PlinyCompute: A Platform for High-Performance, Distributed, Data-Intensive Tool Development

This paper describes PlinyCompute, a system for development of high-performance, data-intensive, distributed computing tools and libraries. In the large, PlinyCompute presents the programmer with a very high-level, declarative interface, relying on automatic, relational-database style optimization to figure out how to stage distributed computations. However, in the small, PlinyCompute presents the capable systems programmer with a persistent object data model and API (the "PC object model") and associated memory management system that has been designed from the ground-up for high performance, distributed, data-intensive computing. This contrasts with most other Big Data systems, which are constructed on top of the Java Virtual Machine (JVM), and hence must at least partially cede performance-critical concerns such as memory management (including layout and de/allocation) and virtual method/function dispatch to the JVM. This hybrid approach---declarative in the large, trusting the programmer's ability to utilize PC object model efficiently in the small---results in a system that is ideal for the development of reusable, data-intensive tools and libraries. Through extensive benchmarking, we show that implementing complex objects manipulation and non-trivial, library-style computations on top of PlinyCompute can result in a speedup of 2x to more than 50x or more compared to equivalent implementations on Spark.Comment: 48 pages, including references and Appendi

OptBPPlanner: Automatic Generation of Optimized Business Process Enactment Plans

Unlike imperative models, the specifi cation of business process (BP) properties in a declarative way allows the user to specify what has to be done instead of having to specify how it has to be done, thereby facilitating the human work involved, avoiding failures, and obtaining a better optimization. Frequently, there are several enactment plans related to a specifi c declarative model, each one presenting specifi c values for different objective functions, e.g., overall completion time. As a major contribution of this work, we propose a method for the automatic generation of optimized BP enactment plans from declarative specifi cations. The proposed method is based on a constraint-based approach for planning and scheduling the BP activities. These optimized plans can then be used for different purposes like simulation, time prediction, recommendations, and generation of optimized BP models. Moreover, a tool-supported method, called OptBPPlanner, has been implemented to demonstrate the feasibility of our approach. Furthermore, the proposed method is validated through a range of test models of varying complexity.Ministerio de Ciencia e Innovación TIN2009-1371

Proceedings of the 3rd Workshop on Domain-Specific Language Design and Implementation (DSLDI 2015)

The goal of the DSLDI workshop is to bring together researchers and practitioners interested in sharing ideas on how DSLs should be designed, implemented, supported by tools, and applied in realistic application contexts. We are both interested in discovering how already known domains such as graph processing or machine learning can be best supported by DSLs, but also in exploring new domains that could be targeted by DSLs. More generally, we are interested in building a community that can drive forward the development of modern DSLs. These informal post-proceedings contain the submitted talk abstracts to the 3rd DSLDI workshop (DSLDI'15), and a summary of the panel discussion on Language Composition

Applying Prolog to Develop Distributed Systems

Development of distributed systems is a difficult task. Declarative programming techniques hold a promising potential for effectively supporting programmer in this challenge. While Datalog-based languages have been actively explored for programming distributed systems, Prolog received relatively little attention in this application area so far. In this paper we present a Prolog-based programming system, called DAHL, for the declarative development of distributed systems. DAHL extends Prolog with an event-driven control mechanism and built-in networking procedures. Our experimental evaluation using a distributed hash-table data structure, a protocol for achieving Byzantine fault tolerance, and a distributed software model checker - all implemented in DAHL - indicates the viability of the approach

Would humans without language be apes?

The bedrock of comparative psychology of cognition, especially where nonhuman primates are concerned, rests on Darwin's famous account according to which continuity would be the main trait leading from the animal to the human mind. This idea was popularized through the statement in which Darwin postulated only quantitative differences between humans and the other species, namely "the difference in mind between man and the higher animals, great as it is, certainly is one of degree and not of kind" (Darwin, 1871, p. 128)..

Interestingness of traces in declarative process mining: The janus LTLPf Approach

Declarative process mining is the set of techniques aimed at extracting behavioural constraints from event logs. These constraints are inherently of a reactive nature, in that their activation restricts the occurrence of other activities. In this way, they are prone to the principle of ex falso quod libet: they can be satisfied even when not activated. As a consequence, constraints can be mined that are hardly interesting to users or even potentially misleading. In this paper, we build on the observation that users typically read and write temporal constraints as if-statements with an explicit indication of the activation condition. Our approach is called Janus, because it permits the specification and verification of reactive constraints that, upon activation, look forward into the future and backwards into the past of a trace. Reactive constraints are expressed using Linear-time Temporal Logic with Past on Finite Traces (LTLp f). To mine them out of event logs, we devise a time bi-directional valuation technique based on triplets of automata operating in an on-line fashion. Our solution proves efficient, being at most quadratic w.r.t. trace length, and effective in recognising interestingness of discovered constraints