renaissance-movie-lens_0
[2024-11-08T16:18:15.462Z] Running test renaissance-movie-lens_0 ...
[2024-11-08T16:18:15.462Z] ===============================================
[2024-11-08T16:18:15.462Z] renaissance-movie-lens_0 Start Time: Fri Nov 8 16:18:14 2024 Epoch Time (ms): 1731082694314
[2024-11-08T16:18:15.462Z] variation: NoOptions
[2024-11-08T16:18:15.462Z] JVM_OPTIONS:
[2024-11-08T16:18:15.462Z] { \
[2024-11-08T16:18:15.462Z] echo ""; echo "TEST SETUP:"; \
[2024-11-08T16:18:15.462Z] echo "Nothing to be done for setup."; \
[2024-11-08T16:18:15.462Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17310819803645/renaissance-movie-lens_0"; \
[2024-11-08T16:18:15.462Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17310819803645/renaissance-movie-lens_0"; \
[2024-11-08T16:18:15.462Z] echo ""; echo "TESTING:"; \
[2024-11-08T16:18:15.462Z] "/home/jenkins/workspace/Test_openjdk17_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_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17310819803645/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-08T16:18:15.462Z] 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/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17310819803645/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-08T16:18:15.462Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-08T16:18:15.462Z] echo "Nothing to be done for teardown."; \
[2024-11-08T16:18:15.462Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17310819803645/TestTargetResult";
[2024-11-08T16:18:15.462Z]
[2024-11-08T16:18:15.462Z] TEST SETUP:
[2024-11-08T16:18:15.462Z] Nothing to be done for setup.
[2024-11-08T16:18:15.462Z]
[2024-11-08T16:18:15.462Z] TESTING:
[2024-11-08T16:18:17.177Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-08T16:18:21.044Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-11-08T16:18:23.676Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-08T16:18:26.084Z] Training: 60056, validation: 20285, test: 19854
[2024-11-08T16:18:26.084Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-08T16:18:26.084Z] GC before operation: completed in 51.877 ms, heap usage 91.983 MB -> 37.087 MB.
[2024-11-08T16:18:31.997Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T16:18:36.726Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T16:18:42.659Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T16:18:45.280Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T16:18:46.968Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T16:18:48.671Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T16:18:51.300Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T16:18:52.996Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T16:18:52.996Z] 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.
[2024-11-08T16:18:52.996Z] The best model improves the baseline by 14.52%.
[2024-11-08T16:18:53.815Z] Movies recommended for you:
[2024-11-08T16:18:53.815Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T16:18:53.815Z] There is no way to check that no silent failure occurred.
[2024-11-08T16:18:53.815Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (29399.799 ms) ======
[2024-11-08T16:18:53.816Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-08T16:18:53.816Z] GC before operation: completed in 120.998 ms, heap usage 322.096 MB -> 54.831 MB.
[2024-11-08T16:18:57.456Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T16:19:01.095Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T16:19:02.781Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T16:19:05.405Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T16:19:06.219Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T16:19:07.905Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T16:19:09.586Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T16:19:11.867Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T16:19:11.867Z] 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.
[2024-11-08T16:19:11.867Z] The best model improves the baseline by 14.52%.
[2024-11-08T16:19:11.867Z] Movies recommended for you:
[2024-11-08T16:19:11.867Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T16:19:11.867Z] There is no way to check that no silent failure occurred.
[2024-11-08T16:19:11.867Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17743.540 ms) ======
[2024-11-08T16:19:11.867Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-08T16:19:11.867Z] GC before operation: completed in 70.649 ms, heap usage 100.917 MB -> 51.789 MB.
[2024-11-08T16:19:13.553Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T16:19:17.183Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T16:19:18.873Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T16:19:23.624Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T16:19:24.440Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T16:19:26.137Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T16:19:26.951Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T16:19:28.651Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T16:19:28.651Z] 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.
[2024-11-08T16:19:28.651Z] The best model improves the baseline by 14.52%.
[2024-11-08T16:19:28.651Z] Movies recommended for you:
[2024-11-08T16:19:28.651Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T16:19:28.651Z] There is no way to check that no silent failure occurred.
[2024-11-08T16:19:28.651Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17070.736 ms) ======
[2024-11-08T16:19:28.651Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-08T16:19:28.651Z] GC before operation: completed in 60.146 ms, heap usage 379.881 MB -> 53.239 MB.
[2024-11-08T16:19:30.342Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T16:19:32.966Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T16:19:34.655Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T16:19:36.344Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T16:19:38.025Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T16:19:38.844Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T16:19:40.533Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T16:19:42.226Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T16:19:42.226Z] 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.
[2024-11-08T16:19:42.226Z] The best model improves the baseline by 14.52%.
[2024-11-08T16:19:42.226Z] Movies recommended for you:
[2024-11-08T16:19:42.226Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T16:19:42.226Z] There is no way to check that no silent failure occurred.
[2024-11-08T16:19:42.226Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (13622.710 ms) ======
[2024-11-08T16:19:42.226Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-08T16:19:42.226Z] GC before operation: completed in 80.617 ms, heap usage 242.043 MB -> 50.294 MB.
[2024-11-08T16:19:45.853Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T16:19:49.492Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T16:19:52.113Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T16:19:55.749Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T16:19:58.366Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T16:20:00.059Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T16:20:01.757Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T16:20:04.392Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T16:20:04.392Z] 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.
[2024-11-08T16:20:04.392Z] The best model improves the baseline by 14.52%.
[2024-11-08T16:20:04.392Z] Movies recommended for you:
[2024-11-08T16:20:04.392Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T16:20:04.392Z] There is no way to check that no silent failure occurred.
[2024-11-08T16:20:04.392Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (22370.243 ms) ======
[2024-11-08T16:20:04.392Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-08T16:20:05.218Z] GC before operation: completed in 116.607 ms, heap usage 244.713 MB -> 50.515 MB.
[2024-11-08T16:20:08.401Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T16:20:12.034Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T16:20:14.677Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T16:20:18.419Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T16:20:20.112Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T16:20:22.742Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T16:20:24.439Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T16:20:26.192Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T16:20:27.009Z] 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.
[2024-11-08T16:20:27.009Z] The best model improves the baseline by 14.52%.
[2024-11-08T16:20:27.009Z] Movies recommended for you:
[2024-11-08T16:20:27.009Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T16:20:27.009Z] There is no way to check that no silent failure occurred.
[2024-11-08T16:20:27.009Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (22225.887 ms) ======
[2024-11-08T16:20:27.009Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-08T16:20:27.009Z] GC before operation: completed in 110.248 ms, heap usage 282.869 MB -> 50.516 MB.
[2024-11-08T16:20:30.642Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T16:20:34.440Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T16:20:37.071Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T16:20:40.719Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T16:20:42.414Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T16:20:44.135Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T16:20:46.785Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T16:20:48.488Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T16:20:48.488Z] 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.
[2024-11-08T16:20:48.488Z] The best model improves the baseline by 14.52%.
[2024-11-08T16:20:49.308Z] Movies recommended for you:
[2024-11-08T16:20:49.308Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T16:20:49.308Z] There is no way to check that no silent failure occurred.
[2024-11-08T16:20:49.308Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (21798.400 ms) ======
[2024-11-08T16:20:49.308Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-08T16:20:49.308Z] GC before operation: completed in 113.274 ms, heap usage 249.584 MB -> 50.658 MB.
[2024-11-08T16:20:51.939Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T16:20:55.580Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T16:20:59.209Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T16:21:02.169Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T16:21:03.863Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T16:21:06.503Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T16:21:08.199Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T16:21:09.898Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T16:21:10.721Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-08T16:21:10.721Z] The best model improves the baseline by 14.52%.
[2024-11-08T16:21:10.721Z] Movies recommended for you:
[2024-11-08T16:21:10.721Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T16:21:10.721Z] There is no way to check that no silent failure occurred.
[2024-11-08T16:21:10.721Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (21486.336 ms) ======
[2024-11-08T16:21:10.721Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-08T16:21:10.721Z] GC before operation: completed in 115.110 ms, heap usage 243.113 MB -> 51.059 MB.
[2024-11-08T16:21:14.354Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T16:21:16.999Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T16:21:20.634Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T16:21:23.400Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T16:21:25.095Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T16:21:27.728Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T16:21:29.424Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T16:21:31.162Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T16:21:31.162Z] 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.
[2024-11-08T16:21:31.162Z] The best model improves the baseline by 14.52%.
[2024-11-08T16:21:31.980Z] Movies recommended for you:
[2024-11-08T16:21:31.980Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T16:21:31.980Z] There is no way to check that no silent failure occurred.
[2024-11-08T16:21:31.980Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (20919.358 ms) ======
[2024-11-08T16:21:31.980Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-08T16:21:31.980Z] GC before operation: completed in 116.556 ms, heap usage 217.361 MB -> 50.844 MB.
[2024-11-08T16:21:34.611Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T16:21:38.250Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T16:21:41.892Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T16:21:44.516Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T16:21:47.155Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T16:21:48.852Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T16:21:50.545Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T16:21:52.233Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T16:21:53.649Z] 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.
[2024-11-08T16:21:53.649Z] The best model improves the baseline by 14.52%.
[2024-11-08T16:21:53.649Z] Movies recommended for you:
[2024-11-08T16:21:53.649Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T16:21:53.649Z] There is no way to check that no silent failure occurred.
[2024-11-08T16:21:53.649Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (21187.029 ms) ======
[2024-11-08T16:21:53.649Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-08T16:21:53.649Z] GC before operation: completed in 119.915 ms, heap usage 199.751 MB -> 50.914 MB.
[2024-11-08T16:21:56.275Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T16:21:59.909Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T16:22:02.534Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T16:22:06.160Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T16:22:07.856Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T16:22:09.633Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T16:22:11.339Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T16:22:13.032Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T16:22:13.853Z] 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.
[2024-11-08T16:22:13.853Z] The best model improves the baseline by 14.52%.
[2024-11-08T16:22:13.853Z] Movies recommended for you:
[2024-11-08T16:22:13.853Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T16:22:13.853Z] There is no way to check that no silent failure occurred.
[2024-11-08T16:22:13.853Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (20812.790 ms) ======
[2024-11-08T16:22:13.853Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-08T16:22:13.853Z] GC before operation: completed in 110.987 ms, heap usage 408.196 MB -> 54.012 MB.
[2024-11-08T16:22:16.628Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T16:22:20.285Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T16:22:23.918Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T16:22:26.567Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T16:22:29.194Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T16:22:30.888Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T16:22:32.581Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T16:22:34.271Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T16:22:35.085Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-08T16:22:35.085Z] The best model improves the baseline by 14.52%.
[2024-11-08T16:22:35.085Z] Movies recommended for you:
[2024-11-08T16:22:35.085Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T16:22:35.085Z] There is no way to check that no silent failure occurred.
[2024-11-08T16:22:35.085Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (21114.644 ms) ======
[2024-11-08T16:22:35.085Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-08T16:22:35.085Z] GC before operation: completed in 105.996 ms, heap usage 270.959 MB -> 50.845 MB.
[2024-11-08T16:22:38.705Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T16:22:41.322Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T16:22:44.939Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T16:22:48.139Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T16:22:49.828Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T16:22:51.516Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T16:22:53.207Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T16:22:55.840Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T16:22:55.840Z] 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.
[2024-11-08T16:22:55.840Z] The best model improves the baseline by 14.52%.
[2024-11-08T16:22:55.840Z] Movies recommended for you:
[2024-11-08T16:22:55.840Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T16:22:55.840Z] There is no way to check that no silent failure occurred.
[2024-11-08T16:22:55.840Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (20656.573 ms) ======
[2024-11-08T16:22:55.840Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-08T16:22:55.840Z] GC before operation: completed in 105.050 ms, heap usage 113.305 MB -> 51.039 MB.
[2024-11-08T16:22:59.467Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T16:23:02.087Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T16:23:05.713Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T16:23:08.340Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T16:23:10.065Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T16:23:11.754Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T16:23:14.383Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T16:23:16.064Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T16:23:16.064Z] 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.
[2024-11-08T16:23:16.064Z] The best model improves the baseline by 14.52%.
[2024-11-08T16:23:16.064Z] Movies recommended for you:
[2024-11-08T16:23:16.064Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T16:23:16.064Z] There is no way to check that no silent failure occurred.
[2024-11-08T16:23:16.064Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (20402.533 ms) ======
[2024-11-08T16:23:16.064Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-08T16:23:16.064Z] GC before operation: completed in 103.517 ms, heap usage 226.336 MB -> 50.778 MB.
[2024-11-08T16:23:19.808Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T16:23:22.434Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T16:23:26.046Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T16:23:29.657Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T16:23:31.339Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T16:23:33.035Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T16:23:34.719Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T16:23:36.977Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T16:23:36.977Z] 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.
[2024-11-08T16:23:36.977Z] The best model improves the baseline by 14.52%.
[2024-11-08T16:23:36.977Z] Movies recommended for you:
[2024-11-08T16:23:36.977Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T16:23:36.977Z] There is no way to check that no silent failure occurred.
[2024-11-08T16:23:36.977Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (20600.252 ms) ======
[2024-11-08T16:23:36.977Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-08T16:23:36.977Z] GC before operation: completed in 119.893 ms, heap usage 395.243 MB -> 54.609 MB.
[2024-11-08T16:23:40.597Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T16:23:43.229Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T16:23:46.835Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T16:23:50.442Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T16:23:52.127Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T16:23:53.816Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T16:23:55.505Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T16:23:57.196Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T16:23:58.016Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-08T16:23:58.016Z] The best model improves the baseline by 14.52%.
[2024-11-08T16:23:58.016Z] Movies recommended for you:
[2024-11-08T16:23:58.016Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T16:23:58.016Z] There is no way to check that no silent failure occurred.
[2024-11-08T16:23:58.016Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (20852.220 ms) ======
[2024-11-08T16:23:58.016Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-08T16:23:58.016Z] GC before operation: completed in 108.537 ms, heap usage 133.463 MB -> 50.993 MB.
[2024-11-08T16:24:01.647Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T16:24:04.271Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T16:24:07.899Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T16:24:10.640Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T16:24:12.317Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T16:24:14.001Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T16:24:16.637Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T16:24:18.328Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T16:24:18.328Z] 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.
[2024-11-08T16:24:18.328Z] The best model improves the baseline by 14.52%.
[2024-11-08T16:24:18.328Z] Movies recommended for you:
[2024-11-08T16:24:18.328Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T16:24:18.328Z] There is no way to check that no silent failure occurred.
[2024-11-08T16:24:18.328Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (20269.968 ms) ======
[2024-11-08T16:24:18.328Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-08T16:24:18.328Z] GC before operation: completed in 125.676 ms, heap usage 395.587 MB -> 54.655 MB.
[2024-11-08T16:24:21.941Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T16:24:24.646Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T16:24:28.264Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T16:24:30.892Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T16:24:33.160Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T16:24:34.860Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T16:24:36.542Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T16:24:38.239Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T16:24:39.055Z] 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.
[2024-11-08T16:24:39.055Z] The best model improves the baseline by 14.52%.
[2024-11-08T16:24:39.055Z] Movies recommended for you:
[2024-11-08T16:24:39.055Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T16:24:39.055Z] There is no way to check that no silent failure occurred.
[2024-11-08T16:24:39.055Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (20440.287 ms) ======
[2024-11-08T16:24:39.055Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-08T16:24:39.055Z] GC before operation: completed in 97.060 ms, heap usage 110.825 MB -> 50.778 MB.
[2024-11-08T16:24:41.668Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T16:24:45.311Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T16:24:47.923Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T16:24:50.524Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T16:24:52.205Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T16:24:53.883Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T16:24:55.557Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T16:24:57.240Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T16:24:57.240Z] 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.
[2024-11-08T16:24:57.240Z] The best model improves the baseline by 14.52%.
[2024-11-08T16:24:57.240Z] Movies recommended for you:
[2024-11-08T16:24:57.240Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T16:24:57.240Z] There is no way to check that no silent failure occurred.
[2024-11-08T16:24:57.240Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (18425.595 ms) ======
[2024-11-08T16:24:57.240Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-08T16:24:57.240Z] GC before operation: completed in 85.338 ms, heap usage 126.186 MB -> 50.959 MB.
[2024-11-08T16:24:59.845Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T16:25:02.449Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T16:25:05.065Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T16:25:07.671Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T16:25:09.354Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T16:25:11.039Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T16:25:12.724Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T16:25:13.542Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T16:25:14.354Z] 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.
[2024-11-08T16:25:14.354Z] The best model improves the baseline by 14.52%.
[2024-11-08T16:25:14.354Z] Movies recommended for you:
[2024-11-08T16:25:14.354Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T16:25:14.354Z] There is no way to check that no silent failure occurred.
[2024-11-08T16:25:14.354Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (16779.013 ms) ======
[2024-11-08T16:25:15.179Z] -----------------------------------
[2024-11-08T16:25:15.179Z] renaissance-movie-lens_0_PASSED
[2024-11-08T16:25:15.179Z] -----------------------------------
[2024-11-08T16:25:15.179Z]
[2024-11-08T16:25:15.179Z] TEST TEARDOWN:
[2024-11-08T16:25:15.179Z] Nothing to be done for teardown.
[2024-11-08T16:25:15.179Z] renaissance-movie-lens_0 Finish Time: Fri Nov 8 16:25:14 2024 Epoch Time (ms): 1731083114475