[2025-01-07T23:10:05.583Z] Running test renaissance-movie-lens_0 ... [2025-01-07T23:10:05.583Z] =============================================== [2025-01-07T23:10:05.583Z] renaissance-movie-lens_0 Start Time: Tue Jan 7 23:10:04 2025 Epoch Time (ms): 1736291404485 [2025-01-07T23:10:05.583Z] variation: NoOptions [2025-01-07T23:10:05.583Z] JVM_OPTIONS: [2025-01-07T23:10:05.583Z] { \ [2025-01-07T23:10:05.584Z] echo ""; echo "TEST SETUP:"; \ [2025-01-07T23:10:05.584Z] echo "Nothing to be done for setup."; \ [2025-01-07T23:10:05.584Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17362871702120/renaissance-movie-lens_0"; \ [2025-01-07T23:10:05.584Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17362871702120/renaissance-movie-lens_0"; \ [2025-01-07T23:10:05.584Z] echo ""; echo "TESTING:"; \ [2025-01-07T23:10:05.584Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/jdkbinary/j2sdk-image/bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17362871702120/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-01-07T23:10:05.584Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17362871702120/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-01-07T23:10:05.584Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-01-07T23:10:05.584Z] echo "Nothing to be done for teardown."; \ [2025-01-07T23:10:05.584Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17362871702120/TestTargetResult"; [2025-01-07T23:10:05.584Z] [2025-01-07T23:10:05.584Z] TEST SETUP: [2025-01-07T23:10:05.584Z] Nothing to be done for setup. [2025-01-07T23:10:05.584Z] [2025-01-07T23:10:05.584Z] TESTING: [2025-01-07T23:10:15.528Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2025-01-07T23:10:29.459Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-01-07T23:10:56.046Z] Got 100004 ratings from 671 users on 9066 movies. [2025-01-07T23:10:56.843Z] Training: 60056, validation: 20285, test: 19854 [2025-01-07T23:10:56.843Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-01-07T23:10:58.444Z] GC before operation: completed in 1516.600 ms, heap usage 158.611 MB -> 27.378 MB. [2025-01-07T23:11:47.631Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-07T23:12:18.816Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-07T23:12:54.865Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-07T23:13:30.716Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-07T23:13:47.389Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-07T23:14:06.722Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-07T23:14:26.241Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-07T23:14:45.357Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-07T23:14:48.165Z] 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. [2025-01-07T23:14:48.950Z] The best model improves the baseline by 14.52%. [2025-01-07T23:14:50.593Z] Movies recommended for you: [2025-01-07T23:14:50.593Z] WARNING: This benchmark provides no result that can be validated. [2025-01-07T23:14:50.593Z] There is no way to check that no silent failure occurred. [2025-01-07T23:14:50.593Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (232258.053 ms) ====== [2025-01-07T23:14:50.593Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-01-07T23:14:54.141Z] GC before operation: completed in 3555.666 ms, heap usage 470.387 MB -> 46.422 MB. [2025-01-07T23:15:29.716Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-07T23:16:00.585Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-07T23:16:26.642Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-07T23:16:52.908Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-07T23:17:06.913Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-07T23:17:23.500Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-07T23:17:42.844Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-07T23:17:59.590Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-07T23:18:02.201Z] 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. [2025-01-07T23:18:02.201Z] The best model improves the baseline by 14.52%. [2025-01-07T23:18:03.816Z] Movies recommended for you: [2025-01-07T23:18:03.816Z] WARNING: This benchmark provides no result that can be validated. [2025-01-07T23:18:03.816Z] There is no way to check that no silent failure occurred. [2025-01-07T23:18:03.816Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (189364.635 ms) ====== [2025-01-07T23:18:03.816Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-01-07T23:18:06.363Z] GC before operation: completed in 2445.492 ms, heap usage 383.665 MB -> 44.432 MB. [2025-01-07T23:18:36.951Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-07T23:18:59.781Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-07T23:19:25.809Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-07T23:19:48.204Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-07T23:20:02.330Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-07T23:20:16.749Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-07T23:20:33.029Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-07T23:20:44.897Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-07T23:20:46.623Z] 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. [2025-01-07T23:20:46.623Z] The best model improves the baseline by 14.52%. [2025-01-07T23:20:47.413Z] Movies recommended for you: [2025-01-07T23:20:47.413Z] WARNING: This benchmark provides no result that can be validated. [2025-01-07T23:20:47.413Z] There is no way to check that no silent failure occurred. [2025-01-07T23:20:47.413Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (161673.123 ms) ====== [2025-01-07T23:20:47.413Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-01-07T23:20:49.050Z] GC before operation: completed in 1368.477 ms, heap usage 185.886 MB -> 42.508 MB. [2025-01-07T23:21:15.151Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-07T23:21:42.147Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-07T23:22:08.934Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-07T23:22:40.213Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-07T23:22:54.670Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-07T23:23:07.567Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-07T23:23:21.893Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-07T23:23:36.365Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-07T23:23:37.197Z] 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. [2025-01-07T23:23:37.197Z] The best model improves the baseline by 14.52%. [2025-01-07T23:23:38.064Z] Movies recommended for you: [2025-01-07T23:23:38.065Z] WARNING: This benchmark provides no result that can be validated. [2025-01-07T23:23:38.065Z] There is no way to check that no silent failure occurred. [2025-01-07T23:23:38.065Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (169325.903 ms) ====== [2025-01-07T23:23:38.065Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-01-07T23:23:38.904Z] GC before operation: completed in 987.168 ms, heap usage 489.913 MB -> 46.867 MB. [2025-01-07T23:24:05.460Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-07T23:24:32.128Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-07T23:24:59.683Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-07T23:25:26.510Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-07T23:25:38.823Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-07T23:25:53.178Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-07T23:26:07.765Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-07T23:26:22.073Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-07T23:26:23.761Z] 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. [2025-01-07T23:26:23.761Z] The best model improves the baseline by 14.52%. [2025-01-07T23:26:24.564Z] Movies recommended for you: [2025-01-07T23:26:24.564Z] WARNING: This benchmark provides no result that can be validated. [2025-01-07T23:26:24.564Z] There is no way to check that no silent failure occurred. [2025-01-07T23:26:24.564Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (165103.507 ms) ====== [2025-01-07T23:26:24.564Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-01-07T23:26:26.299Z] GC before operation: completed in 1376.068 ms, heap usage 509.741 MB -> 47.067 MB. [2025-01-07T23:26:52.881Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-07T23:27:15.850Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-07T23:27:47.325Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-07T23:28:13.916Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-07T23:28:28.224Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-07T23:28:42.720Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-07T23:29:00.059Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-07T23:29:17.124Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-07T23:29:17.124Z] 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. [2025-01-07T23:29:17.959Z] The best model improves the baseline by 14.52%. [2025-01-07T23:29:18.775Z] Movies recommended for you: [2025-01-07T23:29:18.775Z] WARNING: This benchmark provides no result that can be validated. [2025-01-07T23:29:18.775Z] There is no way to check that no silent failure occurred. [2025-01-07T23:29:18.775Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (172745.105 ms) ====== [2025-01-07T23:29:18.775Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-01-07T23:29:19.617Z] GC before operation: completed in 1409.769 ms, heap usage 476.094 MB -> 46.959 MB. [2025-01-07T23:29:50.865Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-07T23:30:17.828Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-07T23:30:44.849Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-07T23:31:07.804Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-07T23:31:18.221Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-07T23:31:30.529Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-07T23:31:42.882Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-07T23:31:56.739Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-07T23:31:57.481Z] 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. [2025-01-07T23:31:58.549Z] The best model improves the baseline by 14.52%. [2025-01-07T23:31:58.549Z] Movies recommended for you: [2025-01-07T23:31:58.549Z] WARNING: This benchmark provides no result that can be validated. [2025-01-07T23:31:58.549Z] There is no way to check that no silent failure occurred. [2025-01-07T23:31:58.549Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (158721.047 ms) ====== [2025-01-07T23:31:58.549Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-01-07T23:32:00.213Z] GC before operation: completed in 1600.006 ms, heap usage 494.523 MB -> 47.153 MB. [2025-01-07T23:32:30.302Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-07T23:32:56.263Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-07T23:33:26.521Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-07T23:33:52.674Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-07T23:34:09.110Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-07T23:34:25.411Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-07T23:34:44.410Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-07T23:34:58.437Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-07T23:35:01.207Z] 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. [2025-01-07T23:35:01.207Z] The best model improves the baseline by 14.52%. [2025-01-07T23:35:01.980Z] Movies recommended for you: [2025-01-07T23:35:01.980Z] WARNING: This benchmark provides no result that can be validated. [2025-01-07T23:35:01.980Z] There is no way to check that no silent failure occurred. [2025-01-07T23:35:01.980Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (181634.266 ms) ====== [2025-01-07T23:35:01.980Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-01-07T23:35:03.534Z] GC before operation: completed in 2038.525 ms, heap usage 522.159 MB -> 46.760 MB. [2025-01-07T23:35:33.794Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-07T23:36:04.128Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-07T23:36:30.451Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-07T23:36:56.216Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-07T23:37:09.955Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-07T23:37:23.713Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-07T23:37:39.848Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-07T23:37:53.905Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-07T23:37:55.149Z] 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. [2025-01-07T23:37:55.913Z] The best model improves the baseline by 14.52%. [2025-01-07T23:37:56.702Z] Movies recommended for you: [2025-01-07T23:37:56.702Z] WARNING: This benchmark provides no result that can be validated. [2025-01-07T23:37:56.702Z] There is no way to check that no silent failure occurred. [2025-01-07T23:37:56.702Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (172452.948 ms) ====== [2025-01-07T23:37:56.702Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-01-07T23:37:58.328Z] GC before operation: completed in 2322.934 ms, heap usage 530.057 MB -> 43.440 MB. [2025-01-07T23:38:23.914Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-07T23:38:49.815Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-07T23:39:20.000Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-07T23:39:42.739Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-07T23:39:56.824Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-07T23:40:13.566Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-07T23:40:30.383Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-07T23:40:44.773Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-07T23:40:45.581Z] 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. [2025-01-07T23:40:45.581Z] The best model improves the baseline by 14.52%. [2025-01-07T23:40:46.442Z] Movies recommended for you: [2025-01-07T23:40:46.443Z] WARNING: This benchmark provides no result that can be validated. [2025-01-07T23:40:46.443Z] There is no way to check that no silent failure occurred. [2025-01-07T23:40:46.443Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (167523.932 ms) ====== [2025-01-07T23:40:46.443Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-01-07T23:40:48.685Z] GC before operation: completed in 2311.265 ms, heap usage 185.448 MB -> 43.143 MB. [2025-01-07T23:41:15.261Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-07T23:41:46.011Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-07T23:42:13.197Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-07T23:42:35.602Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-07T23:42:51.887Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-07T23:43:05.773Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-07T23:43:22.052Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-07T23:43:36.295Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-07T23:43:37.050Z] 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. [2025-01-07T23:43:37.817Z] The best model improves the baseline by 14.52%. [2025-01-07T23:43:38.595Z] Movies recommended for you: [2025-01-07T23:43:38.595Z] WARNING: This benchmark provides no result that can be validated. [2025-01-07T23:43:38.595Z] There is no way to check that no silent failure occurred. [2025-01-07T23:43:38.595Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (169867.902 ms) ====== [2025-01-07T23:43:38.595Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-01-07T23:43:40.198Z] GC before operation: completed in 1585.041 ms, heap usage 484.758 MB -> 42.336 MB. [2025-01-07T23:44:05.952Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-07T23:44:31.691Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-07T23:44:57.996Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-07T23:45:20.069Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-07T23:45:36.155Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-07T23:45:47.922Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-07T23:46:04.143Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-07T23:46:16.353Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-07T23:46:18.052Z] 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. [2025-01-07T23:46:18.052Z] The best model improves the baseline by 14.52%. [2025-01-07T23:46:18.854Z] Movies recommended for you: [2025-01-07T23:46:18.854Z] WARNING: This benchmark provides no result that can be validated. [2025-01-07T23:46:18.854Z] There is no way to check that no silent failure occurred. [2025-01-07T23:46:18.854Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (159059.113 ms) ====== [2025-01-07T23:46:18.854Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-01-07T23:46:20.477Z] GC before operation: completed in 1004.027 ms, heap usage 499.489 MB -> 42.597 MB. [2025-01-07T23:46:42.349Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-07T23:47:04.382Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-07T23:47:26.482Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-07T23:47:46.001Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-07T23:47:57.687Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-07T23:48:07.597Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-07T23:48:23.646Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-07T23:48:35.370Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-07T23:48:36.159Z] 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. [2025-01-07T23:48:36.159Z] The best model improves the baseline by 14.52%. [2025-01-07T23:48:36.958Z] Movies recommended for you: [2025-01-07T23:48:36.958Z] WARNING: This benchmark provides no result that can be validated. [2025-01-07T23:48:36.958Z] There is no way to check that no silent failure occurred. [2025-01-07T23:48:36.958Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (136956.438 ms) ====== [2025-01-07T23:48:36.958Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-01-07T23:48:37.721Z] GC before operation: completed in 801.353 ms, heap usage 454.831 MB -> 42.771 MB. [2025-01-07T23:49:00.283Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-07T23:49:19.001Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-07T23:49:41.004Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-07T23:50:00.022Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-07T23:50:09.991Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-07T23:50:20.305Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-07T23:50:36.359Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-07T23:50:50.002Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-07T23:50:50.002Z] 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. [2025-01-07T23:50:50.002Z] The best model improves the baseline by 14.52%. [2025-01-07T23:50:50.766Z] Movies recommended for you: [2025-01-07T23:50:50.766Z] WARNING: This benchmark provides no result that can be validated. [2025-01-07T23:50:50.766Z] There is no way to check that no silent failure occurred. [2025-01-07T23:50:50.766Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (132831.129 ms) ====== [2025-01-07T23:50:50.766Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-01-07T23:50:51.527Z] GC before operation: completed in 978.514 ms, heap usage 464.506 MB -> 42.566 MB. [2025-01-07T23:51:13.634Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-07T23:51:32.415Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-07T23:51:54.955Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-07T23:52:11.128Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-07T23:52:22.903Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-07T23:52:34.530Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-07T23:52:44.319Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-07T23:52:55.151Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-07T23:52:55.973Z] 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. [2025-01-07T23:52:55.973Z] The best model improves the baseline by 14.52%. [2025-01-07T23:52:56.770Z] Movies recommended for you: [2025-01-07T23:52:56.770Z] WARNING: This benchmark provides no result that can be validated. [2025-01-07T23:52:56.770Z] There is no way to check that no silent failure occurred. [2025-01-07T23:52:56.770Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (124925.640 ms) ====== [2025-01-07T23:52:56.770Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-01-07T23:52:57.581Z] GC before operation: completed in 1069.542 ms, heap usage 493.100 MB -> 42.681 MB. [2025-01-07T23:53:14.284Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-07T23:53:33.895Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-07T23:53:53.257Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-07T23:54:07.364Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-07T23:54:15.893Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-07T23:54:26.163Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-07T23:54:36.430Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-07T23:54:44.998Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-07T23:54:45.798Z] 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. [2025-01-07T23:54:45.798Z] The best model improves the baseline by 14.52%. [2025-01-07T23:54:46.589Z] Movies recommended for you: [2025-01-07T23:54:46.589Z] WARNING: This benchmark provides no result that can be validated. [2025-01-07T23:54:46.589Z] There is no way to check that no silent failure occurred. [2025-01-07T23:54:46.589Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (108793.047 ms) ====== [2025-01-07T23:54:46.589Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-01-07T23:54:47.388Z] GC before operation: completed in 592.521 ms, heap usage 479.468 MB -> 42.768 MB. [2025-01-07T23:55:04.149Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-07T23:55:24.151Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-07T23:55:46.591Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-07T23:56:05.875Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-07T23:56:17.909Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-07T23:56:29.980Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-07T23:56:44.592Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-07T23:56:58.766Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-07T23:57:00.613Z] 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. [2025-01-07T23:57:00.613Z] The best model improves the baseline by 14.52%. [2025-01-07T23:57:01.441Z] Movies recommended for you: [2025-01-07T23:57:01.441Z] WARNING: This benchmark provides no result that can be validated. [2025-01-07T23:57:01.441Z] There is no way to check that no silent failure occurred. [2025-01-07T23:57:01.441Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (134053.932 ms) ====== [2025-01-07T23:57:01.441Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-01-07T23:57:03.160Z] GC before operation: completed in 1549.227 ms, heap usage 473.618 MB -> 43.286 MB. [2025-01-07T23:57:30.038Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-07T23:57:52.996Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-07T23:58:24.457Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-07T23:58:47.088Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-07T23:59:01.204Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-07T23:59:13.260Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-07T23:59:28.117Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-07T23:59:40.273Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-07T23:59:41.086Z] 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. [2025-01-07T23:59:41.086Z] The best model improves the baseline by 14.52%. [2025-01-07T23:59:41.086Z] Movies recommended for you: [2025-01-07T23:59:41.086Z] WARNING: This benchmark provides no result that can be validated. [2025-01-07T23:59:41.086Z] There is no way to check that no silent failure occurred. [2025-01-07T23:59:41.086Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (158718.969 ms) ====== [2025-01-07T23:59:41.086Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-01-07T23:59:42.782Z] GC before operation: completed in 997.894 ms, heap usage 487.129 MB -> 45.018 MB. [2025-01-08T00:00:05.523Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-08T00:00:28.274Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-08T00:00:54.497Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-08T00:01:17.407Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-08T00:01:29.540Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-08T00:01:43.577Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-08T00:01:55.620Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-08T00:02:07.943Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-08T00:02:09.245Z] 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. [2025-01-08T00:02:09.245Z] The best model improves the baseline by 14.52%. [2025-01-08T00:02:09.245Z] Movies recommended for you: [2025-01-08T00:02:09.245Z] WARNING: This benchmark provides no result that can be validated. [2025-01-08T00:02:09.245Z] There is no way to check that no silent failure occurred. [2025-01-08T00:02:09.245Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (146614.767 ms) ====== [2025-01-08T00:02:09.245Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-01-08T00:02:10.899Z] GC before operation: completed in 1564.104 ms, heap usage 468.600 MB -> 43.522 MB. [2025-01-08T00:02:30.126Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-08T00:02:52.569Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-08T00:03:19.102Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-08T00:03:38.279Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-08T00:03:52.913Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-08T00:04:09.371Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-08T00:04:21.374Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-08T00:04:35.583Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-08T00:04:36.395Z] 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. [2025-01-08T00:04:36.395Z] The best model improves the baseline by 14.52%. [2025-01-08T00:04:37.214Z] Movies recommended for you: [2025-01-08T00:04:37.214Z] WARNING: This benchmark provides no result that can be validated. [2025-01-08T00:04:37.214Z] There is no way to check that no silent failure occurred. [2025-01-08T00:04:37.214Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (146450.940 ms) ====== [2025-01-08T00:04:41.848Z] ----------------------------------- [2025-01-08T00:04:41.848Z] renaissance-movie-lens_0_PASSED [2025-01-08T00:04:41.848Z] ----------------------------------- [2025-01-08T00:04:41.848Z] [2025-01-08T00:04:41.848Z] TEST TEARDOWN: [2025-01-08T00:04:41.848Z] Nothing to be done for teardown. [2025-01-08T00:04:41.848Z] renaissance-movie-lens_0 Finish Time: Wed Jan 8 00:04:41 2025 Epoch Time (ms): 1736294681186