Code Generation for Efficient Query Processing in Managed Runtimes

In this paper we examine opportunities arising from the conver-gence of two trends in data management: in-memory database sys-tems (IMDBs), which have received renewed attention following the availability of affordable, very large main memory systems; and language-integrated query, which transparently integrates database queries with programming languages (thus addressing the famous ‘impedance mismatch ’ problem). Language-integrated query not only gives application developers a more convenient way to query external data sources like IMDBs, but also to use the same querying language to query an application’s in-memory collections. The lat-ter offers further transparency to developers as the query language and all data is represented in the data model of the host program-ming language. However, compared to IMDBs, this additional free-dom comes at a higher cost for query evaluation. Our vision is to improve in-memory query processing of application objects by introducing database technologies to managed runtimes. We focus on querying and we leverage query compilation to im-prove query processing on application objects. We explore dif-ferent query compilation strategies and study how they improve the performance of query processing over application data. We take C] as the host programming language as it supports language-integrated query through the LINQ framework. Our techniques de-liver significant performance improvements over the default LINQ implementation. Our work makes important first steps towards a future where data processing applications will commonly run on machines that can store their entire datasets in-memory, and will be written in a single programming language employing language-integrated query and IMDB-inspired runtimes to provide transparent and highly efficient querying. 1

Benchmarking : Erfahrungsaustausch steigert Wettbewerbsfähigkeit

Themenheft: KMU – Rückgrat der Schweizer WirtschaftWie positioniere ich mich gegenüber neuen Anbietern? Sind meine Personalkosten marktgerecht? Mit solchen oder ähnlichen Fragen sehen sich Unternehmer im Alltag konfrontiert. Hilfreich ist der regelmässige Austausch mit Gleichgesinnten. Geschäftsführer und Unternehmer sind stärker denn je mit den Herausforderungen der hochdynamischen Umweltsphären konfrontiert. Trotz der Konsultation externer Berater, Ratschlägen aus dem Familien- und Freundeskreis oder des Austauschs im Rahmen lokaler Gremien fehlt vielen Unternehmern eine Plattform, um wichtige Fragen mit Gleichgesinnten diskutieren zu können. Diese Möglichkeit bieten sogenannte «Erfahrungsgruppen» (ERFA-Gruppen). Dort werden reale Probleme besprochen und leistungsorientierte Vergleiche (Benchmarking) durchgeführt, um Leistungslücken zu identifizieren. So wird mittels Benchmarking eine kontinuierliche Optimierung angestrebt und versucht, Wettbewerbsvorteile zu schaffen. Entscheidend für den Erfolg einer ERFA-Gruppe ist eine grosse Offenheit unter den Teilnehmenden. Nur so lassen sich substanzielle Antworten finden. Unternehmer sind aber verständlicherweise eher zurückhaltend, wenn es darum geht, die eigene interne Situation direkten Mitbewerbern offenzulegen. Um trotzdem die notwendige Transparenz zu erreichen, besteht eine ERFA-Gruppe idealerweise aus Unternehmen, die zwar die Situation und die Probleme der jeweiligen Branche kennen, jedoch auf anderen regionalen Märkten aktiv sind. Ein branchenübergreifendes Benchmarking ist ebenfalls ein erfolgreiches Instrument, um von den Besten zu lernen. Hier sinkt die Hemmschwelle für die Offenlegung noch tiefer, da die anderen in der Gruppe engagierten Unternehmen keine direkten Konkurrenten darstellen

Friendships in Integrative Settings: Network Analyses in Organized Sports and a Comparison with School

Social networks affect health. In this empirical study, friendship networks in integrative organized sports were examined and then compared with friendship networks in integrative school. Relevant factors for friendship network formation were investigated, with a particular interest in the relevance of intellectual disability. Advanced social network analysis was performed using exponential random graph modeling (ERGM) on individual attributes and dyadic factors, while controlling for network structures. A meta-analysis of estimated ERGMs in each setting, organized sports and school, was conducted. When controlling for all other included factors, intellectual disability is not relevant for friendship networks in organized sports. Athletic ability and gender homophily are relevant factors, while language and similarity in athletic ability are not. Contrary to the results for organized sports, intellectual disability and speaking a foreign language at home are negative factors in friendship networks at school. Athletic ability is important in both settings. Regarding dyadic factors, gender homophily is important in both settings, but similarity in athletic ability is not. To foster the psychosocial health of children with intellectual disabilities, they should be encouraged to participate in integrative organized sports as, there, they are part of friendship networks in a manner equal to their peers without an intellectual disability

Efficient query processing in managed runtimes

This thesis presents strategies to improve the query evaluation performance over huge volumes of relational-like data that is stored in the memory space of managed applications. Storing and processing application data in the memory space of managed applications is motivated by the convergence of two recent trends in data management. First, dropping DRAM prices have led to memory capacities that allow the entire working set of an application to fit into main memory and to the emergence of in-memory database systems (IMDBs). Second, language-integrated query transparently integrates query processing syntax into programming languages and, therefore, allows complex queries to be composed in the application. IMDBs typically serve as data stores to applications written in an object-oriented language running on a managed runtime. In this thesis, we propose a deeper integration of the two by storing all application data in the memory space of the application and using language-integrated query, combined with query compilation techniques, to provide fast query processing. As a starting point, we look into storing data as runtime-managed objects in collection types provided by the programming language. Queries are formulated using language-integrated query and dynamically compiled to specialized functions that produce the result of the query in a more efficient way by leveraging query compilation techniques similar to those used in modern database systems. We show that the generated query functions significantly improve query processing performance compared to the default execution model for language-integrated query. However, we also identify additional inefficiencies that can only be addressed by processing queries using low-level techniques which cannot be applied to runtime-managed objects. To address this, we introduce a staging phase in the generated code that makes query-relevant managed data accessible to low-level query code. Our experiments in .NET show an improvement in query evaluation performance of up to an order of magnitude over the default language-integrated query implementation. Motivated by additional inefficiencies caused by automatic garbage collection, we introduce a new collection type, the black-box collection. Black-box collections integrate the in-memory storage layer of a relational database system to store data and hide the internal storage layout from the application by employing existing object-relational mapping techniques (hence, the name black-box). Our experiments show that black-box collections provide better query performance than runtime-managed collections by allowing the generated query code to directly access the underlying relational in-memory data store using low-level techniques. Black-box collections also outperform a modern commercial database system. By removing huge volumes of collection data from the managed heap, black-box collections further improve the overall performance and response time of the application and improve the application’s scalability when facing huge volumes of collection data. To enable a deeper integration of the data store with the application, we introduce self-managed collections. Self-managed collections are a new type of collection for managed applications that, in contrast to black-box collections, store objects. As the data elements stored in the collection are objects, they are directly accessible from the application using references which allows for better integration of the data store with the application. Self-managed collections manually manage the memory of objects stored within them in a private heap that is excluded from garbage collection. We introduce a special collection syntax and a novel type-safe manual memory management system for this purpose. As was the case for black-box collections, self-managed collections improve query performance by utilizing a database-inspired data layout and allowing the use of low-level techniques. By also supporting references between collection objects, they outperform black-box collections

Recycling in pipelined query evaluation

htmlabstractDatabase systems typically execute queries in isolation. Sharing recurring intermediate and final results between successive query invocations is ignored or only exploited by caching final query results. The DBA is kept in the loop to make explicit sharing decisions by identifying and/or defining materialized views. Thus decisions are made only after a long time and sharing opportunities may be missed. Recycling intermediate results has been proposed as a method to make database query engines profit from opportunities to reuse fine-grained partial query results, that is fully autonomous and is able to continuously adapt to changes in the workload. The technique was recently revisited in the context of MonetDB, a system that by default materializes all intermediate results. Materializing intermediate results can consume significant system resources, therefore most other database systems avoid this where possible, following a pipelined query architecture instead. The novelty of this paper is to show how recycling can successfully be applied in pipelined query executors, by tracking the benefit of materializing possible intermediate results and then choosing the ones making best use of a limited intermediate result cache. We present ways to maximize the potential of recycling by leveraging subsumption and proactive query rewriting. We have implemented our approach in the Vectorwise database engine and have experimentally evaluated its potential using both synthetic and real-world datasets. Our results show that intermediate result recycling significantly improves performance

The Spartan 1 mission

The first Spartan mission is documented. The Spartan program, an outgrowth of a joint Naval Research Laboratory (NRL)/National Aeronautics and Space Administration (NASA)-Goddard Space Flight Center (GSFC) development effort, was instituted by NASA for launching autonomous, recoverable payloads from the space shuttle. These payloads have a precise pointing system and are intended to support a wide range of space-science observations and experiments. The first Spartan, carrying an NRL X-ray astronomy instrument, was launched by the orbiter Discovery (STS51G) on June 20, 1985 and recovered successfully 45 h later, on June 22. During this period, Spartan 1 conducted a preprogrammed series of observations of two X-ray sources: the Perseus cluster of galaxies and the center of our galaxy. The mission was successful from both on engineering and a scientific viewpoint. Only one problem was encountered, the attitude control system (ACS) shut down earlier than planned because of high attitude control system gas consumption. A preplanned emergency mode then placed Spartan 1 into a stable, safe condition and allowed a safe recovery. The events are described of the mission and presents X-ray maps of the two observed sources, which were produced from the flight data

Zum Zusammenhang zwischen der Einstellung der Lehrkraft zu inklusivem Sportunterricht und sozialer Interaktionen von Kindern

This paper focuses on two questions: Do children with and without intellectual disabilities in inclusive physical education differ in their social interactions? And does this correlate to the attitude that physical education teachers have toward inclusive education? To this end, in a cross-sectional analysis, 1502 children and 84 teachers at the elementary school level were surveyed. Social network analyses show that children with special educational needs (SEN) receive significantly fewer social interactions in physical education classes than children without SEN but have the same number of outgoing interactions. However, social interactions are not related to teacher attitude. On this basis, the role of the teacher in children’s social interactions is discussed.Im Zentrum des Beitrags stehen zwei Fragen: 1. Unterscheiden sich Kinder mit und ohne kognitive Beeinträchtigung im inklusiven Sportunterricht in ihren sozialen Interaktionen? 2. Besteht dabei ein Zusammenhang mit der Einstellung der Sportlehrkraft gegenüber inklusiver Bildung? Dazu wurden in einer Querschnittsanalyse 1502 Kinder und 84 Lehrkräfte auf Grundschulstufe befragt. Soziale Netzwerkanalysen zeigen, dass Kinder mit sonderpädagogischem Förderbedarf (SPF) im Sportunterricht signifikant weniger soziale Interaktionen erhalten als Kinder ohne SPF, jedoch gleich viele ausgehende Interaktionen aufweisen. Die sozialen Interaktionen hängen jedoch nicht mit der Einstellung der Lehrkraft zusammen. Auf dieser Basis wird die Rolle der Lehrkraft für die sozialen Interaktionen der Kinder diskutiert

Visualization of Tensor Fields in Mechanics

Tensors are used to describe complex physical processes in many applications. Examples include the distribution of stresses in technical materials, acting forces during seismic events, or remodeling of biological tissues. While tensors encode such complex information mathematically precisely, the semantic interpretation of a tensor is challenging. Visualization can be beneficial here and is frequently used by domain experts. Typical strategies include the use of glyphs, color plots, lines, and isosurfaces. However, data complexity is nowadays accompanied by the sheer amount of data produced by large-scale simulations and adds another level of obstruction between user and data. Given the limitations of traditional methods, and the extra cognitive effort of simple methods, more advanced tensor field visualization approaches have been the focus of this work. This survey aims to provide an overview of recent research results with a strong application-oriented focus, targeting applications based on continuum mechanics, namely the fields of structural, bio-, and geomechanics. As such, the survey is complementing and extending previously published surveys. Its utility is twofold: (i) It serves as basis for the visualization community to get an overview of recent visualization techniques. (ii) It emphasizes and explains the necessity for further research for visualizations in this context