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nLDE SPARQL engine: computing diefficiency metrics based on answer traces and query processing performance benchmarking

dataset
posted on 18.10.2017 by Maribel Acosta, Maria-Esther Vidal, York Sure-Vetter

This dataset contains results of various metric tests performed in the SPARQL query engine nLDE: the network of Linked Data Eddies, in different configurations. The queries themselves are available via the nLDE website and tests are explained in depth within the associated publication.

To compute the diefficiency metrics dief@t and dief@k, we need the answer trace produced by the SPARQL query engines when executing queries. Answer traces record the exact point in time when an engine produces an answer when executing a query.

We executed SPARQL queries using three different configurations of the nLDE engine: Selective, NotAdaptive, Random. The resulting answer trace for each query execution is stored in the CSV file `nLDEBenchmark1AnswerTrace.csv`. The structure of this file is as follows:

  • `query`: id of the query executed. Example: 'Q9.sparql'
  • `approach`: name of the approach (or engine) used to execute the query.
  • `tuple`: the value `i` indicates that this row corresponds to the ith answer produced by `approach` when executing `query`.
  • `time`: elapsed time (in seconds) since `approach` started the execution of `query` until the answer `i` is produced.

In addition, to compare the performance of the nLDE engine using the metrics dief@t and dief@k as well as conventional metrics used in the query processing literature, such as: execution time, time for the first tuple, and number of answers produced. We measured the performance of the nLDE engine using conventional metrics. The results are available at the CSV file i`nLDEBenchmark1Metrics`. The structure of this CSV file is as follows:

  • `query`: id of the query executed. Example: 'Q9.sparql'
  • `approach`: name of the approach (or engine) used to execute the query.
  • `tfft`: time (in seconds) required by `approach` to produce the first tuple when executing `query`.
  • `totaltime`: elapsed time (in seconds) since `approach` started the execution of `query` until the last answer of `query` is produced.
  • `comp`: number of answers produced by `approach` when executing `query`.

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