renaissance-movie-lens_0
[2024-08-07T21:22:57.546Z] Running test renaissance-movie-lens_0 ...
[2024-08-07T21:22:57.546Z] ===============================================
[2024-08-07T21:22:57.546Z] renaissance-movie-lens_0 Start Time: Wed Aug 7 21:22:57 2024 Epoch Time (ms): 1723065777043
[2024-08-07T21:22:57.546Z] variation: NoOptions
[2024-08-07T21:22:57.546Z] JVM_OPTIONS:
[2024-08-07T21:22:57.546Z] { \
[2024-08-07T21:22:57.546Z] echo ""; echo "TEST SETUP:"; \
[2024-08-07T21:22:57.546Z] echo "Nothing to be done for setup."; \
[2024-08-07T21:22:57.546Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_1723064333819/renaissance-movie-lens_0"; \
[2024-08-07T21:22:57.546Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_1723064333819/renaissance-movie-lens_0"; \
[2024-08-07T21:22:57.546Z] echo ""; echo "TESTING:"; \
[2024-08-07T21:22:57.546Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_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_s390x_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_1723064333819/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-07T21:22:57.546Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_1723064333819/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-07T21:22:57.546Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-07T21:22:57.546Z] echo "Nothing to be done for teardown."; \
[2024-08-07T21:22:57.546Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_1723064333819/TestTargetResult";
[2024-08-07T21:22:57.546Z]
[2024-08-07T21:22:57.546Z] TEST SETUP:
[2024-08-07T21:22:57.546Z] Nothing to be done for setup.
[2024-08-07T21:22:57.546Z]
[2024-08-07T21:22:57.546Z] TESTING:
[2024-08-07T21:23:01.340Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-07T21:23:03.382Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads.
[2024-08-07T21:23:07.111Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-07T21:23:07.735Z] Training: 60056, validation: 20285, test: 19854
[2024-08-07T21:23:07.735Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-07T21:23:07.735Z] GC before operation: completed in 67.365 ms, heap usage 137.333 MB -> 37.101 MB.
[2024-08-07T21:23:14.800Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:23:20.770Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:23:27.295Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:23:32.055Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:23:34.895Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:23:37.737Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:23:42.476Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:23:45.408Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:23:46.090Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-07T21:23:46.090Z] The best model improves the baseline by 14.34%.
[2024-08-07T21:23:46.090Z] Movies recommended for you:
[2024-08-07T21:23:46.090Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:23:46.090Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:23:46.090Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (38629.994 ms) ======
[2024-08-07T21:23:46.090Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-07T21:23:46.702Z] GC before operation: completed in 169.010 ms, heap usage 114.878 MB -> 55.938 MB.
[2024-08-07T21:23:52.600Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:23:58.606Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:24:04.807Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:24:08.657Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:24:12.530Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:24:14.583Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:24:18.807Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:24:22.681Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:24:22.681Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-07T21:24:22.681Z] The best model improves the baseline by 14.34%.
[2024-08-07T21:24:22.681Z] Movies recommended for you:
[2024-08-07T21:24:22.681Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:24:22.681Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:24:22.681Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (36540.155 ms) ======
[2024-08-07T21:24:22.681Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-07T21:24:23.327Z] GC before operation: completed in 163.390 ms, heap usage 71.170 MB -> 52.181 MB.
[2024-08-07T21:24:28.037Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:24:31.797Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:24:35.569Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:24:38.353Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:24:40.345Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:24:43.123Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:24:45.135Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:24:47.109Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:24:47.109Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-07T21:24:47.109Z] The best model improves the baseline by 14.34%.
[2024-08-07T21:24:47.109Z] Movies recommended for you:
[2024-08-07T21:24:47.109Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:24:47.110Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:24:47.110Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (24244.947 ms) ======
[2024-08-07T21:24:47.110Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-07T21:24:47.748Z] GC before operation: completed in 140.848 ms, heap usage 354.260 MB -> 52.688 MB.
[2024-08-07T21:24:51.504Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:24:55.234Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:25:00.515Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:25:04.233Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:25:06.302Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:25:09.097Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:25:11.936Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:25:14.019Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:25:14.780Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-07T21:25:14.780Z] The best model improves the baseline by 14.34%.
[2024-08-07T21:25:14.780Z] Movies recommended for you:
[2024-08-07T21:25:14.780Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:25:14.780Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:25:14.780Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (27412.516 ms) ======
[2024-08-07T21:25:14.780Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-07T21:25:15.397Z] GC before operation: completed in 270.106 ms, heap usage 246.459 MB -> 49.658 MB.
[2024-08-07T21:25:19.398Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:25:23.179Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:25:26.994Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:25:31.776Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:25:33.826Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:25:35.840Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:25:37.599Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:25:39.606Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:25:40.204Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-07T21:25:40.204Z] The best model improves the baseline by 14.34%.
[2024-08-07T21:25:40.204Z] Movies recommended for you:
[2024-08-07T21:25:40.204Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:25:40.204Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:25:40.204Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (25041.070 ms) ======
[2024-08-07T21:25:40.204Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-07T21:25:40.204Z] GC before operation: completed in 94.334 ms, heap usage 241.744 MB -> 49.883 MB.
[2024-08-07T21:25:43.942Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:25:47.660Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:25:51.326Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:25:54.167Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:25:57.037Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:25:59.032Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:26:01.054Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:26:03.179Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:26:03.815Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-07T21:26:03.815Z] The best model improves the baseline by 14.34%.
[2024-08-07T21:26:03.815Z] Movies recommended for you:
[2024-08-07T21:26:03.815Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:26:03.815Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:26:03.815Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (23449.476 ms) ======
[2024-08-07T21:26:03.815Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-07T21:26:03.815Z] GC before operation: completed in 214.343 ms, heap usage 115.785 MB -> 49.740 MB.
[2024-08-07T21:26:08.612Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:26:12.322Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:26:16.082Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:26:19.761Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:26:21.944Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:26:24.108Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:26:26.941Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:26:28.992Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:26:28.992Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-07T21:26:28.992Z] The best model improves the baseline by 14.34%.
[2024-08-07T21:26:28.992Z] Movies recommended for you:
[2024-08-07T21:26:28.992Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:26:28.992Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:26:28.992Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (25234.846 ms) ======
[2024-08-07T21:26:28.992Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-07T21:26:29.614Z] GC before operation: completed in 155.849 ms, heap usage 114.600 MB -> 49.936 MB.
[2024-08-07T21:26:33.355Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:26:38.205Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:26:42.874Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:26:46.682Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:26:49.478Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:26:52.420Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:26:55.266Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:26:58.141Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:26:58.141Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-07T21:26:58.141Z] The best model improves the baseline by 14.34%.
[2024-08-07T21:26:58.141Z] Movies recommended for you:
[2024-08-07T21:26:58.141Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:26:58.141Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:26:58.141Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (28964.614 ms) ======
[2024-08-07T21:26:58.141Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-07T21:26:58.141Z] GC before operation: completed in 119.657 ms, heap usage 318.946 MB -> 50.546 MB.
[2024-08-07T21:27:03.186Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:27:07.976Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:27:12.807Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:27:16.532Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:27:18.602Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:27:20.666Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:27:23.597Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:27:25.584Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:27:25.584Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-07T21:27:25.584Z] The best model improves the baseline by 14.34%.
[2024-08-07T21:27:26.190Z] Movies recommended for you:
[2024-08-07T21:27:26.190Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:27:26.190Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:27:26.190Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (27465.133 ms) ======
[2024-08-07T21:27:26.190Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-07T21:27:26.190Z] GC before operation: completed in 106.710 ms, heap usage 149.570 MB -> 50.063 MB.
[2024-08-07T21:27:29.087Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:27:32.792Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:27:36.472Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:27:39.282Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:27:40.566Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:27:43.406Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:27:45.538Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:27:47.545Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:27:47.545Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-07T21:27:47.545Z] The best model improves the baseline by 14.34%.
[2024-08-07T21:27:47.545Z] Movies recommended for you:
[2024-08-07T21:27:47.545Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:27:47.545Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:27:47.545Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (21704.011 ms) ======
[2024-08-07T21:27:47.545Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-07T21:27:48.147Z] GC before operation: completed in 163.282 ms, heap usage 234.746 MB -> 50.192 MB.
[2024-08-07T21:27:51.871Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:27:55.574Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:28:00.350Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:28:04.151Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:28:07.974Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:28:10.953Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:28:13.725Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:28:15.809Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:28:16.436Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-07T21:28:16.436Z] The best model improves the baseline by 14.34%.
[2024-08-07T21:28:16.436Z] Movies recommended for you:
[2024-08-07T21:28:16.436Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:28:16.436Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:28:16.436Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (28693.421 ms) ======
[2024-08-07T21:28:16.436Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-07T21:28:16.436Z] GC before operation: completed in 149.195 ms, heap usage 192.790 MB -> 49.906 MB.
[2024-08-07T21:28:21.502Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:28:25.291Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:28:29.399Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:28:32.226Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:28:35.106Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:28:37.986Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:28:40.027Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:28:42.046Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:28:42.670Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-07T21:28:42.670Z] The best model improves the baseline by 14.34%.
[2024-08-07T21:28:42.670Z] Movies recommended for you:
[2024-08-07T21:28:42.670Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:28:42.670Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:28:42.670Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (26199.618 ms) ======
[2024-08-07T21:28:42.670Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-07T21:28:43.308Z] GC before operation: completed in 221.800 ms, heap usage 219.191 MB -> 50.098 MB.
[2024-08-07T21:28:47.159Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:28:50.986Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:28:55.822Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:28:59.771Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:29:02.724Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:29:05.571Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:29:07.622Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:29:09.664Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:29:10.281Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-07T21:29:10.887Z] The best model improves the baseline by 14.34%.
[2024-08-07T21:29:10.887Z] Movies recommended for you:
[2024-08-07T21:29:10.887Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:29:10.887Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:29:10.887Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (27628.581 ms) ======
[2024-08-07T21:29:10.887Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-07T21:29:10.887Z] GC before operation: completed in 98.734 ms, heap usage 261.852 MB -> 50.422 MB.
[2024-08-07T21:29:14.105Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:29:17.827Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:29:21.609Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:29:26.417Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:29:29.364Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:29:33.376Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:29:36.337Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:29:39.326Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:29:40.039Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-07T21:29:40.039Z] The best model improves the baseline by 14.34%.
[2024-08-07T21:29:40.659Z] Movies recommended for you:
[2024-08-07T21:29:40.659Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:29:40.659Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:29:40.659Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (29639.850 ms) ======
[2024-08-07T21:29:40.659Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-07T21:29:40.659Z] GC before operation: completed in 230.650 ms, heap usage 260.657 MB -> 50.186 MB.
[2024-08-07T21:29:45.433Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:29:50.278Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:29:55.334Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:29:59.120Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:30:02.135Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:30:05.019Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:30:08.856Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:30:10.880Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:30:10.880Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-07T21:30:11.526Z] The best model improves the baseline by 14.34%.
[2024-08-07T21:30:11.526Z] Movies recommended for you:
[2024-08-07T21:30:11.526Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:30:11.526Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:30:11.526Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (30558.787 ms) ======
[2024-08-07T21:30:11.526Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-07T21:30:11.526Z] GC before operation: completed in 172.498 ms, heap usage 261.964 MB -> 50.340 MB.
[2024-08-07T21:30:16.376Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:30:20.129Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:30:23.912Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:30:26.719Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:30:28.747Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:30:32.567Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:30:34.661Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:30:38.018Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:30:38.018Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-07T21:30:38.018Z] The best model improves the baseline by 14.34%.
[2024-08-07T21:30:38.659Z] Movies recommended for you:
[2024-08-07T21:30:38.659Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:30:38.659Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:30:38.659Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (26897.228 ms) ======
[2024-08-07T21:30:38.659Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-07T21:30:38.659Z] GC before operation: completed in 100.007 ms, heap usage 271.366 MB -> 50.469 MB.
[2024-08-07T21:30:42.417Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:30:47.086Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:30:50.820Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:30:54.561Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:30:57.355Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:31:00.413Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:31:02.476Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:31:06.411Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:31:07.108Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-07T21:31:07.108Z] The best model improves the baseline by 14.34%.
[2024-08-07T21:31:07.108Z] Movies recommended for you:
[2024-08-07T21:31:07.108Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:31:07.108Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:31:07.108Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (28647.535 ms) ======
[2024-08-07T21:31:07.108Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-07T21:31:07.108Z] GC before operation: completed in 215.758 ms, heap usage 239.733 MB -> 50.199 MB.
[2024-08-07T21:31:13.087Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:31:18.018Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:31:22.260Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:31:26.078Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:31:28.926Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:31:31.784Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:31:35.620Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:31:38.586Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:31:39.290Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-07T21:31:39.290Z] The best model improves the baseline by 14.34%.
[2024-08-07T21:31:39.290Z] Movies recommended for you:
[2024-08-07T21:31:39.290Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:31:39.290Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:31:39.290Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (31906.273 ms) ======
[2024-08-07T21:31:39.290Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-07T21:31:39.290Z] GC before operation: completed in 163.243 ms, heap usage 262.732 MB -> 50.442 MB.
[2024-08-07T21:31:44.221Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:31:50.124Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:31:54.840Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:31:58.653Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:32:00.695Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:32:03.543Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:32:07.083Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:32:10.105Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:32:10.936Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-07T21:32:10.936Z] The best model improves the baseline by 14.34%.
[2024-08-07T21:32:10.936Z] Movies recommended for you:
[2024-08-07T21:32:10.936Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:32:10.936Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:32:10.936Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (31718.479 ms) ======
[2024-08-07T21:32:10.936Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-07T21:32:11.547Z] GC before operation: completed in 204.397 ms, heap usage 269.079 MB -> 50.615 MB.
[2024-08-07T21:32:15.249Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:32:20.227Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:32:25.246Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:32:30.022Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:32:32.011Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:32:34.949Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:32:38.946Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:32:41.887Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:32:41.887Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-07T21:32:42.493Z] The best model improves the baseline by 14.34%.
[2024-08-07T21:32:42.493Z] Movies recommended for you:
[2024-08-07T21:32:42.493Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:32:42.493Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:32:42.493Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (31001.591 ms) ======
[2024-08-07T21:32:42.493Z] -----------------------------------
[2024-08-07T21:32:42.493Z] renaissance-movie-lens_0_PASSED
[2024-08-07T21:32:42.493Z] -----------------------------------
[2024-08-07T21:32:42.493Z]
[2024-08-07T21:32:42.493Z] TEST TEARDOWN:
[2024-08-07T21:32:42.493Z] Nothing to be done for teardown.
[2024-08-07T21:32:42.493Z] renaissance-movie-lens_0 Finish Time: Wed Aug 7 21:32:42 2024 Epoch Time (ms): 1723066362431