renaissance-movie-lens_0
[2024-11-13T21:47:07.141Z] Running test renaissance-movie-lens_0 ...
[2024-11-13T21:47:07.141Z] ===============================================
[2024-11-13T21:47:07.141Z] renaissance-movie-lens_0 Start Time: Wed Nov 13 21:47:06 2024 Epoch Time (ms): 1731534426488
[2024-11-13T21:47:07.141Z] variation: NoOptions
[2024-11-13T21:47:07.141Z] JVM_OPTIONS:
[2024-11-13T21:47:07.141Z] { \
[2024-11-13T21:47:07.141Z] echo ""; echo "TEST SETUP:"; \
[2024-11-13T21:47:07.141Z] echo "Nothing to be done for setup."; \
[2024-11-13T21:47:07.141Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17315335725362/renaissance-movie-lens_0"; \
[2024-11-13T21:47:07.141Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17315335725362/renaissance-movie-lens_0"; \
[2024-11-13T21:47:07.141Z] echo ""; echo "TESTING:"; \
[2024-11-13T21:47:07.141Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_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_ppc64le_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17315335725362/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-13T21:47:07.141Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17315335725362/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-13T21:47:07.141Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-13T21:47:07.141Z] echo "Nothing to be done for teardown."; \
[2024-11-13T21:47:07.141Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17315335725362/TestTargetResult";
[2024-11-13T21:47:07.141Z]
[2024-11-13T21:47:07.141Z] TEST SETUP:
[2024-11-13T21:47:07.141Z] Nothing to be done for setup.
[2024-11-13T21:47:07.141Z]
[2024-11-13T21:47:07.141Z] TESTING:
[2024-11-13T21:47:10.107Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-13T21:47:12.026Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-11-13T21:47:14.996Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-13T21:47:14.996Z] Training: 60056, validation: 20285, test: 19854
[2024-11-13T21:47:14.996Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-13T21:47:14.996Z] GC before operation: completed in 56.696 ms, heap usage 130.177 MB -> 37.170 MB.
[2024-11-13T21:47:20.283Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T21:47:23.246Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T21:47:26.216Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T21:47:28.144Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T21:47:29.760Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T21:47:31.681Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T21:47:32.629Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T21:47:34.555Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T21:47:34.555Z] 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.
[2024-11-13T21:47:34.555Z] The best model improves the baseline by 14.52%.
[2024-11-13T21:47:34.555Z] Movies recommended for you:
[2024-11-13T21:47:34.555Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T21:47:34.555Z] There is no way to check that no silent failure occurred.
[2024-11-13T21:47:35.493Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (20113.374 ms) ======
[2024-11-13T21:47:35.493Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-13T21:47:35.493Z] GC before operation: completed in 75.866 ms, heap usage 146.450 MB -> 53.725 MB.
[2024-11-13T21:47:37.412Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T21:47:40.388Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T21:47:42.307Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T21:47:45.279Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T21:47:46.221Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T21:47:47.155Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T21:47:49.074Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T21:47:50.008Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T21:47:50.943Z] 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.
[2024-11-13T21:47:50.943Z] The best model improves the baseline by 14.52%.
[2024-11-13T21:47:50.943Z] Movies recommended for you:
[2024-11-13T21:47:50.943Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T21:47:50.943Z] There is no way to check that no silent failure occurred.
[2024-11-13T21:47:50.943Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (15584.489 ms) ======
[2024-11-13T21:47:50.943Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-13T21:47:50.943Z] GC before operation: completed in 65.641 ms, heap usage 236.801 MB -> 53.164 MB.
[2024-11-13T21:47:52.871Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T21:47:54.803Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T21:47:58.012Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T21:47:59.935Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T21:48:01.721Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T21:48:02.659Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T21:48:03.809Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T21:48:04.745Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T21:48:04.745Z] 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.
[2024-11-13T21:48:04.745Z] The best model improves the baseline by 14.52%.
[2024-11-13T21:48:05.684Z] Movies recommended for you:
[2024-11-13T21:48:05.685Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T21:48:05.685Z] There is no way to check that no silent failure occurred.
[2024-11-13T21:48:05.685Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (14478.083 ms) ======
[2024-11-13T21:48:05.685Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-13T21:48:05.685Z] GC before operation: completed in 63.548 ms, heap usage 323.727 MB -> 50.175 MB.
[2024-11-13T21:48:07.606Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T21:48:09.525Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T21:48:11.445Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T21:48:13.378Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T21:48:15.338Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T21:48:16.284Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T21:48:18.223Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T21:48:19.158Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T21:48:19.158Z] 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.
[2024-11-13T21:48:19.158Z] The best model improves the baseline by 14.52%.
[2024-11-13T21:48:19.158Z] Movies recommended for you:
[2024-11-13T21:48:19.158Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T21:48:19.158Z] There is no way to check that no silent failure occurred.
[2024-11-13T21:48:19.158Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (14083.249 ms) ======
[2024-11-13T21:48:19.158Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-13T21:48:19.158Z] GC before operation: completed in 69.629 ms, heap usage 163.033 MB -> 50.433 MB.
[2024-11-13T21:48:21.098Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T21:48:24.068Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T21:48:26.002Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T21:48:27.933Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T21:48:28.874Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T21:48:30.795Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T21:48:31.736Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T21:48:32.672Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T21:48:33.608Z] 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.
[2024-11-13T21:48:33.608Z] The best model improves the baseline by 14.52%.
[2024-11-13T21:48:33.608Z] Movies recommended for you:
[2024-11-13T21:48:33.608Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T21:48:33.608Z] There is no way to check that no silent failure occurred.
[2024-11-13T21:48:33.609Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (14034.751 ms) ======
[2024-11-13T21:48:33.609Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-13T21:48:33.609Z] GC before operation: completed in 75.811 ms, heap usage 189.009 MB -> 50.586 MB.
[2024-11-13T21:48:35.531Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T21:48:37.450Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T21:48:40.096Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T21:48:41.031Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T21:48:42.952Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T21:48:43.888Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T21:48:44.940Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T21:48:46.865Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T21:48:46.865Z] 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.
[2024-11-13T21:48:46.865Z] The best model improves the baseline by 14.52%.
[2024-11-13T21:48:46.865Z] Movies recommended for you:
[2024-11-13T21:48:46.865Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T21:48:46.865Z] There is no way to check that no silent failure occurred.
[2024-11-13T21:48:46.865Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (13226.744 ms) ======
[2024-11-13T21:48:46.865Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-13T21:48:46.865Z] GC before operation: completed in 84.293 ms, heap usage 127.829 MB -> 50.490 MB.
[2024-11-13T21:48:48.786Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T21:48:50.714Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T21:48:52.641Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T21:48:54.572Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T21:48:55.515Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T21:48:57.435Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T21:48:58.377Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T21:48:59.314Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T21:48:59.314Z] 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.
[2024-11-13T21:49:00.251Z] The best model improves the baseline by 14.52%.
[2024-11-13T21:49:00.251Z] Movies recommended for you:
[2024-11-13T21:49:00.251Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T21:49:00.251Z] There is no way to check that no silent failure occurred.
[2024-11-13T21:49:00.251Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (13036.541 ms) ======
[2024-11-13T21:49:00.251Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-13T21:49:00.251Z] GC before operation: completed in 71.521 ms, heap usage 65.324 MB -> 53.076 MB.
[2024-11-13T21:49:02.175Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T21:49:04.112Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T21:49:06.030Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T21:49:07.950Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T21:49:08.889Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T21:49:10.809Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T21:49:12.431Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T21:49:12.431Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T21:49:13.367Z] 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.
[2024-11-13T21:49:13.367Z] The best model improves the baseline by 14.52%.
[2024-11-13T21:49:13.367Z] Movies recommended for you:
[2024-11-13T21:49:13.367Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T21:49:13.367Z] There is no way to check that no silent failure occurred.
[2024-11-13T21:49:13.367Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (13187.240 ms) ======
[2024-11-13T21:49:13.367Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-13T21:49:13.367Z] GC before operation: completed in 78.872 ms, heap usage 313.634 MB -> 51.124 MB.
[2024-11-13T21:49:15.290Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T21:49:17.212Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T21:49:19.131Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T21:49:21.053Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T21:49:21.988Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T21:49:23.908Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T21:49:24.842Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T21:49:25.778Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T21:49:25.778Z] 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.
[2024-11-13T21:49:25.778Z] The best model improves the baseline by 14.52%.
[2024-11-13T21:49:25.778Z] Movies recommended for you:
[2024-11-13T21:49:25.778Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T21:49:25.778Z] There is no way to check that no silent failure occurred.
[2024-11-13T21:49:25.778Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (12981.485 ms) ======
[2024-11-13T21:49:25.778Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-13T21:49:26.715Z] GC before operation: completed in 67.774 ms, heap usage 422.330 MB -> 54.253 MB.
[2024-11-13T21:49:28.635Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T21:49:30.561Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T21:49:32.480Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T21:49:34.404Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T21:49:35.350Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T21:49:36.286Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T21:49:38.208Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T21:49:39.143Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T21:49:39.143Z] 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.
[2024-11-13T21:49:39.143Z] The best model improves the baseline by 14.52%.
[2024-11-13T21:49:39.143Z] Movies recommended for you:
[2024-11-13T21:49:39.143Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T21:49:39.143Z] There is no way to check that no silent failure occurred.
[2024-11-13T21:49:39.143Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (13097.182 ms) ======
[2024-11-13T21:49:39.143Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-13T21:49:39.143Z] GC before operation: completed in 84.440 ms, heap usage 481.303 MB -> 56.893 MB.
[2024-11-13T21:49:41.063Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T21:49:44.043Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T21:49:46.471Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T21:49:47.413Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T21:49:49.340Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T21:49:50.278Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T21:49:51.212Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T21:49:53.147Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T21:49:53.147Z] 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.
[2024-11-13T21:49:53.147Z] The best model improves the baseline by 14.52%.
[2024-11-13T21:49:53.147Z] Movies recommended for you:
[2024-11-13T21:49:53.147Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T21:49:53.147Z] There is no way to check that no silent failure occurred.
[2024-11-13T21:49:53.147Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (13820.639 ms) ======
[2024-11-13T21:49:53.147Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-13T21:49:53.147Z] GC before operation: completed in 118.768 ms, heap usage 178.918 MB -> 52.819 MB.
[2024-11-13T21:49:56.112Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T21:49:58.033Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T21:49:59.955Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T21:50:01.877Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T21:50:03.810Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T21:50:04.745Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T21:50:06.663Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T21:50:07.596Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T21:50:07.596Z] 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.
[2024-11-13T21:50:07.596Z] The best model improves the baseline by 14.52%.
[2024-11-13T21:50:07.596Z] Movies recommended for you:
[2024-11-13T21:50:07.596Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T21:50:07.596Z] There is no way to check that no silent failure occurred.
[2024-11-13T21:50:07.596Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14626.455 ms) ======
[2024-11-13T21:50:07.596Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-13T21:50:08.534Z] GC before operation: completed in 72.153 ms, heap usage 472.101 MB -> 54.310 MB.
[2024-11-13T21:50:10.464Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T21:50:12.386Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T21:50:14.336Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T21:50:16.266Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T21:50:18.186Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T21:50:19.120Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T21:50:20.054Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T21:50:22.320Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T21:50:22.320Z] 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.
[2024-11-13T21:50:22.320Z] The best model improves the baseline by 14.52%.
[2024-11-13T21:50:22.320Z] Movies recommended for you:
[2024-11-13T21:50:22.320Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T21:50:22.320Z] There is no way to check that no silent failure occurred.
[2024-11-13T21:50:22.320Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (13884.099 ms) ======
[2024-11-13T21:50:22.320Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-13T21:50:22.320Z] GC before operation: completed in 64.236 ms, heap usage 197.785 MB -> 51.050 MB.
[2024-11-13T21:50:23.598Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T21:50:25.516Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T21:50:28.486Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T21:50:29.421Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T21:50:31.342Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T21:50:32.284Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T21:50:33.220Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T21:50:34.155Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T21:50:35.093Z] 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.
[2024-11-13T21:50:35.093Z] The best model improves the baseline by 14.52%.
[2024-11-13T21:50:35.093Z] Movies recommended for you:
[2024-11-13T21:50:35.093Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T21:50:35.093Z] There is no way to check that no silent failure occurred.
[2024-11-13T21:50:35.093Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (12847.356 ms) ======
[2024-11-13T21:50:35.093Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-13T21:50:35.093Z] GC before operation: completed in 66.379 ms, heap usage 290.591 MB -> 50.793 MB.
[2024-11-13T21:50:37.025Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T21:50:38.949Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T21:50:40.867Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T21:50:42.786Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T21:50:44.758Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T21:50:45.692Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T21:50:47.617Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T21:50:48.553Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T21:50:48.553Z] 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.
[2024-11-13T21:50:48.554Z] The best model improves the baseline by 14.52%.
[2024-11-13T21:50:48.554Z] Movies recommended for you:
[2024-11-13T21:50:48.554Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T21:50:48.554Z] There is no way to check that no silent failure occurred.
[2024-11-13T21:50:48.554Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (13745.482 ms) ======
[2024-11-13T21:50:48.554Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-13T21:50:48.554Z] GC before operation: completed in 66.263 ms, heap usage 391.436 MB -> 53.351 MB.
[2024-11-13T21:50:51.531Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T21:50:53.467Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T21:50:56.240Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T21:50:57.175Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T21:50:58.111Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T21:50:59.044Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T21:51:00.966Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T21:51:01.901Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T21:51:02.838Z] 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.
[2024-11-13T21:51:02.838Z] The best model improves the baseline by 14.52%.
[2024-11-13T21:51:02.838Z] Movies recommended for you:
[2024-11-13T21:51:02.838Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T21:51:02.838Z] There is no way to check that no silent failure occurred.
[2024-11-13T21:51:02.838Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (13806.853 ms) ======
[2024-11-13T21:51:02.838Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-13T21:51:02.838Z] GC before operation: completed in 70.786 ms, heap usage 172.385 MB -> 53.243 MB.
[2024-11-13T21:51:04.757Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T21:51:06.680Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T21:51:09.643Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T21:51:11.574Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T21:51:12.511Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T21:51:13.447Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T21:51:15.370Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T21:51:16.308Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T21:51:16.308Z] 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.
[2024-11-13T21:51:16.308Z] The best model improves the baseline by 14.52%.
[2024-11-13T21:51:17.243Z] Movies recommended for you:
[2024-11-13T21:51:17.243Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T21:51:17.243Z] There is no way to check that no silent failure occurred.
[2024-11-13T21:51:17.243Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14156.341 ms) ======
[2024-11-13T21:51:17.243Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-13T21:51:17.243Z] GC before operation: completed in 71.032 ms, heap usage 317.448 MB -> 53.278 MB.
[2024-11-13T21:51:19.166Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T21:51:22.135Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T21:51:24.060Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T21:51:25.981Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T21:51:26.924Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T21:51:27.865Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T21:51:29.784Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T21:51:30.718Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T21:51:30.718Z] 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.
[2024-11-13T21:51:30.718Z] The best model improves the baseline by 14.52%.
[2024-11-13T21:51:31.656Z] Movies recommended for you:
[2024-11-13T21:51:31.656Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T21:51:31.656Z] There is no way to check that no silent failure occurred.
[2024-11-13T21:51:31.656Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14342.102 ms) ======
[2024-11-13T21:51:31.656Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-13T21:51:31.656Z] GC before operation: completed in 109.284 ms, heap usage 85.316 MB -> 53.990 MB.
[2024-11-13T21:51:34.267Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T21:51:36.187Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T21:51:38.108Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T21:51:40.028Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T21:51:41.949Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T21:51:42.883Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T21:51:43.817Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T21:51:45.761Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T21:51:45.761Z] 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.
[2024-11-13T21:51:45.761Z] The best model improves the baseline by 14.52%.
[2024-11-13T21:51:45.761Z] Movies recommended for you:
[2024-11-13T21:51:45.761Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T21:51:45.761Z] There is no way to check that no silent failure occurred.
[2024-11-13T21:51:45.761Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14422.107 ms) ======
[2024-11-13T21:51:45.761Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-13T21:51:45.761Z] GC before operation: completed in 69.655 ms, heap usage 249.224 MB -> 51.155 MB.
[2024-11-13T21:51:47.683Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T21:51:49.605Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T21:51:51.527Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T21:51:53.448Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T21:51:55.371Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T21:51:56.305Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T21:51:57.239Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T21:51:58.176Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T21:51:59.111Z] 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.
[2024-11-13T21:51:59.111Z] The best model improves the baseline by 14.52%.
[2024-11-13T21:51:59.111Z] Movies recommended for you:
[2024-11-13T21:51:59.111Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T21:51:59.111Z] There is no way to check that no silent failure occurred.
[2024-11-13T21:51:59.111Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (13000.253 ms) ======
[2024-11-13T21:51:59.111Z] -----------------------------------
[2024-11-13T21:51:59.111Z] renaissance-movie-lens_0_PASSED
[2024-11-13T21:51:59.111Z] -----------------------------------
[2024-11-13T21:51:59.111Z]
[2024-11-13T21:51:59.111Z] TEST TEARDOWN:
[2024-11-13T21:51:59.111Z] Nothing to be done for teardown.
[2024-11-13T21:51:59.111Z] renaissance-movie-lens_0 Finish Time: Wed Nov 13 21:51:58 2024 Epoch Time (ms): 1731534718864