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ALOJA: A systematic study of Hadoop deployment variables to enable automated characterization of cost-effectiveness.

, , , , , , , , , , , , and . IEEE BigData, page 905-913. IEEE Computer Society, (2014)

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ALOJA-ML: A Framework for Automating Characterization and Knowledge Discovery in Hadoop Deployments., , , , , and . KDD, page 1701-1710. ACM, (2015)SparkFuzz: searching correctness regressions in modern query engines., , , , and . DBTest@SIGMOD, page 1:1-1:6. ACM, (2020)Microbenchmark.. Encyclopedia of Big Data Technologies, Springer, (2019)ALOJA: A Benchmarking and Predictive Platform for Big Data Performance Analysis., , and . WBDB, volume 10044 of Lecture Notes in Computer Science, page 71-84. Springer, (2015)Business Process Mining from E-Commerce Web Logs., , , and . BPM, volume 8094 of Lecture Notes in Computer Science, page 65-80. Springer, (2013)ALOJA: A systematic study of Hadoop deployment variables to enable automated characterization of cost-effectiveness., , , , , , , , , and 3 other author(s). IEEE BigData, page 905-913. IEEE Computer Society, (2014)Big Data Benchmark Compendium., , , , , , and . TPCTC, volume 9508 of Lecture Notes in Computer Science, page 135-155. Springer, (2015)ALOJA: A Framework for Benchmarking and Predictive Analytics in Big Data Deployments., , , , , and . CoRR, (2015)The state of SQL-on-Hadoop in the cloud., , , , , , and . IEEE BigData, page 1432-1443. IEEE Computer Society, (2016)From performance profiling to predictive analytics while evaluating hadoop cost-efficiency in ALOJA., , , , , , , , and . IEEE BigData, page 1220-1229. IEEE Computer Society, (2015)