bluuebunny/crossref_metadata_2025_split huggingface dataset:
Efficiently approximating query optimizer plan diagrams
Authors: Dey Atreyee , Bhaumik Sourjya , D Harish , Haritsa Jayant R. 
Published: June 2014

Given a parametrized n-dimensional SQL query template and a choice of query optimizer, a plan diagram is a color-coded pictorial enumeration of the execution plan choices of the optimizer over the query parameter space. These diagrams have proved to be a powerful metaphor for the analysis and redesign of modern optimizers, and are gaining currency in diverse industrial and academic institutions. However, their utility is adversely impacted by the impractically large computational overheads incurred when standard brute-force exhaustive approaches are used for producing fine-grained diagrams on high-dimensional query templates.
In this paper, we investigate strategies for efficiently producing close approximations to complex plan diagrams. Our techniques are customized to the features available in the optimizer's API, ranging from the generic optimizers that provide only the optimal plan for a query, to those that also support costing of sub-optimal plans and enumerating rank-ordered lists of plans. The techniques collectively feature both random and grid sampling, as well as inference techniques based on nearest-neighbor classifiers, parametric query optimization and plan cost monotonicity.
Extensive experimentation with a representative set of TPC-H and TPC-DS-based query templates on industrial-strength optimizers indicates that our techniques are capable of delivering 90% accurate diagrams while incurring less than 15% of the computational overheads of the exhaustive approach. In fact, for full-featured optimizers, we can guarantee zero error with less than 10% overheads. These approximation techniques have been implemented in the publicly available Picasso optimizer visualization tool.
Optimizer plan change management
Authors: Ziauddin Mohamed , Das Dinesh , Su Hong , Zhu Yali , Yagoub Khaled 
Published: June 2014

Execution plans for SQL statements have a significant impact on the overall performance of database systems. New optimizer statistics, configuration parameter changes, software upgrades and hardware resource utilization are among a multitude of factors that may cause the query optimizer to generate new plans. While most of these plan changes are beneficial or benign, a few rogue plans can potentially wreak havoc on system performance or availability, affecting critical and time-sensitive business application needs. The normally desirable ability of a query optimizer to adapt to system changes may sometimes cause it to pick a sub-optimal plan compromising the stability of the system.
In this paper, we present the new SQL Plan Management feature in Oracle 11g. It provides a comprehensive solution for managing plan changes to provide stable and optimal performance for a set of SQL statements. Two of its most important goals are preventing sub-optimal plans from being executed while allowing new plans to be used if they are verifiably better than previous plans. This feature is tightly integrated with Oracle's query optimizer.
SQL Plan Management is available to users via both command-line and graphical interfaces. We describe the feature and then, using an industrial-strength application suite, present experimental results that show that SQL Plan Management provides stable and optimal performance for SQL statements with no performance regressions.
AlvisP2P
Authors: Luu Toan , Skobeltsyn Gleb , Klemm Fabius , Puh Maroje , Žarko Ivana Podnar , Rajman Martin , Aberer Karl 
Published: June 2014

In this paper we present the
AlvisP2P
IR engine, which enables efficient retrieval with multi-keyword queries from a global document collection available in a P2P network. In such a network, each peer publishes its local index and invests a part of its local computing resources (storage, CPU, bandwidth) to maintain a fraction of a global P2P index. This investment is rewarded by the network-wide accessibility of the local documents via the global search facility.

The AlvisP2P engine uses an optimized overlay network and relies on novel indexing/retrieval mechanisms that ensure low bandwidth consumption, thus enabling unlimited network growth.
Our demonstration shows how an easy-to-install AlvisP2P client can be used to join an existing P2P network, index local (text or even multimedia) documents with collection-specific indexing mechanisms, and control access rights to them.
Mining patterns and rules for software specification discovery
Authors: Lo David , Khoo Siau-Cheng 
Published: June 2014

Software specifications are often lacking, incomplete and outdated in the industry. Lack and incomplete specifications cause various software engineering problems. Studies have shown that program comprehension takes up to 45% of software development costs. One of the root causes of the high cost is the lack-of documented specification. Also, outdated and incomplete specification might potentially cause bugs and compatibility issues. In this paper, we describe novel data mining techniques to mine or reverse engineer these specifications from the pool of software engineering data.
A large amount of software data is available for analysis. One form of software data is program execution traces. A program trace can be viewed as a sequence of events collected when a program is run. A set of program traces in turn can be viewed as a sequence database. In this paper, we present some novel work in mining software specifications by employing novel pattern mining and rule mining techniques. Performance studies show the scalability of our technique. Case studies on traces of a real industrial application show the utility of our technique in recovering program specifications from execution traces.
Oracle SecureFiles
Authors: Mukherjee Niloy , Ganesh Amit , Djegaradjane Vinayagam , Muthulingam Sujatha , Zhang Wei , Kunchithapadam Krishna , Lynn Scott , Aleti Bharath , Shergill Kam , Wang Shaoyu 
Published: June 2014

Digital unstructured data volumes across enterprise, Internet and multimedia applications are predicted to surpass 6.023x10
23
(Avogadro's number) bits a year in the next fifteen years. This poses tremendous scalability challenges for data management solutions in the coming decades. Filesystems seem to be preferred by data management application designers for providing storage solutions for such unstructured data volumes.

Oracle SecureFiles is emerging as the database solution to break the performance barrier that has kept unstructured content out of database management systems and to provide advanced filesystem functionality, while letting applications fully leverage the strengths of the RDBMS from transactions to partitioning to rollforward recovery. A set of preliminary performance results was presented at the 34th International Conference on Very Large Data Bases (VLDB 2008). It was claimed that SecureFiles would scale maximally as physical storage systems scale up. We legitimize our claims on SecureFiles scalability through this paper, presenting the scalability aspects of SecureFiles through a performance evaluation of I/O bound filesystem like operations on one of the latest high performance cluster of servers and storage.
We are presenting benchmark results that we believe represent a world record database insertion rate for any published result - at over 4.4GB/S using a cluster of seven servers. For 100 byte rows, that represents an insertion rate of 45 billion records a second in relational terms. In terms of unstructured data storage, the scale represents an insertion rate of more than 3.7 million 100 MB high-resolution multimedia videos a day.
Cooperative update exchange in the Youtopia system
Authors: Kot Łucja , Koch Christoph 
Published: June 2014

Youtopia is a platform for collaborative management and integration of relational data. At the heart of Youtopia is an update exchange abstraction: changes to the data propagate through the system to satisfy user-specified mappings. We present a novel change propagation model that combines a deterministic chase with human intervention. The process is fundamentally cooperative and gives users significant control over how mappings are repaired. An additional advantage of our model is that mapping cycles can be permitted without compromising correctness.
We investigate potential harmful interference between updates in our model; we introduce two appropriate notions of serializability that avoid such interference if enforced. The first is very general and related to classical final-state serializability; the second is more restrictive but highly practical and related to conflict-serializability. We present an algorithm to enforce the latter notion. Our algorithm is an optimistic one, and as such may sometimes require updates to be aborted. We develop techniques for reducing the number of aborts and we test these experimentally.
Improving OLTP scalability using speculative lock inheritance
Authors: Johnson Ryan , Pandis Ippokratis , Ailamaki Anastasia 
Published: June 2014

Transaction processing workloads provide ample request level concurrency which highly parallel architectures can exploit. However, the resulting heavy utilization of core database services also causes resource contention within the database engine itself and limits scalability. Meanwhile, many database workloads consist of short transactions which access only a few database records each, often with stringent response time requirements. Performance of these short transactions is determined largely by the amount of overhead the database engine imposes for services such as logging, locking, and transaction management.
This paper highlights the negative scalability impact of database locking, an effect which is especially severe for short transactions running on highly concurrent multicore hardware. We propose and evaluate Speculative Lock Inheritance, a technique where hot database locks pass directly from transaction to transaction, bypassing the lock manager bottleneck. We implement SLI in the Shore-MT storage manager and show that lock inheritance fundamentally improves scalability by decoupling the number of simultaneous requests for popular locks from the number of threads in the system, eliminating contention within the lock manager even as core counts continue to increase. We achieve this effect with only minor changes to the lock manager and without changes to consistency or other application-visible effects.
Data processing on FPGAs
Authors: Mueller Rene , Teubner Jens , Alonso Gustavo 
Published: June 2014

Computer architectures are quickly changing toward heterogeneous many-core systems. Such a trend opens up interesting opportunities but also raises immense challenges since the efficient use of heterogeneous many-core systems is not a trivial problem. In this paper, we explore how to program data processing operators on top of field-programmable gate arrays (FPGAs). FPGAs are very versatile in terms of how they can be used and can also be added as additional processing units in standard CPU sockets.
In the paper, we study how data processing can be accelerated using an FPGA. Our results indicate that efficient usage of FPGAs involves non-trivial aspects such as having the right computation model (an asynchronous sorting network in this case); a careful implementation that balances all the design constraints in an FPGA; and the proper integration strategy to link the FPGA to the rest of the system. Once these issues are properly addressed, our experiments show that FPGAs exhibit performance figures competitive with those of modern general-purpose CPUs while offering significant advantages in terms of power consumption and parallel stream evaluation.
Inverting schema mappings
Authors: Arenas Marcelo , Pérez Jorge , Reutter Juan , Riveros Cristian 
Published: June 2014

The inversion of schema mappings has been identified as one of the fundamental operators for the development of a general framework for metadata management. In fact, during the last years three alternative notions of inversion for schema mappings have been proposed (Fagin-inverse [10], quasi-inverse [14] and maximum recovery [2]). However, the procedures that have been developed for computing these operators have some features that limit their practical applicability. First, these algorithms work in exponential time and produce inverse mappings of exponential size. Second, these algorithms express inverses in some mappings languages which include features that are difficult to use in practice. A typical example is the use of disjunction in the conclusion of the mapping rules, which makes the process of exchanging data much more complicated.
In this paper, we propose solutions for the two problems mentioned above. First, we provide a polynomial time algorithm that computes the three inverse operators mentioned above given a mapping specified by a set of tuple-generating dependencies (tgds). This algorithm uses an output mapping language that can express these three operators in a compact way and, in fact, can compute inverses for a much larger class of mappings. Unfortunately, it has already been proved that this type of mapping languages has to include some features that are difficult to use in practice and, hence, this is also the case for our output mapping language. Thus, as our second contribution, we propose a new and natural notion of inversion that overcomes this limitation. In particular, every mapping specified by a set of tgds admits an inverse under this new notion that can be expressed in a mapping language that slightly extends tgds, and that has the same good properties for data exchange as tgds. Finally, as our last contribution, we provide an algorithm for computing such inverses.
An evaluation of checkpoint recovery for massively multiplayer online games
Authors: Vaz Salles Marcos , Cao Tuan , Sowell Benjamin , Demers Alan , Gehrke Johannes , Koch Christoph , White Walker 
Published: June 2014

Massively multiplayer online games (MMOs) have emerged as an exciting new class of applications for database technology. MMOs simulate long-lived, interactive virtual worlds, which proceed by applying updates in frames or ticks, typically at 30 or 60 Hz. In order to sustain the resulting high update rates of such games, game state is kept entirely in main memory by the game servers. Nevertheless, durability in MMOs is usually achieved by a standard DBMS implementing ARIES-style recovery. This architecture limits scalability, forcing MMO developers to either invest in high-end hardware or to over-partition their virtual worlds.
In this paper, we evaluate the applicability of existing checkpoint recovery techniques developed for main-memory DBMS to MMO workloads. Our thorough experimental evaluation uses a detailed simulation model fed with update traces generated synthetically and from a prototype game server. Based on our results, we recommend MMO developers to adopt a copy-on-update scheme with a double-backup disk organization to checkpoint game state. This scheme outperforms alternatives in terms of the latency introduced in the game as well the time necessary to recover after a crash.
The case for determinism in database systems
Authors: Thomson Alexander , Abadi Daniel J. 
Published: June 2014

Replication is a widely used method for achieving high availability in database systems. Due to the nondeterminism inherent in traditional concurrency control schemes, however, special care must be taken to ensure that replicas don't diverge. Log shipping, eager commit protocols, and lazy synchronization protocols are well-understood methods for safely replicating databases, but each comes with its own cost in availability, performance, or consistency.
In this paper, we propose a distributed database system which combines a simple deadlock avoidance technique with concurrency control schemes that guarantee equivalence to a predetermined serial ordering of transactions. This effectively removes all nondeterminism from typical OLTP workloads, allowing active replication with no synchronization overhead whatsoever. Further, our system eliminates the requirement for two-phase commit for any kind of distributed transaction, even across multiple nodes within the same replica. By eschewing deadlock detection and two-phase commit, our system under many workloads outperforms traditional systems that allow nondeterministic transaction reordering.
The performance of MapReduce
Authors: Jiang Dawei , Ooi Beng Chin , Shi Lei , Wu Sai 
Published: June 2014

MapReduce has been widely used for large-scale data analysis in the Cloud. The system is well recognized for its elastic scalability and fine-grained fault tolerance although its performance has been noted to be suboptimal in the database context. According to a recent study [19], Hadoop, an open source implementation of MapReduce, is slower than two state-of-the-art parallel database systems in performing a variety of analytical tasks by a factor of 3.1 to 6.5. MapReduce can achieve better performance with the allocation of more compute nodes from the cloud to speed up computation; however, this approach of "renting more nodes" is not cost effective in a pay-as-you-go environment. Users desire an economical elastically scalable data processing system, and therefore, are interested in whether MapReduce can offer both elastic scalability and efficiency.
In this paper, we conduct a performance study of MapReduce (Hadoop) on a 100-node cluster of Amazon EC2 with various levels of parallelism. We identify five design factors that affect the performance of Hadoop, and investigate alternative but known methods for each factor. We show that by carefully tuning these factors, the overall performance of Hadoop can be improved by a factor of 2.5 to 3.5 for the same benchmark used in [19], and is thus more comparable to that of parallel database systems. Our results show that it is therefore possible to build a cloud data processing system that is both elastically scalable and efficient.
Aether
Authors: Johnson Ryan , Pandis Ippokratis , Stoica Radu , Athanassoulis Manos , Ailamaki Anastasia 
Published: June 2014

The shift to multi-core hardware brings new challenges to database systems, as the software parallelism determines performance. Even though database systems traditionally accommodate simultaneous requests, a multitude of synchronization barriers serialize execution. Write-ahead logging is a fundamental, omnipresent component in ARIES-style concurrency and recovery, and one of the most important yet-to-be addressed potential bottlenecks, especially in OLTP workloads making frequent small changes to data.
In this paper, we identify four logging-related impediments to database system scalability. Each issue challenges different level in the software architecture: (a) the high volume of small-sized I/O requests may saturate the disk, (b) transactions hold locks while waiting for the log flush, (c) extensive context switching overwhelms the OS scheduler with threads executing log I/Os, and (d) contention appears as transactions serialize accesses to in-memory log data structures. We demonstrate these problems and address them with techniques that, when combined, comprise a holistic, scalable approach to logging. Our solution achieves a 20%-69% speedup over a modern database system when running log-intensive workloads, such as the TPC-B and TATP benchmarks. Moreover, it achieves log insert throughput over 1.8GB/s for small log records on a single socket server, an order of magnitude higher than the traditional way of accessing the log using a single mutex.
Global detection of complex copying relationships between sources
Authors: Dong Xin Luna , Berti-Equille Laure , Hu Yifan , Srivastava Divesh 
Published: June 2014

Web technologies have enabled data sharing between sources but also simplified copying (and often publishing without proper attribution). The copying relationships can be complex: some sources copy from multiple sources on different subsets of data; some co-copy from the same source, and some transitively copy from another. Understanding such copying relationships is desirable both for business purposes and for improving many key components in data integration, such as resolving conflicts across various sources, reconciling distinct references to the same real-world entity, and efficiently answering queries over multiple sources. Recent works have studied how to detect copying between a pair of sources, but the techniques can fall short in the presence of complex copying relationships.
In this paper we describe techniques that discover global copying relationships between a set of structured sources. Towards this goal we make two contributions. First, we propose a global detection algorithm that identifies co-copying and transitive copying, returning only source pairs with direct copying. Second, global detection requires accurate decisions on copying direction; we significantly improve over previous techniques on this by considering various types of evidence for copying and correlation of copying on different data items. Experimental results on real-world data and synthetic data show high effectiveness and efficiency of our techniques.
FlashStore
Authors: Debnath Biplob , Sengupta Sudipta , Li Jin 
Published: June 2014

We present FlashStore, a high throughput persistent key-value store, that uses flash memory as a non-volatile cache between RAM and hard disk. FlashStore is designed to store the working set of key-value pairs on flash and use one flash read per key lookup. As the working set changes over time, space is made for the current working set by destaging recently unused key-value pairs to hard disk and recycling pages in the flash store. FlashStore organizes key-value pairs in a log-structure on flash to exploit faster sequential write performance. It uses an in-memory hash table to index them, with hash collisions resolved by a variant of cuckoo hashing. The in-memory hash table stores compact key signatures instead of full keys so as to strike tradeoffs between RAM usage and false flash read operations.
FlashStore can be used as a high throughput persistent key-value storage layer for a broad range of server class applications. We compare FlashStore with BerkeleyDB, an embedded key-value store application, running on hard disk and flash separately, so as to bring out the performance gain of FlashStore in not only using flash as a cache above hard disk but also in its use of flash aware algorithms. We use real-world data traces from two data center applications, namely, Xbox LIVE Primetime online multi-player game and inline storage deduplication, to drive and evaluate the design of FlashStore on traditional and low power server platforms. FlashStore outperforms BerkeleyDB by up to 60x on throughput (ops/sec), up to 50x on energy efficiency (ops/Joule), and up to 85x on cost efficiency (ops/sec/dollar) on the evaluated datasets.