Ruby | EPFL Graph Search

Ruby est un langage de programmation libre. Il est interprété, orienté objet et multi-paradigme. Le langage a été standardisé au Japon en 2011 (JIS X 3017:2011), et en 2012 par l'Organisation internationale de normalisation (ISO 30170:2012). Historique Yukihiro « Matz » Matsumoto est le créateur de Ruby. Frustré par son expérience en développement Smalltalk et Lisp, il commence la conception d'un nouveau langage en 1993 sous Emacs, puis publie une première version en 1995 sous licence libre. Il enchaîne depuis les nouvelles versions. Depuis l'arrivée d'une documentation anglophone, et du framework web Ruby on Rails en 2004, Ruby a connu un certain engouement qui n'a cessé de croître jusqu'en 2008 dans le monde de la programmation, puis une érosion lente si on en juge par son index Tiobe. Philosophie Ruby est fortement orienté objet et se rapproche ainsi du paradigme objet de Smalltalk :

toute donnée est un objet, y compris les types primitifs ;
toute foncti

Incremental View Maintenance for Collection Programming

Christoph Koch, Daniel Lupei, Val Tannen

In the context of incremental view maintenance (IVM), delta query derivation is an essential technique for speeding up the processing of large, dynamic datasets. The goal is to generate delta queries that, given a small change in the input, can update the materialized view more efficiently than via recomputation. In this work we propose the first solution for the efficient incrementalization of positive nested relational calculus (NRC+) on bags (with integer multiplicities). More precisely, we model the cost of NRC+ operators and classify queries as efficiently incrementalizable if their delta has a strictly lower cost than full re-evaluation. Then, we identify NRC+, a large fragment of NRC+ that is efficiently incrementalizable and we provide a semantics-preserving translation that takes any NRC+ query to a collection of IncNRC+ queries. Furthermore, we prove that incremental maintenance for NRC+ is within the complexity class NC0 and we showcase how recursive IVM, a technique that has provided significant speedups over traditional IVM in the case of flat queries, can also be applied to IncNRC+.

ACM2016

Compilation Techniques for Incremental Collection Processing

Daniel Lupei

Many map-reduce frameworks as well as NoSQL systems rely on collection programming as their interface of choice due to its rich semantics along with an easily parallelizable set of primitives. Unfortunately, the potential of collection programming is not entirely fulfilled by current systems as they lack efficient incremental view maintenance (IVM) techniques for queries producing large nested results. This comes as a consequence of the fact that the nesting of collections does not enjoy the same algebraic properties underscoring the optimization potential of typical collection processing constructs. We propose the first solution for the efficient incrementalization of collection programming in terms of its core constructs as captured by the positive nested relational calculus (NRC+) on bags (with integer multiplicities). We take an approach based on delta query derivation, whose goal is to generate delta queries which, given a small change in the input, can update the materialized view more efficiently than via recomputation. More precisely, we model the cost of NRC+ operators and classify queries as efficiently incrementalizable if their delta has a strictly lower cost than full re-evaluation. Then, we identify IncNRC+, a large fragment of NRC+ that is efficiently incrementalizable and we provide a semantics-preserving translation that takes any NRC+ query to a collection of IncNRC+ queries. Furthermore, we prove that incrementalmaintenance for NRC+ is within the complexity class NC0 and we showcase how Recursive IVM, a technique that has provided significant speedups over traditional IVM in the case of flat queries, can also be applied to IncNRC+ . Existing systems are also limited wrt. the size of inner collections that they can effectively handle before running into severe performance bottlenecks. In particular, in the face of nested collections with skewed cardinalities developers typically have to undergo a painful process of manual query re-writes in order to ensure that the largest inner collections in their workloads are not impacted by these limitations. To address these issues we developed SLeNDer, a compilation framework that given a nested query generates a set of semantically equivalent (partially) shredded queries that can be efficiently evaluated and incrementalized using state of the art techniques for handling skew and applying delta changes, respectively. The derived queries expose nested collections to the same opportunities for distributing their processing and incrementally updating their contents as those enjoyed by top-level collections, leading on our benchmark to up to 16.8x and 21.9x speedups in terms of offline and online processing, respectively. In order to enable efficient IVM for the increasingly common case of collection programming with functional values as in Links, we also discuss the efficient incrementalization of simplytyped lambda calculi, under the constraint that their primitives are themselves efficiently incrementalizable.

EPFL2017

Semantics-preserving inlining for metaprogramming

Sébastien Jean R Doeraene, Martin Odersky, Nicolas Alexander Stucki

Inlining is used in many different ways in programming languages: some languages use it as a compiler-directive solely for optimization, some use it as a metaprogramming feature, and others lay their design in-between. This paper presents inlining through the lens of metaprogramming and we describe a powerful set of metaprogramming constructs that help programmers to unfold domain-specific decisions at compile-time. In a multi-paradigm language like Scala, the concern for generality of inlining poses several interesting questions and the challenge we tackle is to offer inlining without changing the model seen by the programmer. In this paper, we explore these questions by explaining the rationale behind the design of Scala-3’s inlining capability and how it relates to its metaprogramming architecture.

2020

Compilation Techniques for Incremental Collection Processing

Daniel Lupei

EPFL2017