Scala overview
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Scala is a multi-paradigm programming language that supports both object-oriented programming and functional programming. Some key features of Scala include: 1. Support for OOP concepts like abstraction, inheritance, polymorphism, and types. 2. Support for functional programming concepts like lambda calculus, higher-order functions, immutability, pattern matching, and tail call optimization. 3. Ability to create internal and external domain-specific languages (DSLs) to provide customized syntax and functionality for a specific problem domain.
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Compare to PySpark, SparkR is a new language binding for Apache Spark and it is designed to be familiar to native R users. In this talk we will walkthrough many examples how several new features in Apache Spark 2.x will enable scalable machine learning on Big Data. In addition to talking about the R interface to the ML Pipeline model, we will explore how SparkR support running user code on large scale data in a distributed manner, and give examples on how that could be used to work with your favorite R packages.
Python
R
Apache Spark
ML
DLThe Evolution of Scala / ScalaßM»¯Õ“
The Evolution of Scala / ScalaßM»¯Õ“scalaconfjp
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Presentation material with Japanese subs, by Prof. Martin Odersky at ScalaMatsuri 2014
http://scalamatsuri.org/en/J
JChristopher Chedeau
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This document describes JSPP, a prototype implementation of JavaScript in C++ using C++11 features. It implements JavaScript's dynamic typing, JSON-like object notation, functions using lambdas, and object properties including prototypal inheritance and property traversal. The implementation comprises about 600 lines of code and allows pasting JavaScript code directly into C++ files to compile. It preserves JavaScript syntax as much as possible but lacks optimizations and a standard library.JSPP: Morphing C++ into Javascript
JSPP: Morphing C++ into JavascriptChristopher Chedeau
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This document describes JSPP, a prototype implementation of JavaScript in C++ using C++11 features. It implements JavaScript's dynamic typing, JSON-like object notation, functions using lambdas, and object properties including prototypal inheritance and property traversal. The implementation comprises about 600 lines of code and allows pasting JavaScript code directly into C++ files to compile. It preserves JavaScript syntax as much as possible but lacks optimizations and a standard library.AestasIT - Internal DSLs in Scala
AestasIT - Internal DSLs in ScalaDmitry Buzdin
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Internal DSLs in Scala allows creating domain-specific languages within Scala by leveraging Scala's features like lightweight syntax, implicit conversions, by-name parameters, and advanced type system. The presentation provides examples of internal DSLs in Scala for tasks automation (Baysick), date/time manipulation (Time DSL), and message processing (Spring Integration DSL). It also recommends some books and links for further reading on implementing internal DSLs in Scala.Report about the LISP Programming Language
Report about the LISP Programming Languagemaldosmelandrew
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Report about the LISP Programming LanguageIN4308 1
IN4308 1Eelco Visser
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Introduction lecture for course on Model-Driven Software Development at Delft University of Technology¶Ù³§³¢½éÉÜ
¶Ù³§³¢½éÉÜa596620989
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DSL is a computer language specialized to a particular application domain, in contrast to a general-purpose language (GPL) that is broadly applicable across domains. There are several common ways to implement a DSL, including using parsers to convert DSL scripts into semantic models or abstract syntax trees that can then be used to generate executable code. DSLs allow expressing solutions to problems in a particular domain in a simpler and more natural way than GPLs.Master in javascript
Master in javascriptRobbin Zhao
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The document discusses JavaScript, including its status as a misunderstood programming language, basic knowledge about the language, and dynamic and functional aspects. It covers JavaScript frameworks and applications, debugging experiences, and literal notation, keywords, functions, object-oriented programming, and DOM/HTML. It provides examples and definitions of terms like typeof, instanceof, this, in, and try/catch.IBM Solutions '99 XML and Java: Lessons Learned
IBM Solutions '99 XML and Java: Lessons LearnedTed Leung
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The document discusses using XML and Java together for building applications. It provides background on XML and Java technologies including parsers, schemas, stylesheets, and servlets. Architectures are presented that use servlets to integrate XML, business objects, and databases in both applet-based and web-based applications. Benefits of the XML and servlet approach include leverage of web server technologies, high scalability, simplified integration, and support for multiple front-ends.Lecture02(constants, variable & data types)
Lecture02(constants, variable & data types)Dhaka University of Engineering & Technology(DUET)
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The document outlines key concepts in C programming including data types, tokens, keywords, identifiers, constants, variables, and scopes. It discusses the five fundamental data types in C (integer, floating-point, double, character, void), tokens like keywords and identifiers, common keywords and their meanings, rules for identifiers, how variables are declared and initialized, what constants are (fixed values that don't change), and the four scopes in C.javascript 
javascript Kaya Ota
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This document provides an agenda and overview of a presentation on JavaScript. It introduces JavaScript, covering its history, cores, uses today, and programming paradigms. It then discusses object-oriented JavaScript, data types and structures, and control statements in JavaScript. The document also mentions functions, prototypes, and JSON before concluding with examples of libraries and frameworks that could be used in a demo program.Scala overview
- 4. FP?lambda calculuslambda x . plus x x(lambda x . plus x x) y rule: alpha ¨C ±äÁ¿Ìæ»» beta ¨C ÖµÓ¦ÓÃ{lisp[ML/erlang/haskell]}functionisvalue[hightorderfunction]; nosideeffect; lazy evaluation; pattern match; currying/partial funcitons; tail recursion optimization; etc¡
- 5. DSL?definition: Domain-Specific Languages/ÁìÓòÌض¨ÓïÑÔinternal DSL±ãÓÚÓÿâÀ´ÌṩÓïÑÔÌØÐÔ easy debug etc¡external DSL easy design and write[withparser] newsyntax etc¡
- 6. not simple??
- 7. base1.ÔÉúÀàÐÍÊǶÔÏóµÄʵÀý123.toByte"1".toInttrue.toString2.º¯ÊýÒ²ÊÇÖµval compare = (x: Int, y: Int) => x > ycompare(1, 2) // result: Boolean = false3.±äÁ¿varVal/lazy val4.×ÖÃæÁ¿/literalsvali = 1234356; //Intval l = 123454L; // Longval f = 0.123; // Floatval c = 'a' or '\u0041'; //Chaarval s = "string" or """ String "ssssss'""" //Stringval symbol = 'name [scala.Symbol("programming scala") //symbol5.Predef.scalaÒ»ÇвÙ×÷¶¼ÊǺ¯ÊýÒ»ÇвÙ×÷¶¼·µ»ØÖµ}=>
- 9. trait
- 11. parameterized typesinvariant/²»±ä: C[T], C is invariant on TÈç¹ûTsub»òTsupÊÇTµÄ×ÓÀà»ò³¬À࣬C[Tsub]»òC[Tsup]¶¼²»ÊÇC[T]Ààcovariant/бä: C[+T], C is covariant on TÈç¹ûTsubÊÇTµÄ×ÓÀ࣬ÔòC[Tsub]Ò²ÊÇC[T]µÄ×ÓÀàContravatiant/Äæ±ä: C[©\T], C is contravariant on TÈç¹ûTsupÊÇTµÄ³¬À࣬ÔòC[Tsup]Ò²ÊÇC[T]µÄ×ÓÀà
- 12. implicit and type bounds
- 13. function
- 15. pattern match & case class
- 17. DSL
- 18. herding xml in scala
- 19. ·¡°Õ°ä¡
- 20. THANKS