Due to their high computational power and internal memory bandwidth, graphic processing
units (GPUs) have been extensively studied by the database systems research community …

With modern computer architecture evolving, two problems conspire against the state-of-the-
art approaches in parallel query execution:(i) to take advantage of many-cores, all query …

There has been a significant amount of excitement and recent work on column-oriented
database systems (" column-stores"). These database systems have been shown to perform …

Dataframes are a popular abstraction to represent, prepare, and analyze data. Despite the
remarkable success of dataframe libraries in Rand Python, dataframes face performance …

Database indices provide a non-discriminative navigational infrastructure to localize tuples
of interest. Their maintenance cost is taken during database updates. In this paper, we study …

Large-scale data analysis lies in the core of modern enterprises and scientific research. With
the emergence of cloud computing, the use of an analytical query processing infrastructure …

Apache Hive is a widely used data warehouse system for Apache Hadoop, and has been
adopted by many organizations for various big data analytics applications. Closely working …

While hardware technology has undergone major advancements over the past decade,
transaction processing systems have remained largely unchanged. The number of cores on …

Computer architectures are quickly changing toward heterogeneous many-core systems.
Such a trend opens up interesting opportunities but also raises immense challenges since …

MapReduce has become an effective approach to big data analytics in large cluster
systems, where SQL-like queries play important roles to interface between users and …