[2024-11-29T14:59:18.766Z] Running test renaissance-movie-lens_0 ... [2024-11-29T14:59:19.104Z] =============================================== [2024-11-29T14:59:19.104Z] renaissance-movie-lens_0 Start Time: Fri Nov 29 14:59:18 2024 Epoch Time (ms): 1732892358863 [2024-11-29T14:59:19.104Z] variation: NoOptions [2024-11-29T14:59:19.447Z] JVM_OPTIONS: [2024-11-29T14:59:19.447Z] { \ [2024-11-29T14:59:19.447Z] echo ""; echo "TEST SETUP:"; \ [2024-11-29T14:59:19.447Z] echo "Nothing to be done for setup."; \ [2024-11-29T14:59:19.447Z] mkdir -p "C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17328911156667\\renaissance-movie-lens_0"; \ [2024-11-29T14:59:19.448Z] cd "C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17328911156667\\renaissance-movie-lens_0"; \ [2024-11-29T14:59:19.448Z] echo ""; echo "TESTING:"; \ [2024-11-29T14:59:19.448Z] "c:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/jdkbinary/j2sdk-image\\bin\\java" -jar "C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17328911156667\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2024-11-29T14:59:19.448Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17328911156667\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-11-29T14:59:19.448Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-11-29T14:59:19.448Z] echo "Nothing to be done for teardown."; \ [2024-11-29T14:59:19.448Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17328911156667\\TestTargetResult"; [2024-11-29T14:59:19.448Z] [2024-11-29T14:59:19.448Z] TEST SETUP: [2024-11-29T14:59:19.448Z] Nothing to be done for setup. [2024-11-29T14:59:19.448Z] [2024-11-29T14:59:19.448Z] TESTING: [2024-11-29T14:59:32.433Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-11-29T14:59:32.433Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-11-29T14:59:36.302Z] Got 100004 ratings from 671 users on 9066 movies. [2024-11-29T14:59:36.303Z] Training: 60056, validation: 20285, test: 19854 [2024-11-29T14:59:36.303Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-11-29T14:59:36.303Z] GC before operation: completed in 216.196 ms, heap usage 139.727 MB -> 26.215 MB. [2024-11-29T14:59:47.176Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-29T14:59:56.006Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-29T15:00:04.826Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-29T15:00:13.666Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-29T15:00:18.341Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-29T15:00:23.036Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-29T15:00:26.798Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-29T15:00:31.487Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-29T15:00:31.487Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2024-11-29T15:00:31.487Z] The best model improves the baseline by 14.52%. [2024-11-29T15:00:31.487Z] Movies recommended for you: [2024-11-29T15:00:31.487Z] WARNING: This benchmark provides no result that can be validated. [2024-11-29T15:00:31.487Z] There is no way to check that no silent failure occurred. [2024-11-29T15:00:31.487Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (55235.349 ms) ====== [2024-11-29T15:00:31.487Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-11-29T15:00:31.815Z] GC before operation: completed in 307.713 ms, heap usage 381.794 MB -> 42.117 MB. [2024-11-29T15:00:38.991Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-29T15:00:46.181Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-29T15:00:53.369Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-29T15:01:00.548Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-29T15:01:03.470Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-29T15:01:08.133Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-29T15:01:11.911Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-29T15:01:15.628Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-29T15:01:16.345Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2024-11-29T15:01:16.345Z] The best model improves the baseline by 14.52%. [2024-11-29T15:01:16.345Z] Movies recommended for you: [2024-11-29T15:01:16.345Z] WARNING: This benchmark provides no result that can be validated. [2024-11-29T15:01:16.345Z] There is no way to check that no silent failure occurred. [2024-11-29T15:01:16.345Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (44513.316 ms) ====== [2024-11-29T15:01:16.345Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-11-29T15:01:16.676Z] GC before operation: completed in 206.302 ms, heap usage 414.026 MB -> 41.626 MB. [2024-11-29T15:01:23.845Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-29T15:01:31.043Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-29T15:01:38.230Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-29T15:01:44.052Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-29T15:01:47.761Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-29T15:01:52.439Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-29T15:01:56.171Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-29T15:01:59.915Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-29T15:01:59.915Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2024-11-29T15:01:59.915Z] The best model improves the baseline by 14.52%. [2024-11-29T15:02:00.242Z] Movies recommended for you: [2024-11-29T15:02:00.242Z] WARNING: This benchmark provides no result that can be validated. [2024-11-29T15:02:00.242Z] There is no way to check that no silent failure occurred. [2024-11-29T15:02:00.242Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (43579.400 ms) ====== [2024-11-29T15:02:00.242Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-11-29T15:02:00.242Z] GC before operation: completed in 183.424 ms, heap usage 233.623 MB -> 41.710 MB. [2024-11-29T15:02:07.447Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-29T15:02:14.623Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-29T15:02:21.802Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-29T15:02:28.984Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-29T15:02:31.895Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-29T15:02:35.613Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-29T15:02:40.288Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-29T15:02:43.999Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-29T15:02:43.999Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2024-11-29T15:02:43.999Z] The best model improves the baseline by 14.52%. [2024-11-29T15:02:44.339Z] Movies recommended for you: [2024-11-29T15:02:44.339Z] WARNING: This benchmark provides no result that can be validated. [2024-11-29T15:02:44.339Z] There is no way to check that no silent failure occurred. [2024-11-29T15:02:44.340Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (43843.140 ms) ====== [2024-11-29T15:02:44.340Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-11-29T15:02:44.340Z] GC before operation: completed in 165.205 ms, heap usage 176.463 MB -> 42.108 MB. [2024-11-29T15:02:51.530Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-29T15:02:58.712Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-29T15:03:04.546Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-29T15:03:11.719Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-29T15:03:15.433Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-29T15:03:19.145Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-29T15:03:23.819Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-29T15:03:27.557Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-29T15:03:27.557Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2024-11-29T15:03:27.557Z] The best model improves the baseline by 14.52%. [2024-11-29T15:03:27.557Z] Movies recommended for you: [2024-11-29T15:03:27.557Z] WARNING: This benchmark provides no result that can be validated. [2024-11-29T15:03:27.557Z] There is no way to check that no silent failure occurred. [2024-11-29T15:03:27.557Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (43304.227 ms) ====== [2024-11-29T15:03:27.557Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-11-29T15:03:27.884Z] GC before operation: completed in 154.126 ms, heap usage 135.287 MB -> 41.915 MB. [2024-11-29T15:03:35.093Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-29T15:03:42.317Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-29T15:03:48.157Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-29T15:03:55.328Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-29T15:03:59.062Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-29T15:04:02.800Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-29T15:04:06.522Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-29T15:04:10.266Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-29T15:04:10.602Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2024-11-29T15:04:10.602Z] The best model improves the baseline by 14.52%. [2024-11-29T15:04:10.928Z] Movies recommended for you: [2024-11-29T15:04:10.928Z] WARNING: This benchmark provides no result that can be validated. [2024-11-29T15:04:10.928Z] There is no way to check that no silent failure occurred. [2024-11-29T15:04:10.928Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (43044.004 ms) ====== [2024-11-29T15:04:10.928Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-11-29T15:04:10.928Z] GC before operation: completed in 122.877 ms, heap usage 172.080 MB -> 42.209 MB. [2024-11-29T15:04:18.102Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-29T15:04:23.930Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-29T15:04:31.117Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-29T15:04:38.296Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-29T15:04:42.000Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-29T15:04:45.716Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-29T15:04:49.443Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-29T15:04:53.165Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-29T15:04:53.519Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2024-11-29T15:04:53.519Z] The best model improves the baseline by 14.52%. [2024-11-29T15:04:53.519Z] Movies recommended for you: [2024-11-29T15:04:53.519Z] WARNING: This benchmark provides no result that can be validated. [2024-11-29T15:04:53.519Z] There is no way to check that no silent failure occurred. [2024-11-29T15:04:53.519Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (42569.307 ms) ====== [2024-11-29T15:04:53.519Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-11-29T15:04:53.849Z] GC before operation: completed in 140.137 ms, heap usage 157.555 MB -> 42.198 MB. [2024-11-29T15:05:01.021Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-29T15:05:06.847Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-29T15:05:14.028Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-29T15:05:19.865Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-29T15:05:24.561Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-29T15:05:28.267Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-29T15:05:32.003Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-29T15:05:35.733Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-29T15:05:36.063Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2024-11-29T15:05:36.063Z] The best model improves the baseline by 14.52%. [2024-11-29T15:05:36.063Z] Movies recommended for you: [2024-11-29T15:05:36.063Z] WARNING: This benchmark provides no result that can be validated. [2024-11-29T15:05:36.063Z] There is no way to check that no silent failure occurred. [2024-11-29T15:05:36.063Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (42419.184 ms) ====== [2024-11-29T15:05:36.063Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-11-29T15:05:36.391Z] GC before operation: completed in 128.832 ms, heap usage 160.957 MB -> 42.613 MB. [2024-11-29T15:05:43.575Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-29T15:05:49.409Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-29T15:05:56.572Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-29T15:06:02.397Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-29T15:06:07.076Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-29T15:06:10.797Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-29T15:06:14.528Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-29T15:06:18.252Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-29T15:06:18.961Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2024-11-29T15:06:18.961Z] The best model improves the baseline by 14.52%. [2024-11-29T15:06:18.961Z] Movies recommended for you: [2024-11-29T15:06:18.962Z] WARNING: This benchmark provides no result that can be validated. [2024-11-29T15:06:18.962Z] There is no way to check that no silent failure occurred. [2024-11-29T15:06:18.962Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (42746.767 ms) ====== [2024-11-29T15:06:18.962Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-11-29T15:06:18.962Z] GC before operation: completed in 124.930 ms, heap usage 167.830 MB -> 42.500 MB. [2024-11-29T15:06:26.137Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-29T15:06:33.312Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-29T15:06:40.490Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-29T15:06:46.319Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-29T15:06:50.054Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-29T15:06:53.786Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-29T15:06:58.472Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-29T15:07:02.215Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-29T15:07:02.215Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2024-11-29T15:07:02.215Z] The best model improves the baseline by 14.52%. [2024-11-29T15:07:02.567Z] Movies recommended for you: [2024-11-29T15:07:02.567Z] WARNING: This benchmark provides no result that can be validated. [2024-11-29T15:07:02.567Z] There is no way to check that no silent failure occurred. [2024-11-29T15:07:02.567Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (43290.361 ms) ====== [2024-11-29T15:07:02.567Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-11-29T15:07:02.567Z] GC before operation: completed in 170.419 ms, heap usage 162.596 MB -> 42.415 MB. [2024-11-29T15:07:09.740Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-29T15:07:15.565Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-29T15:07:22.735Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-29T15:07:29.921Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-29T15:07:33.639Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-29T15:07:37.395Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-29T15:07:42.077Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-29T15:07:45.819Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-29T15:07:45.819Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2024-11-29T15:07:45.819Z] The best model improves the baseline by 14.52%. [2024-11-29T15:07:45.819Z] Movies recommended for you: [2024-11-29T15:07:45.819Z] WARNING: This benchmark provides no result that can be validated. [2024-11-29T15:07:45.819Z] There is no way to check that no silent failure occurred. [2024-11-29T15:07:45.819Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (43343.369 ms) ====== [2024-11-29T15:07:45.819Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-11-29T15:07:46.154Z] GC before operation: completed in 116.147 ms, heap usage 153.911 MB -> 42.091 MB. [2024-11-29T15:07:53.347Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-29T15:07:59.157Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-29T15:08:06.332Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-29T15:08:13.511Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-29T15:08:17.235Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-29T15:08:20.953Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-29T15:08:25.656Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-29T15:08:29.407Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-29T15:08:29.407Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2024-11-29T15:08:29.407Z] The best model improves the baseline by 14.52%. [2024-11-29T15:08:29.407Z] Movies recommended for you: [2024-11-29T15:08:29.407Z] WARNING: This benchmark provides no result that can be validated. [2024-11-29T15:08:29.407Z] There is no way to check that no silent failure occurred. [2024-11-29T15:08:29.407Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (43491.244 ms) ====== [2024-11-29T15:08:29.407Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-11-29T15:08:29.738Z] GC before operation: completed in 117.273 ms, heap usage 185.856 MB -> 42.545 MB. [2024-11-29T15:08:36.895Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-29T15:08:44.102Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-29T15:08:49.933Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-29T15:08:57.108Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-29T15:09:00.823Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-29T15:09:05.514Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-29T15:09:09.232Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-29T15:09:12.990Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-29T15:09:12.990Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2024-11-29T15:09:12.990Z] The best model improves the baseline by 14.52%. [2024-11-29T15:09:13.320Z] Movies recommended for you: [2024-11-29T15:09:13.320Z] WARNING: This benchmark provides no result that can be validated. [2024-11-29T15:09:13.320Z] There is no way to check that no silent failure occurred. [2024-11-29T15:09:13.320Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (43659.327 ms) ====== [2024-11-29T15:09:13.320Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-11-29T15:09:13.320Z] GC before operation: completed in 128.372 ms, heap usage 143.098 MB -> 42.419 MB. [2024-11-29T15:09:20.491Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-29T15:09:27.682Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-29T15:09:34.897Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-29T15:09:40.730Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-29T15:09:44.446Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-29T15:09:49.138Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-29T15:09:52.864Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-29T15:09:56.597Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-29T15:09:56.597Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2024-11-29T15:09:56.597Z] The best model improves the baseline by 14.52%. [2024-11-29T15:09:56.928Z] Movies recommended for you: [2024-11-29T15:09:56.928Z] WARNING: This benchmark provides no result that can be validated. [2024-11-29T15:09:56.928Z] There is no way to check that no silent failure occurred. [2024-11-29T15:09:56.928Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (43394.780 ms) ====== [2024-11-29T15:09:56.928Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-11-29T15:09:56.928Z] GC before operation: completed in 107.861 ms, heap usage 164.202 MB -> 42.307 MB. [2024-11-29T15:10:04.088Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-29T15:10:11.269Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-29T15:10:18.469Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-29T15:10:24.296Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-29T15:10:28.023Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-29T15:10:31.756Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-29T15:10:36.437Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-29T15:10:40.171Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-29T15:10:40.504Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2024-11-29T15:10:40.504Z] The best model improves the baseline by 14.52%. [2024-11-29T15:10:40.504Z] Movies recommended for you: [2024-11-29T15:10:40.504Z] WARNING: This benchmark provides no result that can be validated. [2024-11-29T15:10:40.504Z] There is no way to check that no silent failure occurred. [2024-11-29T15:10:40.504Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (43606.130 ms) ====== [2024-11-29T15:10:40.504Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-11-29T15:10:40.837Z] GC before operation: completed in 151.592 ms, heap usage 155.247 MB -> 42.312 MB. [2024-11-29T15:10:48.011Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-29T15:10:53.830Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-29T15:11:01.014Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-29T15:11:08.197Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-29T15:11:11.110Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-29T15:11:14.828Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-29T15:11:19.524Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-29T15:11:23.274Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-29T15:11:23.274Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2024-11-29T15:11:23.274Z] The best model improves the baseline by 14.52%. [2024-11-29T15:11:23.274Z] Movies recommended for you: [2024-11-29T15:11:23.274Z] WARNING: This benchmark provides no result that can be validated. [2024-11-29T15:11:23.274Z] There is no way to check that no silent failure occurred. [2024-11-29T15:11:23.274Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (42636.802 ms) ====== [2024-11-29T15:11:23.274Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-11-29T15:11:23.604Z] GC before operation: completed in 125.452 ms, heap usage 142.228 MB -> 42.425 MB. [2024-11-29T15:11:30.773Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-29T15:11:37.947Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-29T15:11:43.771Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-29T15:11:50.990Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-29T15:11:54.709Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-29T15:11:58.414Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-29T15:12:02.131Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-29T15:12:05.855Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-29T15:12:06.558Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2024-11-29T15:12:06.558Z] The best model improves the baseline by 14.52%. [2024-11-29T15:12:06.558Z] Movies recommended for you: [2024-11-29T15:12:06.558Z] WARNING: This benchmark provides no result that can be validated. [2024-11-29T15:12:06.558Z] There is no way to check that no silent failure occurred. [2024-11-29T15:12:06.558Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (43190.545 ms) ====== [2024-11-29T15:12:06.558Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-11-29T15:12:06.886Z] GC before operation: completed in 122.225 ms, heap usage 163.890 MB -> 42.482 MB. [2024-11-29T15:12:14.058Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-29T15:12:19.871Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-29T15:12:27.071Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-29T15:12:34.248Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-29T15:12:37.978Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-29T15:12:41.689Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-29T15:12:45.434Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-29T15:12:49.174Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-29T15:12:49.507Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2024-11-29T15:12:49.507Z] The best model improves the baseline by 14.52%. [2024-11-29T15:12:49.839Z] Movies recommended for you: [2024-11-29T15:12:49.839Z] WARNING: This benchmark provides no result that can be validated. [2024-11-29T15:12:49.839Z] There is no way to check that no silent failure occurred. [2024-11-29T15:12:49.839Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (42999.907 ms) ====== [2024-11-29T15:12:49.839Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-11-29T15:12:49.839Z] GC before operation: completed in 123.123 ms, heap usage 150.437 MB -> 42.415 MB. [2024-11-29T15:12:57.018Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-29T15:13:04.197Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-29T15:13:10.022Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-29T15:13:17.217Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-29T15:13:20.953Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-29T15:13:24.676Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-29T15:13:28.441Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-29T15:13:32.164Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-29T15:13:32.867Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2024-11-29T15:13:32.867Z] The best model improves the baseline by 14.52%. [2024-11-29T15:13:32.867Z] Movies recommended for you: [2024-11-29T15:13:32.867Z] WARNING: This benchmark provides no result that can be validated. [2024-11-29T15:13:32.867Z] There is no way to check that no silent failure occurred. [2024-11-29T15:13:32.867Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (42966.281 ms) ====== [2024-11-29T15:13:32.867Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-11-29T15:13:32.867Z] GC before operation: completed in 113.091 ms, heap usage 143.790 MB -> 42.528 MB. [2024-11-29T15:13:40.083Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-29T15:13:47.234Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-29T15:13:54.405Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-29T15:14:00.225Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-29T15:14:03.947Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-29T15:14:07.694Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-29T15:14:12.373Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-29T15:14:16.095Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-29T15:14:16.095Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536. [2024-11-29T15:14:16.095Z] The best model improves the baseline by 14.52%. [2024-11-29T15:14:16.425Z] Movies recommended for you: [2024-11-29T15:14:16.425Z] WARNING: This benchmark provides no result that can be validated. [2024-11-29T15:14:16.425Z] There is no way to check that no silent failure occurred. [2024-11-29T15:14:16.425Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (43419.452 ms) ====== [2024-11-29T15:14:16.757Z] ----------------------------------- [2024-11-29T15:14:16.757Z] renaissance-movie-lens_0_PASSED [2024-11-29T15:14:16.757Z] ----------------------------------- [2024-11-29T15:14:17.446Z] [2024-11-29T15:14:17.446Z] TEST TEARDOWN: [2024-11-29T15:14:17.446Z] Nothing to be done for teardown. [2024-11-29T15:14:17.446Z] renaissance-movie-lens_0 Finish Time: Fri Nov 29 15:14:17 2024 Epoch Time (ms): 1732893257226