renaissance-movie-lens_0
[2024-08-17T01:08:25.605Z] Running test renaissance-movie-lens_0 ...
[2024-08-17T01:08:25.605Z] ===============================================
[2024-08-17T01:08:25.605Z] renaissance-movie-lens_0 Start Time: Sat Aug 17 01:08:25 2024 Epoch Time (ms): 1723856905317
[2024-08-17T01:08:25.605Z] variation: NoOptions
[2024-08-17T01:08:25.605Z] JVM_OPTIONS:
[2024-08-17T01:08:25.605Z] { \
[2024-08-17T01:08:25.605Z] echo ""; echo "TEST SETUP:"; \
[2024-08-17T01:08:25.605Z] echo "Nothing to be done for setup."; \
[2024-08-17T01:08:25.605Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17238569057990/renaissance-movie-lens_0"; \
[2024-08-17T01:08:25.605Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17238569057990/renaissance-movie-lens_0"; \
[2024-08-17T01:08:25.605Z] echo ""; echo "TESTING:"; \
[2024-08-17T01:08:25.605Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_rerun/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_rerun/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17238569057990/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-17T01:08:25.605Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17238569057990/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-17T01:08:25.605Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-17T01:08:25.605Z] echo "Nothing to be done for teardown."; \
[2024-08-17T01:08:25.605Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17238569057990/TestTargetResult";
[2024-08-17T01:08:25.605Z]
[2024-08-17T01:08:25.605Z] TEST SETUP:
[2024-08-17T01:08:25.605Z] Nothing to be done for setup.
[2024-08-17T01:08:25.605Z]
[2024-08-17T01:08:25.605Z] TESTING:
[2024-08-17T01:08:27.540Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-17T01:08:28.780Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads.
[2024-08-17T01:08:30.738Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-17T01:08:31.333Z] Training: 60056, validation: 20285, test: 19854
[2024-08-17T01:08:31.333Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-17T01:08:31.333Z] GC before operation: completed in 44.547 ms, heap usage 74.974 MB -> 37.100 MB.
[2024-08-17T01:08:35.912Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T01:08:37.846Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T01:08:41.432Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T01:08:43.374Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T01:08:44.608Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T01:08:45.837Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T01:08:47.065Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T01:08:48.303Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T01:08:48.911Z] 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.
[2024-08-17T01:08:48.911Z] The best model improves the baseline by 14.34%.
[2024-08-17T01:08:48.911Z] Movies recommended for you:
[2024-08-17T01:08:48.911Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T01:08:48.911Z] There is no way to check that no silent failure occurred.
[2024-08-17T01:08:48.911Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (17762.791 ms) ======
[2024-08-17T01:08:48.911Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-17T01:08:48.911Z] GC before operation: completed in 110.400 ms, heap usage 188.868 MB -> 58.780 MB.
[2024-08-17T01:08:51.637Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T01:08:53.566Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T01:08:55.500Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T01:08:57.771Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T01:08:59.123Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T01:08:59.717Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T01:09:00.952Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T01:09:02.178Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T01:09:02.769Z] 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.
[2024-08-17T01:09:02.769Z] The best model improves the baseline by 14.34%.
[2024-08-17T01:09:02.769Z] Movies recommended for you:
[2024-08-17T01:09:02.769Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T01:09:02.769Z] There is no way to check that no silent failure occurred.
[2024-08-17T01:09:02.769Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (13561.697 ms) ======
[2024-08-17T01:09:02.769Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-17T01:09:02.769Z] GC before operation: completed in 75.833 ms, heap usage 183.885 MB -> 49.099 MB.
[2024-08-17T01:09:04.709Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T01:09:06.647Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T01:09:08.579Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T01:09:10.508Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T01:09:11.737Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T01:09:12.972Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T01:09:14.220Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T01:09:15.448Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T01:09:15.448Z] 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.
[2024-08-17T01:09:15.448Z] The best model improves the baseline by 14.34%.
[2024-08-17T01:09:15.448Z] Movies recommended for you:
[2024-08-17T01:09:15.448Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T01:09:15.448Z] There is no way to check that no silent failure occurred.
[2024-08-17T01:09:15.448Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (12811.445 ms) ======
[2024-08-17T01:09:15.448Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-17T01:09:15.448Z] GC before operation: completed in 63.583 ms, heap usage 279.485 MB -> 49.586 MB.
[2024-08-17T01:09:17.399Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T01:09:19.325Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T01:09:21.255Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T01:09:23.180Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T01:09:23.769Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T01:09:24.997Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T01:09:26.239Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T01:09:27.470Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T01:09:28.059Z] 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.
[2024-08-17T01:09:28.059Z] The best model improves the baseline by 14.34%.
[2024-08-17T01:09:28.059Z] Movies recommended for you:
[2024-08-17T01:09:28.059Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T01:09:28.059Z] There is no way to check that no silent failure occurred.
[2024-08-17T01:09:28.059Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (12258.293 ms) ======
[2024-08-17T01:09:28.059Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-17T01:09:28.059Z] GC before operation: completed in 64.323 ms, heap usage 190.535 MB -> 49.826 MB.
[2024-08-17T01:09:29.623Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T01:09:31.549Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T01:09:33.488Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T01:09:35.445Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T01:09:36.738Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T01:09:37.330Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T01:09:38.569Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T01:09:39.798Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T01:09:39.798Z] 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.
[2024-08-17T01:09:39.798Z] The best model improves the baseline by 14.34%.
[2024-08-17T01:09:39.798Z] Movies recommended for you:
[2024-08-17T01:09:39.798Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T01:09:39.798Z] There is no way to check that no silent failure occurred.
[2024-08-17T01:09:39.798Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (11866.513 ms) ======
[2024-08-17T01:09:39.798Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-17T01:09:39.798Z] GC before operation: completed in 70.790 ms, heap usage 275.703 MB -> 50.099 MB.
[2024-08-17T01:09:41.725Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T01:09:42.969Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T01:09:44.894Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T01:09:46.829Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T01:09:48.063Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T01:09:49.292Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T01:09:50.521Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T01:09:51.113Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T01:09:51.719Z] 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.
[2024-08-17T01:09:51.719Z] The best model improves the baseline by 14.34%.
[2024-08-17T01:09:51.719Z] Movies recommended for you:
[2024-08-17T01:09:51.719Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T01:09:51.719Z] There is no way to check that no silent failure occurred.
[2024-08-17T01:09:51.719Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (11850.421 ms) ======
[2024-08-17T01:09:51.719Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-17T01:09:51.719Z] GC before operation: completed in 74.696 ms, heap usage 109.160 MB -> 49.865 MB.
[2024-08-17T01:09:53.654Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T01:09:55.213Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T01:09:57.146Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T01:09:59.072Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T01:10:00.299Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T01:10:01.524Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T01:10:02.749Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T01:10:03.977Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T01:10:03.977Z] 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.
[2024-08-17T01:10:03.977Z] The best model improves the baseline by 14.34%.
[2024-08-17T01:10:03.977Z] Movies recommended for you:
[2024-08-17T01:10:03.977Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T01:10:03.977Z] There is no way to check that no silent failure occurred.
[2024-08-17T01:10:03.977Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (12422.616 ms) ======
[2024-08-17T01:10:03.977Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-17T01:10:04.567Z] GC before operation: completed in 70.474 ms, heap usage 91.723 MB -> 50.105 MB.
[2024-08-17T01:10:05.791Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T01:10:07.721Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T01:10:09.644Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T01:10:10.888Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T01:10:12.118Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T01:10:12.710Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T01:10:13.934Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T01:10:15.162Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T01:10:15.162Z] 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.
[2024-08-17T01:10:15.162Z] The best model improves the baseline by 14.34%.
[2024-08-17T01:10:15.162Z] Movies recommended for you:
[2024-08-17T01:10:15.162Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T01:10:15.162Z] There is no way to check that no silent failure occurred.
[2024-08-17T01:10:15.162Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (10936.763 ms) ======
[2024-08-17T01:10:15.162Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-17T01:10:15.162Z] GC before operation: completed in 62.316 ms, heap usage 225.566 MB -> 50.486 MB.
[2024-08-17T01:10:17.111Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T01:10:19.037Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T01:10:20.965Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T01:10:22.891Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T01:10:23.483Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T01:10:24.714Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T01:10:25.941Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T01:10:26.532Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T01:10:26.532Z] 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.
[2024-08-17T01:10:26.532Z] The best model improves the baseline by 14.34%.
[2024-08-17T01:10:27.123Z] Movies recommended for you:
[2024-08-17T01:10:27.123Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T01:10:27.123Z] There is no way to check that no silent failure occurred.
[2024-08-17T01:10:27.123Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (11578.688 ms) ======
[2024-08-17T01:10:27.123Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-17T01:10:27.123Z] GC before operation: completed in 63.626 ms, heap usage 275.282 MB -> 50.423 MB.
[2024-08-17T01:10:28.765Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T01:10:30.021Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T01:10:31.949Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T01:10:33.188Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T01:10:34.416Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T01:10:35.659Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T01:10:36.925Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T01:10:37.514Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T01:10:37.514Z] 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.
[2024-08-17T01:10:37.514Z] The best model improves the baseline by 14.34%.
[2024-08-17T01:10:37.514Z] Movies recommended for you:
[2024-08-17T01:10:37.514Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T01:10:37.514Z] There is no way to check that no silent failure occurred.
[2024-08-17T01:10:37.514Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (10835.521 ms) ======
[2024-08-17T01:10:37.514Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-17T01:10:38.105Z] GC before operation: completed in 57.655 ms, heap usage 110.367 MB -> 50.284 MB.
[2024-08-17T01:10:39.332Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T01:10:41.257Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T01:10:42.486Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T01:10:43.713Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T01:10:44.945Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T01:10:46.174Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T01:10:47.399Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T01:10:47.989Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T01:10:48.577Z] 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.
[2024-08-17T01:10:48.578Z] The best model improves the baseline by 14.34%.
[2024-08-17T01:10:48.578Z] Movies recommended for you:
[2024-08-17T01:10:48.578Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T01:10:48.578Z] There is no way to check that no silent failure occurred.
[2024-08-17T01:10:48.578Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (10553.593 ms) ======
[2024-08-17T01:10:48.578Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-17T01:10:48.578Z] GC before operation: completed in 55.538 ms, heap usage 62.191 MB -> 50.026 MB.
[2024-08-17T01:10:50.502Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T01:10:51.728Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T01:10:53.656Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T01:10:55.581Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T01:10:56.811Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T01:10:57.397Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T01:10:58.674Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T01:10:59.907Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T01:10:59.907Z] 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.
[2024-08-17T01:10:59.907Z] The best model improves the baseline by 14.34%.
[2024-08-17T01:10:59.907Z] Movies recommended for you:
[2024-08-17T01:10:59.907Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T01:10:59.907Z] There is no way to check that no silent failure occurred.
[2024-08-17T01:10:59.907Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (11409.856 ms) ======
[2024-08-17T01:10:59.907Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-17T01:10:59.907Z] GC before operation: completed in 65.640 ms, heap usage 95.075 MB -> 50.105 MB.
[2024-08-17T01:11:01.832Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T01:11:03.056Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T01:11:04.988Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T01:11:06.220Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T01:11:07.457Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T01:11:08.693Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T01:11:09.934Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T01:11:11.160Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T01:11:11.160Z] 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.
[2024-08-17T01:11:11.160Z] The best model improves the baseline by 14.34%.
[2024-08-17T01:11:11.160Z] Movies recommended for you:
[2024-08-17T01:11:11.160Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T01:11:11.160Z] There is no way to check that no silent failure occurred.
[2024-08-17T01:11:11.160Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (11160.877 ms) ======
[2024-08-17T01:11:11.160Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-17T01:11:11.160Z] GC before operation: completed in 63.483 ms, heap usage 247.138 MB -> 50.426 MB.
[2024-08-17T01:11:13.089Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T01:11:14.323Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T01:11:16.250Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T01:11:17.481Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T01:11:18.719Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T01:11:19.968Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T01:11:21.195Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T01:11:21.783Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T01:11:22.373Z] 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.
[2024-08-17T01:11:22.373Z] The best model improves the baseline by 14.34%.
[2024-08-17T01:11:22.373Z] Movies recommended for you:
[2024-08-17T01:11:22.373Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T01:11:22.373Z] There is no way to check that no silent failure occurred.
[2024-08-17T01:11:22.373Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (11055.205 ms) ======
[2024-08-17T01:11:22.373Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-17T01:11:22.373Z] GC before operation: completed in 66.377 ms, heap usage 111.263 MB -> 50.130 MB.
[2024-08-17T01:11:24.298Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T01:11:25.530Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T01:11:27.470Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T01:11:29.408Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T01:11:29.999Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T01:11:31.230Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T01:11:32.454Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T01:11:33.138Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T01:11:33.138Z] 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.
[2024-08-17T01:11:33.138Z] The best model improves the baseline by 14.34%.
[2024-08-17T01:11:33.138Z] Movies recommended for you:
[2024-08-17T01:11:33.139Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T01:11:33.139Z] There is no way to check that no silent failure occurred.
[2024-08-17T01:11:33.139Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (11144.669 ms) ======
[2024-08-17T01:11:33.139Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-17T01:11:33.730Z] GC before operation: completed in 62.057 ms, heap usage 226.651 MB -> 50.429 MB.
[2024-08-17T01:11:34.958Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T01:11:36.885Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T01:11:38.110Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T01:11:40.041Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T01:11:41.271Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T01:11:41.910Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T01:11:43.139Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T01:11:43.727Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T01:11:44.317Z] 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.
[2024-08-17T01:11:44.317Z] The best model improves the baseline by 14.34%.
[2024-08-17T01:11:44.317Z] Movies recommended for you:
[2024-08-17T01:11:44.317Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T01:11:44.317Z] There is no way to check that no silent failure occurred.
[2024-08-17T01:11:44.317Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (10842.233 ms) ======
[2024-08-17T01:11:44.317Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-17T01:11:44.317Z] GC before operation: completed in 71.161 ms, heap usage 275.632 MB -> 50.563 MB.
[2024-08-17T01:11:46.247Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T01:11:47.474Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T01:11:49.404Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T01:11:50.631Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T01:11:51.867Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T01:11:52.458Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T01:11:53.686Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T01:11:54.303Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T01:11:54.303Z] 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.
[2024-08-17T01:11:54.303Z] The best model improves the baseline by 14.34%.
[2024-08-17T01:11:54.303Z] Movies recommended for you:
[2024-08-17T01:11:54.303Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T01:11:54.303Z] There is no way to check that no silent failure occurred.
[2024-08-17T01:11:54.303Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (10181.430 ms) ======
[2024-08-17T01:11:54.303Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-17T01:11:54.893Z] GC before operation: completed in 57.352 ms, heap usage 274.981 MB -> 50.468 MB.
[2024-08-17T01:11:56.121Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T01:11:57.349Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T01:12:00.053Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T01:12:01.297Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T01:12:02.558Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T01:12:03.146Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T01:12:04.379Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T01:12:04.974Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T01:12:05.582Z] 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.
[2024-08-17T01:12:05.582Z] The best model improves the baseline by 14.34%.
[2024-08-17T01:12:05.582Z] Movies recommended for you:
[2024-08-17T01:12:05.582Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T01:12:05.582Z] There is no way to check that no silent failure occurred.
[2024-08-17T01:12:05.582Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (10743.199 ms) ======
[2024-08-17T01:12:05.582Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-17T01:12:05.582Z] GC before operation: completed in 64.255 ms, heap usage 107.833 MB -> 50.310 MB.
[2024-08-17T01:12:06.814Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T01:12:08.746Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T01:12:10.685Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T01:12:11.923Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T01:12:13.158Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T01:12:14.383Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T01:12:14.972Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T01:12:16.203Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T01:12:16.203Z] 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.
[2024-08-17T01:12:16.203Z] The best model improves the baseline by 14.34%.
[2024-08-17T01:12:16.203Z] Movies recommended for you:
[2024-08-17T01:12:16.203Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T01:12:16.203Z] There is no way to check that no silent failure occurred.
[2024-08-17T01:12:16.203Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (11002.686 ms) ======
[2024-08-17T01:12:16.203Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-17T01:12:16.791Z] GC before operation: completed in 70.561 ms, heap usage 227.274 MB -> 50.551 MB.
[2024-08-17T01:12:18.021Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T01:12:19.950Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T01:12:21.180Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T01:12:22.420Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T01:12:23.653Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T01:12:24.883Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T01:12:25.487Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T01:12:26.730Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T01:12:26.730Z] 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.
[2024-08-17T01:12:26.730Z] The best model improves the baseline by 14.34%.
[2024-08-17T01:12:27.320Z] Movies recommended for you:
[2024-08-17T01:12:27.320Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T01:12:27.320Z] There is no way to check that no silent failure occurred.
[2024-08-17T01:12:27.320Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (10548.041 ms) ======
[2024-08-17T01:12:27.320Z] -----------------------------------
[2024-08-17T01:12:27.320Z] renaissance-movie-lens_0_PASSED
[2024-08-17T01:12:27.320Z] -----------------------------------
[2024-08-17T01:12:27.320Z]
[2024-08-17T01:12:27.320Z] TEST TEARDOWN:
[2024-08-17T01:12:27.320Z] Nothing to be done for teardown.
[2024-08-17T01:12:27.320Z] renaissance-movie-lens_0 Finish Time: Sat Aug 17 01:12:26 2024 Epoch Time (ms): 1723857146987