From: Evaluating partitioning and bucketing strategies for Hive-based Big Data Warehousing systems
SF = 30 | SF = 100 | SF = 300 | SF = 30 | SF = 100 | SF = 300 | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
HIVE | PRESTO | |||||||||||
SS | SS-B | SS | SS-B | SS | SS-B | SS | SS-B | SS | SS-B | SS | SS-B | |
Q1.1 | 25 | 23 | 31 | 29 | 44 | 45 | 5 | 5 | 13 | 14 | 36 | 35 |
Q1.2 | 24 | 24 | 29 | 30 | 42 | 45 | 5 | 6 | 13 | 12 | 34 | 34 |
Q1.3 | 24 | 24 | 29 | 30 | 43 | 44 | 4 | 5 | 13 | 12 | 35 | 36 |
Q2.1 | 32 | 33 | 47 | 59 | 531 | 702 | 8 | 11 | 19 | 27 | 59 | 82 |
Q2.2 | 31 | 31 | 46 | 51 | 531 | 681 | 7 | 9 | 18 | 23 | 51 | 67 |
Q2.3 | 30 | 31 | 44 | 54 | 531 | 699 | 7 | 9 | 17 | 22 | 49 | 62 |
Q3.1 | 35 | 34 | 59 | 64 | 651 | 684 | 8 | 11 | 29 | 30 | 81 | 88 |
Q3.2 | 30 | 30 | 45 | 46 | 677 | 688 | 6 | 7 | 17 | 20 | 51 | 57 |
Q3.3 | 33 | 33 | 219 | 224 | 665 | 702 | 5 | 7 | 15 | 17 | 43 | 52 |
Q3.4 | 34 | 32 | 222 | 225 | 675 | 870 | 6 | 7 | 15 | 16 | 43 | 52 |
Q4.1 | 38 | 39 | 86 | 100 | 226 | 256 | 13 | 18 | 43 | 49 | 119 | 142 |
Q4.2 | 49 | 50 | 70 | 70 | 141 | 155 | 9 | 14 | 26 | 33 | 69 | 90 |
Q4.3 | 34 | 37 | 54 | 65 | 116 | 141 | 8 | 12 | 23 | 29 | 63 | 77 |
Total | 420 | 420 | 982 | 1047 | 4874 | 5712 | 92 | 121 | 262 | 305 | 733 | 876 |
Diff. | 0% | 7% | 17% | 32% | 16% | 19% |