The Theta-Join is a powerful operation to connect tuples of different relational tables based on arbitrary conditions. The operation is a fundamental requirement for many data-driven use cases, such as data cleaning, consistency checking, and hypothesis testing. However, processing theta-joins without equality predicates ...

Recently proposed index structures, that combine trie-based and comparison-based search mechanisms, considerably improve retrieval throughput for in-memory database systems. However, most of these index structures allocate small memory chunks when required. This stands in contrast to block-based index structures, that ...

Cardinality estimation is a fundamental task in database query processing and optimization. As shown in recent papers, machine learning (ML)-based approaches may deliver more accurate cardinality estimations than traditional approaches. However, a lot of training queries have to be executed during the model training phase ...

Even though most clustering algorithms serve knowledge discovery in fields other than computer science, most of them still require users to be familiar with programming or data mining to some extent. As that often prevents efficient research, we developed an easy to use, highly explainable clustering method accompanied ...

Entity resolution is the data integration task of identifying matching entities (e.g. products, customers) in one or several data sources. Previous approaches for matching and clustering entities between multiple (>2) sources either treated the different sources as a single source or assumed that the individual sources ...

Given a large graph, graph sampling determines a subgraph with similar characteristics for certain metrics of the original graph. The samples are much smaller thereby accelerating and simplifying the analysis and visualization of large graphs. We focus on the implementation of distributed graph sampling for Big Data ...

Comma-separated values (CSV) is a widely-used format for data exchange. Due to the format's prevalence, virtually all industrial-strength database systems and stream processing frameworks support importing CSV input. However, loading CSV input close to the speed of I/O hardware is challenging. Modern I/O devices such as ...

As regularly reported in the media, automated classifications and decisions based on machine learning models can cause unfair treatment of certain groups of a general population. Classically, the machine learning models are designed to make highly accurate decisions in general. When one machine learning model is not ...

In order to guarantee the reproducibility of research results, large research communities, conferences and journals increasingly demand the provision of original research data. Since this is often not possible or desired, a certain tact and sensitivity is needed. With our method, combining provenance and evolution, we ...

Mobile devices have become ubiquitous; smartphones, tablets and wearables are essential commodities for many people. The ubiquity of mobile devices combined with their ever increasing capabilities, open new possibilities for Internet-of-Things (IoT) applications where mobile devices act as both data generators as well ...