renaissance-movie-lens_0
[2024-08-10T02:08:25.971Z] Running test renaissance-movie-lens_0 ...
[2024-08-10T02:08:25.971Z] ===============================================
[2024-08-10T02:08:25.971Z] renaissance-movie-lens_0 Start Time: Sat Aug 10 02:08:25 2024 Epoch Time (ms): 1723255705468
[2024-08-10T02:08:25.971Z] variation: NoOptions
[2024-08-10T02:08:25.971Z] JVM_OPTIONS:
[2024-08-10T02:08:25.971Z] { \
[2024-08-10T02:08:25.971Z] echo ""; echo "TEST SETUP:"; \
[2024-08-10T02:08:25.971Z] echo "Nothing to be done for setup."; \
[2024-08-10T02:08:25.971Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17232547063536/renaissance-movie-lens_0"; \
[2024-08-10T02:08:25.971Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17232547063536/renaissance-movie-lens_0"; \
[2024-08-10T02:08:25.971Z] echo ""; echo "TESTING:"; \
[2024-08-10T02:08:25.971Z] "/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_17232547063536/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-10T02:08:25.971Z] 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_17232547063536/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-10T02:08:25.971Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-10T02:08:25.971Z] echo "Nothing to be done for teardown."; \
[2024-08-10T02:08:25.971Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_testList_0/aqa-tests/TKG/../TKG/output_17232547063536/TestTargetResult";
[2024-08-10T02:08:25.971Z]
[2024-08-10T02:08:25.971Z] TEST SETUP:
[2024-08-10T02:08:25.971Z] Nothing to be done for setup.
[2024-08-10T02:08:25.971Z]
[2024-08-10T02:08:25.971Z] TESTING:
[2024-08-10T02:08:30.662Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-10T02:08:31.935Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads.
[2024-08-10T02:08:35.978Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-10T02:08:36.585Z] Training: 60056, validation: 20285, test: 19854
[2024-08-10T02:08:36.585Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-10T02:08:36.585Z] GC before operation: completed in 105.557 ms, heap usage 44.843 MB -> 36.994 MB.
[2024-08-10T02:08:42.329Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:08:47.011Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:08:51.741Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:08:54.492Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:08:56.497Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:08:57.771Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:08:59.747Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:09:01.790Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:09:02.413Z] 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.
[2024-08-10T02:09:02.413Z] The best model improves the baseline by 14.34%.
[2024-08-10T02:09:02.413Z] Movies recommended for you:
[2024-08-10T02:09:02.413Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:09:02.413Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:09:02.413Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (25796.111 ms) ======
[2024-08-10T02:09:02.413Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-10T02:09:02.413Z] GC before operation: completed in 223.413 ms, heap usage 186.773 MB -> 52.852 MB.
[2024-08-10T02:09:05.166Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:09:07.935Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:09:10.685Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:09:13.474Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:09:14.747Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:09:16.717Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:09:17.981Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:09:20.362Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:09:20.362Z] 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.
[2024-08-10T02:09:20.362Z] The best model improves the baseline by 14.34%.
[2024-08-10T02:09:20.362Z] Movies recommended for you:
[2024-08-10T02:09:20.362Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:09:20.362Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:09:20.362Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17821.245 ms) ======
[2024-08-10T02:09:20.362Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-10T02:09:20.362Z] GC before operation: completed in 95.971 ms, heap usage 227.050 MB -> 49.060 MB.
[2024-08-10T02:09:23.137Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:09:25.985Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:09:28.763Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:09:31.600Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:09:32.871Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:09:34.857Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:09:36.123Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:09:38.110Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:09:38.110Z] 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.
[2024-08-10T02:09:38.110Z] The best model improves the baseline by 14.34%.
[2024-08-10T02:09:38.110Z] Movies recommended for you:
[2024-08-10T02:09:38.110Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:09:38.110Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:09:38.110Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17747.567 ms) ======
[2024-08-10T02:09:38.110Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-10T02:09:38.110Z] GC before operation: completed in 116.926 ms, heap usage 275.465 MB -> 49.394 MB.
[2024-08-10T02:09:40.875Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:09:43.728Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:09:47.415Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:09:49.454Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:09:50.748Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:09:52.014Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:09:54.031Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:09:55.313Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:09:55.313Z] 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.
[2024-08-10T02:09:55.313Z] The best model improves the baseline by 14.34%.
[2024-08-10T02:09:55.936Z] Movies recommended for you:
[2024-08-10T02:09:55.937Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:09:55.937Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:09:55.937Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (17258.573 ms) ======
[2024-08-10T02:09:55.937Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-10T02:09:55.937Z] GC before operation: completed in 85.391 ms, heap usage 324.391 MB -> 49.908 MB.
[2024-08-10T02:09:58.745Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:10:01.867Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:10:03.857Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:10:06.647Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:10:07.959Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:10:09.230Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:10:11.279Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:10:12.567Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:10:12.567Z] 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.
[2024-08-10T02:10:12.567Z] The best model improves the baseline by 14.34%.
[2024-08-10T02:10:12.567Z] Movies recommended for you:
[2024-08-10T02:10:12.567Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:10:12.567Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:10:12.567Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (17103.089 ms) ======
[2024-08-10T02:10:12.567Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-10T02:10:13.177Z] GC before operation: completed in 106.340 ms, heap usage 187.094 MB -> 49.872 MB.
[2024-08-10T02:10:15.198Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:10:17.955Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:10:20.703Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:10:23.551Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:10:24.820Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:10:26.149Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:10:28.167Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:10:29.429Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:10:30.026Z] 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.
[2024-08-10T02:10:30.026Z] The best model improves the baseline by 14.34%.
[2024-08-10T02:10:30.026Z] Movies recommended for you:
[2024-08-10T02:10:30.026Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:10:30.026Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:10:30.026Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (17009.829 ms) ======
[2024-08-10T02:10:30.026Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-10T02:10:30.026Z] GC before operation: completed in 110.399 ms, heap usage 275.625 MB -> 49.927 MB.
[2024-08-10T02:10:32.850Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:10:35.659Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:10:38.453Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:10:40.530Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:10:42.539Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:10:44.209Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:10:46.237Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:10:47.500Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:10:47.500Z] 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.
[2024-08-10T02:10:47.500Z] The best model improves the baseline by 14.34%.
[2024-08-10T02:10:47.500Z] Movies recommended for you:
[2024-08-10T02:10:47.500Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:10:47.500Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:10:47.500Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (17713.017 ms) ======
[2024-08-10T02:10:47.500Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-10T02:10:48.122Z] GC before operation: completed in 91.145 ms, heap usage 109.761 MB -> 49.988 MB.
[2024-08-10T02:10:50.114Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:10:52.891Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:10:55.663Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:10:57.650Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:10:59.633Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:11:00.913Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:11:02.990Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:11:04.270Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:11:04.874Z] 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.
[2024-08-10T02:11:04.874Z] The best model improves the baseline by 14.34%.
[2024-08-10T02:11:04.874Z] Movies recommended for you:
[2024-08-10T02:11:04.874Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:11:04.874Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:11:04.874Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (17096.973 ms) ======
[2024-08-10T02:11:04.874Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-10T02:11:04.874Z] GC before operation: completed in 107.660 ms, heap usage 319.990 MB -> 50.496 MB.
[2024-08-10T02:11:07.668Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:11:10.488Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:11:13.249Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:11:16.011Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:11:17.304Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:11:18.595Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:11:20.596Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:11:21.854Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:11:21.854Z] 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.
[2024-08-10T02:11:21.854Z] The best model improves the baseline by 14.34%.
[2024-08-10T02:11:22.457Z] Movies recommended for you:
[2024-08-10T02:11:22.457Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:11:22.458Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:11:22.458Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (17168.954 ms) ======
[2024-08-10T02:11:22.458Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-10T02:11:22.458Z] GC before operation: completed in 108.299 ms, heap usage 273.720 MB -> 50.289 MB.
[2024-08-10T02:11:24.485Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:11:26.779Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:11:29.551Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:11:31.509Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:11:33.476Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:11:34.726Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:11:35.973Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:11:37.219Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:11:37.814Z] 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.
[2024-08-10T02:11:37.814Z] The best model improves the baseline by 14.34%.
[2024-08-10T02:11:37.814Z] Movies recommended for you:
[2024-08-10T02:11:37.814Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:11:37.814Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:11:37.814Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15480.069 ms) ======
[2024-08-10T02:11:37.814Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-10T02:11:37.814Z] GC before operation: completed in 109.323 ms, heap usage 275.591 MB -> 50.263 MB.
[2024-08-10T02:11:40.607Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:11:42.578Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:11:45.313Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:11:48.070Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:11:49.428Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:11:50.700Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:11:51.951Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:11:53.227Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:11:53.227Z] 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.
[2024-08-10T02:11:53.227Z] The best model improves the baseline by 14.34%.
[2024-08-10T02:11:53.831Z] Movies recommended for you:
[2024-08-10T02:11:53.831Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:11:53.831Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:11:53.831Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15684.100 ms) ======
[2024-08-10T02:11:53.831Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-10T02:11:53.831Z] GC before operation: completed in 96.576 ms, heap usage 137.649 MB -> 49.840 MB.
[2024-08-10T02:11:55.818Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:11:58.594Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:12:00.559Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:12:03.315Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:12:04.575Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:12:05.867Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:12:07.503Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:12:08.763Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:12:08.763Z] 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.
[2024-08-10T02:12:08.763Z] The best model improves the baseline by 14.34%.
[2024-08-10T02:12:09.363Z] Movies recommended for you:
[2024-08-10T02:12:09.363Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:12:09.363Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:12:09.363Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15436.155 ms) ======
[2024-08-10T02:12:09.363Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-10T02:12:09.363Z] GC before operation: completed in 93.446 ms, heap usage 249.485 MB -> 50.064 MB.
[2024-08-10T02:12:11.362Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:12:14.165Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:12:16.132Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:12:18.102Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:12:20.095Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:12:21.383Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:12:23.403Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:12:24.694Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:12:25.357Z] 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.
[2024-08-10T02:12:25.357Z] The best model improves the baseline by 14.34%.
[2024-08-10T02:12:25.357Z] Movies recommended for you:
[2024-08-10T02:12:25.357Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:12:25.357Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:12:25.357Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15977.931 ms) ======
[2024-08-10T02:12:25.357Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-10T02:12:25.358Z] GC before operation: completed in 99.112 ms, heap usage 274.859 MB -> 50.335 MB.
[2024-08-10T02:12:28.167Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:12:30.159Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:12:32.951Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:12:35.790Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:12:37.065Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:12:39.127Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:12:41.269Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:12:42.545Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:12:43.211Z] 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.
[2024-08-10T02:12:43.211Z] The best model improves the baseline by 14.34%.
[2024-08-10T02:12:43.211Z] Movies recommended for you:
[2024-08-10T02:12:43.211Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:12:43.211Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:12:43.211Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (17726.374 ms) ======
[2024-08-10T02:12:43.211Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-10T02:12:43.211Z] GC before operation: completed in 122.841 ms, heap usage 276.116 MB -> 50.115 MB.
[2024-08-10T02:12:46.116Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:12:48.900Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:12:50.903Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:12:53.672Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:12:54.937Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:12:56.199Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:12:58.207Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:12:59.468Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:13:00.066Z] 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.
[2024-08-10T02:13:00.066Z] The best model improves the baseline by 14.34%.
[2024-08-10T02:13:00.066Z] Movies recommended for you:
[2024-08-10T02:13:00.066Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:13:00.066Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:13:00.066Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (16896.632 ms) ======
[2024-08-10T02:13:00.066Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-10T02:13:00.066Z] GC before operation: completed in 111.745 ms, heap usage 274.940 MB -> 50.249 MB.
[2024-08-10T02:13:02.826Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:13:04.810Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:13:07.585Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:13:09.585Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:13:10.827Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:13:12.105Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:13:13.390Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:13:15.389Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:13:15.389Z] 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.
[2024-08-10T02:13:15.389Z] The best model improves the baseline by 14.34%.
[2024-08-10T02:13:15.390Z] Movies recommended for you:
[2024-08-10T02:13:15.390Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:13:15.390Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:13:15.390Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15405.468 ms) ======
[2024-08-10T02:13:15.390Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-10T02:13:15.390Z] GC before operation: completed in 102.909 ms, heap usage 147.506 MB -> 50.237 MB.
[2024-08-10T02:13:18.158Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:13:20.165Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:13:22.973Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:13:24.982Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:13:26.234Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:13:27.836Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:13:29.095Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:13:30.362Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:13:30.362Z] 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.
[2024-08-10T02:13:30.362Z] The best model improves the baseline by 14.34%.
[2024-08-10T02:13:30.362Z] Movies recommended for you:
[2024-08-10T02:13:30.362Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:13:30.362Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:13:30.362Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14975.949 ms) ======
[2024-08-10T02:13:30.362Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-10T02:13:30.968Z] GC before operation: completed in 92.394 ms, heap usage 227.152 MB -> 50.112 MB.
[2024-08-10T02:13:32.922Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:13:34.877Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:13:37.642Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:13:39.657Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:13:40.929Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:13:42.201Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:13:44.162Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:13:45.450Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:13:45.450Z] 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.
[2024-08-10T02:13:45.450Z] The best model improves the baseline by 14.34%.
[2024-08-10T02:13:45.450Z] Movies recommended for you:
[2024-08-10T02:13:45.450Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:13:45.450Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:13:45.450Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14978.189 ms) ======
[2024-08-10T02:13:45.450Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-10T02:13:46.056Z] GC before operation: completed in 135.382 ms, heap usage 379.403 MB -> 53.536 MB.
[2024-08-10T02:13:48.047Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:13:50.844Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:13:53.616Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:13:55.591Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:13:56.871Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:13:58.137Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:13:59.422Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:14:01.405Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:14:01.405Z] 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.
[2024-08-10T02:14:01.405Z] The best model improves the baseline by 14.34%.
[2024-08-10T02:14:01.405Z] Movies recommended for you:
[2024-08-10T02:14:01.405Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:14:01.405Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:14:01.405Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (15529.737 ms) ======
[2024-08-10T02:14:01.405Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-10T02:14:01.405Z] GC before operation: completed in 125.503 ms, heap usage 87.544 MB -> 50.211 MB.
[2024-08-10T02:14:04.175Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:14:06.154Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:14:09.026Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:14:11.016Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:14:12.995Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:14:14.259Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:14:15.513Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:14:16.809Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:14:17.432Z] 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.
[2024-08-10T02:14:17.432Z] The best model improves the baseline by 14.34%.
[2024-08-10T02:14:17.432Z] Movies recommended for you:
[2024-08-10T02:14:17.432Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:14:17.432Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:14:17.432Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (15762.890 ms) ======
[2024-08-10T02:14:18.039Z] -----------------------------------
[2024-08-10T02:14:18.039Z] renaissance-movie-lens_0_PASSED
[2024-08-10T02:14:18.039Z] -----------------------------------
[2024-08-10T02:14:18.039Z]
[2024-08-10T02:14:18.039Z] TEST TEARDOWN:
[2024-08-10T02:14:18.039Z] Nothing to be done for teardown.
[2024-08-10T02:14:18.039Z] renaissance-movie-lens_0 Finish Time: Sat Aug 10 02:14:17 2024 Epoch Time (ms): 1723256057496