[2025-02-19T22:19:03.059Z] Running test renaissance-movie-lens_0 ... [2025-02-19T22:19:03.059Z] =============================================== [2025-02-19T22:19:03.059Z] renaissance-movie-lens_0 Start Time: Wed Feb 19 22:19:02 2025 Epoch Time (ms): 1740003542092 [2025-02-19T22:19:03.059Z] variation: NoOptions [2025-02-19T22:19:03.059Z] JVM_OPTIONS: [2025-02-19T22:19:03.059Z] { \ [2025-02-19T22:19:03.059Z] echo ""; echo "TEST SETUP:"; \ [2025-02-19T22:19:03.059Z] echo "Nothing to be done for setup."; \ [2025-02-19T22:19:03.059Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17400025649794/renaissance-movie-lens_0"; \ [2025-02-19T22:19:03.059Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17400025649794/renaissance-movie-lens_0"; \ [2025-02-19T22:19:03.059Z] echo ""; echo "TESTING:"; \ [2025-02-19T22:19:03.059Z] "/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_17400025649794/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-02-19T22:19:03.059Z] 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_17400025649794/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-02-19T22:19:03.059Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-02-19T22:19:03.059Z] echo "Nothing to be done for teardown."; \ [2025-02-19T22:19:03.059Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17400025649794/TestTargetResult"; [2025-02-19T22:19:03.059Z] [2025-02-19T22:19:03.059Z] TEST SETUP: [2025-02-19T22:19:03.059Z] Nothing to be done for setup. [2025-02-19T22:19:03.059Z] [2025-02-19T22:19:03.059Z] TESTING: [2025-02-19T22:19:06.091Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2025-02-19T22:19:08.054Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-02-19T22:19:11.089Z] Got 100004 ratings from 671 users on 9066 movies. [2025-02-19T22:19:12.047Z] Training: 60056, validation: 20285, test: 19854 [2025-02-19T22:19:12.047Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-02-19T22:19:12.047Z] GC before operation: completed in 76.269 ms, heap usage 104.852 MB -> 36.430 MB. [2025-02-19T22:19:17.280Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-19T22:19:21.460Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-19T22:19:24.488Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-19T22:19:26.456Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-19T22:19:28.415Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-19T22:19:30.406Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-19T22:19:32.403Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-19T22:19:33.384Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-19T22:19:33.384Z] 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. [2025-02-19T22:19:33.384Z] The best model improves the baseline by 14.52%. [2025-02-19T22:19:34.340Z] Movies recommended for you: [2025-02-19T22:19:34.340Z] WARNING: This benchmark provides no result that can be validated. [2025-02-19T22:19:34.340Z] There is no way to check that no silent failure occurred. [2025-02-19T22:19:34.340Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (22108.012 ms) ====== [2025-02-19T22:19:34.340Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-02-19T22:19:34.340Z] GC before operation: completed in 92.793 ms, heap usage 288.568 MB -> 49.124 MB. [2025-02-19T22:19:37.367Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-19T22:19:39.392Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-19T22:19:42.446Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-19T22:19:44.413Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-19T22:19:46.376Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-19T22:19:47.332Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-19T22:19:49.301Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-19T22:19:50.275Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-19T22:19:51.235Z] 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. [2025-02-19T22:19:51.236Z] The best model improves the baseline by 14.52%. [2025-02-19T22:19:51.236Z] Movies recommended for you: [2025-02-19T22:19:51.236Z] WARNING: This benchmark provides no result that can be validated. [2025-02-19T22:19:51.236Z] There is no way to check that no silent failure occurred. [2025-02-19T22:19:51.236Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17036.011 ms) ====== [2025-02-19T22:19:51.236Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-02-19T22:19:51.236Z] GC before operation: completed in 101.221 ms, heap usage 272.535 MB -> 49.115 MB. [2025-02-19T22:19:53.240Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-19T22:19:56.279Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-19T22:19:58.242Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-19T22:20:01.027Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-19T22:20:01.990Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-19T22:20:03.957Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-19T22:20:04.926Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-19T22:20:06.945Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-19T22:20:06.945Z] 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. [2025-02-19T22:20:06.945Z] The best model improves the baseline by 14.52%. [2025-02-19T22:20:06.945Z] Movies recommended for you: [2025-02-19T22:20:06.945Z] WARNING: This benchmark provides no result that can be validated. [2025-02-19T22:20:06.945Z] There is no way to check that no silent failure occurred. [2025-02-19T22:20:06.945Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (15831.441 ms) ====== [2025-02-19T22:20:06.945Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-02-19T22:20:06.945Z] GC before operation: completed in 99.803 ms, heap usage 169.898 MB -> 49.373 MB. [2025-02-19T22:20:10.026Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-19T22:20:12.019Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-19T22:20:13.993Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-19T22:20:17.069Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-19T22:20:18.026Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-19T22:20:19.991Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-19T22:20:20.963Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-19T22:20:21.918Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-19T22:20:22.873Z] 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. [2025-02-19T22:20:22.873Z] The best model improves the baseline by 14.52%. [2025-02-19T22:20:22.873Z] Movies recommended for you: [2025-02-19T22:20:22.873Z] WARNING: This benchmark provides no result that can be validated. [2025-02-19T22:20:22.873Z] There is no way to check that no silent failure occurred. [2025-02-19T22:20:22.873Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (15617.162 ms) ====== [2025-02-19T22:20:22.873Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-02-19T22:20:22.873Z] GC before operation: completed in 106.792 ms, heap usage 251.520 MB -> 49.734 MB. [2025-02-19T22:20:25.999Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-19T22:20:27.970Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-19T22:20:29.936Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-19T22:20:33.021Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-19T22:20:33.976Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-19T22:20:34.942Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-19T22:20:36.914Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-19T22:20:38.041Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-19T22:20:39.000Z] 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. [2025-02-19T22:20:39.000Z] The best model improves the baseline by 14.52%. [2025-02-19T22:20:39.000Z] Movies recommended for you: [2025-02-19T22:20:39.000Z] WARNING: This benchmark provides no result that can be validated. [2025-02-19T22:20:39.000Z] There is no way to check that no silent failure occurred. [2025-02-19T22:20:39.000Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15774.942 ms) ====== [2025-02-19T22:20:39.000Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-02-19T22:20:39.000Z] GC before operation: completed in 93.669 ms, heap usage 202.372 MB -> 49.900 MB. [2025-02-19T22:20:41.028Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-19T22:20:43.002Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-19T22:20:46.044Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-19T22:20:47.842Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-19T22:20:48.799Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-19T22:20:50.774Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-19T22:20:51.738Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-19T22:20:52.693Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-19T22:20:53.664Z] 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. [2025-02-19T22:20:53.664Z] The best model improves the baseline by 14.52%. [2025-02-19T22:20:53.664Z] Movies recommended for you: [2025-02-19T22:20:53.664Z] WARNING: This benchmark provides no result that can be validated. [2025-02-19T22:20:53.664Z] There is no way to check that no silent failure occurred. [2025-02-19T22:20:53.664Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (14806.873 ms) ====== [2025-02-19T22:20:53.664Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-02-19T22:20:53.664Z] GC before operation: completed in 105.748 ms, heap usage 221.850 MB -> 49.792 MB. [2025-02-19T22:20:56.711Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-19T22:20:58.687Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-19T22:21:00.660Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-19T22:21:02.642Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-19T22:21:04.615Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-19T22:21:05.577Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-19T22:21:06.539Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-19T22:21:08.517Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-19T22:21:08.517Z] 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. [2025-02-19T22:21:08.517Z] The best model improves the baseline by 14.52%. [2025-02-19T22:21:08.517Z] Movies recommended for you: [2025-02-19T22:21:08.517Z] WARNING: This benchmark provides no result that can be validated. [2025-02-19T22:21:08.517Z] There is no way to check that no silent failure occurred. [2025-02-19T22:21:08.517Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15075.952 ms) ====== [2025-02-19T22:21:08.517Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-02-19T22:21:08.517Z] GC before operation: completed in 96.216 ms, heap usage 323.742 MB -> 50.125 MB. [2025-02-19T22:21:11.551Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-19T22:21:13.527Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-19T22:21:15.513Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-19T22:21:17.474Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-19T22:21:18.439Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-19T22:21:20.408Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-19T22:21:21.368Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-19T22:21:23.347Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-19T22:21:23.347Z] 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. [2025-02-19T22:21:23.347Z] The best model improves the baseline by 14.52%. [2025-02-19T22:21:23.347Z] Movies recommended for you: [2025-02-19T22:21:23.347Z] WARNING: This benchmark provides no result that can be validated. [2025-02-19T22:21:23.347Z] There is no way to check that no silent failure occurred. [2025-02-19T22:21:23.347Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (14559.127 ms) ====== [2025-02-19T22:21:23.347Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-02-19T22:21:23.347Z] GC before operation: completed in 96.818 ms, heap usage 115.376 MB -> 50.141 MB. [2025-02-19T22:21:26.392Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-19T22:21:28.375Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-19T22:21:30.348Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-19T22:21:32.315Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-19T22:21:33.271Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-19T22:21:36.464Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-19T22:21:36.464Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-19T22:21:37.422Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-19T22:21:38.383Z] 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. [2025-02-19T22:21:38.383Z] The best model improves the baseline by 14.52%. [2025-02-19T22:21:38.383Z] Movies recommended for you: [2025-02-19T22:21:38.383Z] WARNING: This benchmark provides no result that can be validated. [2025-02-19T22:21:38.383Z] There is no way to check that no silent failure occurred. [2025-02-19T22:21:38.383Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (14785.424 ms) ====== [2025-02-19T22:21:38.383Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-02-19T22:21:38.383Z] GC before operation: completed in 93.665 ms, heap usage 324.079 MB -> 50.222 MB. [2025-02-19T22:21:41.429Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-19T22:21:43.391Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-19T22:21:45.364Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-19T22:21:47.332Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-19T22:21:49.314Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-19T22:21:50.270Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-19T22:21:51.224Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-19T22:21:53.209Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-19T22:21:53.209Z] 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. [2025-02-19T22:21:53.209Z] The best model improves the baseline by 14.52%. [2025-02-19T22:21:53.209Z] Movies recommended for you: [2025-02-19T22:21:53.209Z] WARNING: This benchmark provides no result that can be validated. [2025-02-19T22:21:53.209Z] There is no way to check that no silent failure occurred. [2025-02-19T22:21:53.209Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14943.599 ms) ====== [2025-02-19T22:21:53.209Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-02-19T22:21:53.209Z] GC before operation: completed in 94.223 ms, heap usage 130.960 MB -> 50.090 MB. [2025-02-19T22:21:55.172Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-19T22:21:58.213Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-19T22:22:00.182Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-19T22:22:02.175Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-19T22:22:03.136Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-19T22:22:05.100Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-19T22:22:06.058Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-19T22:22:08.029Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-19T22:22:08.029Z] 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. [2025-02-19T22:22:08.029Z] The best model improves the baseline by 14.52%. [2025-02-19T22:22:08.029Z] Movies recommended for you: [2025-02-19T22:22:08.029Z] WARNING: This benchmark provides no result that can be validated. [2025-02-19T22:22:08.029Z] There is no way to check that no silent failure occurred. [2025-02-19T22:22:08.029Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14842.849 ms) ====== [2025-02-19T22:22:08.029Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-02-19T22:22:08.029Z] GC before operation: completed in 98.059 ms, heap usage 105.166 MB -> 49.860 MB. [2025-02-19T22:22:11.076Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-19T22:22:13.047Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-19T22:22:15.012Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-19T22:22:16.976Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-19T22:22:18.942Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-19T22:22:20.256Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-19T22:22:21.666Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-19T22:22:22.657Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-19T22:22:23.617Z] 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. [2025-02-19T22:22:23.617Z] The best model improves the baseline by 14.52%. [2025-02-19T22:22:23.617Z] Movies recommended for you: [2025-02-19T22:22:23.617Z] WARNING: This benchmark provides no result that can be validated. [2025-02-19T22:22:23.617Z] There is no way to check that no silent failure occurred. [2025-02-19T22:22:23.617Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15170.879 ms) ====== [2025-02-19T22:22:23.617Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-02-19T22:22:23.617Z] GC before operation: completed in 95.580 ms, heap usage 131.041 MB -> 50.021 MB. [2025-02-19T22:22:25.597Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-19T22:22:28.653Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-19T22:22:30.632Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-19T22:22:32.597Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-19T22:22:34.560Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-19T22:22:35.515Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-19T22:22:36.470Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-19T22:22:38.434Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-19T22:22:38.434Z] 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. [2025-02-19T22:22:38.434Z] The best model improves the baseline by 14.52%. [2025-02-19T22:22:38.434Z] Movies recommended for you: [2025-02-19T22:22:38.434Z] WARNING: This benchmark provides no result that can be validated. [2025-02-19T22:22:38.434Z] There is no way to check that no silent failure occurred. [2025-02-19T22:22:38.434Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15083.090 ms) ====== [2025-02-19T22:22:38.434Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-02-19T22:22:38.434Z] GC before operation: completed in 98.073 ms, heap usage 296.972 MB -> 50.361 MB. [2025-02-19T22:22:41.498Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-19T22:22:43.462Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-19T22:22:45.463Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-19T22:22:47.607Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-19T22:22:48.577Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-19T22:22:50.587Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-19T22:22:51.544Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-19T22:22:53.504Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-19T22:22:53.504Z] 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. [2025-02-19T22:22:53.504Z] The best model improves the baseline by 14.52%. [2025-02-19T22:22:53.504Z] Movies recommended for you: [2025-02-19T22:22:53.504Z] WARNING: This benchmark provides no result that can be validated. [2025-02-19T22:22:53.504Z] There is no way to check that no silent failure occurred. [2025-02-19T22:22:53.504Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14779.356 ms) ====== [2025-02-19T22:22:53.504Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-02-19T22:22:53.504Z] GC before operation: completed in 97.277 ms, heap usage 80.097 MB -> 49.854 MB. [2025-02-19T22:22:55.485Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-19T22:22:58.528Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-19T22:23:00.495Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-19T22:23:02.484Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-19T22:23:04.072Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-19T22:23:05.030Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-19T22:23:06.993Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-19T22:23:08.078Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-19T22:23:08.078Z] 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. [2025-02-19T22:23:08.079Z] The best model improves the baseline by 14.52%. [2025-02-19T22:23:08.079Z] Movies recommended for you: [2025-02-19T22:23:08.079Z] WARNING: This benchmark provides no result that can be validated. [2025-02-19T22:23:08.079Z] There is no way to check that no silent failure occurred. [2025-02-19T22:23:08.079Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14527.029 ms) ====== [2025-02-19T22:23:08.079Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-02-19T22:23:08.079Z] GC before operation: completed in 93.169 ms, heap usage 155.287 MB -> 50.185 MB. [2025-02-19T22:23:10.040Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-19T22:23:13.078Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-19T22:23:15.049Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-19T22:23:17.021Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-19T22:23:17.977Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-19T22:23:19.952Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-19T22:23:20.910Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-19T22:23:21.871Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-19T22:23:22.830Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-02-19T22:23:22.830Z] The best model improves the baseline by 14.52%. [2025-02-19T22:23:22.830Z] Movies recommended for you: [2025-02-19T22:23:22.830Z] WARNING: This benchmark provides no result that can be validated. [2025-02-19T22:23:22.830Z] There is no way to check that no silent failure occurred. [2025-02-19T22:23:22.830Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14278.915 ms) ====== [2025-02-19T22:23:22.830Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-02-19T22:23:22.830Z] GC before operation: completed in 109.966 ms, heap usage 152.451 MB -> 50.197 MB. [2025-02-19T22:23:24.796Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-19T22:23:26.761Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-19T22:23:29.794Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-19T22:23:31.764Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-19T22:23:32.720Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-19T22:23:33.702Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-19T22:23:35.672Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-19T22:23:36.642Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-19T22:23:36.642Z] 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. [2025-02-19T22:23:36.643Z] The best model improves the baseline by 14.52%. [2025-02-19T22:23:37.599Z] Movies recommended for you: [2025-02-19T22:23:37.599Z] WARNING: This benchmark provides no result that can be validated. [2025-02-19T22:23:37.599Z] There is no way to check that no silent failure occurred. [2025-02-19T22:23:37.599Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14502.704 ms) ====== [2025-02-19T22:23:37.599Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-02-19T22:23:37.599Z] GC before operation: completed in 102.965 ms, heap usage 123.354 MB -> 50.052 MB. [2025-02-19T22:23:39.569Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-19T22:23:41.570Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-19T22:23:43.548Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-19T22:23:46.537Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-19T22:23:47.496Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-19T22:23:48.455Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-19T22:23:50.466Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-19T22:23:51.437Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-19T22:23:51.437Z] 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. [2025-02-19T22:23:51.437Z] The best model improves the baseline by 14.52%. [2025-02-19T22:23:51.437Z] Movies recommended for you: [2025-02-19T22:23:51.437Z] WARNING: This benchmark provides no result that can be validated. [2025-02-19T22:23:51.437Z] There is no way to check that no silent failure occurred. [2025-02-19T22:23:51.437Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14594.907 ms) ====== [2025-02-19T22:23:51.437Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-02-19T22:23:52.393Z] GC before operation: completed in 101.695 ms, heap usage 310.451 MB -> 50.276 MB. [2025-02-19T22:23:54.385Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-19T22:23:56.358Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-19T22:23:58.338Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-19T22:24:00.300Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-19T22:24:02.261Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-19T22:24:03.219Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-19T22:24:04.173Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-19T22:24:06.146Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-19T22:24:06.146Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-02-19T22:24:06.146Z] The best model improves the baseline by 14.52%. [2025-02-19T22:24:06.146Z] Movies recommended for you: [2025-02-19T22:24:06.146Z] WARNING: This benchmark provides no result that can be validated. [2025-02-19T22:24:06.146Z] There is no way to check that no silent failure occurred. [2025-02-19T22:24:06.146Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14340.831 ms) ====== [2025-02-19T22:24:06.146Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-02-19T22:24:06.146Z] GC before operation: completed in 93.186 ms, heap usage 270.832 MB -> 50.428 MB. [2025-02-19T22:24:08.109Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-19T22:24:11.149Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-19T22:24:13.108Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-19T22:24:15.099Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-19T22:24:16.059Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-19T22:24:17.024Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-19T22:24:19.010Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-19T22:24:19.969Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-19T22:24:19.969Z] 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. [2025-02-19T22:24:20.931Z] The best model improves the baseline by 14.52%. [2025-02-19T22:24:20.931Z] Movies recommended for you: [2025-02-19T22:24:20.931Z] WARNING: This benchmark provides no result that can be validated. [2025-02-19T22:24:20.931Z] There is no way to check that no silent failure occurred. [2025-02-19T22:24:20.931Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14144.380 ms) ====== [2025-02-19T22:24:20.931Z] ----------------------------------- [2025-02-19T22:24:20.931Z] renaissance-movie-lens_0_PASSED [2025-02-19T22:24:20.931Z] ----------------------------------- [2025-02-19T22:24:20.931Z] [2025-02-19T22:24:20.931Z] TEST TEARDOWN: [2025-02-19T22:24:20.931Z] Nothing to be done for teardown. [2025-02-19T22:24:20.931Z] renaissance-movie-lens_0 Finish Time: Wed Feb 19 22:24:20 2025 Epoch Time (ms): 1740003860543