renaissance-movie-lens_0
[2024-11-22T22:14:35.383Z] Running test renaissance-movie-lens_0 ...
[2024-11-22T22:14:35.383Z] ===============================================
[2024-11-22T22:14:35.383Z] renaissance-movie-lens_0 Start Time: Fri Nov 22 22:14:35 2024 Epoch Time (ms): 1732313675083
[2024-11-22T22:14:35.383Z] variation: NoOptions
[2024-11-22T22:14:35.383Z] JVM_OPTIONS:
[2024-11-22T22:14:35.383Z] { \
[2024-11-22T22:14:35.383Z] echo ""; echo "TEST SETUP:"; \
[2024-11-22T22:14:35.383Z] echo "Nothing to be done for setup."; \
[2024-11-22T22:14:35.383Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17323126817191/renaissance-movie-lens_0"; \
[2024-11-22T22:14:35.383Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17323126817191/renaissance-movie-lens_0"; \
[2024-11-22T22:14:35.383Z] echo ""; echo "TESTING:"; \
[2024-11-22T22:14:35.383Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/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_ppc64le_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17323126817191/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-22T22:14:35.383Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17323126817191/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-22T22:14:35.383Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-22T22:14:35.383Z] echo "Nothing to be done for teardown."; \
[2024-11-22T22:14:35.383Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17323126817191/TestTargetResult";
[2024-11-22T22:14:35.383Z]
[2024-11-22T22:14:35.383Z] TEST SETUP:
[2024-11-22T22:14:35.383Z] Nothing to be done for setup.
[2024-11-22T22:14:35.383Z]
[2024-11-22T22:14:35.383Z] TESTING:
[2024-11-22T22:14:39.495Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-22T22:14:43.531Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-11-22T22:14:44.812Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-22T22:14:44.812Z] Training: 60056, validation: 20285, test: 19854
[2024-11-22T22:14:44.812Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-22T22:14:44.812Z] GC before operation: completed in 71.924 ms, heap usage 110.565 MB -> 36.448 MB.
[2024-11-22T22:14:51.460Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-22T22:14:54.446Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-22T22:14:57.441Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-22T22:15:00.416Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-22T22:15:02.376Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-22T22:15:04.316Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-22T22:15:06.245Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-22T22:15:08.178Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-22T22:15:08.178Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-22T22:15:08.178Z] The best model improves the baseline by 14.52%.
[2024-11-22T22:15:08.178Z] Movies recommended for you:
[2024-11-22T22:15:08.178Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-22T22:15:08.178Z] There is no way to check that no silent failure occurred.
[2024-11-22T22:15:08.178Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (23413.100 ms) ======
[2024-11-22T22:15:08.178Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-22T22:15:08.178Z] GC before operation: completed in 112.214 ms, heap usage 337.212 MB -> 48.287 MB.
[2024-11-22T22:15:11.233Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-22T22:15:14.206Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-22T22:15:17.184Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-22T22:15:19.115Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-22T22:15:21.045Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-22T22:15:22.008Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-22T22:15:23.951Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-22T22:15:25.893Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-22T22:15:25.893Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-22T22:15:25.893Z] The best model improves the baseline by 14.52%.
[2024-11-22T22:15:25.893Z] Movies recommended for you:
[2024-11-22T22:15:25.893Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-22T22:15:25.893Z] There is no way to check that no silent failure occurred.
[2024-11-22T22:15:25.893Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17561.311 ms) ======
[2024-11-22T22:15:25.893Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-22T22:15:25.893Z] GC before operation: completed in 98.615 ms, heap usage 266.060 MB -> 49.127 MB.
[2024-11-22T22:15:28.878Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-22T22:15:31.862Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-22T22:15:33.796Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-22T22:15:35.721Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-22T22:15:37.669Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-22T22:15:38.612Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-22T22:15:40.542Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-22T22:15:41.478Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-22T22:15:42.454Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-22T22:15:42.454Z] The best model improves the baseline by 14.52%.
[2024-11-22T22:15:42.454Z] Movies recommended for you:
[2024-11-22T22:15:42.454Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-22T22:15:42.454Z] There is no way to check that no silent failure occurred.
[2024-11-22T22:15:42.454Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16075.965 ms) ======
[2024-11-22T22:15:42.454Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-22T22:15:42.454Z] GC before operation: completed in 105.132 ms, heap usage 296.316 MB -> 49.374 MB.
[2024-11-22T22:15:44.374Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-22T22:15:47.351Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-22T22:15:49.273Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-22T22:15:51.202Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-22T22:15:53.135Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-22T22:15:54.072Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-22T22:15:55.999Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-22T22:15:57.934Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-22T22:15:57.934Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-22T22:15:57.934Z] The best model improves the baseline by 14.52%.
[2024-11-22T22:15:57.934Z] Movies recommended for you:
[2024-11-22T22:15:57.934Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-22T22:15:57.934Z] There is no way to check that no silent failure occurred.
[2024-11-22T22:15:57.934Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (15542.045 ms) ======
[2024-11-22T22:15:57.934Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-22T22:15:57.934Z] GC before operation: completed in 107.035 ms, heap usage 154.252 MB -> 49.652 MB.
[2024-11-22T22:16:00.917Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-22T22:16:02.846Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-22T22:16:05.856Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-22T22:16:08.938Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-22T22:16:08.938Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-22T22:16:10.867Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-22T22:16:13.910Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-22T22:16:13.910Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-22T22:16:13.910Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-22T22:16:13.910Z] The best model improves the baseline by 14.52%.
[2024-11-22T22:16:13.910Z] Movies recommended for you:
[2024-11-22T22:16:13.910Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-22T22:16:13.910Z] There is no way to check that no silent failure occurred.
[2024-11-22T22:16:13.910Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16247.088 ms) ======
[2024-11-22T22:16:13.910Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-22T22:16:13.910Z] GC before operation: completed in 109.253 ms, heap usage 128.089 MB -> 49.759 MB.
[2024-11-22T22:16:17.059Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-22T22:16:27.762Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-22T22:16:27.762Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-22T22:16:27.762Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-22T22:16:27.762Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-22T22:16:27.762Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-22T22:16:28.873Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-22T22:16:29.813Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-22T22:16:29.813Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-22T22:16:29.813Z] The best model improves the baseline by 14.52%.
[2024-11-22T22:16:29.813Z] Movies recommended for you:
[2024-11-22T22:16:29.813Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-22T22:16:29.813Z] There is no way to check that no silent failure occurred.
[2024-11-22T22:16:29.813Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15565.037 ms) ======
[2024-11-22T22:16:29.813Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-22T22:16:29.813Z] GC before operation: completed in 97.053 ms, heap usage 186.762 MB -> 49.814 MB.
[2024-11-22T22:16:32.804Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-22T22:16:34.733Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-22T22:16:36.703Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-22T22:16:39.683Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-22T22:16:40.621Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-22T22:16:42.551Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-22T22:16:43.491Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-22T22:16:45.422Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-22T22:16:45.422Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-22T22:16:45.422Z] The best model improves the baseline by 14.52%.
[2024-11-22T22:16:45.422Z] Movies recommended for you:
[2024-11-22T22:16:45.422Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-22T22:16:45.422Z] There is no way to check that no silent failure occurred.
[2024-11-22T22:16:45.422Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15500.860 ms) ======
[2024-11-22T22:16:45.422Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-22T22:16:45.422Z] GC before operation: completed in 98.424 ms, heap usage 265.340 MB -> 50.011 MB.
[2024-11-22T22:16:48.401Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-22T22:16:50.329Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-22T22:16:53.314Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-22T22:16:55.301Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-22T22:16:56.239Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-22T22:16:57.199Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-22T22:16:59.121Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-22T22:17:00.060Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-22T22:17:00.998Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-22T22:17:00.998Z] The best model improves the baseline by 14.52%.
[2024-11-22T22:17:00.998Z] Movies recommended for you:
[2024-11-22T22:17:00.998Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-22T22:17:00.998Z] There is no way to check that no silent failure occurred.
[2024-11-22T22:17:00.998Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15340.141 ms) ======
[2024-11-22T22:17:00.998Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-22T22:17:00.998Z] GC before operation: completed in 92.462 ms, heap usage 187.400 MB -> 50.251 MB.
[2024-11-22T22:17:04.091Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-22T22:17:06.933Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-22T22:17:08.052Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-22T22:17:11.045Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-22T22:17:12.150Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-22T22:17:13.092Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-22T22:17:14.030Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-22T22:17:15.982Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-22T22:17:15.982Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-22T22:17:15.982Z] The best model improves the baseline by 14.52%.
[2024-11-22T22:17:15.982Z] Movies recommended for you:
[2024-11-22T22:17:15.982Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-22T22:17:15.982Z] There is no way to check that no silent failure occurred.
[2024-11-22T22:17:15.982Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15296.408 ms) ======
[2024-11-22T22:17:15.982Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-22T22:17:15.983Z] GC before operation: completed in 95.141 ms, heap usage 62.914 MB -> 49.897 MB.
[2024-11-22T22:17:18.950Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-22T22:17:20.879Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-22T22:17:22.851Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-22T22:17:24.789Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-22T22:17:26.738Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-22T22:17:27.680Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-22T22:17:29.621Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-22T22:17:31.623Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-22T22:17:31.623Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-22T22:17:31.623Z] The best model improves the baseline by 14.52%.
[2024-11-22T22:17:31.623Z] Movies recommended for you:
[2024-11-22T22:17:31.623Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-22T22:17:31.623Z] There is no way to check that no silent failure occurred.
[2024-11-22T22:17:31.623Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14929.308 ms) ======
[2024-11-22T22:17:31.623Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-22T22:17:31.623Z] GC before operation: completed in 95.288 ms, heap usage 282.885 MB -> 50.257 MB.
[2024-11-22T22:17:33.554Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-22T22:17:37.072Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-22T22:17:38.018Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-22T22:17:40.996Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-22T22:17:41.932Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-22T22:17:45.544Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-22T22:17:45.544Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-22T22:17:46.479Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-22T22:17:46.479Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-22T22:17:46.479Z] The best model improves the baseline by 14.52%.
[2024-11-22T22:17:46.479Z] Movies recommended for you:
[2024-11-22T22:17:46.479Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-22T22:17:46.479Z] There is no way to check that no silent failure occurred.
[2024-11-22T22:17:46.479Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15353.187 ms) ======
[2024-11-22T22:17:46.479Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-22T22:17:46.479Z] GC before operation: completed in 97.312 ms, heap usage 153.592 MB -> 49.859 MB.
[2024-11-22T22:17:49.458Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-22T22:17:51.383Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-22T22:17:54.355Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-22T22:17:56.278Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-22T22:18:03.426Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-22T22:18:03.426Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-22T22:18:03.426Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-22T22:18:03.426Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-22T22:18:03.426Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-22T22:18:03.426Z] The best model improves the baseline by 14.52%.
[2024-11-22T22:18:03.426Z] Movies recommended for you:
[2024-11-22T22:18:03.426Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-22T22:18:03.426Z] There is no way to check that no silent failure occurred.
[2024-11-22T22:18:03.426Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15102.059 ms) ======
[2024-11-22T22:18:03.426Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-22T22:18:03.426Z] GC before operation: completed in 97.231 ms, heap usage 73.206 MB -> 50.998 MB.
[2024-11-22T22:18:04.365Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-22T22:18:06.477Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-22T22:18:09.459Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-22T22:18:11.383Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-22T22:18:13.305Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-22T22:18:14.244Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-22T22:18:16.176Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-22T22:18:17.112Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-22T22:18:17.112Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-22T22:18:17.112Z] The best model improves the baseline by 14.52%.
[2024-11-22T22:18:18.046Z] Movies recommended for you:
[2024-11-22T22:18:18.046Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-22T22:18:18.046Z] There is no way to check that no silent failure occurred.
[2024-11-22T22:18:18.046Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15543.460 ms) ======
[2024-11-22T22:18:18.046Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-22T22:18:18.046Z] GC before operation: completed in 93.148 ms, heap usage 185.765 MB -> 50.246 MB.
[2024-11-22T22:18:19.979Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-22T22:18:22.943Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-22T22:18:24.866Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-22T22:18:26.786Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-22T22:18:28.708Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-22T22:18:29.650Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-22T22:18:31.602Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-22T22:18:32.537Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-22T22:18:32.537Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-22T22:18:32.537Z] The best model improves the baseline by 14.52%.
[2024-11-22T22:18:32.537Z] Movies recommended for you:
[2024-11-22T22:18:32.537Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-22T22:18:32.537Z] There is no way to check that no silent failure occurred.
[2024-11-22T22:18:32.537Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15134.947 ms) ======
[2024-11-22T22:18:32.537Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-22T22:18:32.537Z] GC before operation: completed in 89.306 ms, heap usage 181.724 MB -> 49.964 MB.
[2024-11-22T22:18:35.744Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-22T22:18:37.665Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-22T22:18:39.594Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-22T22:18:41.517Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-22T22:18:43.438Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-22T22:18:44.373Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-22T22:18:46.297Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-22T22:18:47.233Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-22T22:18:47.233Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-22T22:18:48.169Z] The best model improves the baseline by 14.52%.
[2024-11-22T22:18:48.169Z] Movies recommended for you:
[2024-11-22T22:18:48.169Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-22T22:18:48.169Z] There is no way to check that no silent failure occurred.
[2024-11-22T22:18:48.169Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14897.704 ms) ======
[2024-11-22T22:18:48.169Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-22T22:18:48.169Z] GC before operation: completed in 88.772 ms, heap usage 102.196 MB -> 50.087 MB.
[2024-11-22T22:18:50.202Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-22T22:18:52.128Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-22T22:18:55.117Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-22T22:18:57.036Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-22T22:18:57.971Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-22T22:18:59.899Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-22T22:19:00.835Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-22T22:19:02.763Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-22T22:19:02.763Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-22T22:19:02.763Z] The best model improves the baseline by 14.52%.
[2024-11-22T22:19:02.763Z] Movies recommended for you:
[2024-11-22T22:19:02.763Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-22T22:19:02.763Z] There is no way to check that no silent failure occurred.
[2024-11-22T22:19:02.763Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14842.877 ms) ======
[2024-11-22T22:19:02.763Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-22T22:19:02.763Z] GC before operation: completed in 105.149 ms, heap usage 252.863 MB -> 50.281 MB.
[2024-11-22T22:19:04.685Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-22T22:19:07.664Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-22T22:19:09.590Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-22T22:19:11.511Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-22T22:19:13.435Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-22T22:19:14.371Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-22T22:19:15.308Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-22T22:19:17.246Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-22T22:19:17.246Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-22T22:19:17.246Z] The best model improves the baseline by 14.52%.
[2024-11-22T22:19:17.246Z] Movies recommended for you:
[2024-11-22T22:19:17.246Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-22T22:19:17.246Z] There is no way to check that no silent failure occurred.
[2024-11-22T22:19:17.246Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14696.402 ms) ======
[2024-11-22T22:19:17.246Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-22T22:19:17.246Z] GC before operation: completed in 93.020 ms, heap usage 200.549 MB -> 50.101 MB.
[2024-11-22T22:19:20.219Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-22T22:19:22.141Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-22T22:19:25.112Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-22T22:19:27.034Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-22T22:19:27.982Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-22T22:19:30.786Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-22T22:19:32.323Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-22T22:19:32.323Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-22T22:19:32.323Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-22T22:19:32.323Z] The best model improves the baseline by 14.52%.
[2024-11-22T22:19:32.323Z] Movies recommended for you:
[2024-11-22T22:19:32.323Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-22T22:19:32.323Z] There is no way to check that no silent failure occurred.
[2024-11-22T22:19:32.323Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (15087.399 ms) ======
[2024-11-22T22:19:32.323Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-22T22:19:33.257Z] GC before operation: completed in 96.589 ms, heap usage 316.739 MB -> 50.244 MB.
[2024-11-22T22:19:35.184Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-22T22:19:37.128Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-22T22:19:40.108Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-22T22:19:42.030Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-22T22:19:42.964Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-22T22:19:44.895Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-22T22:19:46.326Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-22T22:19:47.274Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-22T22:19:47.274Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-22T22:19:47.274Z] The best model improves the baseline by 14.52%.
[2024-11-22T22:19:47.274Z] Movies recommended for you:
[2024-11-22T22:19:47.274Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-22T22:19:47.274Z] There is no way to check that no silent failure occurred.
[2024-11-22T22:19:47.274Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14819.332 ms) ======
[2024-11-22T22:19:47.274Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-22T22:19:48.210Z] GC before operation: completed in 87.054 ms, heap usage 62.766 MB -> 50.188 MB.
[2024-11-22T22:19:50.134Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-22T22:19:52.070Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-22T22:19:55.071Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-22T22:19:56.991Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-22T22:19:58.050Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-22T22:19:58.985Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-22T22:20:00.908Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-22T22:20:01.843Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-22T22:20:01.843Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-22T22:20:01.843Z] The best model improves the baseline by 14.52%.
[2024-11-22T22:20:02.777Z] Movies recommended for you:
[2024-11-22T22:20:02.777Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-22T22:20:02.777Z] There is no way to check that no silent failure occurred.
[2024-11-22T22:20:02.777Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14634.517 ms) ======
[2024-11-22T22:20:02.777Z] -----------------------------------
[2024-11-22T22:20:02.777Z] renaissance-movie-lens_0_PASSED
[2024-11-22T22:20:02.777Z] -----------------------------------
[2024-11-22T22:20:02.777Z]
[2024-11-22T22:20:02.777Z] TEST TEARDOWN:
[2024-11-22T22:20:02.777Z] Nothing to be done for teardown.
[2024-11-22T22:20:02.777Z] renaissance-movie-lens_0 Finish Time: Fri Nov 22 22:20:02 2024 Epoch Time (ms): 1732314002396