renaissance-movie-lens_0
[2024-11-13T23:54:20.037Z] Running test renaissance-movie-lens_0 ...
[2024-11-13T23:54:20.037Z] ===============================================
[2024-11-13T23:54:20.037Z] renaissance-movie-lens_0 Start Time: Wed Nov 13 23:54:18 2024 Epoch Time (ms): 1731542058844
[2024-11-13T23:54:20.037Z] variation: NoOptions
[2024-11-13T23:54:20.037Z] JVM_OPTIONS:
[2024-11-13T23:54:20.037Z] { \
[2024-11-13T23:54:20.037Z] echo ""; echo "TEST SETUP:"; \
[2024-11-13T23:54:20.037Z] echo "Nothing to be done for setup."; \
[2024-11-13T23:54:20.037Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17315408864566/renaissance-movie-lens_0"; \
[2024-11-13T23:54:20.037Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17315408864566/renaissance-movie-lens_0"; \
[2024-11-13T23:54:20.037Z] echo ""; echo "TESTING:"; \
[2024-11-13T23:54:20.037Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_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_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17315408864566/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-13T23:54:20.037Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17315408864566/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-13T23:54:20.037Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-13T23:54:20.037Z] echo "Nothing to be done for teardown."; \
[2024-11-13T23:54:20.037Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17315408864566/TestTargetResult";
[2024-11-13T23:54:20.037Z]
[2024-11-13T23:54:20.037Z] TEST SETUP:
[2024-11-13T23:54:20.037Z] Nothing to be done for setup.
[2024-11-13T23:54:20.037Z]
[2024-11-13T23:54:20.037Z] TESTING:
[2024-11-13T23:54:23.237Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-13T23:54:26.436Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-11-13T23:54:31.587Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-13T23:54:31.587Z] Training: 60056, validation: 20285, test: 19854
[2024-11-13T23:54:31.587Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-13T23:54:31.587Z] GC before operation: completed in 72.681 ms, heap usage 82.223 MB -> 36.420 MB.
[2024-11-13T23:54:41.148Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T23:54:47.547Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T23:54:50.877Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T23:54:55.003Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T23:54:57.607Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T23:55:00.112Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T23:55:01.959Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T23:55:04.476Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T23:55:04.476Z] 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.
[2024-11-13T23:55:04.476Z] The best model improves the baseline by 14.52%.
[2024-11-13T23:55:04.857Z] Movies recommended for you:
[2024-11-13T23:55:04.857Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T23:55:04.857Z] There is no way to check that no silent failure occurred.
[2024-11-13T23:55:04.857Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (33281.410 ms) ======
[2024-11-13T23:55:04.857Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-13T23:55:04.857Z] GC before operation: completed in 107.912 ms, heap usage 239.458 MB -> 49.954 MB.
[2024-11-13T23:55:08.988Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T23:55:13.230Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T23:55:16.597Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T23:55:19.817Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T23:55:22.366Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T23:55:24.285Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T23:55:26.169Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T23:55:28.707Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T23:55:28.707Z] 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.
[2024-11-13T23:55:28.707Z] The best model improves the baseline by 14.52%.
[2024-11-13T23:55:29.097Z] Movies recommended for you:
[2024-11-13T23:55:29.097Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T23:55:29.098Z] There is no way to check that no silent failure occurred.
[2024-11-13T23:55:29.098Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (23985.962 ms) ======
[2024-11-13T23:55:29.098Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-13T23:55:29.098Z] GC before operation: completed in 101.870 ms, heap usage 74.165 MB -> 49.078 MB.
[2024-11-13T23:55:33.220Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T23:55:36.507Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T23:55:39.767Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T23:55:42.247Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T23:55:44.758Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T23:55:46.678Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T23:55:48.567Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T23:55:50.407Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T23:55:50.775Z] 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.
[2024-11-13T23:55:50.775Z] The best model improves the baseline by 14.52%.
[2024-11-13T23:55:50.775Z] Movies recommended for you:
[2024-11-13T23:55:50.775Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T23:55:50.775Z] There is no way to check that no silent failure occurred.
[2024-11-13T23:55:50.775Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (21734.392 ms) ======
[2024-11-13T23:55:50.775Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-13T23:55:50.775Z] GC before operation: completed in 103.819 ms, heap usage 180.785 MB -> 49.327 MB.
[2024-11-13T23:55:54.909Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T23:55:57.551Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T23:56:00.776Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T23:56:04.031Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T23:56:06.534Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T23:56:08.398Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T23:56:10.238Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T23:56:12.090Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T23:56:12.090Z] 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.
[2024-11-13T23:56:12.090Z] The best model improves the baseline by 14.52%.
[2024-11-13T23:56:12.467Z] Movies recommended for you:
[2024-11-13T23:56:12.467Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T23:56:12.467Z] There is no way to check that no silent failure occurred.
[2024-11-13T23:56:12.467Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (21465.834 ms) ======
[2024-11-13T23:56:12.467Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-13T23:56:12.467Z] GC before operation: completed in 91.927 ms, heap usage 151.053 MB -> 49.617 MB.
[2024-11-13T23:56:15.707Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T23:56:18.951Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T23:56:22.184Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T23:56:25.588Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T23:56:27.477Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T23:56:29.324Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T23:56:31.160Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T23:56:33.676Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T23:56:33.676Z] 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.
[2024-11-13T23:56:33.676Z] The best model improves the baseline by 14.52%.
[2024-11-13T23:56:33.676Z] Movies recommended for you:
[2024-11-13T23:56:33.676Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T23:56:33.676Z] There is no way to check that no silent failure occurred.
[2024-11-13T23:56:33.676Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (21329.966 ms) ======
[2024-11-13T23:56:33.676Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-13T23:56:34.044Z] GC before operation: completed in 93.747 ms, heap usage 142.668 MB -> 49.808 MB.
[2024-11-13T23:56:37.276Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T23:56:40.486Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T23:56:42.991Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T23:56:46.245Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T23:56:48.091Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T23:56:49.415Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T23:56:51.284Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T23:56:53.940Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T23:56:53.940Z] 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.
[2024-11-13T23:56:53.940Z] The best model improves the baseline by 14.52%.
[2024-11-13T23:56:53.940Z] Movies recommended for you:
[2024-11-13T23:56:53.940Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T23:56:53.940Z] There is no way to check that no silent failure occurred.
[2024-11-13T23:56:53.940Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (20140.899 ms) ======
[2024-11-13T23:56:53.940Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-13T23:56:54.308Z] GC before operation: completed in 118.450 ms, heap usage 185.961 MB -> 49.794 MB.
[2024-11-13T23:56:57.557Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T23:57:00.047Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T23:57:03.293Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T23:57:06.572Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T23:57:08.387Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T23:57:10.257Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T23:57:12.105Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T23:57:13.397Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T23:57:13.794Z] 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.
[2024-11-13T23:57:13.794Z] The best model improves the baseline by 14.52%.
[2024-11-13T23:57:14.165Z] Movies recommended for you:
[2024-11-13T23:57:14.165Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T23:57:14.165Z] There is no way to check that no silent failure occurred.
[2024-11-13T23:57:14.165Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (19831.045 ms) ======
[2024-11-13T23:57:14.165Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-13T23:57:14.165Z] GC before operation: completed in 93.871 ms, heap usage 269.122 MB -> 50.029 MB.
[2024-11-13T23:57:17.375Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T23:57:19.897Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T23:57:23.255Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T23:57:25.762Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T23:57:27.607Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T23:57:29.448Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T23:57:31.305Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T23:57:33.177Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T23:57:33.177Z] 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.
[2024-11-13T23:57:33.177Z] The best model improves the baseline by 14.52%.
[2024-11-13T23:57:33.555Z] Movies recommended for you:
[2024-11-13T23:57:33.555Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T23:57:33.555Z] There is no way to check that no silent failure occurred.
[2024-11-13T23:57:33.555Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (19362.312 ms) ======
[2024-11-13T23:57:33.555Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-13T23:57:33.555Z] GC before operation: completed in 90.022 ms, heap usage 120.996 MB -> 50.142 MB.
[2024-11-13T23:57:36.786Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T23:57:39.975Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T23:57:42.470Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T23:57:45.100Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T23:57:46.940Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T23:57:48.804Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T23:57:50.783Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T23:57:52.663Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T23:57:52.663Z] 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.
[2024-11-13T23:57:52.663Z] The best model improves the baseline by 14.52%.
[2024-11-13T23:57:53.031Z] Movies recommended for you:
[2024-11-13T23:57:53.031Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T23:57:53.031Z] There is no way to check that no silent failure occurred.
[2024-11-13T23:57:53.031Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (19431.068 ms) ======
[2024-11-13T23:57:53.031Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-13T23:57:53.031Z] GC before operation: completed in 93.467 ms, heap usage 192.067 MB -> 50.059 MB.
[2024-11-13T23:57:56.245Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T23:57:59.529Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T23:58:02.027Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T23:58:05.264Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T23:58:06.543Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T23:58:08.417Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T23:58:10.276Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T23:58:12.096Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T23:58:12.096Z] 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.
[2024-11-13T23:58:12.463Z] The best model improves the baseline by 14.52%.
[2024-11-13T23:58:12.463Z] Movies recommended for you:
[2024-11-13T23:58:12.463Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T23:58:12.463Z] There is no way to check that no silent failure occurred.
[2024-11-13T23:58:12.463Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (19407.637 ms) ======
[2024-11-13T23:58:12.463Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-13T23:58:12.463Z] GC before operation: completed in 92.931 ms, heap usage 182.999 MB -> 50.156 MB.
[2024-11-13T23:58:15.715Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T23:58:18.307Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T23:58:21.591Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T23:58:24.076Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T23:58:25.920Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T23:58:27.771Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T23:58:29.625Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T23:58:31.576Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T23:58:31.965Z] 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.
[2024-11-13T23:58:31.965Z] The best model improves the baseline by 14.52%.
[2024-11-13T23:58:31.965Z] Movies recommended for you:
[2024-11-13T23:58:31.966Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T23:58:31.966Z] There is no way to check that no silent failure occurred.
[2024-11-13T23:58:31.966Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (19478.157 ms) ======
[2024-11-13T23:58:31.966Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-13T23:58:31.966Z] GC before operation: completed in 95.076 ms, heap usage 124.557 MB -> 49.812 MB.
[2024-11-13T23:58:35.185Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T23:58:37.675Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T23:58:40.926Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T23:58:43.427Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T23:58:45.285Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T23:58:47.127Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T23:58:48.987Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T23:58:50.837Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T23:58:50.837Z] 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.
[2024-11-13T23:58:50.837Z] The best model improves the baseline by 14.52%.
[2024-11-13T23:58:51.231Z] Movies recommended for you:
[2024-11-13T23:58:51.231Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T23:58:51.231Z] There is no way to check that no silent failure occurred.
[2024-11-13T23:58:51.231Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (18911.317 ms) ======
[2024-11-13T23:58:51.231Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-13T23:58:51.231Z] GC before operation: completed in 93.492 ms, heap usage 124.581 MB -> 49.976 MB.
[2024-11-13T23:58:54.474Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T23:58:56.954Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T23:59:00.191Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T23:59:02.672Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T23:59:04.546Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T23:59:06.391Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T23:59:08.249Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T23:59:10.768Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T23:59:10.768Z] 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.
[2024-11-13T23:59:10.768Z] The best model improves the baseline by 14.52%.
[2024-11-13T23:59:11.145Z] Movies recommended for you:
[2024-11-13T23:59:11.145Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T23:59:11.145Z] There is no way to check that no silent failure occurred.
[2024-11-13T23:59:11.145Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (19835.259 ms) ======
[2024-11-13T23:59:11.145Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-13T23:59:11.145Z] GC before operation: completed in 93.776 ms, heap usage 175.965 MB -> 50.223 MB.
[2024-11-13T23:59:14.410Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T23:59:16.907Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T23:59:20.146Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T23:59:23.390Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T23:59:24.696Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T23:59:26.570Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T23:59:28.412Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T23:59:30.267Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T23:59:30.268Z] 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.
[2024-11-13T23:59:30.641Z] The best model improves the baseline by 14.52%.
[2024-11-13T23:59:30.641Z] Movies recommended for you:
[2024-11-13T23:59:30.641Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T23:59:30.641Z] There is no way to check that no silent failure occurred.
[2024-11-13T23:59:30.641Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (19515.966 ms) ======
[2024-11-13T23:59:30.641Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-13T23:59:30.641Z] GC before operation: completed in 92.448 ms, heap usage 194.573 MB -> 49.981 MB.
[2024-11-13T23:59:33.925Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T23:59:37.153Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T23:59:40.424Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-13T23:59:42.943Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-13T23:59:44.284Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-13T23:59:46.256Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-13T23:59:48.125Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-13T23:59:50.008Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-13T23:59:50.009Z] 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.
[2024-11-13T23:59:50.009Z] The best model improves the baseline by 14.52%.
[2024-11-13T23:59:50.395Z] Movies recommended for you:
[2024-11-13T23:59:50.395Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-13T23:59:50.395Z] There is no way to check that no silent failure occurred.
[2024-11-13T23:59:50.395Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (19576.034 ms) ======
[2024-11-13T23:59:50.395Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-13T23:59:50.395Z] GC before operation: completed in 92.235 ms, heap usage 199.658 MB -> 50.157 MB.
[2024-11-13T23:59:53.631Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-13T23:59:56.126Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-13T23:59:59.368Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T00:00:01.876Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T00:00:03.734Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T00:00:05.575Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T00:00:08.054Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T00:00:09.887Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T00:00:09.887Z] 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.
[2024-11-14T00:00:09.887Z] The best model improves the baseline by 14.52%.
[2024-11-14T00:00:10.260Z] Movies recommended for you:
[2024-11-14T00:00:10.260Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T00:00:10.260Z] There is no way to check that no silent failure occurred.
[2024-11-14T00:00:10.260Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (19763.218 ms) ======
[2024-11-14T00:00:10.260Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-14T00:00:10.260Z] GC before operation: completed in 97.884 ms, heap usage 201.220 MB -> 50.230 MB.
[2024-11-14T00:00:13.596Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T00:00:16.083Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T00:00:19.331Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T00:00:21.867Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T00:00:23.776Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T00:00:25.625Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T00:00:27.509Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T00:00:29.366Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T00:00:29.366Z] 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.
[2024-11-14T00:00:29.366Z] The best model improves the baseline by 14.52%.
[2024-11-14T00:00:29.366Z] Movies recommended for you:
[2024-11-14T00:00:29.366Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T00:00:29.366Z] There is no way to check that no silent failure occurred.
[2024-11-14T00:00:29.366Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (19295.822 ms) ======
[2024-11-14T00:00:29.366Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-14T00:00:29.737Z] GC before operation: completed in 107.717 ms, heap usage 134.681 MB -> 49.994 MB.
[2024-11-14T00:00:33.007Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T00:00:36.256Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T00:00:38.743Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T00:00:41.333Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T00:00:43.213Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T00:00:45.037Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T00:00:46.890Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T00:00:48.748Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T00:00:48.748Z] 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.
[2024-11-14T00:00:48.748Z] The best model improves the baseline by 14.52%.
[2024-11-14T00:00:49.137Z] Movies recommended for you:
[2024-11-14T00:00:49.137Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T00:00:49.137Z] There is no way to check that no silent failure occurred.
[2024-11-14T00:00:49.137Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (19374.645 ms) ======
[2024-11-14T00:00:49.137Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-14T00:00:49.137Z] GC before operation: completed in 93.455 ms, heap usage 131.902 MB -> 50.055 MB.
[2024-11-14T00:00:52.392Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T00:00:55.626Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T00:00:58.131Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T00:01:00.626Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T00:01:02.486Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T00:01:04.350Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T00:01:06.227Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T00:01:08.078Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T00:01:08.462Z] 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.
[2024-11-14T00:01:08.462Z] The best model improves the baseline by 14.52%.
[2024-11-14T00:01:08.462Z] Movies recommended for you:
[2024-11-14T00:01:08.462Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T00:01:08.462Z] There is no way to check that no silent failure occurred.
[2024-11-14T00:01:08.462Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (19454.673 ms) ======
[2024-11-14T00:01:08.462Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-14T00:01:08.462Z] GC before operation: completed in 95.044 ms, heap usage 139.380 MB -> 50.239 MB.
[2024-11-14T00:01:11.855Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T00:01:14.353Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T00:01:17.643Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T00:01:20.103Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T00:01:21.973Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T00:01:23.852Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T00:01:25.690Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T00:01:27.538Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T00:01:27.908Z] 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.
[2024-11-14T00:01:27.908Z] The best model improves the baseline by 14.52%.
[2024-11-14T00:01:27.908Z] Movies recommended for you:
[2024-11-14T00:01:27.908Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T00:01:27.908Z] There is no way to check that no silent failure occurred.
[2024-11-14T00:01:27.908Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (19321.887 ms) ======
[2024-11-14T00:01:28.706Z] -----------------------------------
[2024-11-14T00:01:28.706Z] renaissance-movie-lens_0_PASSED
[2024-11-14T00:01:28.706Z] -----------------------------------
[2024-11-14T00:01:28.706Z]
[2024-11-14T00:01:28.706Z] TEST TEARDOWN:
[2024-11-14T00:01:28.706Z] Nothing to be done for teardown.
[2024-11-14T00:01:28.706Z] renaissance-movie-lens_0 Finish Time: Thu Nov 14 00:01:28 2024 Epoch Time (ms): 1731542488472