JSON is one of the most popular data encoding formats, with wide adoption in Databases and BigData frameworks as well as native support in popular programming languages such as JavaScript/Node.js, Python, and R. Nevertheless, JSON data processing can easily become a performance bottleneck in data-intensive applications because of parse and serialization overhead. In this paper, we introduce F ad . js , a runtime system for efficient processing of JSON objects in data-intensive applications. F ad . js is based on (1) speculative just-in-time (JIT) compilation and (2) selective access to data. Experiments show that applications using F ad . js achieve speedups up to 2.7x for encoding and 9.9x for decoding JSON data when compared to state-of-the art JSON processing libraries.

This paper describes a number of XQuery-related projects. Its goal is to show that XQuery is a useful tool for many different application scenarios. In particular, this paper tries to correct a common myth that XQuery is merely a query language and that SQL is the better query language. Instead, XQuery is a full-fledged programming language for Web applications and services. Furthermore, this paper tries to correct a second myth that XQuery is slow. This paper gives an overview of the state-of-the-art in XQuery implementation and optimization techniques and discusses one particular open-source XQuery processor, Zorba, in more detail. Among others, this paper presents an XQuery Benchmark Service which helps practitioners and XQuery processor vendors to find performance problems in an XQuery processor.

There has been a great deal of hype about Amazon's simple storage service (S3). S3 provides infinite scalability and high availability at low cost. Currently, S3 is used mostly to store multi-media documents (videos, photos, audio) which are shared by a community of people and rarely updated. The purpose of this paper is to demonstrate the opportunities and limitations of using S3 as a storage system for general-purpose database applications which involve small objects and frequent updates. Read, write, and commit protocols are presented. Furthermore, the cost ($), performance, and consistency properties of such a storage system are studied.

Optimizing nested queries is an intricate problem. It becomes even harder if in a nested query the linking predicate or the correlation predicate occurs disjunctively. We present the first unnesting strategy that can effectively deal with such queries. The starting point of our approach is to translate SQL into the relational algebra extended by bypass operators. Then we present for the first time unnesting equivalences which are valid for algebraic expressions containing bypass operators. Applying these to the translated queries results in our effective unnesting strategy for nested SQL queries with disjunction. With an extensive experimental study (including three commercial DBMSs), we demonstrate the possible performance gains of our approach.

While indoor positioning systems based on 802.11 and fingerprinting work pretty well, it is unknown how to distribute large amounts of fingerprint data to mobile devices. Even worse, many mobile devices are restricted in terms of memory capabilites. We identified three classes of mobile devices representing different levels of storage capabilities. For each of these classes, we present a distribution approach for fingerprint data: the Union of Access Points (UAP), the Strongest Access Point (SAP), and the Intersection of Access Points (IAP) algorithm. These approaches utilize the 802.11 network to download only a subset of the fingerprint data to a mobile device. The subset covers the area close to the actual position of the mobile device in such a way that position estimates can be computed. The size of the subset is different for each of the three algorithms.

The XPath language incorporates powerful primitives for formulating queries containing nested subexpressions which are existentially or universally quantified. However, even the best published approaches for evaluating XPath have unsatisfactory performance when applied to nested queries. We examine optimization techniques that unnest complex XPath queries. For this purpose, we classify XPath expressions particularly with regard to properties that are relevant for unnesting. We present algebraic equivalences that transform nested expressions into unnested expressions. In our experiments we compare the evaluation times with existing XPath evaluators and the naive evaluation.

We present the first complete translation of XPath into an algebra, paving the way for a comprehensive, state-of-the-art XPath (and later on, XQuery) compiler based on algebraic optimization techniques. Our translation includes all XPath features such as nested expressions, position-based predicates and node-set functions. The translated algebraic expressions can be executed using the proven, scalable, iterator-based approach, as we demonstrate in form of a corresponding physical algebra in our native XML DBMS Natix. A first glance at performance results shows that even without further optimization of the expressions, we provide a competitive evaluation technique for XPath queries.

We present a method to evaluate path queries based on the novel concept of partial path instances. Our method (1) maximizes performance by means of sequential scans or asynchronous I/O, (2) does not require a special storage format, (3) relies on simple navigational primitives on trees, and (4) can be complemented by existing logical and physical optimizations such as duplicate elimination, duplicate prevention and path rewriting.We use a physical algebra which separates those navigation operations that require I/O from those that do not. All I/O operations necessary for the evaluation of a path are isolated in a single operator, which may employ efficient I/O scheduling strategies such as sequential scans or asynchronous I/O.Performance results for queries from the XMark benchmark show that reordering the navigation operations can increase performance up to a factor of four.