[2024-11-14T22:11:52.119Z] Running test renaissance-movie-lens_0 ... [2024-11-14T22:11:52.119Z] =============================================== [2024-11-14T22:11:52.119Z] renaissance-movie-lens_0 Start Time: Thu Nov 14 22:11:51 2024 Epoch Time (ms): 1731622311833 [2024-11-14T22:11:52.119Z] variation: NoOptions [2024-11-14T22:11:52.119Z] JVM_OPTIONS: [2024-11-14T22:11:52.119Z] { \ [2024-11-14T22:11:52.119Z] echo ""; echo "TEST SETUP:"; \ [2024-11-14T22:11:52.119Z] echo "Nothing to be done for setup."; \ [2024-11-14T22:11:52.119Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17316213061146/renaissance-movie-lens_0"; \ [2024-11-14T22:11:52.119Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17316213061146/renaissance-movie-lens_0"; \ [2024-11-14T22:11:52.119Z] echo ""; echo "TESTING:"; \ [2024-11-14T22:11:52.119Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/jdkbinary/j2sdk-image/bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17316213061146/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-11-14T22:11:52.119Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17316213061146/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-11-14T22:11:52.119Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-11-14T22:11:52.119Z] echo "Nothing to be done for teardown."; \ [2024-11-14T22:11:52.120Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17316213061146/TestTargetResult"; [2024-11-14T22:11:52.120Z] [2024-11-14T22:11:52.120Z] TEST SETUP: [2024-11-14T22:11:52.120Z] Nothing to be done for setup. [2024-11-14T22:11:52.120Z] [2024-11-14T22:11:52.120Z] TESTING: [2024-11-14T22:11:56.212Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-11-14T22:11:58.133Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-11-14T22:12:03.431Z] Got 100004 ratings from 671 users on 9066 movies. [2024-11-14T22:12:03.431Z] Training: 60056, validation: 20285, test: 19854 [2024-11-14T22:12:03.431Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-11-14T22:12:04.365Z] GC before operation: completed in 240.936 ms, heap usage 132.720 MB -> 25.886 MB. [2024-11-14T22:12:10.983Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-14T22:12:13.965Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-14T22:12:18.072Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-14T22:12:21.052Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-14T22:12:21.997Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-14T22:12:23.922Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-14T22:12:25.850Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-14T22:12:27.796Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-14T22:12:27.796Z] 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. [2024-11-14T22:12:28.735Z] The best model improves the baseline by 14.52%. [2024-11-14T22:12:28.735Z] Movies recommended for you: [2024-11-14T22:12:28.735Z] WARNING: This benchmark provides no result that can be validated. [2024-11-14T22:12:28.735Z] There is no way to check that no silent failure occurred. [2024-11-14T22:12:28.735Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (24513.805 ms) ====== [2024-11-14T22:12:28.735Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-11-14T22:12:28.735Z] GC before operation: completed in 341.821 ms, heap usage 336.155 MB -> 46.979 MB. [2024-11-14T22:12:31.710Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-14T22:12:34.692Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-14T22:12:37.510Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-14T22:12:39.437Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-14T22:12:41.368Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-14T22:12:43.295Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-14T22:12:45.224Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-14T22:12:46.165Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-14T22:12:47.103Z] 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. [2024-11-14T22:12:47.103Z] The best model improves the baseline by 14.52%. [2024-11-14T22:12:47.103Z] Movies recommended for you: [2024-11-14T22:12:47.103Z] WARNING: This benchmark provides no result that can be validated. [2024-11-14T22:12:47.103Z] There is no way to check that no silent failure occurred. [2024-11-14T22:12:47.103Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17980.101 ms) ====== [2024-11-14T22:12:47.103Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-11-14T22:12:47.103Z] GC before operation: completed in 208.686 ms, heap usage 273.654 MB -> 41.195 MB. [2024-11-14T22:12:50.079Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-14T22:12:52.002Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-14T22:12:54.975Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-14T22:12:56.900Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-14T22:12:58.827Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-14T22:13:00.768Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-14T22:13:01.707Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-14T22:13:03.640Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-14T22:13:03.640Z] 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. [2024-11-14T22:13:03.640Z] The best model improves the baseline by 14.52%. [2024-11-14T22:13:03.640Z] Movies recommended for you: [2024-11-14T22:13:03.640Z] WARNING: This benchmark provides no result that can be validated. [2024-11-14T22:13:03.640Z] There is no way to check that no silent failure occurred. [2024-11-14T22:13:03.640Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16988.692 ms) ====== [2024-11-14T22:13:03.640Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-11-14T22:13:04.576Z] GC before operation: completed in 237.899 ms, heap usage 357.929 MB -> 41.647 MB. [2024-11-14T22:13:06.508Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-14T22:13:09.481Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-14T22:13:11.413Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-14T22:13:14.393Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-14T22:13:15.331Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-14T22:13:17.257Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-14T22:13:19.196Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-14T22:13:20.157Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-14T22:13:20.157Z] 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. [2024-11-14T22:13:20.157Z] The best model improves the baseline by 14.52%. [2024-11-14T22:13:21.096Z] Movies recommended for you: [2024-11-14T22:13:21.096Z] WARNING: This benchmark provides no result that can be validated. [2024-11-14T22:13:21.096Z] There is no way to check that no silent failure occurred. [2024-11-14T22:13:21.096Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16404.994 ms) ====== [2024-11-14T22:13:21.096Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-11-14T22:13:21.096Z] GC before operation: completed in 171.330 ms, heap usage 55.193 MB -> 41.575 MB. [2024-11-14T22:13:23.025Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-14T22:13:25.999Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-14T22:13:27.928Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-14T22:13:30.911Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-14T22:13:31.848Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-14T22:13:33.777Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-14T22:13:34.723Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-14T22:13:36.654Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-14T22:13:36.654Z] 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. [2024-11-14T22:13:36.654Z] The best model improves the baseline by 14.52%. [2024-11-14T22:13:36.654Z] Movies recommended for you: [2024-11-14T22:13:36.654Z] WARNING: This benchmark provides no result that can be validated. [2024-11-14T22:13:36.654Z] There is no way to check that no silent failure occurred. [2024-11-14T22:13:36.654Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15931.324 ms) ====== [2024-11-14T22:13:36.654Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-11-14T22:13:36.654Z] GC before operation: completed in 199.388 ms, heap usage 360.121 MB -> 42.272 MB. [2024-11-14T22:13:39.452Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-14T22:13:41.378Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-14T22:13:44.377Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-14T22:13:46.307Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-14T22:13:48.233Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-14T22:13:49.172Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-14T22:13:51.111Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-14T22:13:52.050Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-14T22:13:52.050Z] 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. [2024-11-14T22:13:52.992Z] The best model improves the baseline by 14.52%. [2024-11-14T22:13:52.992Z] Movies recommended for you: [2024-11-14T22:13:52.992Z] WARNING: This benchmark provides no result that can be validated. [2024-11-14T22:13:52.992Z] There is no way to check that no silent failure occurred. [2024-11-14T22:13:52.992Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15667.614 ms) ====== [2024-11-14T22:13:52.992Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-11-14T22:13:52.992Z] GC before operation: completed in 170.738 ms, heap usage 71.422 MB -> 41.505 MB. [2024-11-14T22:13:54.923Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-14T22:13:57.910Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-14T22:13:59.836Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-14T22:14:01.765Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-14T22:14:03.690Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-14T22:14:04.642Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-14T22:14:06.575Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-14T22:14:07.519Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-14T22:14:08.459Z] 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. [2024-11-14T22:14:08.459Z] The best model improves the baseline by 14.52%. [2024-11-14T22:14:08.459Z] Movies recommended for you: [2024-11-14T22:14:08.459Z] WARNING: This benchmark provides no result that can be validated. [2024-11-14T22:14:08.459Z] There is no way to check that no silent failure occurred. [2024-11-14T22:14:08.459Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15583.409 ms) ====== [2024-11-14T22:14:08.459Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-11-14T22:14:08.459Z] GC before operation: completed in 193.566 ms, heap usage 63.689 MB -> 43.974 MB. [2024-11-14T22:14:10.399Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-14T22:14:13.380Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-14T22:14:15.313Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-14T22:14:17.237Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-14T22:14:19.163Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-14T22:14:20.100Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-14T22:14:22.036Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-14T22:14:22.987Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-14T22:14:23.928Z] 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. [2024-11-14T22:14:23.928Z] The best model improves the baseline by 14.52%. [2024-11-14T22:14:23.928Z] Movies recommended for you: [2024-11-14T22:14:23.928Z] WARNING: This benchmark provides no result that can be validated. [2024-11-14T22:14:23.928Z] There is no way to check that no silent failure occurred. [2024-11-14T22:14:23.928Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15169.852 ms) ====== [2024-11-14T22:14:23.928Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-11-14T22:14:23.928Z] GC before operation: completed in 177.157 ms, heap usage 89.120 MB -> 41.959 MB. [2024-11-14T22:14:25.860Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-14T22:14:28.832Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-14T22:14:30.761Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-14T22:14:32.692Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-14T22:14:34.628Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-14T22:14:35.570Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-14T22:14:37.502Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-14T22:14:38.440Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-14T22:14:38.440Z] 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. [2024-11-14T22:14:40.068Z] The best model improves the baseline by 14.52%. [2024-11-14T22:14:40.068Z] Movies recommended for you: [2024-11-14T22:14:40.068Z] WARNING: This benchmark provides no result that can be validated. [2024-11-14T22:14:40.068Z] There is no way to check that no silent failure occurred. [2024-11-14T22:14:40.068Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15068.579 ms) ====== [2024-11-14T22:14:40.068Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-11-14T22:14:40.068Z] GC before operation: completed in 187.293 ms, heap usage 73.651 MB -> 41.780 MB. [2024-11-14T22:14:41.175Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-14T22:14:43.110Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-14T22:14:46.085Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-14T22:14:48.015Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-14T22:14:49.940Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-14T22:14:50.878Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-14T22:14:51.819Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-14T22:14:53.747Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-14T22:14:53.747Z] 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. [2024-11-14T22:14:53.747Z] The best model improves the baseline by 14.52%. [2024-11-14T22:14:53.747Z] Movies recommended for you: [2024-11-14T22:14:53.747Z] WARNING: This benchmark provides no result that can be validated. [2024-11-14T22:14:53.747Z] There is no way to check that no silent failure occurred. [2024-11-14T22:14:53.747Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14908.579 ms) ====== [2024-11-14T22:14:53.747Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-11-14T22:14:54.685Z] GC before operation: completed in 216.446 ms, heap usage 63.167 MB -> 41.895 MB. [2024-11-14T22:14:56.612Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-14T22:14:58.538Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-14T22:15:01.527Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-14T22:15:03.452Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-14T22:15:04.387Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-14T22:15:06.309Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-14T22:15:07.251Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-14T22:15:09.352Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-14T22:15:09.352Z] 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. [2024-11-14T22:15:09.352Z] The best model improves the baseline by 14.52%. [2024-11-14T22:15:09.352Z] Movies recommended for you: [2024-11-14T22:15:09.352Z] WARNING: This benchmark provides no result that can be validated. [2024-11-14T22:15:09.352Z] There is no way to check that no silent failure occurred. [2024-11-14T22:15:09.352Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14723.079 ms) ====== [2024-11-14T22:15:09.352Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-11-14T22:15:09.352Z] GC before operation: completed in 150.293 ms, heap usage 87.782 MB -> 41.602 MB. [2024-11-14T22:15:11.281Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-14T22:15:13.240Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-14T22:15:16.225Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-14T22:15:18.174Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-14T22:15:19.116Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-14T22:15:21.037Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-14T22:15:21.974Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-14T22:15:23.924Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-14T22:15:23.924Z] 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. [2024-11-14T22:15:23.924Z] The best model improves the baseline by 14.52%. [2024-11-14T22:15:23.924Z] Movies recommended for you: [2024-11-14T22:15:23.924Z] WARNING: This benchmark provides no result that can be validated. [2024-11-14T22:15:23.924Z] There is no way to check that no silent failure occurred. [2024-11-14T22:15:23.924Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14767.894 ms) ====== [2024-11-14T22:15:23.924Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-11-14T22:15:23.924Z] GC before operation: completed in 155.189 ms, heap usage 63.226 MB -> 43.557 MB. [2024-11-14T22:15:25.851Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-14T22:15:28.863Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-14T22:15:30.788Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-14T22:15:32.723Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-14T22:15:34.652Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-14T22:15:35.590Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-14T22:15:37.521Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-14T22:15:38.457Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-14T22:15:38.457Z] 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. [2024-11-14T22:15:38.457Z] The best model improves the baseline by 14.52%. [2024-11-14T22:15:39.399Z] Movies recommended for you: [2024-11-14T22:15:39.399Z] WARNING: This benchmark provides no result that can be validated. [2024-11-14T22:15:39.399Z] There is no way to check that no silent failure occurred. [2024-11-14T22:15:39.399Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (14778.299 ms) ====== [2024-11-14T22:15:39.399Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-11-14T22:15:39.399Z] GC before operation: completed in 209.077 ms, heap usage 357.957 MB -> 60.017 MB. [2024-11-14T22:15:42.195Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-14T22:15:43.301Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-14T22:15:46.274Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-14T22:15:48.207Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-14T22:15:49.157Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-14T22:15:51.090Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-14T22:15:52.041Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-14T22:15:53.966Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-14T22:15:53.966Z] 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. [2024-11-14T22:15:53.966Z] The best model improves the baseline by 14.52%. [2024-11-14T22:15:53.966Z] Movies recommended for you: [2024-11-14T22:15:53.966Z] WARNING: This benchmark provides no result that can be validated. [2024-11-14T22:15:53.966Z] There is no way to check that no silent failure occurred. [2024-11-14T22:15:53.966Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14921.773 ms) ====== [2024-11-14T22:15:53.966Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-11-14T22:15:53.966Z] GC before operation: completed in 148.758 ms, heap usage 194.567 MB -> 49.231 MB. [2024-11-14T22:15:55.893Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-14T22:15:58.892Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-14T22:16:00.816Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-14T22:16:02.743Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-14T22:16:04.666Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-14T22:16:05.605Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-14T22:16:06.542Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-14T22:16:08.470Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-14T22:16:08.470Z] 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. [2024-11-14T22:16:08.470Z] The best model improves the baseline by 14.52%. [2024-11-14T22:16:08.470Z] Movies recommended for you: [2024-11-14T22:16:08.470Z] WARNING: This benchmark provides no result that can be validated. [2024-11-14T22:16:08.470Z] There is no way to check that no silent failure occurred. [2024-11-14T22:16:08.470Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14468.028 ms) ====== [2024-11-14T22:16:08.470Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-11-14T22:16:08.470Z] GC before operation: completed in 195.393 ms, heap usage 120.212 MB -> 70.603 MB. [2024-11-14T22:16:11.443Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-14T22:16:13.366Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-14T22:16:15.310Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-14T22:16:17.249Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-14T22:16:19.176Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-14T22:16:20.120Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-14T22:16:22.050Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-14T22:16:22.987Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-14T22:16:23.924Z] 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. [2024-11-14T22:16:23.924Z] The best model improves the baseline by 14.52%. [2024-11-14T22:16:23.924Z] Movies recommended for you: [2024-11-14T22:16:23.924Z] WARNING: This benchmark provides no result that can be validated. [2024-11-14T22:16:23.924Z] There is no way to check that no silent failure occurred. [2024-11-14T22:16:23.924Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14906.061 ms) ====== [2024-11-14T22:16:23.924Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-11-14T22:16:23.924Z] GC before operation: completed in 162.859 ms, heap usage 145.790 MB -> 49.955 MB. [2024-11-14T22:16:25.853Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-14T22:16:27.791Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-14T22:16:30.760Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-14T22:16:32.689Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-14T22:16:33.626Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-14T22:16:35.560Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-14T22:16:36.504Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-14T22:16:37.447Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-14T22:16:38.385Z] 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. [2024-11-14T22:16:38.386Z] The best model improves the baseline by 14.52%. [2024-11-14T22:16:38.386Z] Movies recommended for you: [2024-11-14T22:16:38.386Z] WARNING: This benchmark provides no result that can be validated. [2024-11-14T22:16:38.386Z] There is no way to check that no silent failure occurred. [2024-11-14T22:16:38.386Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14296.676 ms) ====== [2024-11-14T22:16:38.386Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-11-14T22:16:38.386Z] GC before operation: completed in 207.423 ms, heap usage 183.595 MB -> 70.527 MB. [2024-11-14T22:16:40.314Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-14T22:16:43.308Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-14T22:16:44.857Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-14T22:16:46.846Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-14T22:16:48.772Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-14T22:16:49.709Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-14T22:16:51.641Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-14T22:16:52.580Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-14T22:16:52.580Z] 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. [2024-11-14T22:16:52.580Z] The best model improves the baseline by 14.52%. [2024-11-14T22:16:53.531Z] Movies recommended for you: [2024-11-14T22:16:53.531Z] WARNING: This benchmark provides no result that can be validated. [2024-11-14T22:16:53.531Z] There is no way to check that no silent failure occurred. [2024-11-14T22:16:53.531Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14591.066 ms) ====== [2024-11-14T22:16:53.531Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-11-14T22:16:53.531Z] GC before operation: completed in 208.153 ms, heap usage 169.579 MB -> 70.399 MB. [2024-11-14T22:16:55.454Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-14T22:16:57.379Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-14T22:17:00.366Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-14T22:17:02.305Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-14T22:17:03.246Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-14T22:17:05.177Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-14T22:17:06.115Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-14T22:17:08.042Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-14T22:17:08.042Z] 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. [2024-11-14T22:17:08.042Z] The best model improves the baseline by 14.52%. [2024-11-14T22:17:08.042Z] Movies recommended for you: [2024-11-14T22:17:08.042Z] WARNING: This benchmark provides no result that can be validated. [2024-11-14T22:17:08.042Z] There is no way to check that no silent failure occurred. [2024-11-14T22:17:08.042Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14705.244 ms) ====== [2024-11-14T22:17:08.042Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-11-14T22:17:08.042Z] GC before operation: completed in 216.927 ms, heap usage 165.493 MB -> 70.649 MB. [2024-11-14T22:17:09.971Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-14T22:17:12.957Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-14T22:17:14.883Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-14T22:17:16.815Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-14T22:17:18.743Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-14T22:17:19.682Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-14T22:17:20.622Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-14T22:17:22.575Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-14T22:17:22.575Z] 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. [2024-11-14T22:17:22.575Z] The best model improves the baseline by 14.52%. [2024-11-14T22:17:23.513Z] Movies recommended for you: [2024-11-14T22:17:23.513Z] WARNING: This benchmark provides no result that can be validated. [2024-11-14T22:17:23.513Z] There is no way to check that no silent failure occurred. [2024-11-14T22:17:23.513Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14928.618 ms) ====== [2024-11-14T22:17:23.513Z] ----------------------------------- [2024-11-14T22:17:23.513Z] renaissance-movie-lens_0_PASSED [2024-11-14T22:17:23.513Z] ----------------------------------- [2024-11-14T22:17:23.513Z] [2024-11-14T22:17:23.513Z] TEST TEARDOWN: [2024-11-14T22:17:23.513Z] Nothing to be done for teardown. [2024-11-14T22:17:23.513Z] renaissance-movie-lens_0 Finish Time: Thu Nov 14 22:17:23 2024 Epoch Time (ms): 1731622643190