renaissance-movie-lens_0
[2024-06-27T00:06:18.936Z] Running test renaissance-movie-lens_0 ...
[2024-06-27T00:06:18.936Z] ===============================================
[2024-06-27T00:06:18.936Z] renaissance-movie-lens_0 Start Time: Thu Jun 27 00:06:16 2024 Epoch Time (ms): 1719446776943
[2024-06-27T00:06:18.936Z] variation: NoOptions
[2024-06-27T00:06:18.936Z] JVM_OPTIONS:
[2024-06-27T00:06:18.936Z] { \
[2024-06-27T00:06:18.936Z] echo ""; echo "TEST SETUP:"; \
[2024-06-27T00:06:18.936Z] echo "Nothing to be done for setup."; \
[2024-06-27T00:06:18.936Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17194459234443/renaissance-movie-lens_0"; \
[2024-06-27T00:06:18.936Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17194459234443/renaissance-movie-lens_0"; \
[2024-06-27T00:06:18.936Z] echo ""; echo "TESTING:"; \
[2024-06-27T00:06:18.936Z] "/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_17194459234443/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-06-27T00:06:18.936Z] 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_17194459234443/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-06-27T00:06:18.936Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-06-27T00:06:18.936Z] echo "Nothing to be done for teardown."; \
[2024-06-27T00:06:18.936Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17194459234443/TestTargetResult";
[2024-06-27T00:06:18.936Z]
[2024-06-27T00:06:18.936Z] TEST SETUP:
[2024-06-27T00:06:18.936Z] Nothing to be done for setup.
[2024-06-27T00:06:18.936Z]
[2024-06-27T00:06:18.936Z] TESTING:
[2024-06-27T00:06:20.849Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-06-27T00:06:21.780Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-06-27T00:06:24.747Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-06-27T00:06:24.747Z] Training: 60056, validation: 20285, test: 19854
[2024-06-27T00:06:24.747Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-06-27T00:06:24.747Z] GC before operation: completed in 60.441 ms, heap usage 125.679 MB -> 37.212 MB.
[2024-06-27T00:06:30.185Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-27T00:06:33.144Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-27T00:06:36.099Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-27T00:06:38.018Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-27T00:06:39.937Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-27T00:06:40.868Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-27T00:06:42.784Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-27T00:06:43.715Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-27T00:06:43.715Z] 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.
[2024-06-27T00:06:44.669Z] The best model improves the baseline by 14.52%.
[2024-06-27T00:06:44.669Z] Movies recommended for you:
[2024-06-27T00:06:44.669Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-27T00:06:44.669Z] There is no way to check that no silent failure occurred.
[2024-06-27T00:06:44.669Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (19216.614 ms) ======
[2024-06-27T00:06:44.669Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-06-27T00:06:44.669Z] GC before operation: completed in 69.206 ms, heap usage 252.699 MB -> 51.308 MB.
[2024-06-27T00:06:46.587Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-27T00:06:49.547Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-27T00:06:53.772Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-27T00:06:55.685Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-27T00:06:56.617Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-27T00:06:58.532Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-27T00:06:59.464Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-27T00:07:01.388Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-27T00:07:01.388Z] 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.
[2024-06-27T00:07:01.388Z] The best model improves the baseline by 14.52%.
[2024-06-27T00:07:01.388Z] Movies recommended for you:
[2024-06-27T00:07:01.388Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-27T00:07:01.388Z] There is no way to check that no silent failure occurred.
[2024-06-27T00:07:01.388Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (16938.344 ms) ======
[2024-06-27T00:07:01.388Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-06-27T00:07:01.388Z] GC before operation: completed in 61.365 ms, heap usage 253.290 MB -> 52.077 MB.
[2024-06-27T00:07:03.310Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-27T00:07:07.354Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-27T00:07:08.288Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-27T00:07:10.202Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-27T00:07:11.133Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-27T00:07:13.054Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-27T00:07:13.985Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-27T00:07:14.918Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-27T00:07:15.855Z] 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.
[2024-06-27T00:07:15.855Z] The best model improves the baseline by 14.52%.
[2024-06-27T00:07:15.855Z] Movies recommended for you:
[2024-06-27T00:07:15.855Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-27T00:07:15.855Z] There is no way to check that no silent failure occurred.
[2024-06-27T00:07:15.855Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (14145.510 ms) ======
[2024-06-27T00:07:15.855Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-06-27T00:07:15.855Z] GC before operation: completed in 62.879 ms, heap usage 365.070 MB -> 55.116 MB.
[2024-06-27T00:07:17.771Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-27T00:07:19.686Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-27T00:07:21.600Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-27T00:07:23.519Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-27T00:07:25.434Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-27T00:07:26.368Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-27T00:07:27.302Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-27T00:07:29.218Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-27T00:07:29.218Z] 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.
[2024-06-27T00:07:29.218Z] The best model improves the baseline by 14.52%.
[2024-06-27T00:07:29.218Z] Movies recommended for you:
[2024-06-27T00:07:29.218Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-27T00:07:29.218Z] There is no way to check that no silent failure occurred.
[2024-06-27T00:07:29.218Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (13447.115 ms) ======
[2024-06-27T00:07:29.218Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-06-27T00:07:29.218Z] GC before operation: completed in 61.512 ms, heap usage 335.166 MB -> 52.752 MB.
[2024-06-27T00:07:31.130Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-27T00:07:33.041Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-27T00:07:34.952Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-27T00:07:36.881Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-27T00:07:38.814Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-27T00:07:39.758Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-27T00:07:40.692Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-27T00:07:42.603Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-27T00:07:42.604Z] 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.
[2024-06-27T00:07:42.604Z] The best model improves the baseline by 14.52%.
[2024-06-27T00:07:42.604Z] Movies recommended for you:
[2024-06-27T00:07:42.604Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-27T00:07:42.604Z] There is no way to check that no silent failure occurred.
[2024-06-27T00:07:42.604Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (13329.427 ms) ======
[2024-06-27T00:07:42.604Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-06-27T00:07:42.604Z] GC before operation: completed in 116.849 ms, heap usage 339.132 MB -> 50.765 MB.
[2024-06-27T00:07:44.515Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-27T00:07:46.425Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-27T00:07:48.336Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-27T00:07:50.308Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-27T00:07:51.237Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-27T00:07:53.148Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-27T00:07:54.078Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-27T00:07:55.010Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-27T00:07:55.947Z] 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.
[2024-06-27T00:07:55.947Z] The best model improves the baseline by 14.52%.
[2024-06-27T00:07:55.947Z] Movies recommended for you:
[2024-06-27T00:07:55.947Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-27T00:07:55.947Z] There is no way to check that no silent failure occurred.
[2024-06-27T00:07:55.947Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (13000.680 ms) ======
[2024-06-27T00:07:55.947Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-06-27T00:07:55.947Z] GC before operation: completed in 80.596 ms, heap usage 166.486 MB -> 53.834 MB.
[2024-06-27T00:07:57.864Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-27T00:07:59.779Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-27T00:08:01.691Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-27T00:08:03.614Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-27T00:08:05.721Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-27T00:08:06.652Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-27T00:08:07.583Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-27T00:08:09.493Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-27T00:08:09.493Z] 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.
[2024-06-27T00:08:09.493Z] The best model improves the baseline by 14.52%.
[2024-06-27T00:08:09.493Z] Movies recommended for you:
[2024-06-27T00:08:09.493Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-27T00:08:09.493Z] There is no way to check that no silent failure occurred.
[2024-06-27T00:08:09.493Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (13822.312 ms) ======
[2024-06-27T00:08:09.493Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-06-27T00:08:09.493Z] GC before operation: completed in 63.433 ms, heap usage 151.133 MB -> 54.004 MB.
[2024-06-27T00:08:11.410Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-27T00:08:13.320Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-27T00:08:16.272Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-27T00:08:17.203Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-27T00:08:19.123Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-27T00:08:20.079Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-27T00:08:21.011Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-27T00:08:22.929Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-27T00:08:22.929Z] 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.
[2024-06-27T00:08:22.929Z] The best model improves the baseline by 14.52%.
[2024-06-27T00:08:22.929Z] Movies recommended for you:
[2024-06-27T00:08:22.929Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-27T00:08:22.929Z] There is no way to check that no silent failure occurred.
[2024-06-27T00:08:22.929Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (13196.760 ms) ======
[2024-06-27T00:08:22.929Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-06-27T00:08:22.929Z] GC before operation: completed in 69.800 ms, heap usage 608.670 MB -> 60.164 MB.
[2024-06-27T00:08:24.871Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-27T00:08:26.785Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-27T00:08:28.697Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-27T00:08:30.608Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-27T00:08:31.539Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-27T00:08:32.470Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-27T00:08:34.381Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-27T00:08:35.315Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-27T00:08:35.315Z] 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.
[2024-06-27T00:08:35.315Z] The best model improves the baseline by 14.52%.
[2024-06-27T00:08:35.315Z] Movies recommended for you:
[2024-06-27T00:08:35.315Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-27T00:08:35.315Z] There is no way to check that no silent failure occurred.
[2024-06-27T00:08:35.315Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (12628.374 ms) ======
[2024-06-27T00:08:35.315Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-06-27T00:08:35.315Z] GC before operation: completed in 64.044 ms, heap usage 366.343 MB -> 54.337 MB.
[2024-06-27T00:08:37.229Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-27T00:08:39.141Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-27T00:08:41.051Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-27T00:08:42.968Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-27T00:08:43.897Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-27T00:08:44.828Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-27T00:08:46.764Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-27T00:08:47.694Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-27T00:08:47.694Z] 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.
[2024-06-27T00:08:47.694Z] The best model improves the baseline by 14.52%.
[2024-06-27T00:08:47.694Z] Movies recommended for you:
[2024-06-27T00:08:47.694Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-27T00:08:47.694Z] There is no way to check that no silent failure occurred.
[2024-06-27T00:08:47.694Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (12299.542 ms) ======
[2024-06-27T00:08:47.694Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-06-27T00:08:47.694Z] GC before operation: completed in 75.395 ms, heap usage 276.130 MB -> 51.054 MB.
[2024-06-27T00:08:49.607Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-27T00:08:51.621Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-27T00:08:53.530Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-27T00:08:55.440Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-27T00:08:57.357Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-27T00:08:58.288Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-27T00:08:59.218Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-27T00:09:02.139Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-27T00:09:02.139Z] 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.
[2024-06-27T00:09:02.139Z] The best model improves the baseline by 14.52%.
[2024-06-27T00:09:02.139Z] Movies recommended for you:
[2024-06-27T00:09:02.139Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-27T00:09:02.139Z] There is no way to check that no silent failure occurred.
[2024-06-27T00:09:02.139Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (13155.162 ms) ======
[2024-06-27T00:09:02.139Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-06-27T00:09:02.139Z] GC before operation: completed in 58.708 ms, heap usage 254.507 MB -> 50.748 MB.
[2024-06-27T00:09:03.069Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-27T00:09:04.985Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-27T00:09:06.897Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-27T00:09:08.810Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-27T00:09:09.742Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-27T00:09:11.661Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-27T00:09:12.598Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-27T00:09:13.528Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-27T00:09:13.528Z] 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.
[2024-06-27T00:09:13.528Z] The best model improves the baseline by 14.52%.
[2024-06-27T00:09:14.459Z] Movies recommended for you:
[2024-06-27T00:09:14.459Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-27T00:09:14.459Z] There is no way to check that no silent failure occurred.
[2024-06-27T00:09:14.459Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (12873.014 ms) ======
[2024-06-27T00:09:14.459Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-06-27T00:09:14.459Z] GC before operation: completed in 63.861 ms, heap usage 249.204 MB -> 51.027 MB.
[2024-06-27T00:09:16.371Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-27T00:09:18.282Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-27T00:09:20.193Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-27T00:09:22.108Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-27T00:09:23.039Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-27T00:09:23.969Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-27T00:09:25.889Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-27T00:09:26.819Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-27T00:09:26.819Z] 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.
[2024-06-27T00:09:26.819Z] The best model improves the baseline by 14.52%.
[2024-06-27T00:09:26.819Z] Movies recommended for you:
[2024-06-27T00:09:26.819Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-27T00:09:26.819Z] There is no way to check that no silent failure occurred.
[2024-06-27T00:09:26.819Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (12751.285 ms) ======
[2024-06-27T00:09:26.819Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-06-27T00:09:26.819Z] GC before operation: completed in 65.019 ms, heap usage 299.849 MB -> 53.003 MB.
[2024-06-27T00:09:28.729Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-27T00:09:30.639Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-27T00:09:32.555Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-27T00:09:34.466Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-27T00:09:35.420Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-27T00:09:36.350Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-27T00:09:37.281Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-27T00:09:38.211Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-27T00:09:39.140Z] 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.
[2024-06-27T00:09:39.140Z] The best model improves the baseline by 14.52%.
[2024-06-27T00:09:39.140Z] Movies recommended for you:
[2024-06-27T00:09:39.140Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-27T00:09:39.140Z] There is no way to check that no silent failure occurred.
[2024-06-27T00:09:39.140Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (11983.993 ms) ======
[2024-06-27T00:09:39.140Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-06-27T00:09:39.140Z] GC before operation: completed in 64.912 ms, heap usage 446.955 MB -> 57.823 MB.
[2024-06-27T00:09:41.061Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-27T00:09:42.970Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-27T00:09:44.878Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-27T00:09:45.809Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-27T00:09:47.722Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-27T00:09:48.653Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-27T00:09:49.582Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-27T00:09:50.644Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-27T00:09:50.644Z] 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.
[2024-06-27T00:09:50.644Z] The best model improves the baseline by 14.52%.
[2024-06-27T00:09:50.644Z] Movies recommended for you:
[2024-06-27T00:09:50.644Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-27T00:09:50.644Z] There is no way to check that no silent failure occurred.
[2024-06-27T00:09:50.644Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (11959.549 ms) ======
[2024-06-27T00:09:50.644Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-06-27T00:09:50.644Z] GC before operation: completed in 60.161 ms, heap usage 93.000 MB -> 53.086 MB.
[2024-06-27T00:09:52.552Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-27T00:09:54.489Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-27T00:09:56.398Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-27T00:09:59.693Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-27T00:09:59.693Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-27T00:10:00.624Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-27T00:10:01.553Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-27T00:10:02.485Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-27T00:10:03.414Z] 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.
[2024-06-27T00:10:03.414Z] The best model improves the baseline by 14.52%.
[2024-06-27T00:10:03.414Z] Movies recommended for you:
[2024-06-27T00:10:03.414Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-27T00:10:03.414Z] There is no way to check that no silent failure occurred.
[2024-06-27T00:10:03.414Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (12220.080 ms) ======
[2024-06-27T00:10:03.414Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-06-27T00:10:03.414Z] GC before operation: completed in 63.129 ms, heap usage 409.071 MB -> 54.504 MB.
[2024-06-27T00:10:05.325Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-27T00:10:07.238Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-27T00:10:09.149Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-27T00:10:11.059Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-27T00:10:11.988Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-27T00:10:12.922Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-27T00:10:14.833Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-27T00:10:15.764Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-27T00:10:15.764Z] 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.
[2024-06-27T00:10:15.764Z] The best model improves the baseline by 14.52%.
[2024-06-27T00:10:15.764Z] Movies recommended for you:
[2024-06-27T00:10:15.764Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-27T00:10:15.764Z] There is no way to check that no silent failure occurred.
[2024-06-27T00:10:15.764Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (12946.810 ms) ======
[2024-06-27T00:10:15.764Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-06-27T00:10:16.700Z] GC before operation: completed in 60.867 ms, heap usage 378.700 MB -> 51.105 MB.
[2024-06-27T00:10:18.610Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-27T00:10:21.562Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-27T00:10:23.475Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-27T00:10:24.411Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-27T00:10:26.321Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-27T00:10:27.253Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-27T00:10:28.184Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-27T00:10:30.104Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-27T00:10:30.104Z] 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.
[2024-06-27T00:10:30.104Z] The best model improves the baseline by 14.52%.
[2024-06-27T00:10:30.104Z] Movies recommended for you:
[2024-06-27T00:10:30.104Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-27T00:10:30.104Z] There is no way to check that no silent failure occurred.
[2024-06-27T00:10:30.104Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (13677.654 ms) ======
[2024-06-27T00:10:30.104Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-06-27T00:10:30.104Z] GC before operation: completed in 65.484 ms, heap usage 129.533 MB -> 54.427 MB.
[2024-06-27T00:10:32.017Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-27T00:10:33.927Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-27T00:10:35.846Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-27T00:10:37.770Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-27T00:10:38.700Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-27T00:10:39.632Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-27T00:10:40.561Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-27T00:10:42.481Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-27T00:10:42.482Z] 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.
[2024-06-27T00:10:42.482Z] The best model improves the baseline by 14.52%.
[2024-06-27T00:10:42.482Z] Movies recommended for you:
[2024-06-27T00:10:42.482Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-27T00:10:42.482Z] There is no way to check that no silent failure occurred.
[2024-06-27T00:10:42.482Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (12301.534 ms) ======
[2024-06-27T00:10:42.482Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-06-27T00:10:42.482Z] GC before operation: completed in 69.322 ms, heap usage 476.225 MB -> 56.963 MB.
[2024-06-27T00:10:44.394Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-27T00:10:46.308Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-27T00:10:48.217Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-27T00:10:50.305Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-27T00:10:51.239Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-27T00:10:52.168Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-27T00:10:53.101Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-27T00:10:54.031Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-27T00:10:55.981Z] 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.
[2024-06-27T00:10:55.981Z] The best model improves the baseline by 14.52%.
[2024-06-27T00:10:55.981Z] Movies recommended for you:
[2024-06-27T00:10:55.981Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-27T00:10:55.981Z] There is no way to check that no silent failure occurred.
[2024-06-27T00:10:55.981Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (12288.752 ms) ======
[2024-06-27T00:10:55.981Z] -----------------------------------
[2024-06-27T00:10:55.981Z] renaissance-movie-lens_0_PASSED
[2024-06-27T00:10:55.981Z] -----------------------------------
[2024-06-27T00:10:55.981Z]
[2024-06-27T00:10:55.981Z] TEST TEARDOWN:
[2024-06-27T00:10:55.981Z] Nothing to be done for teardown.
[2024-06-27T00:10:55.981Z] renaissance-movie-lens_0 Finish Time: Thu Jun 27 00:10:54 2024 Epoch Time (ms): 1719447054651