In the introduction to scale out piece, I promised to address the matter of data-to-memory ratio, and to talk about when scale-out makes sense. Here we will see that scale-out makes sense whenever data does not fit in memory on a single commodity server. The gains in processing power are immediate, even when going from one box to just two, with both systems having all in memory.

As an initial take on the issue we run 100 GB and 1000 GB on the test system. 100 GB is trivially in memory, 1000 GB is not, as the memory is 384 GB total, of which 360 GB may be used for the processes.

We run 2 workloads on the 100 GB database, having pre-loaded the data in memory:

run power throughput composite
1 349,027.7 420,503.1 383,102.1
2 387,890.3 433,066.6 409,856.5

This is directly comparable to the 100 GB single-server results. Comparing the second runs, we see a 1.53x gain in power and a 1.8x gain in throughput from 2x the platform. This is fully on the level for a workload that is not trivially parallel, as we have seen in the previous articles. The difference between the first and second runs at 100 GB comes, for both single-server and cluster, from the latency of allocating transient query memory. For an official run, where the weakest link is the first power test, this would simply have to be pre-allocated.

We run 2 workloads on the 1000 GB database, starting from cold.

The result is:

run power throughput composite
1 136,744.5 147,374.6 141,960.1
2 199,652.0 125,161.1 158,078.0

The 1000 GB result is not for competition with this platform; more memory would be needed. For actual applications, the numbers are still in the usable range, though.

The 1000 GB setup uses 4 SSDs for storage, one per server process. The server processes are each bound to their own physical CPU.

We look at the meters: 32M pages (8M per process) are in memory at each time. Over the 2 benchmark executions there are a total of 494M disk reads. The total CPU time is 165,674 seconds of CPU, of which about 10% are system, over 10,063 seconds of real-time. Cumulative disk-read wait-time is 130,177 s. This gives an average disk read throughput of 384 MB/s.

This is easily sustained by 4 SSDs; in practice, the maximum throughput we see for reading is 1 GB/s (256 MB/s per SSD). Newer SSDs would do maybe twice that. Using rotating media would not be an option.

Without the drop in CPU caused by waiting for SSD, we would have numbers very close to the 100 GB numbers.

The interconnect traffic for the two runs was 1,077 GB with no message compression. The write block time was 448 seconds of thread-time. So we see that blocking on write hurts platform utilization when running under optimal conditions, but compared to going to secondary storage, it is not a large factor.

The 1000 GB scale has a transient peak memory consumption of 42 GB. This consists of hash-join build sides and GROUP BYs. The greatest memory consumers are Q9 with 9 GB, Q13 with 11 GB, and Q16 with 7 GB. Having many of these at a time drives up the transient peak. The peak gets higher as the scale grows, also because a larger scale requires more concurrent query streams. At the 384 GB for 1000 GB ratio, we do not yet get into memory saving plans like hash joins in many passes or index use instead of hash. When the data size grows, replicated hash build sides will become less convenient, and communication will increase. Q9 and Q13 can be done by index with almost no transient memory, but these plans are easily 3x less efficient for CPU. These will probably help at 3000 GB and be necessary at least part of the time at 10,000 GB.

The I/O volume in MB per index over the 2 executions is:

index MB
LINEITEM 1,987,483
ORDERS 1,440,526
PARTSUPP 199,335
PART 161,717
CUSTOMER 43,276
O_CK 19,085
SUPPLIER 13,393

Of this, maybe 600 GB could be saved by stream compressing o_comment. Otherwise this cannot be helped without adding memory. The lineitem reads are mostly for l_extendedprice, which is not compressible. If compressing o_comment made l_extendedprice always fit in memory, then there would be a radical drop in I/O. Also, as a matter of fact, the buffer management policy of least-recently-used works the very worst for big scans, specifically those of l_extendedprice: If the head is replaced when reading the tail, and the next read starts from the head, then the whole table/column is read all over again. Caching policies that specially recognized scans of this sort could further reduce I/O. Clustering lineitems/orders on date, as Actian Vector TPC-H implementations do, also starts yielding a greater gain when not running from memory: One column (e.g., l_shipdate) may be scanned for the whole table but, if the matches are bunched together, then most of l_extendedprice will not be read at all. Still, if going for top ranks in the races, all will be from memory, or at least there will be SSDs with read throughput around 150 MB/s per core, so these tricks become relatively less important.

In the 100 GB numerical quantities summaries, we see much the same picture as in the single-server. Queries get faster, but their relative times are not radically different. The throughput test (many queries at a time) times are more or less multiples of the power (single user) times. This picture breaks at 1000 GB where I/O first drops the performance to under half and introduces huge variation in execution times within a single query. The time entirely depends on which queries are running along with or right before the execution and on whether these have the same or different working sets. All the streams have the same queries with different parameters, but the query order in each stream is different.

The numerical quantities follow for all the runs. Note that the first 1000 GB run is cold. A competition grade 1000 GB result can be made with double the memory, and the more CPU the better. We will try one at Amazon in a bit.

***

The conclusion is that scale-out pays from the get-go. At present prices, a system with twice the power of a single node of the test system is cost effective. Scales of up to 500 GB are single commodity server, under $10K. Rather than going from a mid-to-large dual-socket box to a quad-socket box, one is likely to be better off having two cheaper dual-socket boxes. These are also readily available on clouds, whereas scale-up configurations are not. Onwards of 1 TB, a cluster is expected to clearly win. At 3 TB, a commodity cluster will clearly be the better deal for both price and absolute performance.

100 GB Run 1

Virt-H Executive Summary

Report Date October 3, 2014
Database Scale Factor 100
Total Data Storage/Database Size 0M
Query Streams for
Throughput Test
5
Virt-H Power 349,027.7
Virt-H Throughput 420,503.1
Virt-H Composite
Query-per-Hour Metric
(Qph@100GB)
383,102.1
Measurement Interval in
Throughput Test (Ts)
94.273000 seconds

Duration of stream execution

Start Date/Time End Date/Time Duration
Stream 0 10/03/2014 15:05:07 10/03/2014 15:05:40 0:00:33
Stream 1 10/03/2014 15:05:42 10/03/2014 15:07:15 0:01:33
Stream 2 10/03/2014 15:05:42 10/03/2014 15:07:15 0:01:33
Stream 3 10/03/2014 15:05:42 10/03/2014 15:07:16 0:01:34
Stream 4 10/03/2014 15:05:42 10/03/2014 15:07:14 0:01:32
Stream 5 10/03/2014 15:05:42 10/03/2014 15:07:15 0:01:33
Refresh 0 10/03/2014 15:05:07 10/03/2014 15:05:13 0:00:06
10/03/2014 15:05:41 10/03/2014 15:05:42 0:00:01
Refresh 1 10/03/2014 15:06:48 10/03/2014 15:07:03 0:00:15
Refresh 2 10/03/2014 15:05:42 10/03/2014 15:06:06 0:00:24
Refresh 3 10/03/2014 15:06:06 10/03/2014 15:06:20 0:00:14
Refresh 4 10/03/2014 15:06:20 10/03/2014 15:06:35 0:00:15
Refresh 5 10/03/2014 15:06:35 10/03/2014 15:06:48 0:00:13

Numerical Quantities Summary Timing Intervals in Seconds:

Query Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8
Stream 0 2.045198 0.337315 1.129548 0.327029 1.230955 0.473090 0.979096 0.852639
Stream 1 4.521951 0.596538 3.464342 1.167101 3.944699 1.744325 5.442328 4.706185
Stream 2 4.678728 0.837205 3.594060 1.911751 3.942459 0.947788 3.821267 4.686319
Stream 3 5.126384 0.932394 0.961762 1.043759 5.359990 1.035597 3.056079 5.803445
Stream 4 4.497118 0.381036 4.665412 1.224975 5.316591 1.666253 2.297872 6.425171
Stream 5 4.080968 0.493741 4.416305 0.879202 5.705877 1.615987 3.846881 3.346686
Min Qi 4.080968 0.381036 0.961762 0.879202 3.942459 0.947788 2.297872 3.346686
Max Qi 5.126384 0.932394 4.665412 1.911751 5.705877 1.744325 5.442328 6.425171
Avg Qi 4.581030 0.648183 3.420376 1.245358 4.853923 1.401990 3.692885 4.993561
Query Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16
Stream 0 3.575916 2.786656 1.579488 0.611454 3.132460 0.685095 0.955559 1.060110
Stream 1 9.551437 7.187181 5.816455 2.004946 9.461347 5.624020 5.517677 2.924265
Stream 2 9.637427 6.641804 6.359532 2.412576 8.819754 3.335494 4.549792 3.163920
Stream 3 11.041451 6.464479 6.982671 3.272975 8.342983 3.448635 4.405911 2.886393
Stream 4 8.860228 6.754529 7.065501 3.225236 8.789565 3.419165 4.240718 2.399092
Stream 5 7.339672 8.121027 6.261988 2.711946 8.764934 3.106366 6.544712 3.472092
Min Qi 7.339672 6.464479 5.816455 2.004946 8.342983 3.106366 4.240718 2.399092
Max Qi 11.041451 8.121027 7.065501 3.272975 9.461347 5.624020 6.544712 3.472092
Avg Qi 9.286043 7.033804 6.497229 2.725536 8.835717 3.786736 5.051762 2.969152
Query Q17 Q18 Q19 Q20 Q21 Q22 RF1 RF2
Stream 0 1.433789 0.972152 0.780247 1.287222 1.360084 0.254051 6.201742 1.219707
Stream 1 3.398354 2.591249 3.021207 4.663204 4.775704 1.116547 8.770115 5.643550
Stream 2 6.811520 3.411846 2.634076 4.296810 4.669635 2.282003 18.039617 6.060465
Stream 3 4.947110 2.479268 2.952951 6.431644 5.469152 1.816467 8.271266 5.498956
Stream 4 5.240237 2.062261 2.734378 6.055141 2.997684 2.519301 7.889700 6.944722
Stream 5 4.839670 3.379315 3.231582 6.255944 3.759509 1.347830 8.707303 4.376033
Min Qi 3.398354 2.062261 2.634076 4.296810 2.997684 1.116547 7.889700 4.376033
Max Qi 6.811520 3.411846 3.231582 6.431644 5.469152 2.519301 18.039617 6.944722
Avg Qi 5.047378 2.784788 2.914839 5.540549 4.334337 1.816430 10.335600 5.704745

100 GB Run 2

Virt-H Executive Summary

Report Date October 3, 2014
Database Scale Factor 100
Total Data Storage/Database Size 0M
Query Streams for
Throughput Test
5
Virt-H Power 387,890.3
Virt-H Throughput 433,066.6
Virt-H Composite
Query-per-Hour Metric
(Qph@100GB)
409,856.5
Measurement Interval in
Throughput Test (Ts)
91.541000 seconds

Duration of stream execution

Start Date/Time End Date/Time Duration
Stream 0 10/03/2014 15:07:19 10/03/2014 15:07:47 0:00:28
Stream 1 10/03/2014 15:07:48 10/03/2014 15:09:19 0:01:31
Stream 2 10/03/2014 15:07:48 10/03/2014 15:09:16 0:01:28
Stream 3 10/03/2014 15:07:48 10/03/2014 15:09:17 0:01:29
Stream 4 10/03/2014 15:07:48 10/03/2014 15:09:16 0:01:28
Stream 5 10/03/2014 15:07:48 10/03/2014 15:09:20 0:01:32
Refresh 0 10/03/2014 15:07:19 10/03/2014 15:07:22 0:00:03
10/03/2014 15:07:47 10/03/2014 15:07:48 0:00:01
Refresh 1 10/03/2014 15:08:45 10/03/2014 15:08:59 0:00:14
Refresh 2 10/03/2014 15:07:49 10/03/2014 15:08:02 0:00:13
Refresh 3 10/03/2014 15:08:02 10/03/2014 15:08:17 0:00:15
Refresh 4 10/03/2014 15:08:17 10/03/2014 15:08:29 0:00:12
Refresh 5 10/03/2014 15:08:29 10/03/2014 15:08:45 0:00:16

Numerical Quantities Summary Timing Intervals in Seconds:

Query Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8
Stream 0 2.081986 0.208487 0.902462 0.313160 1.312273 0.493157 0.926629 0.786345
Stream 1 2.755427 0.911578 3.618085 0.664407 3.740112 2.118189 4.738754 6.551446
Stream 2 4.189612 0.957921 5.267355 2.152479 6.068005 1.263380 4.251842 3.620160
Stream 3 4.708834 0.981651 2.411839 0.790955 4.384516 1.322670 2.641571 4.771831
Stream 4 3.739567 1.185884 2.863871 1.517891 5.946967 1.179960 3.840560 4.926325
Stream 5 5.258746 0.705228 3.460904 0.951328 4.530620 1.104500 3.226494 4.041142
Min Qi 2.755427 0.705228 2.411839 0.664407 3.740112 1.104500 2.641571 3.620160
Max Qi 5.258746 1.185884 5.267355 2.152479 6.068005 2.118189 4.738754 6.551446
Avg Qi 4.130437 0.948452 3.524411 1.215412 4.934044 1.397740 3.739844 4.782181
Query Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16
Stream 0 3.226685 1.878227 1.802562 0.676499 3.145884 0.653129 0.963449 0.990524
Stream 1 8.842030 5.630466 5.728147 2.643227 9.615551 3.197855 4.676538 4.285251
Stream 2 9.508612 5.288044 4.319998 1.492915 9.431995 3.206360 3.859749 3.201996
Stream 3 10.480224 5.880274 4.517320 2.509405 6.913159 2.892479 6.408602 2.938061
Stream 4 8.824111 5.752413 5.997959 2.581237 8.954756 3.351951 2.420598 4.148455
Stream 5 4.905553 7.099111 5.121041 2.516020 9.354924 3.955638 4.389209 3.818902
Min Qi 4.905553 5.288044 4.319998 1.492915 6.913159 2.892479 2.420598 2.938061
Max Qi 10.480224 7.099111 5.997959 2.643227 9.615551 3.955638 6.408602 4.285251
Avg Qi 8.512106 5.930062 5.136893 2.348561 8.854077 3.320857 4.350939 3.678533
Query Q17 Q18 Q19 Q20 Q21 Q22 RF1 RF2
Stream 0 1.405338 0.868313 0.806277 1.123366 1.314028 0.233214 2.590459 1.230242
Stream 1 5.191045 3.171244 3.403836 4.604523 3.721133 0.892096 7.136841 6.500452
Stream 2 6.282687 2.845465 3.024786 4.086546 3.530743 0.619683 9.263671 4.826173
Stream 3 6.040787 2.659766 2.787273 6.210077 3.902190 2.175417 7.974860 6.689780
Stream 4 4.978721 2.542674 3.518783 4.385571 3.906211 0.918752 6.303352 5.139326
Stream 5 5.208600 3.761975 3.682886 7.874493 5.017600 2.087150 7.999074 7.978154
Min Qi 4.978721 2.542674 2.787273 4.086546 3.530743 0.619683 6.303352 4.826173
Max Qi 6.282687 3.761975 3.682886 7.874493 5.017600 2.175417 9.263671 7.978154
Avg Qi 5.540368 2.996225 3.283513 5.432242 4.015575 1.338620 7.735560 6.226777

1000 GB Run 1

Virt-H Executive Summary

Report Date October 3, 2014
Database Scale Factor 1000
Total Data Storage/Database Size 26M
Query Streams for
Throughput Test
7
Virt-H Power 136,744.5
Virt-H Throughput 147,374.6
Virt-H Composite
Query-per-Hour Metric
(Qph@1000GB)
141,960.1
Measurement Interval in
Throughput Test (Ts)
3,761.953000 seconds

Duration of stream execution

Start Date/Time End Date/Time Duration
Stream 0 10/03/2014 09:18:42 10/03/2014 09:34:12 0:15:30
Stream 1 10/03/2014 09:34:43 10/03/2014 10:35:42 1:00:59
Stream 2 10/03/2014 09:34:43 10/03/2014 10:37:14 1:02:31
Stream 3 10/03/2014 09:34:43 10/03/2014 10:37:25 1:02:42
Stream 4 10/03/2014 09:34:43 10/03/2014 10:33:31 0:58:48
Stream 5 10/03/2014 09:34:43 10/03/2014 10:35:26 1:00:43
Stream 6 10/03/2014 09:34:43 10/03/2014 10:28:00 0:53:17
Stream 7 10/03/2014 09:34:43 10/03/2014 10:35:42 1:00:59
Refresh 0 10/03/2014 09:18:42 10/03/2014 09:19:27 0:00:45
10/03/2014 09:34:12 10/03/2014 09:34:42 0:00:30
Refresh 1 10/03/2014 09:43:03 10/03/2014 09:43:38 0:00:35
Refresh 2 10/03/2014 09:34:43 10/03/2014 09:36:54 0:02:11
Refresh 3 10/03/2014 09:36:53 10/03/2014 09:38:39 0:01:46
Refresh 4 10/03/2014 09:38:39 10/03/2014 09:39:22 0:00:43
Refresh 5 10/03/2014 09:39:23 10/03/2014 09:41:09 0:01:46
Refresh 6 10/03/2014 09:41:09 10/03/2014 09:42:15 0:01:06
Refresh 7 10/03/2014 09:42:15 10/03/2014 09:43:02 0:00:47

Numerical Quantities Summary Timing Intervals in Seconds:

Query Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8
Stream 0 104.488583 18.351559 24.631282 36.195531 36.319915 3.807790 22.750889 31.190630
Stream 1 209.323441 26.205435 59.637373 245.808484 60.699333 22.369379 289.435780 335.733425
Stream 2 109.134446 64.185831 96.131735 108.459418 310.273986 53.595127 152.242755 104.350098
Stream 3 73.321611 215.535408 69.543101 12.423757 64.445611 38.254747 122.952872 98.713213
Stream 4 110.875875 4.272757 78.697314 16.316807 59.746855 23.447211 353.190412 342.549908
Stream 5 41.972337 5.978707 60.784575 34.219229 42.372449 344.590640 146.186614 274.972270
Stream 6 115.760155 18.692078 58.493147 9.193234 49.831932 19.081395 60.603109 128.095501
Stream 7 58.601744 118.126585 297.327543 298.578268 714.284222 108.475250 91.868151 55.881029
Min Qi 41.972337 4.272757 58.493147 9.193234 42.372449 19.081395 60.603109 55.881029
Max Qi 209.323441 215.535408 297.327543 298.578268 714.284222 344.590640 353.190412 342.549908
Avg Qi 102.712801 64.713829 102.944970 103.571314 185.950627 87.116250 173.782813 191.470778
Query Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16
Stream 0 41.777880 10.035063 16.125611 9.245638 209.443782 111.271310 37.821595 9.483838
Stream 1 244.243830 63.473338 207.741931 33.696956 561.057408 141.026049 126.818051 54.774792
Stream 2 189.297446 144.853756 56.292537 184.781273 501.330052 49.965102 107.736393 85.691079
Stream 3 231.060699 355.394713 43.483645 11.806590 555.445111 36.722686 251.241817 9.057850
Stream 4 227.371508 32.207115 108.880658 139.922550 532.697956 57.106583 159.198489 153.088913
Stream 5 416.113856 108.689389 62.847727 702.712683 622.906487 58.198961 89.707091 85.614769
Stream 6 228.019243 62.474213 88.227994 282.932978 432.387869 238.544027 61.486269 56.950548
Stream 7 230.564416 69.197517 130.708759 120.531103 551.112816 57.438478 82.256530 63.796403
Min Qi 189.297446 32.207115 43.483645 11.806590 432.387869 36.722686 61.486269 9.057850
Max Qi 416.113856 355.394713 207.741931 702.712683 622.906487 238.544027 251.241817 153.088913
Avg Qi 252.381571 119.470006 99.740464 210.912019 536.705386 91.285984 125.492091 72.710622
Query Q17 Q18 Q19 Q20 Q21 Q22 RF1 RF2
Stream 0 22.897349 47.870269 12.735580 25.982194 46.091766 6.623306 45.120559 30.016788
Stream 1 123.444839 22.212194 647.523826 97.431531 81.592165 4.573040 21.068225 14.486185
Stream 2 80.853865 622.651044 288.656211 336.409076 70.925079 33.578052 82.910543 48.001583
Stream 3 392.340812 84.967695 57.181935 473.720060 497.262620 66.966740 54.778284 50.940094
Stream 4 97.069440 301.705125 338.035788 258.992426 103.699408 28.750257 23.858757 13.626079
Stream 5 69.882110 34.277914 146.031938 179.656129 104.788154 10.836148 54.319823 52.077352
Stream 6 141.310431 247.242904 94.392791 702.775460 80.142930 19.969889 46.027410 19.136271
Stream 7 89.018281 51.105998 281.234432 79.046122 84.341517 26.221892 33.169666 13.309634
Min Qi 69.882110 22.212194 57.181935 79.046122 70.925079 4.573040 21.068225 13.309634
Max Qi 392.340812 622.651044 647.523826 702.775460 497.262620 66.966740 82.910543 52.077352
Avg Qi 141.988540 194.880411 264.722417 304.004401 146.107410 27.270860 45.161815 30.225314

1000 GB Run 2

Virt-H Executive Summary

Report Date October 3, 2014
Database Scale Factor 1000
Total Data Storage/Database Size 26M
Query Streams for
Throughput Test
7
Virt-H Power 199,652.0
Virt-H Throughput 125,161.1
Virt-H Composite
Query-per-Hour Metric
(Qph@1000GB)
158,078.0
Measurement Interval in
Throughput Test (Ts)
4,429.608000 seconds

Duration of stream execution

Start Date/Time End Date/Time Duration
Stream 0 10/03/2014 10:37:29 10/03/2014 10:52:26 0:14:57
Stream 1 10/03/2014 10:52:35 10/03/2014 12:05:19 1:12:44
Stream 2 10/03/2014 10:52:35 10/03/2014 12:06:25 1:13:50
Stream 3 10/03/2014 10:52:35 10/03/2014 12:03:08 1:10:33
Stream 4 10/03/2014 10:52:35 10/03/2014 12:05:20 1:12:45
Stream 5 10/03/2014 10:52:35 10/03/2014 11:57:40 1:05:05
Stream 6 10/03/2014 10:52:35 10/03/2014 12:05:28 1:12:53
Stream 7 10/03/2014 10:52:35 10/03/2014 12:05:25 1:12:50
Refresh 0 10/03/2014 10:37:29 10/03/2014 10:37:52 0:00:23
10/03/2014 10:52:25 10/03/2014 10:52:34 0:00:09
Refresh 1 10/03/2014 11:01:44 10/03/2014 11:02:29 0:00:45
Refresh 2 10/03/2014 10:52:35 10/03/2014 10:54:50 0:02:15
Refresh 3 10/03/2014 10:54:50 10/03/2014 10:57:02 0:02:12
Refresh 4 10/03/2014 10:57:05 10/03/2014 10:58:47 0:01:42
Refresh 5 10/03/2014 10:58:47 10/03/2014 10:59:46 0:00:59
Refresh 6 10/03/2014 10:59:45 10/03/2014 11:00:38 0:00:53
Refresh 7 10/03/2014 11:00:39 10/03/2014 11:01:44 0:01:05

Numerical Quantities Summary Timing Intervals in Seconds:

Query Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8
Stream 0 34.105419 1.439089 9.802183 2.033956 10.525742 3.356152 23.953729 36.199533
Stream 1 26.598252 150.572833 41.930330 86.870320 50.604856 201.001372 61.638366 244.013359
Stream 2 50.129895 102.219282 12.380935 102.319615 62.577229 43.454392 891.076608 407.640626
Stream 3 269.947278 53.172724 54.649973 11.460062 66.695722 17.336698 63.371232 91.158050
Stream 4 41.149221 22.520836 28.707973 509.984321 68.916549 17.525025 702.191490 666.450230
Stream 5 59.179045 30.734442 99.504351 11.145990 101.334340 21.660836 74.625589 535.160207
Stream 6 225.105215 55.567328 46.749707 554.474507 215.657091 54.362551 72.960653 442.194302
Stream 7 220.993226 28.528230 47.543365 336.191006 308.931194 9.767397 850.258452 66.121298
Min Qi 26.598252 22.520836 12.380935 11.145990 50.604856 9.767397 61.638366 66.121298
Max Qi 269.947278 150.572833 99.504351 554.474507 308.931194 201.001372 891.076608 666.450230
Avg Qi 127.586019 63.330811 47.352376 230.349403 124.959569 52.158324 388.017484 350.391153
Query Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16
Stream 0 50.439615 9.287196 15.892947 7.112715 250.527755 131.478131 54.458992 10.525842
Stream 1 420.919329 317.402771 101.818338 403.213385 724.539887 160.669174 65.374584 28.563034
Stream 2 464.378760 210.938167 23.395678 545.086468 736.005716 54.680686 398.880053 34.018918
Stream 3 350.083270 321.781561 48.652019 435.954962 378.872739 100.588804 289.350342 190.140640
Stream 4 306.265994 249.621982 79.280220 221.255121 348.932746 49.555802 100.062439 61.368814
Stream 5 511.923087 133.018420 134.199065 9.655693 662.658830 104.380635 82.847242 59.952271
Stream 6 578.362701 61.221715 145.613349 47.957006 621.993889 256.150595 77.124777 91.163005
Stream 7 418.450091 391.818564 29.360218 17.236628 761.850888 31.952329 50.393082 27.530882
Min Qi 306.265994 61.221715 23.395678 9.655693 348.932746 31.952329 50.393082 27.530882
Max Qi 578.362701 391.818564 145.613349 545.086468 761.850888 256.150595 398.880053 190.140640
Avg Qi 435.769033 240.829026 80.331270 240.051323 604.979242 108.282575 152.004646 70.391081
Query Q17 Q18 Q19 Q20 Q21 Q22 RF1 RF2
Stream 0 22.444111 37.978532 13.347320 26.553364 115.511143 7.670304 22.771613 8.761026
Stream 1 329.153807 19.198590 258.455295 556.256015 99.647793 14.878746 32.803289 8.771923
Stream 2 76.940373 74.916489 75.246897 16.035355 14.403643 32.348500 91.981362 41.426540
Stream 3 88.918404 238.858707 221.257060 688.441713 247.669761 5.345632 70.780594 49.352955
Stream 4 497.105081 167.874781 67.668514 76.820831 78.585717 3.655421 73.165786 29.401670
Stream 5 309.991618 123.023557 380.801141 347.055909 93.478502 18.351491 33.338814 12.557542
Stream 6 57.200926 154.489850 386.007137 103.558355 32.676369 92.863316 35.576966 14.061801
Stream 7 160.332088 46.934177 340.957970 84.479720 78.985110 60.568796 44.362737 8.831746
Min Qi 57.200926 19.198590 67.668514 16.035355 14.403643 3.655421 32.803289 8.771923
Max Qi 497.105081 238.858707 386.007137 688.441713 247.669761 92.863316 91.981362 49.352955
Avg Qi 217.091757 117.899450 247.199145 267.521128 92.206699 32.573129 54.572793 23.486311

To be continued...

In Hoc Signo Vinces (TPC-H) Series