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We present the design and a first performance evaluation of Thrill – a prototype of a general purpose big data processing framework with a convenient data-flow style programming interface. Thrill is somewhat similar to Apache Spark and Apache Flink with at least two main differences. First, Thrill is based on C++ which enables performance advantages due to(More)
Static mapping is the assignment of parallel processes to the processing elements (PEs) of a parallel system, where the assignment does not change during the application's lifetime. In our scenario we model an application's computations and their dependencies by an application graph. This graph is first partitioned into (nearly) equally sized blocks. These(More)
We present the design and a first performance evaluation of Thrill — a prototype of a general purpose big data processing framework with a convenient data-flow style programming interface. Thrill is somewhat similar to Apache Spark and Apache Flink with at least two main differences. First, Thrill is based on C++ which enables(More)
Thrill is a prototype of a high-performance general purpose big data processing framework. In the Reduce operation, which is similar to Reduce in MapReduce, Thrill performs an all-to-all hash based data shuffle of large amounts of data. Elements only occuring on a single worker could however be reduced locally without shuffling them. To find these elements,(More)
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