User-defined aggregations (UDAs) are integral to large-scale data-processing systems,
such as MapReduce and Hadoop, because they let programmers express application …

High performance architectures for processing distributed data streams, such as Flink, Spark
Streaming, and Storm, are increasingly deployed in emerging data-driven computing …

Spark is a new promising platform for scalable data-parallel computation. It provides several
high-level application programming interfaces (APIs) to perform parallel data aggregation …

The sheer scale of today's data processing needs has led to a new paradigm of software
systems centered around requirements for high-throughput, distributed, low-latency …

MapReduce framework has become one of the more popular big data processing
frameworks. In the MapReduce framework, the test of the commutativity problem of the …

Der exponentielle Anstieg elektronisch gespeicherter Daten erfordert leistungsfähige
Systeme zur Verarbeitung und Analyse großer Datenmengen. Parallel relationale …

Applications of aggregation for information summary have great meanings in various fields.
In big data era, processing aggregate function in parallel is drawing researchers' attention …

With the continuous development of the MapReduce programming model, it is necessary to
ensure the reliability of MapReduce programs. In practice, the non-commutativity of Reduce …

With the continuous development of the MapReduce programming model, it is necessary to
ensure the reliability of MapReduce programs. In practice, the non-commutativity of Reduce …

Data-parallel applications have become prevalent due to the fast development of big data
technologies. The performances of these applications are obviously one of the most crucial …