renaissance-movie-lens_0
[2024-07-31T20:44:04.183Z] Running test renaissance-movie-lens_0 ...
[2024-07-31T20:44:04.183Z] ===============================================
[2024-07-31T20:44:04.183Z] renaissance-movie-lens_0 Start Time: Wed Jul 31 20:44:03 2024 Epoch Time (ms): 1722458643800
[2024-07-31T20:44:04.183Z] variation: NoOptions
[2024-07-31T20:44:04.183Z] JVM_OPTIONS:
[2024-07-31T20:44:04.183Z] { \
[2024-07-31T20:44:04.183Z] echo ""; echo "TEST SETUP:"; \
[2024-07-31T20:44:04.183Z] echo "Nothing to be done for setup."; \
[2024-07-31T20:44:04.183Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17224577659937/renaissance-movie-lens_0"; \
[2024-07-31T20:44:04.183Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17224577659937/renaissance-movie-lens_0"; \
[2024-07-31T20:44:04.183Z] echo ""; echo "TESTING:"; \
[2024-07-31T20:44:04.183Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17224577659937/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-07-31T20:44:04.183Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17224577659937/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-07-31T20:44:04.183Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-07-31T20:44:04.183Z] echo "Nothing to be done for teardown."; \
[2024-07-31T20:44:04.183Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17224577659937/TestTargetResult";
[2024-07-31T20:44:04.183Z]
[2024-07-31T20:44:04.183Z] TEST SETUP:
[2024-07-31T20:44:04.183Z] Nothing to be done for setup.
[2024-07-31T20:44:04.183Z]
[2024-07-31T20:44:04.183Z] TESTING:
[2024-07-31T20:44:07.095Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-07-31T20:44:08.979Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-07-31T20:44:11.892Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-07-31T20:44:11.892Z] Training: 60056, validation: 20285, test: 19854
[2024-07-31T20:44:11.892Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-07-31T20:44:11.892Z] GC before operation: completed in 55.861 ms, heap usage 112.334 MB -> 37.322 MB.
[2024-07-31T20:44:17.109Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T20:44:20.028Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T20:44:22.949Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T20:44:25.871Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T20:44:26.794Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T20:44:28.847Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T20:44:30.747Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T20:44:31.666Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T20:44:32.586Z] 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.
[2024-07-31T20:44:32.586Z] The best model improves the baseline by 14.52%.
[2024-07-31T20:44:32.586Z] Movies recommended for you:
[2024-07-31T20:44:32.586Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T20:44:32.586Z] There is no way to check that no silent failure occurred.
[2024-07-31T20:44:32.586Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (20324.593 ms) ======
[2024-07-31T20:44:32.586Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-07-31T20:44:32.586Z] GC before operation: completed in 82.862 ms, heap usage 139.750 MB -> 55.871 MB.
[2024-07-31T20:44:35.518Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T20:44:37.403Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T20:44:40.319Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T20:44:42.224Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T20:44:43.145Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T20:44:45.033Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T20:44:46.918Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T20:44:47.836Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T20:44:47.836Z] 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.
[2024-07-31T20:44:47.836Z] The best model improves the baseline by 14.52%.
[2024-07-31T20:44:47.836Z] Movies recommended for you:
[2024-07-31T20:44:47.836Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T20:44:47.836Z] There is no way to check that no silent failure occurred.
[2024-07-31T20:44:47.836Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (15648.104 ms) ======
[2024-07-31T20:44:47.836Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-07-31T20:44:47.836Z] GC before operation: completed in 72.203 ms, heap usage 236.444 MB -> 49.717 MB.
[2024-07-31T20:44:50.750Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T20:44:52.637Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T20:44:55.226Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T20:44:57.142Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T20:44:58.060Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T20:44:59.948Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T20:45:00.866Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T20:45:02.760Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T20:45:02.760Z] 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.
[2024-07-31T20:45:02.760Z] The best model improves the baseline by 14.52%.
[2024-07-31T20:45:02.760Z] Movies recommended for you:
[2024-07-31T20:45:02.760Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T20:45:02.760Z] There is no way to check that no silent failure occurred.
[2024-07-31T20:45:02.761Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (14558.522 ms) ======
[2024-07-31T20:45:02.761Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-07-31T20:45:02.761Z] GC before operation: completed in 66.910 ms, heap usage 291.234 MB -> 50.053 MB.
[2024-07-31T20:45:04.678Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T20:45:07.605Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T20:45:09.492Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T20:45:11.379Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T20:45:13.265Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T20:45:14.183Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T20:45:15.103Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T20:45:16.993Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T20:45:16.993Z] 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.
[2024-07-31T20:45:16.993Z] The best model improves the baseline by 14.52%.
[2024-07-31T20:45:16.993Z] Movies recommended for you:
[2024-07-31T20:45:16.993Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T20:45:16.993Z] There is no way to check that no silent failure occurred.
[2024-07-31T20:45:16.993Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (14127.808 ms) ======
[2024-07-31T20:45:16.993Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-07-31T20:45:16.993Z] GC before operation: completed in 68.789 ms, heap usage 219.521 MB -> 50.363 MB.
[2024-07-31T20:45:18.881Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T20:45:21.800Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T20:45:23.694Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T20:45:25.582Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T20:45:27.471Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T20:45:28.393Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T20:45:29.343Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T20:45:31.230Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T20:45:31.230Z] 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.
[2024-07-31T20:45:31.230Z] The best model improves the baseline by 14.52%.
[2024-07-31T20:45:31.230Z] Movies recommended for you:
[2024-07-31T20:45:31.230Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T20:45:31.230Z] There is no way to check that no silent failure occurred.
[2024-07-31T20:45:31.230Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (14444.760 ms) ======
[2024-07-31T20:45:31.230Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-07-31T20:45:31.230Z] GC before operation: completed in 71.189 ms, heap usage 116.574 MB -> 50.442 MB.
[2024-07-31T20:45:33.117Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T20:45:35.003Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T20:45:37.926Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T20:45:39.816Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T20:45:40.735Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T20:45:41.658Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T20:45:43.545Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T20:45:44.464Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T20:45:44.464Z] 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.
[2024-07-31T20:45:44.464Z] The best model improves the baseline by 14.52%.
[2024-07-31T20:45:44.464Z] Movies recommended for you:
[2024-07-31T20:45:44.464Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T20:45:44.464Z] There is no way to check that no silent failure occurred.
[2024-07-31T20:45:44.464Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (13342.430 ms) ======
[2024-07-31T20:45:44.464Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-07-31T20:45:45.382Z] GC before operation: completed in 84.775 ms, heap usage 87.156 MB -> 50.373 MB.
[2024-07-31T20:45:47.270Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T20:45:49.165Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T20:45:51.728Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T20:45:52.647Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T20:45:54.531Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T20:45:55.449Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T20:45:56.369Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T20:45:58.254Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T20:45:58.254Z] 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.
[2024-07-31T20:45:58.254Z] The best model improves the baseline by 14.52%.
[2024-07-31T20:45:58.254Z] Movies recommended for you:
[2024-07-31T20:45:58.254Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T20:45:58.254Z] There is no way to check that no silent failure occurred.
[2024-07-31T20:45:58.254Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (13144.003 ms) ======
[2024-07-31T20:45:58.254Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-07-31T20:45:58.254Z] GC before operation: completed in 93.756 ms, heap usage 116.567 MB -> 50.669 MB.
[2024-07-31T20:46:00.341Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T20:46:02.229Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T20:46:04.114Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T20:46:06.003Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T20:46:06.920Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T20:46:08.805Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T20:46:09.729Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T20:46:10.732Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T20:46:10.732Z] 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.
[2024-07-31T20:46:10.732Z] The best model improves the baseline by 14.52%.
[2024-07-31T20:46:11.754Z] Movies recommended for you:
[2024-07-31T20:46:11.754Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T20:46:11.754Z] There is no way to check that no silent failure occurred.
[2024-07-31T20:46:11.754Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (13019.139 ms) ======
[2024-07-31T20:46:11.754Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-07-31T20:46:11.754Z] GC before operation: completed in 88.875 ms, heap usage 86.902 MB -> 50.804 MB.
[2024-07-31T20:46:13.660Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T20:46:15.552Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T20:46:17.448Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T20:46:19.342Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T20:46:20.261Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T20:46:21.180Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T20:46:23.068Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T20:46:23.986Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T20:46:23.986Z] 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.
[2024-07-31T20:46:23.986Z] The best model improves the baseline by 14.52%.
[2024-07-31T20:46:23.986Z] Movies recommended for you:
[2024-07-31T20:46:23.986Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T20:46:23.986Z] There is no way to check that no silent failure occurred.
[2024-07-31T20:46:23.986Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (12941.547 ms) ======
[2024-07-31T20:46:23.986Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-07-31T20:46:23.986Z] GC before operation: completed in 67.602 ms, heap usage 124.934 MB -> 50.783 MB.
[2024-07-31T20:46:25.880Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T20:46:27.766Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T20:46:30.684Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T20:46:32.571Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T20:46:33.491Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T20:46:34.412Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T20:46:35.330Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T20:46:37.322Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T20:46:37.322Z] 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.
[2024-07-31T20:46:37.322Z] The best model improves the baseline by 14.52%.
[2024-07-31T20:46:37.322Z] Movies recommended for you:
[2024-07-31T20:46:37.322Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T20:46:37.322Z] There is no way to check that no silent failure occurred.
[2024-07-31T20:46:37.322Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (12869.637 ms) ======
[2024-07-31T20:46:37.322Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-07-31T20:46:37.322Z] GC before operation: completed in 82.180 ms, heap usage 62.023 MB -> 54.356 MB.
[2024-07-31T20:46:39.882Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T20:46:40.804Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T20:46:43.720Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T20:46:44.640Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T20:46:46.524Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T20:46:47.441Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T20:46:48.359Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T20:46:50.245Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T20:46:50.245Z] 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.
[2024-07-31T20:46:50.245Z] The best model improves the baseline by 14.52%.
[2024-07-31T20:46:50.245Z] Movies recommended for you:
[2024-07-31T20:46:50.245Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T20:46:50.245Z] There is no way to check that no silent failure occurred.
[2024-07-31T20:46:50.245Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (12871.858 ms) ======
[2024-07-31T20:46:50.245Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-07-31T20:46:50.245Z] GC before operation: completed in 67.977 ms, heap usage 106.088 MB -> 50.511 MB.
[2024-07-31T20:46:52.131Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T20:46:54.018Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T20:46:55.903Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T20:46:57.788Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T20:46:59.675Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T20:47:00.596Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T20:47:01.516Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T20:47:02.434Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T20:47:03.353Z] 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.
[2024-07-31T20:47:03.353Z] The best model improves the baseline by 14.52%.
[2024-07-31T20:47:03.353Z] Movies recommended for you:
[2024-07-31T20:47:03.353Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T20:47:03.353Z] There is no way to check that no silent failure occurred.
[2024-07-31T20:47:03.353Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (12969.979 ms) ======
[2024-07-31T20:47:03.353Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-07-31T20:47:03.353Z] GC before operation: completed in 69.044 ms, heap usage 86.589 MB -> 50.651 MB.
[2024-07-31T20:47:05.239Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T20:47:07.125Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T20:47:09.016Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T20:47:10.916Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T20:47:12.806Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T20:47:13.729Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T20:47:14.657Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T20:47:16.544Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T20:47:16.544Z] 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.
[2024-07-31T20:47:16.544Z] The best model improves the baseline by 14.52%.
[2024-07-31T20:47:16.544Z] Movies recommended for you:
[2024-07-31T20:47:16.544Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T20:47:16.544Z] There is no way to check that no silent failure occurred.
[2024-07-31T20:47:16.544Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (13315.555 ms) ======
[2024-07-31T20:47:16.544Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-07-31T20:47:16.544Z] GC before operation: completed in 70.575 ms, heap usage 216.535 MB -> 51.078 MB.
[2024-07-31T20:47:18.458Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T20:47:20.347Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T20:47:22.232Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T20:47:24.131Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T20:47:26.017Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T20:47:26.936Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T20:47:27.855Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T20:47:29.800Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T20:47:29.800Z] 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.
[2024-07-31T20:47:29.800Z] The best model improves the baseline by 14.52%.
[2024-07-31T20:47:29.800Z] Movies recommended for you:
[2024-07-31T20:47:29.800Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T20:47:29.800Z] There is no way to check that no silent failure occurred.
[2024-07-31T20:47:29.800Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (13036.834 ms) ======
[2024-07-31T20:47:29.800Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-07-31T20:47:29.800Z] GC before operation: completed in 96.103 ms, heap usage 290.867 MB -> 50.814 MB.
[2024-07-31T20:47:31.699Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T20:47:33.584Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T20:47:35.486Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T20:47:38.083Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T20:47:39.005Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T20:47:39.923Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T20:47:40.842Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T20:47:42.728Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T20:47:42.728Z] 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.
[2024-07-31T20:47:42.728Z] The best model improves the baseline by 14.52%.
[2024-07-31T20:47:42.728Z] Movies recommended for you:
[2024-07-31T20:47:42.728Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T20:47:42.728Z] There is no way to check that no silent failure occurred.
[2024-07-31T20:47:42.728Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (12816.190 ms) ======
[2024-07-31T20:47:42.728Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-07-31T20:47:42.728Z] GC before operation: completed in 90.196 ms, heap usage 104.452 MB -> 50.814 MB.
[2024-07-31T20:47:44.623Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T20:47:46.513Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T20:47:48.397Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T20:47:50.282Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T20:47:51.200Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T20:47:53.089Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T20:47:54.007Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T20:47:54.925Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T20:47:55.843Z] 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.
[2024-07-31T20:47:55.843Z] The best model improves the baseline by 14.52%.
[2024-07-31T20:47:55.843Z] Movies recommended for you:
[2024-07-31T20:47:55.843Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T20:47:55.843Z] There is no way to check that no silent failure occurred.
[2024-07-31T20:47:55.843Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (12910.454 ms) ======
[2024-07-31T20:47:55.843Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-07-31T20:47:55.843Z] GC before operation: completed in 101.435 ms, heap usage 85.602 MB -> 50.910 MB.
[2024-07-31T20:47:57.731Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T20:47:59.617Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T20:48:01.509Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T20:48:03.397Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T20:48:05.285Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T20:48:06.203Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T20:48:07.122Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T20:48:08.039Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T20:48:08.955Z] 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.
[2024-07-31T20:48:08.955Z] The best model improves the baseline by 14.52%.
[2024-07-31T20:48:08.955Z] Movies recommended for you:
[2024-07-31T20:48:08.955Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T20:48:08.955Z] There is no way to check that no silent failure occurred.
[2024-07-31T20:48:08.955Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (12987.357 ms) ======
[2024-07-31T20:48:08.955Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-07-31T20:48:08.955Z] GC before operation: completed in 87.502 ms, heap usage 254.847 MB -> 50.870 MB.
[2024-07-31T20:48:10.840Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T20:48:12.728Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T20:48:14.615Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T20:48:16.507Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T20:48:17.426Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T20:48:19.312Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T20:48:20.235Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T20:48:21.153Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T20:48:21.153Z] 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.
[2024-07-31T20:48:21.153Z] The best model improves the baseline by 14.52%.
[2024-07-31T20:48:21.153Z] Movies recommended for you:
[2024-07-31T20:48:21.153Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T20:48:21.153Z] There is no way to check that no silent failure occurred.
[2024-07-31T20:48:21.153Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (12798.999 ms) ======
[2024-07-31T20:48:21.153Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-07-31T20:48:22.071Z] GC before operation: completed in 78.384 ms, heap usage 86.040 MB -> 50.783 MB.
[2024-07-31T20:48:23.965Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T20:48:25.853Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T20:48:27.740Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T20:48:29.628Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T20:48:30.545Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T20:48:32.137Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T20:48:33.057Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T20:48:33.975Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T20:48:33.975Z] 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.
[2024-07-31T20:48:33.975Z] The best model improves the baseline by 14.52%.
[2024-07-31T20:48:33.975Z] Movies recommended for you:
[2024-07-31T20:48:33.975Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T20:48:33.975Z] There is no way to check that no silent failure occurred.
[2024-07-31T20:48:33.975Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (12661.423 ms) ======
[2024-07-31T20:48:33.975Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-07-31T20:48:33.975Z] GC before operation: completed in 78.765 ms, heap usage 389.366 MB -> 51.271 MB.
[2024-07-31T20:48:35.883Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-07-31T20:48:37.778Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-07-31T20:48:40.697Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-07-31T20:48:41.616Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-07-31T20:48:43.505Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-07-31T20:48:44.423Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-07-31T20:48:45.342Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-07-31T20:48:47.234Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-07-31T20:48:47.234Z] 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.
[2024-07-31T20:48:47.234Z] The best model improves the baseline by 14.52%.
[2024-07-31T20:48:47.234Z] Movies recommended for you:
[2024-07-31T20:48:47.234Z] WARNING: This benchmark provides no result that can be validated.
[2024-07-31T20:48:47.234Z] There is no way to check that no silent failure occurred.
[2024-07-31T20:48:47.234Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (12785.445 ms) ======
[2024-07-31T20:48:48.153Z] -----------------------------------
[2024-07-31T20:48:48.153Z] renaissance-movie-lens_0_PASSED
[2024-07-31T20:48:48.153Z] -----------------------------------
[2024-07-31T20:48:48.153Z]
[2024-07-31T20:48:48.153Z] TEST TEARDOWN:
[2024-07-31T20:48:48.153Z] Nothing to be done for teardown.
[2024-07-31T20:48:48.153Z] renaissance-movie-lens_0 Finish Time: Wed Jul 31 20:48:47 2024 Epoch Time (ms): 1722458927183