[2025-03-04T23:06:12.193Z] Running test renaissance-movie-lens_0 ... [2025-03-04T23:06:12.193Z] =============================================== [2025-03-04T23:06:12.510Z] renaissance-movie-lens_0 Start Time: Tue Mar 4 23:06:12 2025 Epoch Time (ms): 1741129572239 [2025-03-04T23:06:12.510Z] variation: NoOptions [2025-03-04T23:06:12.863Z] JVM_OPTIONS: [2025-03-04T23:06:12.863Z] { \ [2025-03-04T23:06:12.863Z] echo ""; echo "TEST SETUP:"; \ [2025-03-04T23:06:12.863Z] echo "Nothing to be done for setup."; \ [2025-03-04T23:06:12.863Z] mkdir -p "C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17411281626605\\renaissance-movie-lens_0"; \ [2025-03-04T23:06:12.863Z] cd "C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17411281626605\\renaissance-movie-lens_0"; \ [2025-03-04T23:06:12.863Z] echo ""; echo "TESTING:"; \ [2025-03-04T23:06:12.863Z] "c:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/jdkbinary/j2sdk-image\\bin\\java" -jar "C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17411281626605\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2025-03-04T23:06:12.863Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17411281626605\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-03-04T23:06:12.863Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-03-04T23:06:12.863Z] echo "Nothing to be done for teardown."; \ [2025-03-04T23:06:12.863Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17411281626605\\TestTargetResult"; [2025-03-04T23:06:12.863Z] [2025-03-04T23:06:12.863Z] TEST SETUP: [2025-03-04T23:06:12.863Z] Nothing to be done for setup. [2025-03-04T23:06:12.863Z] [2025-03-04T23:06:12.863Z] TESTING: [2025-03-04T23:06:25.897Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2025-03-04T23:06:28.317Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-03-04T23:06:33.130Z] Got 100004 ratings from 671 users on 9066 movies. [2025-03-04T23:06:33.130Z] Training: 60056, validation: 20285, test: 19854 [2025-03-04T23:06:33.130Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-03-04T23:06:33.130Z] GC before operation: completed in 239.924 ms, heap usage 178.919 MB -> 26.625 MB. [2025-03-04T23:06:46.425Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T23:06:57.229Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T23:07:08.030Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T23:07:18.821Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T23:07:23.528Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T23:07:29.363Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T23:07:34.115Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T23:07:39.997Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T23:07:39.997Z] 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. [2025-03-04T23:07:39.997Z] The best model improves the baseline by 14.52%. [2025-03-04T23:07:39.997Z] Movies recommended for you: [2025-03-04T23:07:39.997Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T23:07:39.997Z] There is no way to check that no silent failure occurred. [2025-03-04T23:07:39.997Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (67331.930 ms) ====== [2025-03-04T23:07:39.997Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-03-04T23:07:40.330Z] GC before operation: completed in 360.538 ms, heap usage 320.070 MB -> 40.460 MB. [2025-03-04T23:07:49.169Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T23:07:56.393Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T23:08:05.210Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T23:08:12.411Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T23:08:17.092Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T23:08:22.907Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T23:08:27.584Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T23:08:32.285Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T23:08:32.285Z] 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. [2025-03-04T23:08:32.285Z] The best model improves the baseline by 14.52%. [2025-03-04T23:08:32.627Z] Movies recommended for you: [2025-03-04T23:08:32.627Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T23:08:32.627Z] There is no way to check that no silent failure occurred. [2025-03-04T23:08:32.627Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (52124.112 ms) ====== [2025-03-04T23:08:32.627Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-03-04T23:08:32.627Z] GC before operation: completed in 247.492 ms, heap usage 340.607 MB -> 41.437 MB. [2025-03-04T23:08:41.611Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T23:08:48.802Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T23:08:57.617Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T23:09:04.814Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T23:09:09.523Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T23:09:13.240Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T23:09:19.080Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T23:09:22.821Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T23:09:23.199Z] 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. [2025-03-04T23:09:23.199Z] The best model improves the baseline by 14.52%. [2025-03-04T23:09:23.540Z] Movies recommended for you: [2025-03-04T23:09:23.540Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T23:09:23.540Z] There is no way to check that no silent failure occurred. [2025-03-04T23:09:23.540Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (50613.270 ms) ====== [2025-03-04T23:09:23.540Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-03-04T23:09:23.540Z] GC before operation: completed in 189.728 ms, heap usage 583.836 MB -> 45.867 MB. [2025-03-04T23:09:32.363Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T23:09:39.592Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T23:09:48.388Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T23:09:55.506Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T23:10:00.213Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T23:10:04.895Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T23:10:09.606Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T23:10:13.377Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T23:10:14.085Z] 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. [2025-03-04T23:10:14.085Z] The best model improves the baseline by 14.52%. [2025-03-04T23:10:14.418Z] Movies recommended for you: [2025-03-04T23:10:14.418Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T23:10:14.418Z] There is no way to check that no silent failure occurred. [2025-03-04T23:10:14.418Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (50720.824 ms) ====== [2025-03-04T23:10:14.418Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-03-04T23:10:14.418Z] GC before operation: completed in 169.065 ms, heap usage 564.487 MB -> 46.064 MB. [2025-03-04T23:10:23.223Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T23:10:30.391Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T23:10:39.204Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T23:10:46.405Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T23:10:51.096Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T23:10:54.813Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T23:11:00.717Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T23:11:04.447Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T23:11:05.145Z] 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. [2025-03-04T23:11:05.145Z] The best model improves the baseline by 14.52%. [2025-03-04T23:11:05.145Z] Movies recommended for you: [2025-03-04T23:11:05.145Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T23:11:05.145Z] There is no way to check that no silent failure occurred. [2025-03-04T23:11:05.145Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (50753.583 ms) ====== [2025-03-04T23:11:05.145Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-03-04T23:11:05.481Z] GC before operation: completed in 177.575 ms, heap usage 546.018 MB -> 46.267 MB. [2025-03-04T23:11:14.271Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T23:11:21.471Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T23:11:28.669Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T23:11:37.447Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T23:11:41.182Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T23:11:44.940Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T23:11:50.759Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T23:11:54.489Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T23:11:54.828Z] 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. [2025-03-04T23:11:54.828Z] The best model improves the baseline by 14.52%. [2025-03-04T23:11:54.828Z] Movies recommended for you: [2025-03-04T23:11:54.828Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T23:11:54.828Z] There is no way to check that no silent failure occurred. [2025-03-04T23:11:54.828Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (49541.111 ms) ====== [2025-03-04T23:11:54.828Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-03-04T23:11:55.161Z] GC before operation: completed in 195.632 ms, heap usage 554.523 MB -> 46.177 MB. [2025-03-04T23:12:03.945Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T23:12:11.130Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T23:12:18.307Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T23:12:27.098Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T23:12:30.844Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T23:12:34.577Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T23:12:40.412Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T23:12:44.176Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T23:12:44.508Z] 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. [2025-03-04T23:12:44.508Z] The best model improves the baseline by 14.52%. [2025-03-04T23:12:44.508Z] Movies recommended for you: [2025-03-04T23:12:44.508Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T23:12:44.508Z] There is no way to check that no silent failure occurred. [2025-03-04T23:12:44.508Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (49438.505 ms) ====== [2025-03-04T23:12:44.508Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-03-04T23:12:44.839Z] GC before operation: completed in 155.077 ms, heap usage 563.153 MB -> 46.376 MB. [2025-03-04T23:12:52.020Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T23:13:00.847Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T23:13:08.032Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T23:13:15.225Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T23:13:19.906Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T23:13:24.602Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T23:13:29.296Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T23:13:33.033Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T23:13:33.752Z] 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. [2025-03-04T23:13:33.753Z] The best model improves the baseline by 14.52%. [2025-03-04T23:13:33.753Z] Movies recommended for you: [2025-03-04T23:13:33.753Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T23:13:33.753Z] There is no way to check that no silent failure occurred. [2025-03-04T23:13:33.753Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (49102.202 ms) ====== [2025-03-04T23:13:33.753Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-03-04T23:13:34.093Z] GC before operation: completed in 164.994 ms, heap usage 543.283 MB -> 46.639 MB. [2025-03-04T23:13:41.309Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T23:13:50.163Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T23:13:57.474Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T23:14:04.656Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T23:14:09.368Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T23:14:14.056Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T23:14:18.729Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T23:14:23.438Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T23:14:23.439Z] 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. [2025-03-04T23:14:23.439Z] The best model improves the baseline by 14.52%. [2025-03-04T23:14:23.439Z] Movies recommended for you: [2025-03-04T23:14:23.439Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T23:14:23.439Z] There is no way to check that no silent failure occurred. [2025-03-04T23:14:23.439Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (49471.720 ms) ====== [2025-03-04T23:14:23.439Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-03-04T23:14:23.768Z] GC before operation: completed in 176.610 ms, heap usage 509.474 MB -> 46.365 MB. [2025-03-04T23:14:30.949Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T23:14:39.754Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T23:14:46.987Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T23:14:54.186Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T23:14:58.850Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T23:15:03.527Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T23:15:08.206Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T23:15:11.959Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T23:15:12.673Z] 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. [2025-03-04T23:15:12.673Z] The best model improves the baseline by 14.52%. [2025-03-04T23:15:12.673Z] Movies recommended for you: [2025-03-04T23:15:12.673Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T23:15:12.673Z] There is no way to check that no silent failure occurred. [2025-03-04T23:15:12.673Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (49086.944 ms) ====== [2025-03-04T23:15:12.673Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-03-04T23:15:13.010Z] GC before operation: completed in 214.637 ms, heap usage 554.406 MB -> 46.594 MB. [2025-03-04T23:15:21.793Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T23:15:28.966Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T23:15:36.169Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T23:15:44.956Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T23:15:48.672Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T23:15:53.365Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T23:15:58.065Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T23:16:01.784Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T23:16:02.510Z] 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. [2025-03-04T23:16:02.510Z] The best model improves the baseline by 14.52%. [2025-03-04T23:16:02.510Z] Movies recommended for you: [2025-03-04T23:16:02.510Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T23:16:02.510Z] There is no way to check that no silent failure occurred. [2025-03-04T23:16:02.510Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (49562.769 ms) ====== [2025-03-04T23:16:02.510Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-03-04T23:16:02.510Z] GC before operation: completed in 135.608 ms, heap usage 551.116 MB -> 46.257 MB. [2025-03-04T23:16:11.285Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T23:16:18.494Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T23:16:25.744Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T23:16:32.928Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T23:16:37.633Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T23:16:42.321Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T23:16:47.014Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T23:16:50.737Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T23:16:51.499Z] 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. [2025-03-04T23:16:51.499Z] The best model improves the baseline by 14.52%. [2025-03-04T23:16:51.499Z] Movies recommended for you: [2025-03-04T23:16:51.499Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T23:16:51.499Z] There is no way to check that no silent failure occurred. [2025-03-04T23:16:51.499Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (48996.714 ms) ====== [2025-03-04T23:16:51.499Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-03-04T23:16:51.829Z] GC before operation: completed in 150.921 ms, heap usage 558.137 MB -> 46.483 MB. [2025-03-04T23:17:00.605Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T23:17:07.820Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T23:17:16.606Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T23:17:23.802Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T23:17:27.517Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T23:17:32.189Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T23:17:36.868Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T23:17:40.594Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T23:17:41.303Z] 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. [2025-03-04T23:17:41.303Z] The best model improves the baseline by 14.52%. [2025-03-04T23:17:41.303Z] Movies recommended for you: [2025-03-04T23:17:41.303Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T23:17:41.303Z] There is no way to check that no silent failure occurred. [2025-03-04T23:17:41.303Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (49543.437 ms) ====== [2025-03-04T23:17:41.303Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-03-04T23:17:41.632Z] GC before operation: completed in 146.041 ms, heap usage 535.118 MB -> 46.642 MB. [2025-03-04T23:17:48.881Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T23:17:57.667Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T23:18:04.845Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T23:18:12.039Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T23:18:16.720Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T23:18:21.383Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T23:18:26.075Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T23:18:29.823Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T23:18:30.554Z] 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. [2025-03-04T23:18:30.554Z] The best model improves the baseline by 14.52%. [2025-03-04T23:18:30.554Z] Movies recommended for you: [2025-03-04T23:18:30.554Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T23:18:30.554Z] There is no way to check that no silent failure occurred. [2025-03-04T23:18:30.554Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (49192.402 ms) ====== [2025-03-04T23:18:30.554Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-03-04T23:18:30.929Z] GC before operation: completed in 178.407 ms, heap usage 554.610 MB -> 46.372 MB. [2025-03-04T23:18:39.742Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T23:18:46.898Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T23:18:55.684Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T23:19:01.517Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T23:19:06.195Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T23:19:10.892Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T23:19:15.622Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T23:19:20.341Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T23:19:20.341Z] 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. [2025-03-04T23:19:20.341Z] The best model improves the baseline by 14.52%. [2025-03-04T23:19:20.681Z] Movies recommended for you: [2025-03-04T23:19:20.681Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T23:19:20.681Z] There is no way to check that no silent failure occurred. [2025-03-04T23:19:20.681Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (49768.461 ms) ====== [2025-03-04T23:19:20.681Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-03-04T23:19:20.681Z] GC before operation: completed in 162.151 ms, heap usage 533.686 MB -> 46.539 MB. [2025-03-04T23:19:29.505Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T23:19:35.350Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T23:19:44.174Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T23:19:51.338Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T23:19:56.021Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T23:20:00.734Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T23:20:05.426Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T23:20:09.241Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T23:20:09.571Z] 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. [2025-03-04T23:20:09.571Z] The best model improves the baseline by 14.52%. [2025-03-04T23:20:09.906Z] Movies recommended for you: [2025-03-04T23:20:09.906Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T23:20:09.906Z] There is no way to check that no silent failure occurred. [2025-03-04T23:20:09.906Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (48999.850 ms) ====== [2025-03-04T23:20:09.906Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-03-04T23:20:09.906Z] GC before operation: completed in 159.775 ms, heap usage 532.508 MB -> 46.558 MB. [2025-03-04T23:20:18.713Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T23:20:25.878Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T23:20:33.065Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T23:20:40.242Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T23:20:44.957Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T23:20:49.635Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T23:20:54.358Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T23:20:59.066Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T23:20:59.066Z] 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. [2025-03-04T23:20:59.066Z] The best model improves the baseline by 14.52%. [2025-03-04T23:20:59.066Z] Movies recommended for you: [2025-03-04T23:20:59.066Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T23:20:59.066Z] There is no way to check that no silent failure occurred. [2025-03-04T23:20:59.066Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (49212.600 ms) ====== [2025-03-04T23:20:59.066Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-03-04T23:20:59.405Z] GC before operation: completed in 161.467 ms, heap usage 484.350 MB -> 46.413 MB. [2025-03-04T23:21:08.197Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T23:21:15.373Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T23:21:24.229Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T23:21:31.396Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T23:21:35.112Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T23:21:39.904Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T23:21:44.658Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T23:21:48.406Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T23:21:49.116Z] 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. [2025-03-04T23:21:49.116Z] The best model improves the baseline by 14.52%. [2025-03-04T23:21:49.116Z] Movies recommended for you: [2025-03-04T23:21:49.116Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T23:21:49.116Z] There is no way to check that no silent failure occurred. [2025-03-04T23:21:49.116Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (49779.334 ms) ====== [2025-03-04T23:21:49.116Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-03-04T23:21:49.440Z] GC before operation: completed in 152.524 ms, heap usage 489.880 MB -> 46.436 MB. [2025-03-04T23:21:56.629Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T23:22:05.440Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T23:22:12.645Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T23:22:19.824Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T23:22:24.497Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T23:22:29.233Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T23:22:33.909Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T23:22:38.624Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T23:22:38.624Z] 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. [2025-03-04T23:22:38.624Z] The best model improves the baseline by 14.52%. [2025-03-04T23:22:38.624Z] Movies recommended for you: [2025-03-04T23:22:38.624Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T23:22:38.624Z] There is no way to check that no silent failure occurred. [2025-03-04T23:22:38.624Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (49349.269 ms) ====== [2025-03-04T23:22:38.624Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-03-04T23:22:38.975Z] GC before operation: completed in 150.336 ms, heap usage 483.807 MB -> 46.659 MB. [2025-03-04T23:22:46.184Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-03-04T23:22:53.362Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-03-04T23:23:02.155Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-03-04T23:23:09.331Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-03-04T23:23:14.123Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-03-04T23:23:17.858Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-03-04T23:23:23.671Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-03-04T23:23:27.390Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-03-04T23:23:27.721Z] 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. [2025-03-04T23:23:27.721Z] The best model improves the baseline by 14.52%. [2025-03-04T23:23:27.721Z] Movies recommended for you: [2025-03-04T23:23:27.721Z] WARNING: This benchmark provides no result that can be validated. [2025-03-04T23:23:27.721Z] There is no way to check that no silent failure occurred. [2025-03-04T23:23:27.721Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (49026.346 ms) ====== [2025-03-04T23:23:28.422Z] ----------------------------------- [2025-03-04T23:23:28.422Z] renaissance-movie-lens_0_PASSED [2025-03-04T23:23:28.422Z] ----------------------------------- [2025-03-04T23:23:29.122Z] [2025-03-04T23:23:29.122Z] TEST TEARDOWN: [2025-03-04T23:23:29.122Z] Nothing to be done for teardown. [2025-03-04T23:23:29.122Z] renaissance-movie-lens_0 Finish Time: Tue Mar 4 23:23:28 2025 Epoch Time (ms): 1741130608919