renaissance-movie-lens_0
[2024-11-21T13:44:14.854Z] Running test renaissance-movie-lens_0 ...
[2024-11-21T13:44:14.854Z] ===============================================
[2024-11-21T13:44:14.854Z] renaissance-movie-lens_0 Start Time: Thu Nov 21 13:44:14 2024 Epoch Time (ms): 1732196654090
[2024-11-21T13:44:14.854Z] variation: NoOptions
[2024-11-21T13:44:14.854Z] JVM_OPTIONS:
[2024-11-21T13:44:14.854Z] { \
[2024-11-21T13:44:14.854Z] echo ""; echo "TEST SETUP:"; \
[2024-11-21T13:44:14.854Z] echo "Nothing to be done for setup."; \
[2024-11-21T13:44:14.854Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_1732191032186/renaissance-movie-lens_0"; \
[2024-11-21T13:44:14.854Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_1732191032186/renaissance-movie-lens_0"; \
[2024-11-21T13:44:14.854Z] echo ""; echo "TESTING:"; \
[2024-11-21T13:44:14.854Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-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_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_1732191032186/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-21T13:44:14.854Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_1732191032186/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-21T13:44:14.854Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-21T13:44:14.854Z] echo "Nothing to be done for teardown."; \
[2024-11-21T13:44:14.854Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_1732191032186/TestTargetResult";
[2024-11-21T13:44:14.854Z]
[2024-11-21T13:44:14.854Z] TEST SETUP:
[2024-11-21T13:44:14.854Z] Nothing to be done for setup.
[2024-11-21T13:44:14.854Z]
[2024-11-21T13:44:14.854Z] TESTING:
[2024-11-21T13:44:31.898Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-21T13:44:46.025Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-11-21T13:45:17.577Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-21T13:45:21.178Z] Training: 60056, validation: 20285, test: 19854
[2024-11-21T13:45:21.178Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-21T13:45:21.178Z] GC before operation: completed in 462.984 ms, heap usage 43.007 MB -> 37.061 MB.
[2024-11-21T13:46:20.797Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T13:47:03.248Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T13:47:39.968Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T13:48:11.019Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T13:48:27.908Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T13:48:44.745Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T13:49:01.407Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T13:49:16.176Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T13:49:17.823Z] 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.
[2024-11-21T13:49:17.823Z] The best model improves the baseline by 14.52%.
[2024-11-21T13:49:19.568Z] Movies recommended for you:
[2024-11-21T13:49:19.568Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T13:49:19.568Z] There is no way to check that no silent failure occurred.
[2024-11-21T13:49:19.568Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (237952.992 ms) ======
[2024-11-21T13:49:19.568Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-21T13:49:19.568Z] GC before operation: completed in 542.501 ms, heap usage 68.782 MB -> 51.161 MB.
[2024-11-21T13:49:42.322Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T13:50:05.096Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T13:50:27.804Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T13:50:45.365Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T13:50:59.632Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T13:51:09.982Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T13:51:24.178Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T13:51:34.937Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T13:51:37.460Z] 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.
[2024-11-21T13:51:37.460Z] The best model improves the baseline by 14.52%.
[2024-11-21T13:51:38.245Z] Movies recommended for you:
[2024-11-21T13:51:38.245Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T13:51:38.245Z] There is no way to check that no silent failure occurred.
[2024-11-21T13:51:38.245Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (138701.659 ms) ======
[2024-11-21T13:51:38.245Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-21T13:51:39.026Z] GC before operation: completed in 586.629 ms, heap usage 165.767 MB -> 49.517 MB.
[2024-11-21T13:51:58.396Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T13:52:17.726Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T13:52:40.014Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T13:52:56.466Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T13:53:06.534Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T13:53:17.197Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T13:53:29.229Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T13:53:39.578Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T13:53:41.275Z] 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.
[2024-11-21T13:53:41.275Z] The best model improves the baseline by 14.52%.
[2024-11-21T13:53:41.275Z] Movies recommended for you:
[2024-11-21T13:53:41.275Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T13:53:41.275Z] There is no way to check that no silent failure occurred.
[2024-11-21T13:53:41.275Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (122412.148 ms) ======
[2024-11-21T13:53:41.275Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-21T13:53:42.094Z] GC before operation: completed in 487.391 ms, heap usage 427.250 MB -> 53.279 MB.
[2024-11-21T13:53:59.376Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T13:54:18.467Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T13:54:40.659Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T13:54:56.759Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T13:55:08.646Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T13:55:19.266Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T13:55:29.326Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T13:55:39.385Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T13:55:41.086Z] 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.
[2024-11-21T13:55:41.086Z] The best model improves the baseline by 14.52%.
[2024-11-21T13:55:41.850Z] Movies recommended for you:
[2024-11-21T13:55:41.850Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T13:55:41.850Z] There is no way to check that no silent failure occurred.
[2024-11-21T13:55:41.850Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (119700.797 ms) ======
[2024-11-21T13:55:41.850Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-21T13:55:42.674Z] GC before operation: completed in 633.179 ms, heap usage 272.758 MB -> 50.260 MB.
[2024-11-21T13:56:01.472Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T13:56:17.797Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T13:56:37.056Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T13:56:53.557Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T13:57:05.470Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T13:57:13.887Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T13:57:25.695Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T13:57:35.970Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T13:57:37.633Z] 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.
[2024-11-21T13:57:37.633Z] The best model improves the baseline by 14.52%.
[2024-11-21T13:57:38.495Z] Movies recommended for you:
[2024-11-21T13:57:38.495Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T13:57:38.495Z] There is no way to check that no silent failure occurred.
[2024-11-21T13:57:38.495Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (115837.541 ms) ======
[2024-11-21T13:57:38.495Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-21T13:57:39.316Z] GC before operation: completed in 604.649 ms, heap usage 424.801 MB -> 53.973 MB.
[2024-11-21T13:57:56.375Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T13:58:15.880Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T13:58:35.304Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T13:58:51.978Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T13:59:04.630Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T13:59:15.041Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T13:59:25.409Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T13:59:35.770Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T13:59:36.594Z] 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.
[2024-11-21T13:59:36.594Z] The best model improves the baseline by 14.52%.
[2024-11-21T13:59:37.401Z] Movies recommended for you:
[2024-11-21T13:59:37.401Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T13:59:37.401Z] There is no way to check that no silent failure occurred.
[2024-11-21T13:59:37.401Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (118531.772 ms) ======
[2024-11-21T13:59:37.401Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-21T13:59:38.237Z] GC before operation: completed in 579.906 ms, heap usage 198.355 MB -> 50.355 MB.
[2024-11-21T13:59:55.004Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:00:11.652Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:00:29.050Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:00:45.673Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:00:59.961Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:01:10.102Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:01:20.534Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:01:30.967Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:01:31.775Z] 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.
[2024-11-21T14:01:31.775Z] The best model improves the baseline by 14.52%.
[2024-11-21T14:01:32.629Z] Movies recommended for you:
[2024-11-21T14:01:32.629Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:01:32.629Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:01:32.629Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (114539.603 ms) ======
[2024-11-21T14:01:32.629Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-21T14:01:33.439Z] GC before operation: completed in 635.713 ms, heap usage 421.370 MB -> 53.872 MB.
[2024-11-21T14:01:50.640Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:02:07.283Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:02:29.951Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:02:46.560Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:02:56.878Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:03:06.142Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:03:16.569Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:03:26.841Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:03:28.564Z] 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.
[2024-11-21T14:03:28.564Z] The best model improves the baseline by 14.52%.
[2024-11-21T14:03:29.400Z] Movies recommended for you:
[2024-11-21T14:03:29.400Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:03:29.400Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:03:29.400Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (115853.850 ms) ======
[2024-11-21T14:03:29.400Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-21T14:03:29.400Z] GC before operation: completed in 576.101 ms, heap usage 137.065 MB -> 50.851 MB.
[2024-11-21T14:03:46.201Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:04:02.832Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:04:22.738Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:04:36.975Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:04:47.195Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:04:57.336Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:05:08.132Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:05:17.020Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:05:18.334Z] 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.
[2024-11-21T14:05:18.334Z] The best model improves the baseline by 14.52%.
[2024-11-21T14:05:19.644Z] Movies recommended for you:
[2024-11-21T14:05:19.644Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:05:19.644Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:05:19.644Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (109513.546 ms) ======
[2024-11-21T14:05:19.644Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-21T14:05:19.644Z] GC before operation: completed in 531.212 ms, heap usage 85.820 MB -> 51.706 MB.
[2024-11-21T14:05:37.922Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:05:52.781Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:06:10.059Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:06:25.413Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:06:36.085Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:06:45.183Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:06:55.887Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:07:04.848Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:07:06.760Z] 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.
[2024-11-21T14:07:06.760Z] The best model improves the baseline by 14.52%.
[2024-11-21T14:07:08.091Z] Movies recommended for you:
[2024-11-21T14:07:08.091Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:07:08.091Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:07:08.091Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (107556.917 ms) ======
[2024-11-21T14:07:08.091Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-21T14:07:08.091Z] GC before operation: completed in 626.450 ms, heap usage 416.521 MB -> 54.090 MB.
[2024-11-21T14:07:23.132Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:07:38.071Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:07:55.453Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:08:10.536Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:08:23.463Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:08:34.298Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:08:47.205Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:08:56.965Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:09:01.046Z] 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.
[2024-11-21T14:09:01.046Z] The best model improves the baseline by 14.52%.
[2024-11-21T14:09:01.046Z] Movies recommended for you:
[2024-11-21T14:09:01.046Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:09:01.046Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:09:01.046Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (112632.199 ms) ======
[2024-11-21T14:09:01.046Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-21T14:09:01.046Z] GC before operation: completed in 708.611 ms, heap usage 315.256 MB -> 50.210 MB.
[2024-11-21T14:09:18.218Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:09:35.753Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:09:55.563Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:10:13.052Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:10:21.918Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:10:31.993Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:10:42.709Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:10:53.373Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:10:56.038Z] 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.
[2024-11-21T14:10:56.038Z] The best model improves the baseline by 14.52%.
[2024-11-21T14:10:57.365Z] Movies recommended for you:
[2024-11-21T14:10:57.365Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:10:57.365Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:10:57.365Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (115671.448 ms) ======
[2024-11-21T14:10:57.365Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-21T14:10:58.692Z] GC before operation: completed in 1024.444 ms, heap usage 201.306 MB -> 48.390 MB.
[2024-11-21T14:11:18.938Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:11:33.962Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:11:51.360Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:12:07.759Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:12:18.639Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:12:25.972Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:12:36.673Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:12:49.412Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:12:50.736Z] 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.
[2024-11-21T14:12:52.065Z] The best model improves the baseline by 14.52%.
[2024-11-21T14:12:52.065Z] Movies recommended for you:
[2024-11-21T14:12:52.065Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:12:52.065Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:12:52.065Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (113781.892 ms) ======
[2024-11-21T14:12:52.065Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-21T14:12:53.669Z] GC before operation: completed in 635.123 ms, heap usage 86.161 MB -> 50.808 MB.
[2024-11-21T14:13:11.043Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:13:28.396Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:13:48.625Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:14:03.706Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:14:12.925Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:14:23.833Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:14:34.692Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:14:43.997Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:14:45.827Z] 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.
[2024-11-21T14:14:45.827Z] The best model improves the baseline by 14.52%.
[2024-11-21T14:14:46.744Z] Movies recommended for you:
[2024-11-21T14:14:46.744Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:14:46.744Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:14:46.744Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (114401.869 ms) ======
[2024-11-21T14:14:46.744Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-21T14:14:47.659Z] GC before operation: completed in 646.580 ms, heap usage 87.679 MB -> 48.468 MB.
[2024-11-21T14:15:03.414Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:15:20.776Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:15:37.146Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:15:53.575Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:16:01.980Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:16:13.658Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:16:24.119Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:16:34.482Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:16:36.147Z] 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.
[2024-11-21T14:16:36.147Z] The best model improves the baseline by 14.52%.
[2024-11-21T14:16:36.962Z] Movies recommended for you:
[2024-11-21T14:16:36.962Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:16:36.962Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:16:36.962Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (109311.151 ms) ======
[2024-11-21T14:16:36.962Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-21T14:16:36.962Z] GC before operation: completed in 554.053 ms, heap usage 130.044 MB -> 48.530 MB.
[2024-11-21T14:16:53.432Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:17:07.748Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:17:27.076Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:17:39.588Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:17:48.026Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:17:56.467Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:18:08.740Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:18:15.827Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:18:17.501Z] 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.
[2024-11-21T14:18:17.501Z] The best model improves the baseline by 14.52%.
[2024-11-21T14:18:17.501Z] Movies recommended for you:
[2024-11-21T14:18:17.501Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:18:17.501Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:18:17.501Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (100490.036 ms) ======
[2024-11-21T14:18:17.501Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-21T14:18:18.318Z] GC before operation: completed in 532.632 ms, heap usage 317.949 MB -> 48.513 MB.
[2024-11-21T14:18:32.245Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:18:46.497Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:19:02.876Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:19:16.965Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:19:27.001Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:19:33.913Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:19:42.289Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:19:49.740Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:19:50.513Z] 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.
[2024-11-21T14:19:50.513Z] The best model improves the baseline by 14.52%.
[2024-11-21T14:19:51.318Z] Movies recommended for you:
[2024-11-21T14:19:51.318Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:19:51.318Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:19:51.318Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (92959.680 ms) ======
[2024-11-21T14:19:51.318Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-21T14:19:52.143Z] GC before operation: completed in 535.795 ms, heap usage 199.738 MB -> 48.487 MB.
[2024-11-21T14:20:06.048Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:20:17.817Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:20:31.702Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:20:45.602Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:20:54.068Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:21:01.684Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:21:08.836Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:21:17.464Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:21:18.410Z] 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.
[2024-11-21T14:21:18.410Z] The best model improves the baseline by 14.52%.
[2024-11-21T14:21:19.202Z] Movies recommended for you:
[2024-11-21T14:21:19.202Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:21:19.202Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:21:19.202Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (87477.864 ms) ======
[2024-11-21T14:21:19.202Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-21T14:21:19.999Z] GC before operation: completed in 476.761 ms, heap usage 101.604 MB -> 48.459 MB.
[2024-11-21T14:21:36.528Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:21:50.655Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:22:03.186Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:22:19.832Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:22:26.969Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:22:34.162Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:22:42.846Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:22:51.484Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:22:53.153Z] 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.
[2024-11-21T14:22:53.153Z] The best model improves the baseline by 14.52%.
[2024-11-21T14:22:53.153Z] Movies recommended for you:
[2024-11-21T14:22:53.153Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:22:53.153Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:22:53.153Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (93744.902 ms) ======
[2024-11-21T14:22:53.153Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-21T14:22:53.937Z] GC before operation: completed in 560.908 ms, heap usage 199.452 MB -> 48.847 MB.
[2024-11-21T14:23:05.974Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:23:19.991Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:23:33.865Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:23:45.847Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:23:52.979Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:24:00.093Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:24:08.517Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:24:15.556Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:24:17.208Z] 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.
[2024-11-21T14:24:17.208Z] The best model improves the baseline by 14.52%.
[2024-11-21T14:24:17.998Z] Movies recommended for you:
[2024-11-21T14:24:17.998Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:24:17.998Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:24:17.998Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (83689.262 ms) ======
[2024-11-21T14:24:20.563Z] -----------------------------------
[2024-11-21T14:24:20.563Z] renaissance-movie-lens_0_PASSED
[2024-11-21T14:24:20.563Z] -----------------------------------
[2024-11-21T14:24:20.563Z]
[2024-11-21T14:24:20.563Z] TEST TEARDOWN:
[2024-11-21T14:24:20.563Z] Nothing to be done for teardown.
[2024-11-21T14:24:21.343Z] renaissance-movie-lens_0 Finish Time: Thu Nov 21 14:24:20 2024 Epoch Time (ms): 1732199060504