[2024-11-16T15:34:49.476Z] Running test renaissance-movie-lens_0 ... [2024-11-16T15:34:49.476Z] =============================================== [2024-11-16T15:34:49.787Z] renaissance-movie-lens_0 Start Time: Sat Nov 16 15:34:49 2024 Epoch Time (ms): 1731771289539 [2024-11-16T15:34:49.787Z] variation: NoOptions [2024-11-16T15:34:50.127Z] JVM_OPTIONS: [2024-11-16T15:34:50.127Z] { \ [2024-11-16T15:34:50.127Z] echo ""; echo "TEST SETUP:"; \ [2024-11-16T15:34:50.127Z] echo "Nothing to be done for setup."; \ [2024-11-16T15:34:50.127Z] mkdir -p "C:/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17317695955338\\renaissance-movie-lens_0"; \ [2024-11-16T15:34:50.127Z] cd "C:/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17317695955338\\renaissance-movie-lens_0"; \ [2024-11-16T15:34:50.127Z] echo ""; echo "TESTING:"; \ [2024-11-16T15:34:50.127Z] "c:/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/jdkbinary/j2sdk-image\\bin\\java" -jar "C:/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17317695955338\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2024-11-16T15:34:50.127Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests/; rm -f -r "C:/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17317695955338\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-11-16T15:34:50.128Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-11-16T15:34:50.128Z] echo "Nothing to be done for teardown."; \ [2024-11-16T15:34:50.128Z] } 2>&1 | tee -a "C:/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17317695955338\\TestTargetResult"; [2024-11-16T15:34:50.128Z] [2024-11-16T15:34:50.128Z] TEST SETUP: [2024-11-16T15:34:50.128Z] Nothing to be done for setup. [2024-11-16T15:34:50.128Z] [2024-11-16T15:34:50.128Z] TESTING: [2024-11-16T15:35:05.786Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-11-16T15:35:07.407Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-11-16T15:35:12.180Z] Got 100004 ratings from 671 users on 9066 movies. [2024-11-16T15:35:12.181Z] Training: 60056, validation: 20285, test: 19854 [2024-11-16T15:35:12.181Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-11-16T15:35:12.598Z] GC before operation: completed in 290.466 ms, heap usage 206.391 MB -> 26.571 MB. [2024-11-16T15:35:25.764Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T15:35:38.791Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T15:35:49.491Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T15:36:00.166Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T15:36:05.950Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T15:36:11.719Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T15:36:17.509Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T15:36:22.180Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T15:36:22.509Z] 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. [2024-11-16T15:36:22.509Z] The best model improves the baseline by 14.52%. [2024-11-16T15:36:22.838Z] Movies recommended for you: [2024-11-16T15:36:22.838Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T15:36:22.838Z] There is no way to check that no silent failure occurred. [2024-11-16T15:36:22.838Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (70221.609 ms) ====== [2024-11-16T15:36:22.838Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-11-16T15:36:23.167Z] GC before operation: completed in 465.399 ms, heap usage 235.040 MB -> 40.356 MB. [2024-11-16T15:36:33.845Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T15:36:42.603Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T15:36:51.332Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T15:37:00.052Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T15:37:04.747Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T15:37:10.534Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T15:37:16.319Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T15:37:21.013Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T15:37:21.013Z] 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. [2024-11-16T15:37:21.013Z] The best model improves the baseline by 14.52%. [2024-11-16T15:37:21.348Z] Movies recommended for you: [2024-11-16T15:37:21.348Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T15:37:21.348Z] There is no way to check that no silent failure occurred. [2024-11-16T15:37:21.348Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (57990.596 ms) ====== [2024-11-16T15:37:21.348Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-11-16T15:37:21.348Z] GC before operation: completed in 300.248 ms, heap usage 780.022 MB -> 46.687 MB. [2024-11-16T15:37:32.007Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T15:37:40.728Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T15:37:49.433Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T15:37:58.174Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T15:38:02.872Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T15:38:07.511Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T15:38:12.140Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T15:38:17.907Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T15:38:17.907Z] 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. [2024-11-16T15:38:17.907Z] The best model improves the baseline by 14.52%. [2024-11-16T15:38:17.907Z] Movies recommended for you: [2024-11-16T15:38:17.907Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T15:38:17.907Z] There is no way to check that no silent failure occurred. [2024-11-16T15:38:17.907Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (56490.145 ms) ====== [2024-11-16T15:38:17.907Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-11-16T15:38:18.227Z] GC before operation: completed in 230.969 ms, heap usage 380.833 MB -> 42.112 MB. [2024-11-16T15:38:26.963Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T15:38:35.707Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T15:38:46.330Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T15:38:55.038Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T15:38:59.689Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T15:39:04.343Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T15:39:10.133Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T15:39:14.789Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T15:39:14.789Z] 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. [2024-11-16T15:39:14.789Z] The best model improves the baseline by 14.52%. [2024-11-16T15:39:15.117Z] Movies recommended for you: [2024-11-16T15:39:15.117Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T15:39:15.117Z] There is no way to check that no silent failure occurred. [2024-11-16T15:39:15.117Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (56829.596 ms) ====== [2024-11-16T15:39:15.117Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-11-16T15:39:15.117Z] GC before operation: completed in 189.881 ms, heap usage 1.089 GB -> 50.728 MB. [2024-11-16T15:39:23.815Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T15:39:32.521Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T15:39:41.270Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T15:39:49.984Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T15:39:55.767Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T15:40:00.408Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T15:40:06.235Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T15:40:10.866Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T15:40:11.189Z] 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. [2024-11-16T15:40:11.189Z] The best model improves the baseline by 14.52%. [2024-11-16T15:40:11.189Z] Movies recommended for you: [2024-11-16T15:40:11.189Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T15:40:11.189Z] There is no way to check that no silent failure occurred. [2024-11-16T15:40:11.189Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (56025.798 ms) ====== [2024-11-16T15:40:11.189Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-11-16T15:40:11.540Z] GC before operation: completed in 214.259 ms, heap usage 1.122 GB -> 51.603 MB. [2024-11-16T15:40:20.265Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T15:40:28.981Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T15:40:37.789Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T15:40:46.526Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T15:40:51.186Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T15:40:56.958Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T15:41:01.622Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T15:41:06.253Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T15:41:06.992Z] 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. [2024-11-16T15:41:06.992Z] The best model improves the baseline by 14.52%. [2024-11-16T15:41:06.992Z] Movies recommended for you: [2024-11-16T15:41:06.992Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T15:41:06.992Z] There is no way to check that no silent failure occurred. [2024-11-16T15:41:06.992Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (55620.014 ms) ====== [2024-11-16T15:41:06.992Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-11-16T15:41:07.317Z] GC before operation: completed in 194.387 ms, heap usage 122.688 MB -> 41.746 MB. [2024-11-16T15:41:16.053Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T15:41:24.767Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T15:41:33.481Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T15:41:42.220Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T15:41:46.866Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T15:41:52.623Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T15:41:57.292Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T15:42:01.926Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T15:42:02.250Z] 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. [2024-11-16T15:42:02.250Z] The best model improves the baseline by 14.52%. [2024-11-16T15:42:02.579Z] Movies recommended for you: [2024-11-16T15:42:02.579Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T15:42:02.579Z] There is no way to check that no silent failure occurred. [2024-11-16T15:42:02.579Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (55218.767 ms) ====== [2024-11-16T15:42:02.579Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-11-16T15:42:02.579Z] GC before operation: completed in 159.521 ms, heap usage 1.020 GB -> 50.017 MB. [2024-11-16T15:42:11.293Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T15:42:20.005Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T15:42:28.743Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T15:42:37.497Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T15:42:42.146Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T15:42:47.927Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T15:42:52.570Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T15:42:57.240Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T15:42:57.572Z] 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. [2024-11-16T15:42:57.572Z] The best model improves the baseline by 14.52%. [2024-11-16T15:42:57.572Z] Movies recommended for you: [2024-11-16T15:42:57.572Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T15:42:57.572Z] There is no way to check that no silent failure occurred. [2024-11-16T15:42:57.572Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (54987.710 ms) ====== [2024-11-16T15:42:57.572Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-11-16T15:42:57.896Z] GC before operation: completed in 168.012 ms, heap usage 1.022 GB -> 50.223 MB. [2024-11-16T15:43:06.641Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T15:43:15.389Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T15:43:24.117Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T15:43:32.841Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T15:43:38.590Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T15:43:43.233Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T15:43:47.858Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T15:43:53.643Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T15:43:53.643Z] 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. [2024-11-16T15:43:53.643Z] The best model improves the baseline by 14.52%. [2024-11-16T15:43:53.643Z] Movies recommended for you: [2024-11-16T15:43:53.643Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T15:43:53.643Z] There is no way to check that no silent failure occurred. [2024-11-16T15:43:53.643Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (55756.007 ms) ====== [2024-11-16T15:43:53.643Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-11-16T15:43:53.643Z] GC before operation: completed in 172.525 ms, heap usage 1.039 GB -> 50.294 MB. [2024-11-16T15:44:02.402Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T15:44:11.124Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T15:44:19.838Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T15:44:28.557Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T15:44:33.189Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T15:44:38.984Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T15:44:43.597Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T15:44:48.247Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T15:44:48.590Z] 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. [2024-11-16T15:44:48.916Z] The best model improves the baseline by 14.52%. [2024-11-16T15:44:48.917Z] Movies recommended for you: [2024-11-16T15:44:48.917Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T15:44:48.917Z] There is no way to check that no silent failure occurred. [2024-11-16T15:44:48.917Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (55158.499 ms) ====== [2024-11-16T15:44:48.917Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-11-16T15:44:49.244Z] GC before operation: completed in 240.629 ms, heap usage 1.009 GB -> 49.922 MB. [2024-11-16T15:44:58.019Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T15:45:06.734Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T15:45:15.456Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T15:45:24.154Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T15:45:28.813Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T15:45:33.454Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T15:45:39.221Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T15:45:43.863Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T15:45:44.205Z] 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. [2024-11-16T15:45:44.205Z] The best model improves the baseline by 14.52%. [2024-11-16T15:45:44.205Z] Movies recommended for you: [2024-11-16T15:45:44.205Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T15:45:44.205Z] There is no way to check that no silent failure occurred. [2024-11-16T15:45:44.205Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (55144.176 ms) ====== [2024-11-16T15:45:44.205Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-11-16T15:45:44.528Z] GC before operation: completed in 160.357 ms, heap usage 1.007 GB -> 49.540 MB. [2024-11-16T15:45:53.273Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T15:46:01.991Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T15:46:10.698Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T15:46:19.445Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T15:46:24.093Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T15:46:28.751Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T15:46:34.521Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T15:46:39.188Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T15:46:39.518Z] 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. [2024-11-16T15:46:39.518Z] The best model improves the baseline by 14.52%. [2024-11-16T15:46:39.518Z] Movies recommended for you: [2024-11-16T15:46:39.518Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T15:46:39.518Z] There is no way to check that no silent failure occurred. [2024-11-16T15:46:39.518Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (55134.309 ms) ====== [2024-11-16T15:46:39.518Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-11-16T15:46:39.841Z] GC before operation: completed in 190.710 ms, heap usage 1.006 GB -> 49.759 MB. [2024-11-16T15:46:48.563Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T15:46:57.353Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T15:47:06.083Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T15:47:14.852Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T15:47:19.494Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T15:47:25.258Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T15:47:29.902Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T15:47:34.536Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T15:47:34.860Z] 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. [2024-11-16T15:47:34.860Z] The best model improves the baseline by 14.52%. [2024-11-16T15:47:35.186Z] Movies recommended for you: [2024-11-16T15:47:35.186Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T15:47:35.186Z] There is no way to check that no silent failure occurred. [2024-11-16T15:47:35.186Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (55360.729 ms) ====== [2024-11-16T15:47:35.186Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-11-16T15:47:35.510Z] GC before operation: completed in 199.622 ms, heap usage 1.024 GB -> 50.387 MB. [2024-11-16T15:47:44.214Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T15:47:53.018Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T15:48:01.732Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T15:48:10.487Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T15:48:15.158Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T15:48:19.809Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T15:48:25.592Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T15:48:30.242Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T15:48:30.242Z] 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. [2024-11-16T15:48:30.242Z] The best model improves the baseline by 14.52%. [2024-11-16T15:48:30.242Z] Movies recommended for you: [2024-11-16T15:48:30.242Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T15:48:30.242Z] There is no way to check that no silent failure occurred. [2024-11-16T15:48:30.242Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (54911.189 ms) ====== [2024-11-16T15:48:30.242Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-11-16T15:48:30.567Z] GC before operation: completed in 158.874 ms, heap usage 1.007 GB -> 49.703 MB. [2024-11-16T15:48:39.289Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T15:48:48.008Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T15:48:56.804Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T15:49:05.502Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T15:49:11.245Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T15:49:15.854Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T15:49:20.482Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T15:49:25.103Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T15:49:25.795Z] 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. [2024-11-16T15:49:25.795Z] The best model improves the baseline by 14.52%. [2024-11-16T15:49:25.795Z] Movies recommended for you: [2024-11-16T15:49:25.795Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T15:49:25.795Z] There is no way to check that no silent failure occurred. [2024-11-16T15:49:25.795Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (55368.558 ms) ====== [2024-11-16T15:49:25.795Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-11-16T15:49:26.119Z] GC before operation: completed in 173.263 ms, heap usage 1.007 GB -> 49.935 MB. [2024-11-16T15:49:34.817Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T15:49:43.576Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T15:49:52.300Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T15:50:01.006Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T15:50:05.619Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T15:50:11.382Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T15:50:16.019Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T15:50:20.659Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T15:50:21.010Z] 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. [2024-11-16T15:50:21.010Z] The best model improves the baseline by 14.52%. [2024-11-16T15:50:21.010Z] Movies recommended for you: [2024-11-16T15:50:21.010Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T15:50:21.010Z] There is no way to check that no silent failure occurred. [2024-11-16T15:50:21.010Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (55141.572 ms) ====== [2024-11-16T15:50:21.010Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-11-16T15:50:21.339Z] GC before operation: completed in 161.458 ms, heap usage 1.012 GB -> 50.124 MB. [2024-11-16T15:50:30.056Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T15:50:38.841Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T15:50:47.543Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T15:50:56.249Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T15:51:00.879Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T15:51:06.695Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T15:51:11.330Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T15:51:15.949Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T15:51:16.297Z] 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. [2024-11-16T15:51:16.297Z] The best model improves the baseline by 14.52%. [2024-11-16T15:51:16.297Z] Movies recommended for you: [2024-11-16T15:51:16.297Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T15:51:16.297Z] There is no way to check that no silent failure occurred. [2024-11-16T15:51:16.297Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (55061.438 ms) ====== [2024-11-16T15:51:16.297Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-11-16T15:51:16.622Z] GC before operation: completed in 159.774 ms, heap usage 1.021 GB -> 50.048 MB. [2024-11-16T15:51:25.336Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T15:51:34.079Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T15:51:42.820Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T15:51:51.507Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T15:51:57.261Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T15:52:01.873Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T15:52:07.675Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T15:52:11.343Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T15:52:12.045Z] 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. [2024-11-16T15:52:12.045Z] The best model improves the baseline by 14.52%. [2024-11-16T15:52:12.372Z] Movies recommended for you: [2024-11-16T15:52:12.372Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T15:52:12.372Z] There is no way to check that no silent failure occurred. [2024-11-16T15:52:12.372Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (55786.025 ms) ====== [2024-11-16T15:52:12.372Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-11-16T15:52:12.372Z] GC before operation: completed in 164.908 ms, heap usage 1.028 GB -> 50.225 MB. [2024-11-16T15:52:21.091Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T15:52:29.826Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T15:52:38.551Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T15:52:47.258Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T15:52:51.870Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T15:52:57.635Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T15:53:02.251Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T15:53:06.858Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T15:53:07.205Z] 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. [2024-11-16T15:53:07.542Z] The best model improves the baseline by 14.52%. [2024-11-16T15:53:07.542Z] Movies recommended for you: [2024-11-16T15:53:07.542Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T15:53:07.542Z] There is no way to check that no silent failure occurred. [2024-11-16T15:53:07.542Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (55091.662 ms) ====== [2024-11-16T15:53:07.542Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-11-16T15:53:07.869Z] GC before operation: completed in 158.680 ms, heap usage 1.013 GB -> 50.180 MB. [2024-11-16T15:53:16.624Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-16T15:53:25.364Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-16T15:53:34.101Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-16T15:53:42.813Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-16T15:53:47.479Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-16T15:53:52.112Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-16T15:53:57.862Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-16T15:54:02.487Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-16T15:54:02.837Z] 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. [2024-11-16T15:54:02.837Z] The best model improves the baseline by 14.52%. [2024-11-16T15:54:02.837Z] Movies recommended for you: [2024-11-16T15:54:02.837Z] WARNING: This benchmark provides no result that can be validated. [2024-11-16T15:54:02.837Z] There is no way to check that no silent failure occurred. [2024-11-16T15:54:02.837Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (55257.266 ms) ====== [2024-11-16T15:54:03.942Z] ----------------------------------- [2024-11-16T15:54:03.942Z] renaissance-movie-lens_0_PASSED [2024-11-16T15:54:03.942Z] ----------------------------------- [2024-11-16T15:54:04.635Z] [2024-11-16T15:54:04.635Z] TEST TEARDOWN: [2024-11-16T15:54:04.635Z] Nothing to be done for teardown. [2024-11-16T15:54:04.635Z] renaissance-movie-lens_0 Finish Time: Sat Nov 16 15:54:04 2024 Epoch Time (ms): 1731772444492