[2024-08-08T03:39:51.620Z] Running test renaissance-movie-lens_0 ... [2024-08-08T03:39:51.620Z] =============================================== [2024-08-08T03:39:51.620Z] renaissance-movie-lens_0 Start Time: Thu Aug 8 03:39:50 2024 Epoch Time (ms): 1723088390759 [2024-08-08T03:39:51.620Z] variation: NoOptions [2024-08-08T03:39:51.620Z] JVM_OPTIONS: [2024-08-08T03:39:51.620Z] { \ [2024-08-08T03:39:51.620Z] echo ""; echo "TEST SETUP:"; \ [2024-08-08T03:39:51.620Z] echo "Nothing to be done for setup."; \ [2024-08-08T03:39:51.620Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17230789718667/renaissance-movie-lens_0"; \ [2024-08-08T03:39:51.620Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17230789718667/renaissance-movie-lens_0"; \ [2024-08-08T03:39:51.620Z] echo ""; echo "TESTING:"; \ [2024-08-08T03:39:51.620Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-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_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17230789718667/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-08-08T03:39:51.620Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17230789718667/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-08T03:39:51.620Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-08T03:39:51.620Z] echo "Nothing to be done for teardown."; \ [2024-08-08T03:39:51.620Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17230789718667/TestTargetResult"; [2024-08-08T03:39:51.620Z] [2024-08-08T03:39:51.620Z] TEST SETUP: [2024-08-08T03:39:51.620Z] Nothing to be done for setup. [2024-08-08T03:39:51.620Z] [2024-08-08T03:39:51.620Z] TESTING: [2024-08-08T03:39:53.769Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-08T03:39:54.864Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-08-08T03:39:57.764Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-08T03:39:58.072Z] Training: 60056, validation: 20285, test: 19854 [2024-08-08T03:39:58.072Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-08T03:39:58.072Z] GC before operation: completed in 38.929 ms, heap usage 103.103 MB -> 37.081 MB. [2024-08-08T03:40:25.475Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T03:40:41.040Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T03:41:03.826Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T03:41:19.428Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T03:41:29.995Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T03:41:38.654Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T03:41:49.264Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T03:41:57.971Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T03:41:57.971Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-08T03:41:57.971Z] The best model improves the baseline by 14.52%. [2024-08-08T03:41:57.971Z] Movies recommended for you: [2024-08-08T03:41:57.971Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T03:41:57.971Z] There is no way to check that no silent failure occurred. [2024-08-08T03:41:57.971Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (119546.727 ms) ====== [2024-08-08T03:41:57.971Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-08T03:41:57.971Z] GC before operation: completed in 61.966 ms, heap usage 138.106 MB -> 72.083 MB. [2024-08-08T03:42:16.810Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T03:42:35.632Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T03:42:58.415Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T03:43:11.264Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T03:43:21.877Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T03:43:28.933Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T03:43:41.797Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T03:43:48.913Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T03:43:48.913Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-08T03:43:48.913Z] The best model improves the baseline by 14.52%. [2024-08-08T03:43:48.913Z] Movies recommended for you: [2024-08-08T03:43:48.913Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T03:43:48.913Z] There is no way to check that no silent failure occurred. [2024-08-08T03:43:48.913Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (111004.856 ms) ====== [2024-08-08T03:43:48.913Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-08T03:43:48.913Z] GC before operation: completed in 59.261 ms, heap usage 360.945 MB -> 77.515 MB. [2024-08-08T03:44:07.771Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T03:44:26.607Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T03:44:49.392Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T03:45:02.293Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T03:45:11.027Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T03:45:19.692Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T03:45:32.549Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T03:45:39.661Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T03:45:39.661Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-08T03:45:39.661Z] The best model improves the baseline by 14.52%. [2024-08-08T03:45:39.661Z] Movies recommended for you: [2024-08-08T03:45:39.661Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T03:45:39.661Z] There is no way to check that no silent failure occurred. [2024-08-08T03:45:39.661Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (110254.591 ms) ====== [2024-08-08T03:45:39.661Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-08T03:45:39.661Z] GC before operation: completed in 62.300 ms, heap usage 349.002 MB -> 77.844 MB. [2024-08-08T03:45:58.476Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T03:46:17.298Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T03:46:36.216Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T03:46:51.793Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T03:47:02.364Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T03:47:09.428Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T03:47:22.282Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T03:47:29.431Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T03:47:29.431Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-08T03:47:29.431Z] The best model improves the baseline by 14.52%. [2024-08-08T03:47:29.431Z] Movies recommended for you: [2024-08-08T03:47:29.431Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T03:47:29.431Z] There is no way to check that no silent failure occurred. [2024-08-08T03:47:29.431Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (109646.126 ms) ====== [2024-08-08T03:47:29.431Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-08T03:47:29.431Z] GC before operation: completed in 65.749 ms, heap usage 420.685 MB -> 78.220 MB. [2024-08-08T03:47:48.284Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T03:48:07.110Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T03:48:25.973Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T03:48:41.637Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T03:48:50.330Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T03:48:59.005Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T03:49:09.598Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T03:49:18.347Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T03:49:18.347Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-08T03:49:18.347Z] The best model improves the baseline by 14.52%. [2024-08-08T03:49:18.347Z] Movies recommended for you: [2024-08-08T03:49:18.347Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T03:49:18.347Z] There is no way to check that no silent failure occurred. [2024-08-08T03:49:18.347Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (109383.219 ms) ====== [2024-08-08T03:49:18.347Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-08T03:49:18.347Z] GC before operation: completed in 60.651 ms, heap usage 261.931 MB -> 78.300 MB. [2024-08-08T03:49:37.299Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T03:49:56.140Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T03:50:18.918Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T03:50:31.875Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T03:50:40.580Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T03:50:47.710Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T03:51:00.620Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T03:51:07.805Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T03:51:07.805Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-08T03:51:07.805Z] The best model improves the baseline by 14.52%. [2024-08-08T03:51:07.805Z] Movies recommended for you: [2024-08-08T03:51:07.805Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T03:51:07.805Z] There is no way to check that no silent failure occurred. [2024-08-08T03:51:07.805Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (108948.709 ms) ====== [2024-08-08T03:51:07.805Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-08T03:51:07.805Z] GC before operation: completed in 61.910 ms, heap usage 196.861 MB -> 78.203 MB. [2024-08-08T03:51:26.662Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T03:51:42.262Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T03:52:04.998Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T03:52:17.891Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T03:52:28.483Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T03:52:35.541Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T03:52:48.408Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T03:52:54.126Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T03:52:54.435Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-08T03:52:54.435Z] The best model improves the baseline by 14.52%. [2024-08-08T03:52:54.834Z] Movies recommended for you: [2024-08-08T03:52:54.834Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T03:52:54.834Z] There is no way to check that no silent failure occurred. [2024-08-08T03:52:54.834Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (107342.942 ms) ====== [2024-08-08T03:52:54.834Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-08T03:52:54.834Z] GC before operation: completed in 58.672 ms, heap usage 401.336 MB -> 78.600 MB. [2024-08-08T03:53:13.695Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T03:53:32.524Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T03:53:51.368Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T03:54:07.042Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T03:54:15.722Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T03:54:24.405Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T03:54:34.982Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T03:54:43.733Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T03:54:43.733Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-08T03:54:43.733Z] The best model improves the baseline by 14.52%. [2024-08-08T03:54:43.733Z] Movies recommended for you: [2024-08-08T03:54:43.733Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T03:54:43.733Z] There is no way to check that no silent failure occurred. [2024-08-08T03:54:43.733Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (107908.175 ms) ====== [2024-08-08T03:54:43.733Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-08T03:54:43.733Z] GC before operation: completed in 59.267 ms, heap usage 321.322 MB -> 78.832 MB. [2024-08-08T03:55:02.567Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T03:55:18.139Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T03:55:40.868Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T03:55:53.745Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T03:56:04.315Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T03:56:11.366Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T03:56:24.214Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T03:56:29.926Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T03:56:30.233Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-08T03:56:30.233Z] The best model improves the baseline by 14.52%. [2024-08-08T03:56:30.233Z] Movies recommended for you: [2024-08-08T03:56:30.233Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T03:56:30.233Z] There is no way to check that no silent failure occurred. [2024-08-08T03:56:30.233Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (107680.448 ms) ====== [2024-08-08T03:56:30.233Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-08T03:56:30.593Z] GC before operation: completed in 62.398 ms, heap usage 335.647 MB -> 78.643 MB. [2024-08-08T03:56:49.455Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T03:57:08.279Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T03:57:27.101Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T03:57:42.802Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T03:57:51.508Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T03:58:00.204Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T03:58:10.786Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T03:58:17.845Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T03:58:18.152Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-08T03:58:18.152Z] The best model improves the baseline by 14.52%. [2024-08-08T03:58:18.152Z] Movies recommended for you: [2024-08-08T03:58:18.152Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T03:58:18.152Z] There is no way to check that no silent failure occurred. [2024-08-08T03:58:18.152Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (107874.718 ms) ====== [2024-08-08T03:58:18.152Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-08T03:58:18.460Z] GC before operation: completed in 65.061 ms, heap usage 351.644 MB -> 78.726 MB. [2024-08-08T03:58:37.349Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T03:58:56.209Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T03:59:15.090Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T03:59:30.768Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T03:59:39.447Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T03:59:48.126Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T03:59:58.710Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:00:07.383Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:00:07.383Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-08T04:00:07.383Z] The best model improves the baseline by 14.52%. [2024-08-08T04:00:07.383Z] Movies recommended for you: [2024-08-08T04:00:07.383Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:00:07.383Z] There is no way to check that no silent failure occurred. [2024-08-08T04:00:07.383Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (108142.717 ms) ====== [2024-08-08T04:00:07.383Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-08T04:00:07.383Z] GC before operation: completed in 62.362 ms, heap usage 224.988 MB -> 78.273 MB. [2024-08-08T04:00:26.296Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:00:41.881Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:01:04.601Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:01:20.265Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:01:27.313Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:01:35.983Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:01:46.560Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:01:55.216Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:01:55.216Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-08T04:01:55.216Z] The best model improves the baseline by 14.52%. [2024-08-08T04:01:55.216Z] Movies recommended for you: [2024-08-08T04:01:55.216Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:01:55.216Z] There is no way to check that no silent failure occurred. [2024-08-08T04:01:55.216Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (107777.447 ms) ====== [2024-08-08T04:01:55.216Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-08T04:01:55.216Z] GC before operation: completed in 64.423 ms, heap usage 238.307 MB -> 78.627 MB. [2024-08-08T04:02:14.118Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:02:29.693Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:02:52.425Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:03:08.094Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:03:15.162Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:03:23.816Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:03:36.661Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:03:42.391Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:03:42.698Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-08T04:03:42.698Z] The best model improves the baseline by 14.52%. [2024-08-08T04:03:42.698Z] Movies recommended for you: [2024-08-08T04:03:42.698Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:03:42.698Z] There is no way to check that no silent failure occurred. [2024-08-08T04:03:42.698Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (108401.669 ms) ====== [2024-08-08T04:03:42.698Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-08T04:03:43.004Z] GC before operation: completed in 73.647 ms, heap usage 347.437 MB -> 76.599 MB. [2024-08-08T04:04:01.906Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:04:20.740Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:04:43.456Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:04:56.539Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:05:05.198Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:05:13.895Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:05:24.453Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:05:31.541Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:05:31.848Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-08T04:05:31.848Z] The best model improves the baseline by 14.52%. [2024-08-08T04:05:31.848Z] Movies recommended for you: [2024-08-08T04:05:31.848Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:05:31.848Z] There is no way to check that no silent failure occurred. [2024-08-08T04:05:31.848Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (109044.840 ms) ====== [2024-08-08T04:05:31.848Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-08T04:05:31.848Z] GC before operation: completed in 65.605 ms, heap usage 473.478 MB -> 76.250 MB. [2024-08-08T04:05:50.930Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:06:09.747Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:06:28.540Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:06:44.163Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:06:52.890Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:07:01.619Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:07:12.174Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:07:20.813Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:07:20.813Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-08T04:07:20.813Z] The best model improves the baseline by 14.52%. [2024-08-08T04:07:20.813Z] Movies recommended for you: [2024-08-08T04:07:20.813Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:07:20.813Z] There is no way to check that no silent failure occurred. [2024-08-08T04:07:20.813Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (108241.168 ms) ====== [2024-08-08T04:07:20.813Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-08T04:07:20.813Z] GC before operation: completed in 63.585 ms, heap usage 343.025 MB -> 75.843 MB. [2024-08-08T04:07:39.712Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:07:58.550Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:08:17.365Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:08:32.957Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:08:41.692Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:08:48.745Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:09:01.591Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:09:07.312Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:09:07.619Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-08T04:09:07.619Z] The best model improves the baseline by 14.52%. [2024-08-08T04:09:07.927Z] Movies recommended for you: [2024-08-08T04:09:07.927Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:09:07.927Z] There is no way to check that no silent failure occurred. [2024-08-08T04:09:07.927Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (107536.312 ms) ====== [2024-08-08T04:09:07.927Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-08T04:09:07.927Z] GC before operation: completed in 61.371 ms, heap usage 458.105 MB -> 75.901 MB. [2024-08-08T04:09:26.807Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:09:45.622Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:10:04.428Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:10:20.099Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:10:30.663Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:10:37.708Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:10:48.264Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:10:56.950Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:10:56.950Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-08T04:10:56.950Z] The best model improves the baseline by 14.52%. [2024-08-08T04:10:56.950Z] Movies recommended for you: [2024-08-08T04:10:56.950Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:10:56.950Z] There is no way to check that no silent failure occurred. [2024-08-08T04:10:56.950Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (108581.558 ms) ====== [2024-08-08T04:10:56.950Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-08T04:10:56.950Z] GC before operation: completed in 57.030 ms, heap usage 409.626 MB -> 69.340 MB. [2024-08-08T04:11:16.029Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:11:31.605Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:11:54.295Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:12:09.918Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:12:18.581Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:12:25.629Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:12:36.215Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:12:44.899Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:12:44.899Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-08T04:12:44.899Z] The best model improves the baseline by 14.52%. [2024-08-08T04:12:44.899Z] Movies recommended for you: [2024-08-08T04:12:44.899Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:12:44.899Z] There is no way to check that no silent failure occurred. [2024-08-08T04:12:44.899Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (107908.634 ms) ====== [2024-08-08T04:12:44.899Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-08T04:12:44.899Z] GC before operation: completed in 59.863 ms, heap usage 341.945 MB -> 76.371 MB. [2024-08-08T04:13:03.846Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:13:22.658Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:13:41.478Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:13:57.086Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:14:05.741Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:14:14.415Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:14:25.026Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:14:32.068Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:14:32.380Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-08T04:14:32.380Z] The best model improves the baseline by 14.52%. [2024-08-08T04:14:32.380Z] Movies recommended for you: [2024-08-08T04:14:32.380Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:14:32.380Z] There is no way to check that no silent failure occurred. [2024-08-08T04:14:32.380Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (107884.714 ms) ====== [2024-08-08T04:14:32.380Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-08T04:14:32.380Z] GC before operation: completed in 61.334 ms, heap usage 272.056 MB -> 76.681 MB. [2024-08-08T04:14:51.207Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:15:10.027Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:15:28.851Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:15:44.656Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:15:53.328Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:16:00.385Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:16:13.224Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:16:20.266Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:16:20.266Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-08T04:16:20.266Z] The best model improves the baseline by 14.52%. [2024-08-08T04:16:20.266Z] Movies recommended for you: [2024-08-08T04:16:20.267Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:16:20.267Z] There is no way to check that no silent failure occurred. [2024-08-08T04:16:20.267Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (107517.822 ms) ====== [2024-08-08T04:16:20.572Z] ----------------------------------- [2024-08-08T04:16:20.572Z] renaissance-movie-lens_0_PASSED [2024-08-08T04:16:20.572Z] ----------------------------------- [2024-08-08T04:16:20.572Z] [2024-08-08T04:16:20.572Z] TEST TEARDOWN: [2024-08-08T04:16:20.572Z] Nothing to be done for teardown. [2024-08-08T04:16:20.572Z] renaissance-movie-lens_0 Finish Time: Thu Aug 8 04:16:20 2024 Epoch Time (ms): 1723090580348