renaissance-movie-lens_0
[2024-08-15T07:15:48.879Z] Running test renaissance-movie-lens_0 ...
[2024-08-15T07:15:48.879Z] ===============================================
[2024-08-15T07:15:48.879Z] renaissance-movie-lens_0 Start Time: Thu Aug 15 07:15:48 2024 Epoch Time (ms): 1723706148515
[2024-08-15T07:15:48.879Z] variation: NoOptions
[2024-08-15T07:15:48.879Z] JVM_OPTIONS:
[2024-08-15T07:15:48.879Z] { \
[2024-08-15T07:15:48.879Z] echo ""; echo "TEST SETUP:"; \
[2024-08-15T07:15:48.879Z] echo "Nothing to be done for setup."; \
[2024-08-15T07:15:48.879Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17237038963107/renaissance-movie-lens_0"; \
[2024-08-15T07:15:48.879Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17237038963107/renaissance-movie-lens_0"; \
[2024-08-15T07:15:48.879Z] echo ""; echo "TESTING:"; \
[2024-08-15T07:15:48.879Z] "/home/jenkins/workspace/Test_openjdk11_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_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17237038963107/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-15T07:15:48.879Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17237038963107/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-15T07:15:48.879Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-15T07:15:48.880Z] echo "Nothing to be done for teardown."; \
[2024-08-15T07:15:48.880Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17237038963107/TestTargetResult";
[2024-08-15T07:15:48.880Z]
[2024-08-15T07:15:48.880Z] TEST SETUP:
[2024-08-15T07:15:48.880Z] Nothing to be done for setup.
[2024-08-15T07:15:48.880Z]
[2024-08-15T07:15:48.880Z] TESTING:
[2024-08-15T07:15:52.725Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-15T07:15:55.578Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads.
[2024-08-15T07:16:06.767Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-15T07:16:08.125Z] Training: 60056, validation: 20285, test: 19854
[2024-08-15T07:16:08.125Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-15T07:16:08.125Z] GC before operation: completed in 235.544 ms, heap usage 117.269 MB -> 36.296 MB.
[2024-08-15T07:16:29.289Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T07:16:34.060Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T07:16:45.499Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T07:16:57.860Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T07:17:02.951Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T07:17:08.244Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T07:17:12.962Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T07:17:17.910Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T07:17:17.910Z] 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.
[2024-08-15T07:17:17.910Z] The best model improves the baseline by 14.34%.
[2024-08-15T07:17:18.552Z] Movies recommended for you:
[2024-08-15T07:17:18.552Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T07:17:18.552Z] There is no way to check that no silent failure occurred.
[2024-08-15T07:17:18.552Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (70295.098 ms) ======
[2024-08-15T07:17:18.552Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-15T07:17:18.552Z] GC before operation: completed in 224.381 ms, heap usage 143.359 MB -> 48.658 MB.
[2024-08-15T07:17:29.409Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T07:17:38.953Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T07:17:46.824Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T07:17:55.981Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T07:17:59.877Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T07:18:03.023Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T07:18:08.111Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T07:18:12.293Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T07:18:12.927Z] 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.
[2024-08-15T07:18:12.927Z] The best model improves the baseline by 14.34%.
[2024-08-15T07:18:13.560Z] Movies recommended for you:
[2024-08-15T07:18:13.560Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T07:18:13.560Z] There is no way to check that no silent failure occurred.
[2024-08-15T07:18:13.560Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (54902.002 ms) ======
[2024-08-15T07:18:13.560Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-15T07:18:13.560Z] GC before operation: completed in 351.405 ms, heap usage 74.858 MB -> 51.487 MB.
[2024-08-15T07:18:19.581Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T07:18:29.158Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T07:18:35.682Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T07:18:44.649Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T07:18:47.608Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T07:18:51.376Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T07:18:55.160Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T07:18:58.028Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T07:18:58.674Z] 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.
[2024-08-15T07:18:58.674Z] The best model improves the baseline by 14.34%.
[2024-08-15T07:18:58.674Z] Movies recommended for you:
[2024-08-15T07:18:58.674Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T07:18:58.674Z] There is no way to check that no silent failure occurred.
[2024-08-15T07:18:58.674Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (44989.644 ms) ======
[2024-08-15T07:18:58.674Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-15T07:18:59.338Z] GC before operation: completed in 817.603 ms, heap usage 158.911 MB -> 48.450 MB.
[2024-08-15T07:19:07.322Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T07:19:15.003Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T07:19:22.770Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T07:19:26.760Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T07:19:30.706Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T07:19:33.668Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T07:19:37.535Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T07:19:41.619Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T07:19:41.619Z] 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.
[2024-08-15T07:19:41.619Z] The best model improves the baseline by 14.34%.
[2024-08-15T07:19:42.352Z] Movies recommended for you:
[2024-08-15T07:19:42.352Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T07:19:42.352Z] There is no way to check that no silent failure occurred.
[2024-08-15T07:19:42.352Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (42743.464 ms) ======
[2024-08-15T07:19:42.352Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-15T07:19:43.049Z] GC before operation: completed in 473.497 ms, heap usage 275.873 MB -> 48.896 MB.
[2024-08-15T07:19:50.549Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T07:19:57.726Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T07:20:03.665Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T07:20:07.781Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T07:20:10.623Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T07:20:13.664Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T07:20:17.552Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T07:20:21.422Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T07:20:22.146Z] 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.
[2024-08-15T07:20:22.146Z] The best model improves the baseline by 14.34%.
[2024-08-15T07:20:22.147Z] Movies recommended for you:
[2024-08-15T07:20:22.147Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T07:20:22.147Z] There is no way to check that no silent failure occurred.
[2024-08-15T07:20:22.147Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (39400.655 ms) ======
[2024-08-15T07:20:22.147Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-15T07:20:22.811Z] GC before operation: completed in 397.404 ms, heap usage 177.534 MB -> 48.972 MB.
[2024-08-15T07:20:30.409Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T07:20:36.592Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T07:20:42.692Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T07:20:47.457Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T07:20:53.631Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T07:20:56.670Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T07:21:00.432Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T07:21:03.489Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T07:21:04.830Z] 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.
[2024-08-15T07:21:04.830Z] The best model improves the baseline by 14.34%.
[2024-08-15T07:21:04.830Z] Movies recommended for you:
[2024-08-15T07:21:04.830Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T07:21:04.830Z] There is no way to check that no silent failure occurred.
[2024-08-15T07:21:04.830Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (42275.396 ms) ======
[2024-08-15T07:21:04.830Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-15T07:21:05.550Z] GC before operation: completed in 648.998 ms, heap usage 253.807 MB -> 48.977 MB.
[2024-08-15T07:21:14.960Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T07:21:24.069Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T07:21:31.710Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T07:21:36.740Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T07:21:40.580Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T07:21:43.488Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T07:21:49.067Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T07:21:53.174Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T07:21:53.822Z] 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.
[2024-08-15T07:21:53.822Z] The best model improves the baseline by 14.34%.
[2024-08-15T07:21:53.822Z] Movies recommended for you:
[2024-08-15T07:21:53.822Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T07:21:53.822Z] There is no way to check that no silent failure occurred.
[2024-08-15T07:21:53.822Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (48450.658 ms) ======
[2024-08-15T07:21:53.822Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-15T07:21:54.446Z] GC before operation: completed in 283.204 ms, heap usage 195.370 MB -> 49.090 MB.
[2024-08-15T07:22:02.314Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T07:22:11.233Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T07:22:16.357Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T07:22:22.530Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T07:22:25.368Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T07:22:29.349Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T07:22:33.860Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T07:22:37.958Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T07:22:37.958Z] 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.
[2024-08-15T07:22:38.645Z] The best model improves the baseline by 14.34%.
[2024-08-15T07:22:38.645Z] Movies recommended for you:
[2024-08-15T07:22:38.645Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T07:22:38.645Z] There is no way to check that no silent failure occurred.
[2024-08-15T07:22:38.645Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (44220.320 ms) ======
[2024-08-15T07:22:38.645Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-15T07:22:38.645Z] GC before operation: completed in 228.478 ms, heap usage 147.918 MB -> 49.318 MB.
[2024-08-15T07:22:44.802Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T07:22:49.562Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T07:22:57.142Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T07:23:02.102Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T07:23:06.062Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T07:23:09.011Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T07:23:11.909Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T07:23:14.936Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T07:23:15.608Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-15T07:23:15.608Z] The best model improves the baseline by 14.34%.
[2024-08-15T07:23:15.608Z] Movies recommended for you:
[2024-08-15T07:23:15.608Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T07:23:15.608Z] There is no way to check that no silent failure occurred.
[2024-08-15T07:23:15.608Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (36872.214 ms) ======
[2024-08-15T07:23:15.608Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-15T07:23:15.608Z] GC before operation: completed in 267.915 ms, heap usage 267.989 MB -> 49.322 MB.
[2024-08-15T07:23:23.518Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T07:23:27.400Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T07:23:33.525Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T07:23:38.295Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T07:23:42.248Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T07:23:46.316Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T07:23:51.415Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T07:23:53.657Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T07:23:54.318Z] 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.
[2024-08-15T07:23:54.318Z] The best model improves the baseline by 14.34%.
[2024-08-15T07:23:54.318Z] Movies recommended for you:
[2024-08-15T07:23:54.318Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T07:23:54.318Z] There is no way to check that no silent failure occurred.
[2024-08-15T07:23:54.318Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (38625.983 ms) ======
[2024-08-15T07:23:54.318Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-15T07:23:54.318Z] GC before operation: completed in 148.466 ms, heap usage 285.060 MB -> 49.411 MB.
[2024-08-15T07:24:00.451Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T07:24:06.890Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T07:24:14.632Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T07:24:19.529Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T07:24:23.393Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T07:24:25.682Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T07:24:29.684Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T07:24:32.552Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T07:24:33.946Z] 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.
[2024-08-15T07:24:33.946Z] The best model improves the baseline by 14.34%.
[2024-08-15T07:24:33.946Z] Movies recommended for you:
[2024-08-15T07:24:33.946Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T07:24:33.946Z] There is no way to check that no silent failure occurred.
[2024-08-15T07:24:33.946Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (39254.224 ms) ======
[2024-08-15T07:24:33.946Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-15T07:24:33.946Z] GC before operation: completed in 382.824 ms, heap usage 171.615 MB -> 49.039 MB.
[2024-08-15T07:24:41.440Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T07:24:47.599Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T07:24:53.963Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T07:25:00.179Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T07:25:04.111Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T07:25:08.252Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T07:25:12.089Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T07:25:15.014Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T07:25:15.687Z] 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.
[2024-08-15T07:25:15.687Z] The best model improves the baseline by 14.34%.
[2024-08-15T07:25:15.687Z] Movies recommended for you:
[2024-08-15T07:25:15.687Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T07:25:15.687Z] There is no way to check that no silent failure occurred.
[2024-08-15T07:25:15.687Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (41491.696 ms) ======
[2024-08-15T07:25:15.687Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-15T07:25:15.687Z] GC before operation: completed in 232.252 ms, heap usage 242.567 MB -> 49.286 MB.
[2024-08-15T07:25:24.993Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T07:25:32.683Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T07:25:40.186Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T07:25:45.057Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T07:25:49.318Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T07:25:52.157Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T07:25:55.128Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T07:25:59.155Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T07:25:59.155Z] 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.
[2024-08-15T07:25:59.821Z] The best model improves the baseline by 14.34%.
[2024-08-15T07:25:59.821Z] Movies recommended for you:
[2024-08-15T07:25:59.821Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T07:25:59.821Z] There is no way to check that no silent failure occurred.
[2024-08-15T07:25:59.821Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (43752.271 ms) ======
[2024-08-15T07:25:59.821Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-15T07:25:59.821Z] GC before operation: completed in 339.149 ms, heap usage 108.396 MB -> 52.687 MB.
[2024-08-15T07:26:07.699Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T07:26:15.203Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T07:26:22.782Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T07:26:27.677Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T07:26:34.125Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T07:26:38.193Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T07:26:42.231Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T07:26:47.629Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T07:26:48.319Z] 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.
[2024-08-15T07:26:48.319Z] The best model improves the baseline by 14.34%.
[2024-08-15T07:26:48.319Z] Movies recommended for you:
[2024-08-15T07:26:48.319Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T07:26:48.319Z] There is no way to check that no silent failure occurred.
[2024-08-15T07:26:48.319Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (48352.378 ms) ======
[2024-08-15T07:26:48.319Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-15T07:26:48.948Z] GC before operation: completed in 288.822 ms, heap usage 250.559 MB -> 49.201 MB.
[2024-08-15T07:26:58.747Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T07:27:07.010Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T07:27:16.338Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T07:27:24.018Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T07:27:28.022Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T07:27:31.950Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T07:27:35.809Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T07:27:39.674Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T07:27:39.674Z] 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.
[2024-08-15T07:27:39.674Z] The best model improves the baseline by 14.34%.
[2024-08-15T07:27:40.307Z] Movies recommended for you:
[2024-08-15T07:27:40.307Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T07:27:40.307Z] There is no way to check that no silent failure occurred.
[2024-08-15T07:27:40.307Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (51373.806 ms) ======
[2024-08-15T07:27:40.307Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-15T07:27:40.307Z] GC before operation: completed in 278.630 ms, heap usage 245.309 MB -> 49.351 MB.
[2024-08-15T07:27:46.238Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T07:27:55.222Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T07:28:03.526Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T07:28:08.277Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T07:28:12.073Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T07:28:14.213Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T07:28:18.007Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T07:28:22.479Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T07:28:23.211Z] 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.
[2024-08-15T07:28:23.211Z] The best model improves the baseline by 14.34%.
[2024-08-15T07:28:23.211Z] Movies recommended for you:
[2024-08-15T07:28:23.211Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T07:28:23.211Z] There is no way to check that no silent failure occurred.
[2024-08-15T07:28:23.211Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (42695.646 ms) ======
[2024-08-15T07:28:23.211Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-15T07:28:23.211Z] GC before operation: completed in 307.382 ms, heap usage 343.327 MB -> 52.716 MB.
[2024-08-15T07:28:30.615Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T07:28:36.562Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T07:28:41.420Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T07:28:48.109Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T07:28:55.081Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T07:28:59.203Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T07:29:03.168Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T07:29:06.123Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T07:29:06.881Z] 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.
[2024-08-15T07:29:06.881Z] The best model improves the baseline by 14.34%.
[2024-08-15T07:29:06.881Z] Movies recommended for you:
[2024-08-15T07:29:06.881Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T07:29:06.881Z] There is no way to check that no silent failure occurred.
[2024-08-15T07:29:06.881Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (43593.824 ms) ======
[2024-08-15T07:29:06.881Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-15T07:29:07.663Z] GC before operation: completed in 741.354 ms, heap usage 203.882 MB -> 51.538 MB.
[2024-08-15T07:29:15.325Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T07:29:23.052Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T07:29:30.658Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T07:29:37.147Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T07:29:40.249Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T07:29:44.310Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T07:29:47.492Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T07:29:52.550Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T07:29:53.252Z] 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.
[2024-08-15T07:29:53.252Z] The best model improves the baseline by 14.34%.
[2024-08-15T07:29:54.098Z] Movies recommended for you:
[2024-08-15T07:29:54.098Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T07:29:54.098Z] There is no way to check that no silent failure occurred.
[2024-08-15T07:29:54.098Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (45895.544 ms) ======
[2024-08-15T07:29:54.099Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-15T07:29:54.099Z] GC before operation: completed in 439.124 ms, heap usage 253.705 MB -> 49.352 MB.
[2024-08-15T07:30:01.542Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T07:30:10.614Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T07:30:20.616Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T07:30:27.401Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T07:30:31.983Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T07:30:36.002Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T07:30:40.050Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T07:30:43.912Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T07:30:44.536Z] 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.
[2024-08-15T07:30:44.536Z] The best model improves the baseline by 14.34%.
[2024-08-15T07:30:45.176Z] Movies recommended for you:
[2024-08-15T07:30:45.176Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T07:30:45.176Z] There is no way to check that no silent failure occurred.
[2024-08-15T07:30:45.176Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (50936.277 ms) ======
[2024-08-15T07:30:45.176Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-15T07:30:45.176Z] GC before operation: completed in 349.230 ms, heap usage 157.712 MB -> 49.464 MB.
[2024-08-15T07:30:51.108Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-15T07:30:55.903Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-15T07:31:04.102Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-15T07:31:12.151Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-15T07:31:15.222Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-15T07:31:19.175Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-15T07:31:25.750Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-15T07:31:29.896Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-15T07:31:29.896Z] 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.
[2024-08-15T07:31:29.896Z] The best model improves the baseline by 14.34%.
[2024-08-15T07:31:30.721Z] Movies recommended for you:
[2024-08-15T07:31:30.721Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-15T07:31:30.721Z] There is no way to check that no silent failure occurred.
[2024-08-15T07:31:30.721Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (45033.334 ms) ======
[2024-08-15T07:31:31.542Z] -----------------------------------
[2024-08-15T07:31:31.542Z] renaissance-movie-lens_0_PASSED
[2024-08-15T07:31:31.542Z] -----------------------------------
[2024-08-15T07:31:31.542Z]
[2024-08-15T07:31:31.542Z] TEST TEARDOWN:
[2024-08-15T07:31:31.542Z] Nothing to be done for teardown.
[2024-08-15T07:31:31.542Z] renaissance-movie-lens_0 Finish Time: Thu Aug 15 07:31:31 2024 Epoch Time (ms): 1723707091186