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Handbook of BigDataBench 3.1 21 Fig. 14. Excerpt of movie review data set Table 13. The summary of E-commence workloads. ID W3-1 W3-6-1 Implementation Description Select query Find the items of which the sales amount is over 100 in a single order Aggregation Count the sales number of query each goods Join query Count the number of each goods that each buyer purchased between certain period of time CF Recommendation using Collaborative Filtering algorithm Native Bayes Sensitive classification using Native Bayes algorithm Project Basic operator W3-6-2 Filter Basic operator W3-6-3 Cross Product Basic operator W3-6-4 OrderBy Basic operator W3-6-5 Union Basic operator W3-6-6 Difference Basic operator W3-6-7 Aggregation Basic operator W3-2 W3-3 W3-4 W3-5 Data set E-commence Transaction Software stack Hive, Shark, Impala E-commence Transaction E-commence Transaction Hive, Shark, Impala Hive, Shark, Impala Amazon Reviews Movie Hadoop, MPI Amazon Movie Reviews E-commerce Transaction E-commerce Transaction E-commerce Transaction E-commerce Transaction E-commerce Transaction E-commerce Transaction E-commerce Transaction Spark, Hadoop, Spark, MPI Hive, Shark, Impala Hive, Shark, Impala Hive, Shark, Impala Hive, Shark, Impala Hive, Shark, Impala Hive, Shark, Impala Hive, Shark, Impala
