[2024-08-22T08:09:27.380Z] Running test renaissance-movie-lens_0 ... [2024-08-22T08:09:27.380Z] =============================================== [2024-08-22T08:09:27.380Z] renaissance-movie-lens_0 Start Time: Thu Aug 22 08:09:27 2024 Epoch Time (ms): 1724314167112 [2024-08-22T08:09:27.380Z] variation: NoOptions [2024-08-22T08:09:27.380Z] JVM_OPTIONS: [2024-08-22T08:09:27.380Z] { \ [2024-08-22T08:09:27.380Z] echo ""; echo "TEST SETUP:"; \ [2024-08-22T08:09:27.380Z] echo "Nothing to be done for setup."; \ [2024-08-22T08:09:27.380Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17243131408626/renaissance-movie-lens_0"; \ [2024-08-22T08:09:27.380Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17243131408626/renaissance-movie-lens_0"; \ [2024-08-22T08:09:27.380Z] echo ""; echo "TESTING:"; \ [2024-08-22T08:09:27.381Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/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_x86-64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17243131408626/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-08-22T08:09:27.381Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17243131408626/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-22T08:09:27.381Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-22T08:09:27.381Z] echo "Nothing to be done for teardown."; \ [2024-08-22T08:09:27.381Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17243131408626/TestTargetResult"; [2024-08-22T08:09:27.381Z] [2024-08-22T08:09:27.381Z] TEST SETUP: [2024-08-22T08:09:27.381Z] Nothing to be done for setup. [2024-08-22T08:09:27.381Z] [2024-08-22T08:09:27.381Z] TESTING: [2024-08-22T08:09:31.806Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-22T08:09:36.224Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-08-22T08:09:43.021Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-22T08:09:43.021Z] Training: 60056, validation: 20285, test: 19854 [2024-08-22T08:09:43.021Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-22T08:09:43.021Z] GC before operation: completed in 129.413 ms, heap usage 68.137 MB -> 36.421 MB. [2024-08-22T08:09:56.692Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:10:03.512Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:10:10.329Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:10:15.872Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:10:19.296Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:10:23.710Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:10:26.167Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:10:29.528Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:10:30.286Z] 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. [2024-08-22T08:10:30.286Z] The best model improves the baseline by 14.52%. [2024-08-22T08:10:30.286Z] Movies recommended for you: [2024-08-22T08:10:30.286Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:10:30.286Z] There is no way to check that no silent failure occurred. [2024-08-22T08:10:30.286Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (47432.513 ms) ====== [2024-08-22T08:10:30.286Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-22T08:10:31.043Z] GC before operation: completed in 189.643 ms, heap usage 161.206 MB -> 49.013 MB. [2024-08-22T08:10:36.577Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:10:42.092Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:10:46.506Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:10:52.084Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:10:54.506Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:10:57.879Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:11:01.248Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:11:03.844Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:11:03.844Z] 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. [2024-08-22T08:11:03.844Z] The best model improves the baseline by 14.52%. [2024-08-22T08:11:04.599Z] Movies recommended for you: [2024-08-22T08:11:04.599Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:11:04.599Z] There is no way to check that no silent failure occurred. [2024-08-22T08:11:04.599Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (33574.104 ms) ====== [2024-08-22T08:11:04.599Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-22T08:11:04.599Z] GC before operation: completed in 160.246 ms, heap usage 94.422 MB -> 48.968 MB. [2024-08-22T08:11:10.128Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:11:14.541Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:11:20.076Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:11:23.470Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:11:26.866Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:11:30.250Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:11:32.682Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:11:36.083Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:11:36.083Z] 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. [2024-08-22T08:11:36.083Z] The best model improves the baseline by 14.52%. [2024-08-22T08:11:36.846Z] Movies recommended for you: [2024-08-22T08:11:36.846Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:11:36.846Z] There is no way to check that no silent failure occurred. [2024-08-22T08:11:36.846Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (31955.349 ms) ====== [2024-08-22T08:11:36.846Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-22T08:11:36.846Z] GC before operation: completed in 190.345 ms, heap usage 153.118 MB -> 49.272 MB. [2024-08-22T08:11:40.203Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:11:43.570Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:11:47.966Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:11:52.387Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:11:54.821Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:11:57.255Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:12:00.193Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:12:01.821Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:12:01.822Z] 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. [2024-08-22T08:12:01.822Z] The best model improves the baseline by 14.52%. [2024-08-22T08:12:01.822Z] Movies recommended for you: [2024-08-22T08:12:01.822Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:12:01.822Z] There is no way to check that no silent failure occurred. [2024-08-22T08:12:01.822Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (25461.558 ms) ====== [2024-08-22T08:12:01.822Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-22T08:12:02.576Z] GC before operation: completed in 79.331 ms, heap usage 317.989 MB -> 49.790 MB. [2024-08-22T08:12:04.999Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:12:08.380Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:12:13.129Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:12:16.783Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:12:19.415Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:12:21.136Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:12:23.928Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:12:25.624Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:12:26.456Z] 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. [2024-08-22T08:12:26.456Z] The best model improves the baseline by 14.52%. [2024-08-22T08:12:26.456Z] Movies recommended for you: [2024-08-22T08:12:26.456Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:12:26.456Z] There is no way to check that no silent failure occurred. [2024-08-22T08:12:26.456Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (24065.442 ms) ====== [2024-08-22T08:12:26.456Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-22T08:12:26.456Z] GC before operation: completed in 138.730 ms, heap usage 192.714 MB -> 49.824 MB. [2024-08-22T08:12:30.099Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:12:33.754Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:12:37.408Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:12:41.060Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:12:43.733Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:12:47.394Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:12:50.077Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:12:52.745Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:12:53.574Z] 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. [2024-08-22T08:12:53.574Z] The best model improves the baseline by 14.52%. [2024-08-22T08:12:53.574Z] Movies recommended for you: [2024-08-22T08:12:53.574Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:12:53.574Z] There is no way to check that no silent failure occurred. [2024-08-22T08:12:53.574Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (27220.408 ms) ====== [2024-08-22T08:12:53.574Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-22T08:12:53.574Z] GC before operation: completed in 226.530 ms, heap usage 104.744 MB -> 49.700 MB. [2024-08-22T08:12:58.906Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:13:03.681Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:13:08.447Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:13:13.200Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:13:15.848Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:13:18.486Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:13:21.133Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:13:23.801Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:13:23.801Z] 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. [2024-08-22T08:13:23.801Z] The best model improves the baseline by 14.52%. [2024-08-22T08:13:23.801Z] Movies recommended for you: [2024-08-22T08:13:23.801Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:13:23.801Z] There is no way to check that no silent failure occurred. [2024-08-22T08:13:23.801Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (30160.564 ms) ====== [2024-08-22T08:13:23.801Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-22T08:13:24.626Z] GC before operation: completed in 244.376 ms, heap usage 244.932 MB -> 50.056 MB. [2024-08-22T08:13:29.402Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:13:34.150Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:13:38.928Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:13:43.697Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:13:46.346Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:13:48.984Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:13:52.671Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:13:55.318Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:13:55.318Z] 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. [2024-08-22T08:13:55.318Z] The best model improves the baseline by 14.52%. [2024-08-22T08:13:55.318Z] Movies recommended for you: [2024-08-22T08:13:55.318Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:13:55.318Z] There is no way to check that no silent failure occurred. [2024-08-22T08:13:55.318Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (31357.214 ms) ====== [2024-08-22T08:13:55.318Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-22T08:13:56.711Z] GC before operation: completed in 172.743 ms, heap usage 205.247 MB -> 50.173 MB. [2024-08-22T08:14:01.472Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:14:05.131Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:14:09.888Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:14:14.630Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:14:17.266Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:14:20.045Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:14:23.710Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:14:26.340Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:14:26.340Z] 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. [2024-08-22T08:14:26.340Z] The best model improves the baseline by 14.52%. [2024-08-22T08:14:27.162Z] Movies recommended for you: [2024-08-22T08:14:27.162Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:14:27.162Z] There is no way to check that no silent failure occurred. [2024-08-22T08:14:27.162Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (31026.307 ms) ====== [2024-08-22T08:14:27.162Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-22T08:14:27.162Z] GC before operation: completed in 193.676 ms, heap usage 90.190 MB -> 50.003 MB. [2024-08-22T08:14:31.909Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:14:36.646Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:14:40.301Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:14:45.073Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:14:46.788Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:14:48.485Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:14:50.181Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:14:51.886Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:14:51.886Z] 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. [2024-08-22T08:14:51.886Z] The best model improves the baseline by 14.52%. [2024-08-22T08:14:52.712Z] Movies recommended for you: [2024-08-22T08:14:52.712Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:14:52.712Z] There is no way to check that no silent failure occurred. [2024-08-22T08:14:52.712Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (25241.085 ms) ====== [2024-08-22T08:14:52.712Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-22T08:14:52.712Z] GC before operation: completed in 104.826 ms, heap usage 68.610 MB -> 50.003 MB. [2024-08-22T08:14:55.930Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:14:58.582Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:15:03.322Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:15:06.968Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:15:09.614Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:15:12.281Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:15:14.929Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:15:17.587Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:15:18.418Z] 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. [2024-08-22T08:15:18.418Z] The best model improves the baseline by 14.52%. [2024-08-22T08:15:18.418Z] Movies recommended for you: [2024-08-22T08:15:18.418Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:15:18.418Z] There is no way to check that no silent failure occurred. [2024-08-22T08:15:18.418Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (26066.908 ms) ====== [2024-08-22T08:15:18.418Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-22T08:15:18.418Z] GC before operation: completed in 185.706 ms, heap usage 63.677 MB -> 49.712 MB. [2024-08-22T08:15:24.364Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:15:28.064Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:15:32.800Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:15:37.577Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:15:41.215Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:15:43.868Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:15:46.505Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:15:49.150Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:15:49.973Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-22T08:15:49.973Z] The best model improves the baseline by 14.52%. [2024-08-22T08:15:49.973Z] Movies recommended for you: [2024-08-22T08:15:49.973Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:15:49.973Z] There is no way to check that no silent failure occurred. [2024-08-22T08:15:49.973Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (31509.664 ms) ====== [2024-08-22T08:15:49.973Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-22T08:15:50.847Z] GC before operation: completed in 206.322 ms, heap usage 224.345 MB -> 50.051 MB. [2024-08-22T08:15:55.207Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:16:00.138Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:16:05.093Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:16:10.058Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:16:12.827Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:16:15.595Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:16:18.360Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:16:21.126Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:16:21.995Z] 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. [2024-08-22T08:16:21.995Z] The best model improves the baseline by 14.52%. [2024-08-22T08:16:21.995Z] Movies recommended for you: [2024-08-22T08:16:21.995Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:16:21.995Z] There is no way to check that no silent failure occurred. [2024-08-22T08:16:21.995Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (31607.623 ms) ====== [2024-08-22T08:16:21.995Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-22T08:16:21.995Z] GC before operation: completed in 174.567 ms, heap usage 62.278 MB -> 50.071 MB. [2024-08-22T08:16:26.953Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:16:30.765Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:16:35.718Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:16:38.476Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:16:40.253Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:16:43.027Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:16:44.809Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:16:47.562Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:16:47.562Z] 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. [2024-08-22T08:16:47.562Z] The best model improves the baseline by 14.52%. [2024-08-22T08:16:47.562Z] Movies recommended for you: [2024-08-22T08:16:47.562Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:16:47.563Z] There is no way to check that no silent failure occurred. [2024-08-22T08:16:47.563Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (25317.516 ms) ====== [2024-08-22T08:16:47.563Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-22T08:16:47.563Z] GC before operation: completed in 136.947 ms, heap usage 129.222 MB -> 49.875 MB. [2024-08-22T08:16:51.479Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:16:54.229Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:16:57.666Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:17:00.434Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:17:02.206Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:17:03.980Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:17:05.752Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:17:07.524Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:17:07.524Z] 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. [2024-08-22T08:17:07.525Z] The best model improves the baseline by 14.52%. [2024-08-22T08:17:07.525Z] Movies recommended for you: [2024-08-22T08:17:07.525Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:17:07.525Z] There is no way to check that no silent failure occurred. [2024-08-22T08:17:07.525Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (19693.597 ms) ====== [2024-08-22T08:17:07.525Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-22T08:17:07.525Z] GC before operation: completed in 81.770 ms, heap usage 200.885 MB -> 50.131 MB. [2024-08-22T08:17:10.281Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:17:14.087Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:17:19.027Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:17:23.968Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:17:25.900Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:17:28.662Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:17:30.444Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:17:33.203Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:17:33.203Z] 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. [2024-08-22T08:17:33.203Z] The best model improves the baseline by 14.52%. [2024-08-22T08:17:33.203Z] Movies recommended for you: [2024-08-22T08:17:33.203Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:17:33.203Z] There is no way to check that no silent failure occurred. [2024-08-22T08:17:33.203Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (26086.713 ms) ====== [2024-08-22T08:17:33.203Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-22T08:17:34.061Z] GC before operation: completed in 194.710 ms, heap usage 96.828 MB -> 50.155 MB. [2024-08-22T08:17:36.815Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:17:40.623Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:17:43.372Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:17:47.193Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:17:48.993Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:17:50.885Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:17:53.664Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:17:55.801Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:17:55.801Z] 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. [2024-08-22T08:17:55.801Z] The best model improves the baseline by 14.52%. [2024-08-22T08:17:56.664Z] Movies recommended for you: [2024-08-22T08:17:56.664Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:17:56.664Z] There is no way to check that no silent failure occurred. [2024-08-22T08:17:56.664Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (22622.374 ms) ====== [2024-08-22T08:17:56.664Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-22T08:17:56.664Z] GC before operation: completed in 141.159 ms, heap usage 113.857 MB -> 49.960 MB. [2024-08-22T08:18:00.475Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:18:05.424Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:18:10.364Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:18:14.169Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:18:15.959Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:18:18.720Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:18:20.519Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:18:23.288Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:18:23.288Z] 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. [2024-08-22T08:18:23.288Z] The best model improves the baseline by 14.52%. [2024-08-22T08:18:23.288Z] Movies recommended for you: [2024-08-22T08:18:23.288Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:18:23.288Z] There is no way to check that no silent failure occurred. [2024-08-22T08:18:23.288Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (27184.965 ms) ====== [2024-08-22T08:18:23.288Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-22T08:18:24.148Z] GC before operation: completed in 133.943 ms, heap usage 141.195 MB -> 50.071 MB. [2024-08-22T08:18:27.968Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:18:30.743Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:18:35.690Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:18:39.500Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:18:42.254Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:18:44.070Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:18:47.920Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:18:50.733Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:18:50.733Z] 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. [2024-08-22T08:18:50.733Z] The best model improves the baseline by 14.52%. [2024-08-22T08:18:50.733Z] Movies recommended for you: [2024-08-22T08:18:50.733Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:18:50.733Z] There is no way to check that no silent failure occurred. [2024-08-22T08:18:50.733Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (27112.914 ms) ====== [2024-08-22T08:18:50.733Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-22T08:18:50.733Z] GC before operation: completed in 208.542 ms, heap usage 78.542 MB -> 50.152 MB. [2024-08-22T08:18:56.291Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:19:00.083Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:19:05.024Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:19:08.836Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:19:10.610Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:19:13.379Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:19:16.154Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:19:17.934Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:19:17.935Z] 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. [2024-08-22T08:19:17.935Z] The best model improves the baseline by 14.52%. [2024-08-22T08:19:18.801Z] Movies recommended for you: [2024-08-22T08:19:18.801Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:19:18.801Z] There is no way to check that no silent failure occurred. [2024-08-22T08:19:18.801Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (27360.678 ms) ====== [2024-08-22T08:19:18.801Z] ----------------------------------- [2024-08-22T08:19:18.801Z] renaissance-movie-lens_0_PASSED [2024-08-22T08:19:18.801Z] ----------------------------------- [2024-08-22T08:19:18.801Z] [2024-08-22T08:19:18.801Z] TEST TEARDOWN: [2024-08-22T08:19:18.801Z] Nothing to be done for teardown. [2024-08-22T08:19:18.801Z] renaissance-movie-lens_0 Finish Time: Thu Aug 22 08:19:18 2024 Epoch Time (ms): 1724314758470