[2024-08-16T16:38:08.409Z] Running test renaissance-movie-lens_0 ... [2024-08-16T16:38:08.409Z] =============================================== [2024-08-16T16:38:08.409Z] renaissance-movie-lens_0 Start Time: Fri Aug 16 12:38:08 2024 Epoch Time (ms): 1723826288266 [2024-08-16T16:38:08.409Z] variation: NoOptions [2024-08-16T16:38:08.409Z] JVM_OPTIONS: [2024-08-16T16:38:08.409Z] { \ [2024-08-16T16:38:08.409Z] echo ""; echo "TEST SETUP:"; \ [2024-08-16T16:38:08.409Z] echo "Nothing to be done for setup."; \ [2024-08-16T16:38:08.409Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17238247553785/renaissance-movie-lens_0"; \ [2024-08-16T16:38:08.409Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17238247553785/renaissance-movie-lens_0"; \ [2024-08-16T16:38:08.409Z] echo ""; echo "TESTING:"; \ [2024-08-16T16:38:08.409Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_testList_0/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17238247553785/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-08-16T16:38:08.409Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17238247553785/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-16T16:38:08.409Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-16T16:38:08.409Z] echo "Nothing to be done for teardown."; \ [2024-08-16T16:38:08.409Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17238247553785/TestTargetResult"; [2024-08-16T16:38:08.409Z] [2024-08-16T16:38:08.409Z] TEST SETUP: [2024-08-16T16:38:08.409Z] Nothing to be done for setup. [2024-08-16T16:38:08.409Z] [2024-08-16T16:38:08.409Z] TESTING: [2024-08-16T16:38:11.206Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-16T16:38:13.623Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2024-08-16T16:38:17.420Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-16T16:38:17.420Z] Training: 60056, validation: 20285, test: 19854 [2024-08-16T16:38:17.420Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-16T16:38:18.085Z] GC before operation: completed in 97.577 ms, heap usage 83.845 MB -> 36.406 MB. [2024-08-16T16:38:25.337Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T16:38:30.167Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T16:38:33.916Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T16:38:37.651Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T16:38:39.701Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T16:38:42.646Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T16:38:44.745Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T16:38:46.786Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T16:38:47.460Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2024-08-16T16:38:47.460Z] The best model improves the baseline by 14.34%. [2024-08-16T16:38:47.460Z] Movies recommended for you: [2024-08-16T16:38:47.460Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T16:38:47.460Z] There is no way to check that no silent failure occurred. [2024-08-16T16:38:47.460Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (29817.506 ms) ====== [2024-08-16T16:38:47.460Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-16T16:38:47.460Z] GC before operation: completed in 176.488 ms, heap usage 255.879 MB -> 46.618 MB. [2024-08-16T16:38:51.270Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T16:38:54.977Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T16:38:58.711Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T16:39:02.011Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T16:39:03.300Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T16:39:05.334Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T16:39:07.421Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T16:39:09.436Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T16:39:10.086Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2024-08-16T16:39:10.086Z] The best model improves the baseline by 14.34%. [2024-08-16T16:39:10.086Z] Movies recommended for you: [2024-08-16T16:39:10.086Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T16:39:10.086Z] There is no way to check that no silent failure occurred. [2024-08-16T16:39:10.086Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (22291.400 ms) ====== [2024-08-16T16:39:10.086Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-16T16:39:10.086Z] GC before operation: completed in 133.615 ms, heap usage 152.088 MB -> 48.484 MB. [2024-08-16T16:39:12.942Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T16:39:15.745Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T16:39:18.580Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T16:39:21.485Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T16:39:23.507Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T16:39:25.556Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T16:39:27.560Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T16:39:28.877Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T16:39:29.512Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2024-08-16T16:39:29.512Z] The best model improves the baseline by 14.34%. [2024-08-16T16:39:29.512Z] Movies recommended for you: [2024-08-16T16:39:29.512Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T16:39:29.512Z] There is no way to check that no silent failure occurred. [2024-08-16T16:39:29.512Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (19216.546 ms) ====== [2024-08-16T16:39:29.512Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-16T16:39:29.512Z] GC before operation: completed in 161.001 ms, heap usage 126.693 MB -> 48.655 MB. [2024-08-16T16:39:33.226Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T16:39:36.155Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T16:39:39.444Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T16:39:42.310Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T16:39:43.575Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T16:39:45.565Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T16:39:47.569Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T16:39:48.885Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T16:39:49.542Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2024-08-16T16:39:49.542Z] The best model improves the baseline by 14.34%. [2024-08-16T16:39:49.542Z] Movies recommended for you: [2024-08-16T16:39:49.542Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T16:39:49.542Z] There is no way to check that no silent failure occurred. [2024-08-16T16:39:49.542Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (19784.649 ms) ====== [2024-08-16T16:39:49.542Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-16T16:39:49.542Z] GC before operation: completed in 169.145 ms, heap usage 153.129 MB -> 49.047 MB. [2024-08-16T16:39:53.283Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T16:39:56.120Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T16:39:59.789Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T16:40:02.686Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T16:40:03.991Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T16:40:06.005Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T16:40:08.017Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T16:40:09.302Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T16:40:09.912Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2024-08-16T16:40:09.913Z] The best model improves the baseline by 14.34%. [2024-08-16T16:40:09.913Z] Movies recommended for you: [2024-08-16T16:40:09.913Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T16:40:09.913Z] There is no way to check that no silent failure occurred. [2024-08-16T16:40:09.913Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (20506.071 ms) ====== [2024-08-16T16:40:09.913Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-16T16:40:09.913Z] GC before operation: completed in 144.089 ms, heap usage 148.494 MB -> 49.203 MB. [2024-08-16T16:40:13.647Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T16:40:16.442Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T16:40:19.346Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T16:40:22.163Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T16:40:23.841Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T16:40:25.142Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T16:40:27.176Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T16:40:29.251Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T16:40:29.251Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2024-08-16T16:40:29.251Z] The best model improves the baseline by 14.34%. [2024-08-16T16:40:29.251Z] Movies recommended for you: [2024-08-16T16:40:29.251Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T16:40:29.251Z] There is no way to check that no silent failure occurred. [2024-08-16T16:40:29.251Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (19086.890 ms) ====== [2024-08-16T16:40:29.251Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-16T16:40:29.251Z] GC before operation: completed in 190.103 ms, heap usage 152.571 MB -> 49.161 MB. [2024-08-16T16:40:33.089Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T16:40:35.954Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T16:40:38.873Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T16:40:41.667Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T16:40:43.747Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T16:40:45.048Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T16:40:47.065Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T16:40:49.126Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T16:40:49.126Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2024-08-16T16:40:49.126Z] The best model improves the baseline by 14.34%. [2024-08-16T16:40:49.126Z] Movies recommended for you: [2024-08-16T16:40:49.126Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T16:40:49.126Z] There is no way to check that no silent failure occurred. [2024-08-16T16:40:49.126Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (19963.536 ms) ====== [2024-08-16T16:40:49.126Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-16T16:40:49.760Z] GC before operation: completed in 191.309 ms, heap usage 137.631 MB -> 49.300 MB. [2024-08-16T16:40:53.528Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T16:40:56.358Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T16:41:00.158Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T16:41:02.985Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T16:41:04.290Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T16:41:06.342Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T16:41:08.445Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T16:41:10.839Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T16:41:10.839Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2024-08-16T16:41:10.839Z] The best model improves the baseline by 14.34%. [2024-08-16T16:41:11.449Z] Movies recommended for you: [2024-08-16T16:41:11.449Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T16:41:11.449Z] There is no way to check that no silent failure occurred. [2024-08-16T16:41:11.449Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (21607.809 ms) ====== [2024-08-16T16:41:11.449Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-16T16:41:11.449Z] GC before operation: completed in 149.139 ms, heap usage 244.148 MB -> 49.666 MB. [2024-08-16T16:41:14.461Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T16:41:18.159Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T16:41:21.065Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T16:41:23.969Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T16:41:26.006Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T16:41:28.026Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T16:41:30.060Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T16:41:31.339Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T16:41:31.339Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2024-08-16T16:41:31.339Z] The best model improves the baseline by 14.34%. [2024-08-16T16:41:31.942Z] Movies recommended for you: [2024-08-16T16:41:31.942Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T16:41:31.942Z] There is no way to check that no silent failure occurred. [2024-08-16T16:41:31.942Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (20359.265 ms) ====== [2024-08-16T16:41:31.942Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-16T16:41:31.942Z] GC before operation: completed in 154.751 ms, heap usage 136.558 MB -> 49.416 MB. [2024-08-16T16:41:35.654Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T16:41:38.515Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T16:41:41.363Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T16:41:44.255Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T16:41:45.546Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T16:41:47.595Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T16:41:49.647Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T16:41:51.351Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T16:41:51.351Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2024-08-16T16:41:51.947Z] The best model improves the baseline by 14.34%. [2024-08-16T16:41:51.947Z] Movies recommended for you: [2024-08-16T16:41:51.947Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T16:41:51.947Z] There is no way to check that no silent failure occurred. [2024-08-16T16:41:51.947Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (19660.410 ms) ====== [2024-08-16T16:41:51.947Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-16T16:41:51.947Z] GC before operation: completed in 169.862 ms, heap usage 141.298 MB -> 49.525 MB. [2024-08-16T16:41:54.793Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T16:41:57.652Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T16:42:01.422Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T16:42:04.249Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T16:42:06.356Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T16:42:08.470Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T16:42:10.556Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T16:42:11.888Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T16:42:12.528Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2024-08-16T16:42:12.528Z] The best model improves the baseline by 14.34%. [2024-08-16T16:42:12.528Z] Movies recommended for you: [2024-08-16T16:42:12.528Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T16:42:12.528Z] There is no way to check that no silent failure occurred. [2024-08-16T16:42:12.528Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (20659.446 ms) ====== [2024-08-16T16:42:12.528Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-16T16:42:12.528Z] GC before operation: completed in 153.677 ms, heap usage 194.871 MB -> 49.310 MB. [2024-08-16T16:42:16.306Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T16:42:19.219Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T16:42:23.090Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T16:42:25.246Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T16:42:27.366Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T16:42:29.423Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T16:42:31.498Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T16:42:33.570Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T16:42:33.570Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2024-08-16T16:42:33.570Z] The best model improves the baseline by 14.34%. [2024-08-16T16:42:33.570Z] Movies recommended for you: [2024-08-16T16:42:33.570Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T16:42:33.570Z] There is no way to check that no silent failure occurred. [2024-08-16T16:42:33.570Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (21332.145 ms) ====== [2024-08-16T16:42:33.570Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-16T16:42:34.206Z] GC before operation: completed in 184.936 ms, heap usage 85.488 MB -> 51.681 MB. [2024-08-16T16:42:37.468Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T16:42:41.347Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T16:42:45.310Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T16:42:48.206Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T16:42:51.190Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T16:42:53.256Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T16:42:55.305Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T16:42:57.436Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T16:42:57.436Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2024-08-16T16:42:57.436Z] The best model improves the baseline by 14.34%. [2024-08-16T16:42:58.088Z] Movies recommended for you: [2024-08-16T16:42:58.088Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T16:42:58.088Z] There is no way to check that no silent failure occurred. [2024-08-16T16:42:58.088Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (23803.645 ms) ====== [2024-08-16T16:42:58.088Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-16T16:42:58.088Z] GC before operation: completed in 168.151 ms, heap usage 127.194 MB -> 50.577 MB. [2024-08-16T16:43:01.871Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T16:43:05.656Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T16:43:09.516Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T16:43:12.455Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T16:43:14.545Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T16:43:16.685Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T16:43:18.033Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T16:43:20.166Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T16:43:20.828Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2024-08-16T16:43:20.828Z] The best model improves the baseline by 14.34%. [2024-08-16T16:43:20.828Z] Movies recommended for you: [2024-08-16T16:43:20.828Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T16:43:20.828Z] There is no way to check that no silent failure occurred. [2024-08-16T16:43:20.828Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (22767.614 ms) ====== [2024-08-16T16:43:20.828Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-16T16:43:20.828Z] GC before operation: completed in 227.497 ms, heap usage 321.073 MB -> 49.539 MB. [2024-08-16T16:43:24.110Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T16:43:27.816Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T16:43:30.725Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T16:43:33.614Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T16:43:35.665Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T16:43:36.934Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T16:43:38.208Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T16:43:40.255Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T16:43:40.255Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2024-08-16T16:43:40.255Z] The best model improves the baseline by 14.34%. [2024-08-16T16:43:40.255Z] Movies recommended for you: [2024-08-16T16:43:40.255Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T16:43:40.255Z] There is no way to check that no silent failure occurred. [2024-08-16T16:43:40.255Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (19347.493 ms) ====== [2024-08-16T16:43:40.255Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-16T16:43:40.859Z] GC before operation: completed in 238.122 ms, heap usage 336.061 MB -> 52.902 MB. [2024-08-16T16:43:43.687Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T16:43:47.443Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T16:43:50.355Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T16:43:53.249Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T16:43:54.574Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T16:43:56.598Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T16:43:59.459Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T16:44:00.860Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T16:44:00.860Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2024-08-16T16:44:00.860Z] The best model improves the baseline by 14.34%. [2024-08-16T16:44:01.476Z] Movies recommended for you: [2024-08-16T16:44:01.476Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T16:44:01.476Z] There is no way to check that no silent failure occurred. [2024-08-16T16:44:01.476Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (20665.455 ms) ====== [2024-08-16T16:44:01.476Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-16T16:44:01.476Z] GC before operation: completed in 160.349 ms, heap usage 158.774 MB -> 49.655 MB. [2024-08-16T16:44:04.317Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T16:44:07.337Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T16:44:11.090Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T16:44:13.987Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T16:44:15.320Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T16:44:17.376Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T16:44:19.442Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T16:44:21.493Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T16:44:22.155Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2024-08-16T16:44:22.155Z] The best model improves the baseline by 14.34%. [2024-08-16T16:44:22.155Z] Movies recommended for you: [2024-08-16T16:44:22.155Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T16:44:22.155Z] There is no way to check that no silent failure occurred. [2024-08-16T16:44:22.155Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (20632.261 ms) ====== [2024-08-16T16:44:22.155Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-16T16:44:22.155Z] GC before operation: completed in 173.445 ms, heap usage 149.169 MB -> 49.470 MB. [2024-08-16T16:44:26.009Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T16:44:28.933Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T16:44:32.726Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T16:44:35.225Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T16:44:37.275Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T16:44:38.556Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T16:44:40.626Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T16:44:42.729Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T16:44:42.729Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2024-08-16T16:44:42.729Z] The best model improves the baseline by 14.34%. [2024-08-16T16:44:42.729Z] Movies recommended for you: [2024-08-16T16:44:42.729Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T16:44:42.729Z] There is no way to check that no silent failure occurred. [2024-08-16T16:44:42.729Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (20563.945 ms) ====== [2024-08-16T16:44:42.729Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-16T16:44:42.729Z] GC before operation: completed in 134.587 ms, heap usage 242.905 MB -> 49.621 MB. [2024-08-16T16:44:47.656Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T16:44:50.556Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T16:44:54.685Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T16:44:58.528Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T16:45:00.704Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T16:45:02.796Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T16:45:04.886Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T16:45:07.016Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T16:45:07.016Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2024-08-16T16:45:07.016Z] The best model improves the baseline by 14.34%. [2024-08-16T16:45:07.699Z] Movies recommended for you: [2024-08-16T16:45:07.699Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T16:45:07.699Z] There is no way to check that no silent failure occurred. [2024-08-16T16:45:07.699Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (24534.339 ms) ====== [2024-08-16T16:45:07.699Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-16T16:45:07.699Z] GC before operation: completed in 198.978 ms, heap usage 87.296 MB -> 52.926 MB. [2024-08-16T16:45:11.650Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-16T16:45:16.515Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-16T16:45:20.226Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-16T16:45:24.117Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-16T16:45:26.320Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-16T16:45:28.386Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-16T16:45:29.731Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-16T16:45:31.791Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-16T16:45:32.420Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2024-08-16T16:45:32.420Z] The best model improves the baseline by 14.34%. [2024-08-16T16:45:32.420Z] Movies recommended for you: [2024-08-16T16:45:32.420Z] WARNING: This benchmark provides no result that can be validated. [2024-08-16T16:45:32.420Z] There is no way to check that no silent failure occurred. [2024-08-16T16:45:32.420Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (24828.155 ms) ====== [2024-08-16T16:45:33.067Z] ----------------------------------- [2024-08-16T16:45:33.068Z] renaissance-movie-lens_0_PASSED [2024-08-16T16:45:33.068Z] ----------------------------------- [2024-08-16T16:45:33.068Z] [2024-08-16T16:45:33.068Z] TEST TEARDOWN: [2024-08-16T16:45:33.068Z] Nothing to be done for teardown. [2024-08-16T16:45:33.068Z] renaissance-movie-lens_0 Finish Time: Fri Aug 16 12:45:32 2024 Epoch Time (ms): 1723826732705