith to improve scalability and resilience.
Lagom is a framework for building reactive microservices in Java. Some key points:
- It is built on top of Play, Akka, and Cassandra to provide reactive capabilities, failure handling, and persistence out of the box.
- Services are automatically reloaded on code changes, making development faster.
- Intra-service communication is simple and works seamlessly in production.
- It aims to take services from development directly to production deployment with minimal additional configuration.
Ironhack Barcelona is a bootcamp teaching non programmers Ruby and javascript. In their meetup they invited me to introduce scala. Several non-ironhackers (senior and java background) signed up so this is a talk that's partly intro to scala for a junior from Ruby and some more generic advanced concepts.
This is a reviewed version of our scala-101 presentation with some extra contents. We prepared this version for the Barcelona Developer Conference 2013.
See the original at: http://www.slideshare.net/IgnasiMarimonClos/scala-101
This document summarizes a Scala meetup for newcomers in Barcelona. It introduces Ignasi Marimon-Clos and Jordi Pradel. Jordi Pradel then discusses refactoring some Java code to make it more functional using Scala features like case classes, traits, pattern matching, and first-class functions. He highlights how Scala allows for concise and immutable code. Jordi concludes by mentioning additional Scala concepts like macros, implicits and more.
Presentation given at the LangChain community meetup London
https://lu.ma/9d5fntgj
Coveres
Agentic AI: Beyond the Buzz
Introduction to AI Agent and Agentic AI
Agent Use case and stats
Introduction to LangGraph
Build agent with LangGraph Studio V2
National Fuels Treatments Initiative: Building a Seamless Map of Hazardous Fu...Safe Software
The National Fuels Treatments Initiative (NFT) is transforming wildfire mitigation by creating a standardized map of nationwide fuels treatment locations across all land ownerships in the United States. While existing state and federal systems capture this data in diverse formats, NFT bridges these gaps, delivering the first truly integrated national view. This dataset will be used to measure the implementation of the National Cohesive Wildland Strategy and demonstrate the positive impact of collective investments in hazardous fuels reduction nationwide. In Phase 1, we developed an ETL pipeline template in FME Form, leveraging a schema-agnostic workflow with dynamic feature handling intended for fast roll-out and light maintenance. This was key as the initiative scaled from a few to over fifty contributors nationwide. By directly pulling from agency data stores, oftentimes ArcGIS Feature Services, NFT preserves existing structures, minimizing preparation needs. External mapping tables ensure consistent attribute and domain alignment, while robust change detection processes keep data current and actionable. Now in Phase 2, we’re migrating pipelines to FME Flow to take advantage of advanced scheduling, monitoring dashboards, and automated notifications to streamline operations. Join us to explore how this initiative exemplifies the power of technology, blending FME, ArcGIS Online, and AWS to solve a national business problem with a scalable, automated solution.
מכונות CNC קידוח אנכיות הן הבחירה הנכונה והטובה ביותר לקידוח ארונות וארגזים לייצור רהיטים. החלק נוסע לאורך ציר ה-x באמצעות ציר דיגיטלי מדויק, ותפוס ע"י צבת מכנית, כך שאין צורך לבצע setup (התאמות) לגדלים שונים של חלקים.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Providing an OGC API Processes REST Interface for FME FlowSafe Software
This presentation will showcase an adapter for FME Flow that provides REST endpoints for FME Workspaces following the OGC API Processes specification. The implementation delivers robust, user-friendly API endpoints, including standardized methods for parameter provision. Additionally, it enhances security and user management by supporting OAuth2 authentication. Join us to discover how these advancements can elevate your enterprise integration workflows and ensure seamless, secure interactions with FME Flow.
Scaling GenAI Inference From Prototype to Production: Real-World Lessons in S...Anish Kumar
Presented by: Anish Kumar
LinkedIn: https://www.linkedin.com/in/anishkumar/
This lightning talk dives into real-world GenAI projects that scaled from prototype to production using Databricks’ fully managed tools. Facing cost and time constraints, we leveraged four key Databricks features—Workflows, Model Serving, Serverless Compute, and Notebooks—to build an AI inference pipeline processing millions of documents (text and audiobooks).
This approach enables rapid experimentation, easy tuning of GenAI prompts and compute settings, seamless data iteration and efficient quality testing—allowing Data Scientists and Engineers to collaborate effectively. Learn how to design modular, parameterized notebooks that run concurrently, manage dependencies and accelerate AI-driven insights.
Whether you're optimizing AI inference, automating complex data workflows or architecting next-gen serverless AI systems, this session delivers actionable strategies to maximize performance while keeping costs low.
Supporting the NextGen 911 Digital Transformation with FMESafe Software
Next Generation 911 involves the transformation of our 911 system from an old analog one to the new digital internet based architecture. The evolution of NG911 opens up a host of new opportunities to improve the system. This includes everything from device based location, to real time text. This can improve location accuracy dramatically as well as provide live updates from the citizen in need along with real time sensor updates. There is also the opportunity to provide multi-media attachments and medical records if the end user approves. This digital transformation and enhancements all require the support of new NENA and CRTC standards, along with integration across a variety of data streams.
This presentation will focus on how FME has supported NG911 transformations to date, and how we are positioning FME to support the enhanced capabilities to come. This session will be of interest to emergency services, municipalities and anyone who may be interested to know more about how emergency services are being improved to provide more accurate, localized information in order to improve the speed and relevance of emergency response and ultimately save more lives and provide better outcomes for those in need.
AudGram Review: Build Visually Appealing, AI-Enhanced Audiograms to Engage Yo...SOFTTECHHUB
AudGram changes everything by bridging the gap between your audio content and the visual engagement your audience craves. This cloud-based platform transforms your existing audio into scroll-stopping visual content that performs across all social media platforms.
Data Validation and System InteroperabilitySafe Software
A non-profit human services agency with specialized health record and billing systems. Challenges solved include access control integrations from employee electronic HR records, multiple regulations compliance, data migrations, benefits enrollments, payroll processing, and automated reporting for business intelligence and analysis.
Floods in Valencia: Two FME-Powered Stories of Data ResilienceSafe Software
In October 2024, the Spanish region of Valencia faced severe flooding that underscored the critical need for accessible and actionable data. This presentation will explore two innovative use cases where FME facilitated data integration and availability during the crisis. The first case demonstrates how FME was used to process and convert satellite imagery and other geospatial data into formats tailored for rapid analysis by emergency teams. The second case delves into making human mobility data—collected from mobile phone signals—accessible as source-destination matrices, offering key insights into population movements during and after the flooding. These stories highlight how FME's powerful capabilities can bridge the gap between raw data and decision-making, fostering resilience and preparedness in the face of natural disasters. Attendees will gain practical insights into how FME can support crisis management and urban planning in a changing climate.
Your startup on AWS - How to architect and maintain a Lean and Mean account J...angelo60207
Prevent infrastructure costs from becoming a significant line item on your startup’s budget! Serial entrepreneur and software architect Angelo Mandato will share his experience with AWS Activate (startup credits from AWS) and knowledge on how to architect a lean and mean AWS account ideal for budget minded and bootstrapped startups. In this session you will learn how to manage a production ready AWS account capable of scaling as your startup grows for less than $100/month before credits. We will discuss AWS Budgets, Cost Explorer, architect priorities, and the importance of having flexible, optimized Infrastructure as Code. We will wrap everything up discussing opportunities where to save with AWS services such as S3, EC2, Load Balancers, Lambda Functions, RDS, and many others.
מכונת קנטים המתאימה לנגריות קטנות או גדולות (כמכונת גיבוי).
מדביקה קנטים מגליל או פסים, עד עובי קנט – 3 מ"מ ועובי חומר עד 40 מ"מ. בקר ממוחשב המתריע על תקלות, ומנועים מאסיביים תעשייתיים כמו במכונות הגדולות.
FME for Distribution & Transmission Integrity Management Program (DIMP & TIMP)Safe Software
Peoples Gas in Chicago, IL has changed to a new Distribution & Transmission Integrity Management Program (DIMP & TIMP) software provider in recent years. In order to successfully deploy the new software we have created a series of ETL processes using FME Form to transform our gas facility data to meet the required DIMP & TIMP data specifications. This presentation will provide an overview of how we used FME to transform data from ESRI’s Utility Network and several other internal and external sources to meet the strict data specifications for the DIMP and TIMP software solutions.
Russia is one of the most aggressive nations when it comes to state coordinated cyberattacks — and Ukraine has been at the center of their crosshairs for 3 years. This report, provided the State Service of Special Communications and Information Protection of Ukraine contains an incredible amount of cybersecurity insights, showcasing the coordinated aggressive cyberwarfare campaigns of Russia against Ukraine.
It brings to the forefront that understanding your adversary, especially an aggressive nation state, is important for cyber defense. Knowing their motivations, capabilities, and tactics becomes an advantage when allocating resources for maximum impact.
Intelligence shows Russia is on a cyber rampage, leveraging FSB, SVR, and GRU resources to professionally target Ukraine’s critical infrastructures, military, and international diplomacy support efforts.
The number of total incidents against Ukraine, originating from Russia, has steadily increased from 1350 in 2021 to 4315 in 2024, but the number of actual critical incidents has been managed down from a high of 1048 in 2022 to a mere 59 in 2024 — showcasing how the rapid detection and response to cyberattacks has been impacted by Ukraine’s improved cyber resilience.
Even against a much larger adversary, Ukraine is showcasing outstanding cybersecurity, enabled by strong strategies and sound tactics. There are lessons to learn for any enterprise that could potentially be targeted by aggressive nation states.
Definitely worth the read!
PyData - Graph Theory for Multi-Agent Integrationbarqawicloud
Graph theory is a well-known concept for algorithms and can be used to orchestrate the building of multi-model pipelines. By translating tasks and dependencies into a Directed Acyclic Graph, we can orchestrate diverse AI models, including NLP, vision, and recommendation capabilities. This tutorial provides a step-by-step approach to designing graph-based AI model pipelines, focusing on clinical use cases from the field.
4. @ignasi35
about me
@ignasi35
1) problem solver, Garbage Collector, mostly
scala, java 8, agile for tech teams
2) kayaker
3) under construction
4) all things JVM
5. @ignasi35
FP in Java 8
Pure Functions
no side effects
if not used, remove it
fixed in — fixed out
36. @ignasi35
XXIst Century DateTime
• Clock
• LocalDate
• a date
• no TimeZone
• birth date, end of war, man on moon,…
• LocalDateTime
• Duration vs Period
• ZonedDateTime
92. @ignasi35
Maybe (aka Optional)
filter: applies predicate and Returns input or None
map: converts content
fold: returns Some(content) or Some(default)
flatMap: see list
get: returns content or throws Exception
getOrElse: returns content or defaultValue
97. @ignasi35
Future (aka CF, aka
CompletableFuture)
!
[FAIL] Does not use map, flatMap, filter.
!
[PASS] CF implemented ADT
!
[FAIL] Because Supplier, Consumer, Function,
Bifuction, … CF’s API sucks.
98. @ignasi35
Future
filter: creates new future applying Predicate
map: converts content if success. New Future
fold: n/a
flatMap: see list
andThen: chains this Future’s content into a Consumer
onSuccess/onFailure: callbacks
recover: equivalent to map() but applied only on Fail
119. @ignasi35
Moar resources
https://github.com/rocketscience-projects/javaslang
by https://twitter.com/danieldietrich
thanks @thomasdarimont for the tip
!
https://github.com/functionaljava/functionaljava
by http://www.functionaljava.org/ (runs in Java7)