Implementing version support for complex objects

New applications in the area of office information systems, computer aided design and manufacturing make new demands upon database management systems. Among others highly structured objects and their history have to be represented and manipulated. The paper discusses some general problems concerning the access and storage of complex objects with their versions and the solutions developed within the AIM/II project. Queries related to versions are distinguished in ASOF queries (asking information valid at a certain moment) and WALK-THROUGH-TIME (WTT) queries (obtaining trend information concerning a certain period). In the paper some new algorithms to handle such queries are presented. A brief analysis gives an indication about the performance of query processing in historical databases

Transactional Consistency and Automatic Management in an Application Data Cache

http://www.usenix.org/events/osdi10/tech/techAbstracts.html#PortsDistributed in-memory application data caches like memcached are a popular solution for scaling database-driven web sites. These systems are easy to add to existing deployments, and increase performance significantly by reducing load on both the database and application servers. Unfortunately, such caches do not integrate well with the database or the application. They cannot maintain transactional consistency across the entire system, violating the isolation properties of the underlying database. They leave the application responsible for locating data in the cache and keeping it up to date, a frequent source of application complexity and programming errors. Addressing both of these problems, we introduce a transactional cache, TxCache, with a simple programming model. TxCache ensures that any data seen within a transaction, whether it comes from the cache or the database, reflects a slightly stale but consistent snapshot of the database. TxCache makes it easy to add caching to an application by simply designating functions as cacheable; it automatically caches their results, and invalidates the cached data as the underlying database changes. Our experiments found that adding TxCache increased the throughput of a web application by up to 5.2×, only slightly less than a non-transactional cache, showing that consistency does not have to come at the price of performance

Fully automated annotation of mitochondrial genomes using a cluster-based approach with de Bruijn graphs

A wide range of scientific fields, such as forensics, anthropology, medicine, and molecular evolution, benefits from the analysis of mitogenomic data. With the development of new sequencing technologies, the amount of mitochondrial sequence data to be analyzed has increased exponentially over the last few years. The accurate annotation of mitochondrial DNA is a prerequisite for any mitogenomic comparative analysis. To sustain with the growth of the available mitochondrial sequence data, highly efficient automatic computational methods are, hence, needed. Automatic annotation methods are typically based on databases that contain information about already annotated (and often pre-curated) mitogenomes of different species. However, the existing approaches have several shortcomings: 1) they do not scale well with the size of the database; 2) they do not allow for a fast (and easy) update of the database; and 3) they can only be applied to a relatively small taxonomic subset of all species. Here, we present a novel approach that does not have any of these aforementioned shortcomings, (1), (2), and (3). The reference database of mitogenomes is represented as a richly annotated de Bruijn graph. To generate gene predictions for a new user-supplied mitogenome, the method utilizes a clustering routine that uses the mapping information of the provided sequence to this graph. The method is implemented in a software package called DeGeCI (De Bruijn graph Gene Cluster Identification). For a large set of mitogenomes, for which expert-curated annotations are available, DeGeCI generates gene predictions of high conformity. In a comparative evaluation with MITOS2, a state-of-the-art annotation tool for mitochondrial genomes, DeGeCI shows better database scalability while still matching MITOS2 in terms of result quality and providing a fully automated means to update the underlying database. Moreover, unlike MITOS2, DeGeCI can be run in parallel on several processors to make use of modern multi-processor systems