[2024-08-14T21:38:49.737Z] Running test renaissance-movie-lens_0 ... [2024-08-14T21:38:49.737Z] =============================================== [2024-08-14T21:38:49.737Z] renaissance-movie-lens_0 Start Time: Wed Aug 14 21:38:49 2024 Epoch Time (ms): 1723671529290 [2024-08-14T21:38:49.737Z] variation: NoOptions [2024-08-14T21:38:49.737Z] JVM_OPTIONS: [2024-08-14T21:38:49.737Z] { \ [2024-08-14T21:38:49.737Z] echo ""; echo "TEST SETUP:"; \ [2024-08-14T21:38:49.737Z] echo "Nothing to be done for setup."; \ [2024-08-14T21:38:49.737Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17236705681355/renaissance-movie-lens_0"; \ [2024-08-14T21:38:49.737Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17236705681355/renaissance-movie-lens_0"; \ [2024-08-14T21:38:49.737Z] echo ""; echo "TESTING:"; \ [2024-08-14T21:38:49.737Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17236705681355/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-08-14T21:38:49.737Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17236705681355/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-14T21:38:49.737Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-14T21:38:49.737Z] echo "Nothing to be done for teardown."; \ [2024-08-14T21:38:49.737Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17236705681355/TestTargetResult"; [2024-08-14T21:38:49.737Z] [2024-08-14T21:38:49.737Z] TEST SETUP: [2024-08-14T21:38:49.737Z] Nothing to be done for setup. [2024-08-14T21:38:49.737Z] [2024-08-14T21:38:49.737Z] TESTING: [2024-08-14T21:38:53.801Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-14T21:38:54.729Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-08-14T21:38:58.794Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-14T21:38:58.794Z] Training: 60056, validation: 20285, test: 19854 [2024-08-14T21:38:58.794Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-14T21:38:58.794Z] GC before operation: completed in 75.793 ms, heap usage 98.976 MB -> 36.442 MB. [2024-08-14T21:39:04.065Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-14T21:39:07.025Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-14T21:39:09.997Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-14T21:39:13.096Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-14T21:39:15.030Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-14T21:39:15.962Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-14T21:39:17.874Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-14T21:39:18.812Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-14T21:39:19.743Z] 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. [2024-08-14T21:39:19.743Z] The best model improves the baseline by 14.52%. [2024-08-14T21:39:19.743Z] Movies recommended for you: [2024-08-14T21:39:19.743Z] WARNING: This benchmark provides no result that can be validated. [2024-08-14T21:39:19.743Z] There is no way to check that no silent failure occurred. [2024-08-14T21:39:19.743Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (21039.851 ms) ====== [2024-08-14T21:39:19.743Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-14T21:39:19.743Z] GC before operation: completed in 84.536 ms, heap usage 315.638 MB -> 48.816 MB. [2024-08-14T21:39:22.714Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-14T21:39:24.625Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-14T21:39:27.576Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-14T21:39:29.488Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-14T21:39:31.617Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-14T21:39:32.553Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-14T21:39:34.462Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-14T21:39:35.390Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-14T21:39:36.318Z] 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. [2024-08-14T21:39:36.318Z] The best model improves the baseline by 14.52%. [2024-08-14T21:39:36.318Z] Movies recommended for you: [2024-08-14T21:39:36.318Z] WARNING: This benchmark provides no result that can be validated. [2024-08-14T21:39:36.318Z] There is no way to check that no silent failure occurred. [2024-08-14T21:39:36.318Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (16288.738 ms) ====== [2024-08-14T21:39:36.318Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-14T21:39:36.318Z] GC before operation: completed in 90.964 ms, heap usage 206.154 MB -> 49.090 MB. [2024-08-14T21:39:38.237Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-14T21:39:41.189Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-14T21:39:43.097Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-14T21:39:45.009Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-14T21:39:46.918Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-14T21:39:47.889Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-14T21:39:49.819Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-14T21:39:50.749Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-14T21:39:50.750Z] 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. [2024-08-14T21:39:50.750Z] The best model improves the baseline by 14.52%. [2024-08-14T21:39:51.683Z] Movies recommended for you: [2024-08-14T21:39:51.683Z] WARNING: This benchmark provides no result that can be validated. [2024-08-14T21:39:51.683Z] There is no way to check that no silent failure occurred. [2024-08-14T21:39:51.683Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (14999.787 ms) ====== [2024-08-14T21:39:51.683Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-14T21:39:51.683Z] GC before operation: completed in 82.761 ms, heap usage 261.080 MB -> 49.469 MB. [2024-08-14T21:39:54.099Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-14T21:39:56.009Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-14T21:39:57.920Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-14T21:39:59.832Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-14T21:40:01.751Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-14T21:40:02.682Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-14T21:40:04.595Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-14T21:40:05.524Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-14T21:40:05.524Z] 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. [2024-08-14T21:40:05.524Z] The best model improves the baseline by 14.52%. [2024-08-14T21:40:05.524Z] Movies recommended for you: [2024-08-14T21:40:05.524Z] WARNING: This benchmark provides no result that can be validated. [2024-08-14T21:40:05.524Z] There is no way to check that no silent failure occurred. [2024-08-14T21:40:05.524Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (14445.915 ms) ====== [2024-08-14T21:40:05.524Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-14T21:40:05.524Z] GC before operation: completed in 80.850 ms, heap usage 140.707 MB -> 49.624 MB. [2024-08-14T21:40:08.474Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-14T21:40:10.425Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-14T21:40:12.473Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-14T21:40:15.428Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-14T21:40:16.363Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-14T21:40:17.294Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-14T21:40:19.205Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-14T21:40:20.135Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-14T21:40:20.135Z] 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. [2024-08-14T21:40:20.135Z] The best model improves the baseline by 14.52%. [2024-08-14T21:40:20.135Z] Movies recommended for you: [2024-08-14T21:40:20.135Z] WARNING: This benchmark provides no result that can be validated. [2024-08-14T21:40:20.135Z] There is no way to check that no silent failure occurred. [2024-08-14T21:40:20.135Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (14631.129 ms) ====== [2024-08-14T21:40:20.135Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-14T21:40:20.135Z] GC before operation: completed in 77.435 ms, heap usage 214.258 MB -> 49.917 MB. [2024-08-14T21:40:23.091Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-14T21:40:25.003Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-14T21:40:26.915Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-14T21:40:28.828Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-14T21:40:30.741Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-14T21:40:31.677Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-14T21:40:32.606Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-14T21:40:34.519Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-14T21:40:34.519Z] 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. [2024-08-14T21:40:34.519Z] The best model improves the baseline by 14.52%. [2024-08-14T21:40:34.519Z] Movies recommended for you: [2024-08-14T21:40:34.519Z] WARNING: This benchmark provides no result that can be validated. [2024-08-14T21:40:34.519Z] There is no way to check that no silent failure occurred. [2024-08-14T21:40:34.519Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (13873.997 ms) ====== [2024-08-14T21:40:34.519Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-14T21:40:34.519Z] GC before operation: completed in 83.640 ms, heap usage 327.295 MB -> 49.903 MB. [2024-08-14T21:40:37.490Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-14T21:40:39.400Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-14T21:40:41.309Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-14T21:40:43.220Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-14T21:40:44.151Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-14T21:40:46.066Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-14T21:40:46.996Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-14T21:40:47.929Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-14T21:40:47.929Z] 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. [2024-08-14T21:40:48.859Z] The best model improves the baseline by 14.52%. [2024-08-14T21:40:48.859Z] Movies recommended for you: [2024-08-14T21:40:48.859Z] WARNING: This benchmark provides no result that can be validated. [2024-08-14T21:40:48.859Z] There is no way to check that no silent failure occurred. [2024-08-14T21:40:48.859Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (13994.175 ms) ====== [2024-08-14T21:40:48.859Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-14T21:40:48.859Z] GC before operation: completed in 80.707 ms, heap usage 151.274 MB -> 49.927 MB. [2024-08-14T21:40:50.789Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-14T21:40:52.700Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-14T21:40:54.614Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-14T21:40:56.527Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-14T21:40:58.439Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-14T21:40:59.372Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-14T21:41:00.302Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-14T21:41:02.214Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-14T21:41:02.214Z] 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. [2024-08-14T21:41:02.214Z] The best model improves the baseline by 14.52%. [2024-08-14T21:41:02.214Z] Movies recommended for you: [2024-08-14T21:41:02.214Z] WARNING: This benchmark provides no result that can be validated. [2024-08-14T21:41:02.214Z] There is no way to check that no silent failure occurred. [2024-08-14T21:41:02.214Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (13650.050 ms) ====== [2024-08-14T21:41:02.214Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-14T21:41:02.214Z] GC before operation: completed in 79.820 ms, heap usage 121.610 MB -> 50.202 MB. [2024-08-14T21:41:04.127Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-14T21:41:07.283Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-14T21:41:08.215Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-14T21:41:10.126Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-14T21:41:12.054Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-14T21:41:12.985Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-14T21:41:13.916Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-14T21:41:15.828Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-14T21:41:15.828Z] 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. [2024-08-14T21:41:15.828Z] The best model improves the baseline by 14.52%. [2024-08-14T21:41:15.828Z] Movies recommended for you: [2024-08-14T21:41:15.828Z] WARNING: This benchmark provides no result that can be validated. [2024-08-14T21:41:15.828Z] There is no way to check that no silent failure occurred. [2024-08-14T21:41:15.828Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (13564.607 ms) ====== [2024-08-14T21:41:15.828Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-14T21:41:15.828Z] GC before operation: completed in 82.456 ms, heap usage 175.928 MB -> 50.058 MB. [2024-08-14T21:41:17.743Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-14T21:41:19.653Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-14T21:41:22.664Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-14T21:41:24.573Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-14T21:41:25.508Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-14T21:41:27.423Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-14T21:41:28.356Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-14T21:41:29.287Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-14T21:41:30.220Z] 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. [2024-08-14T21:41:30.220Z] The best model improves the baseline by 14.52%. [2024-08-14T21:41:30.220Z] Movies recommended for you: [2024-08-14T21:41:30.220Z] WARNING: This benchmark provides no result that can be validated. [2024-08-14T21:41:30.220Z] There is no way to check that no silent failure occurred. [2024-08-14T21:41:30.220Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14031.497 ms) ====== [2024-08-14T21:41:30.220Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-14T21:41:30.220Z] GC before operation: completed in 84.636 ms, heap usage 123.497 MB -> 50.119 MB. [2024-08-14T21:41:32.131Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-14T21:41:34.046Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-14T21:41:35.965Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-14T21:41:37.875Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-14T21:41:39.788Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-14T21:41:40.733Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-14T21:41:41.665Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-14T21:41:43.577Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-14T21:41:43.577Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-14T21:41:43.577Z] The best model improves the baseline by 14.52%. [2024-08-14T21:41:43.577Z] Movies recommended for you: [2024-08-14T21:41:43.577Z] WARNING: This benchmark provides no result that can be validated. [2024-08-14T21:41:43.577Z] There is no way to check that no silent failure occurred. [2024-08-14T21:41:43.577Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (13485.804 ms) ====== [2024-08-14T21:41:43.577Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-14T21:41:43.577Z] GC before operation: completed in 81.736 ms, heap usage 89.311 MB -> 49.886 MB. [2024-08-14T21:41:45.488Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-14T21:41:47.399Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-14T21:41:49.311Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-14T21:41:51.221Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-14T21:41:53.131Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-14T21:41:54.062Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-14T21:41:54.991Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-14T21:41:56.688Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-14T21:41:56.688Z] 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. [2024-08-14T21:41:56.688Z] The best model improves the baseline by 14.52%. [2024-08-14T21:41:56.688Z] Movies recommended for you: [2024-08-14T21:41:56.688Z] WARNING: This benchmark provides no result that can be validated. [2024-08-14T21:41:56.688Z] There is no way to check that no silent failure occurred. [2024-08-14T21:41:56.688Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (13381.421 ms) ====== [2024-08-14T21:41:56.688Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-14T21:41:56.688Z] GC before operation: completed in 80.756 ms, heap usage 296.445 MB -> 50.159 MB. [2024-08-14T21:41:59.639Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-14T21:42:01.553Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-14T21:42:03.468Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-14T21:42:05.379Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-14T21:42:06.309Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-14T21:42:07.242Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-14T21:42:09.156Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-14T21:42:10.087Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-14T21:42:10.087Z] 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. [2024-08-14T21:42:11.056Z] The best model improves the baseline by 14.52%. [2024-08-14T21:42:11.056Z] Movies recommended for you: [2024-08-14T21:42:11.056Z] WARNING: This benchmark provides no result that can be validated. [2024-08-14T21:42:11.056Z] There is no way to check that no silent failure occurred. [2024-08-14T21:42:11.056Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (13514.419 ms) ====== [2024-08-14T21:42:11.056Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-14T21:42:11.056Z] GC before operation: completed in 82.882 ms, heap usage 184.674 MB -> 50.300 MB. [2024-08-14T21:42:12.965Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-14T21:42:14.878Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-14T21:42:16.787Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-14T21:42:18.699Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-14T21:42:20.610Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-14T21:42:21.540Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-14T21:42:22.471Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-14T21:42:24.388Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-14T21:42:24.388Z] 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. [2024-08-14T21:42:24.388Z] The best model improves the baseline by 14.52%. [2024-08-14T21:42:24.388Z] Movies recommended for you: [2024-08-14T21:42:24.388Z] WARNING: This benchmark provides no result that can be validated. [2024-08-14T21:42:24.388Z] There is no way to check that no silent failure occurred. [2024-08-14T21:42:24.388Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (13683.659 ms) ====== [2024-08-14T21:42:24.388Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-14T21:42:24.388Z] GC before operation: completed in 95.592 ms, heap usage 199.294 MB -> 49.990 MB. [2024-08-14T21:42:27.339Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-14T21:42:29.248Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-14T21:42:31.161Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-14T21:42:33.074Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-14T21:42:34.008Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-14T21:42:35.919Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-14T21:42:36.849Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-14T21:42:37.780Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-14T21:42:38.714Z] 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. [2024-08-14T21:42:38.714Z] The best model improves the baseline by 14.52%. [2024-08-14T21:42:38.714Z] Movies recommended for you: [2024-08-14T21:42:38.714Z] WARNING: This benchmark provides no result that can be validated. [2024-08-14T21:42:38.714Z] There is no way to check that no silent failure occurred. [2024-08-14T21:42:38.714Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (13988.598 ms) ====== [2024-08-14T21:42:38.714Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-14T21:42:38.714Z] GC before operation: completed in 96.412 ms, heap usage 263.873 MB -> 50.262 MB. [2024-08-14T21:42:40.628Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-14T21:42:43.583Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-14T21:42:45.493Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-14T21:42:47.404Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-14T21:42:48.333Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-14T21:42:50.246Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-14T21:42:51.176Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-14T21:42:52.276Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-14T21:42:52.276Z] 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. [2024-08-14T21:42:52.276Z] The best model improves the baseline by 14.52%. [2024-08-14T21:42:53.205Z] Movies recommended for you: [2024-08-14T21:42:53.205Z] WARNING: This benchmark provides no result that can be validated. [2024-08-14T21:42:53.205Z] There is no way to check that no silent failure occurred. [2024-08-14T21:42:53.205Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14205.647 ms) ====== [2024-08-14T21:42:53.205Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-14T21:42:53.205Z] GC before operation: completed in 89.207 ms, heap usage 80.348 MB -> 50.159 MB. [2024-08-14T21:42:56.130Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-14T21:42:57.066Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-14T21:42:58.978Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-14T21:43:00.897Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-14T21:43:01.828Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-14T21:43:03.743Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-14T21:43:04.673Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-14T21:43:05.610Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-14T21:43:06.545Z] 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. [2024-08-14T21:43:06.545Z] The best model improves the baseline by 14.52%. [2024-08-14T21:43:06.545Z] Movies recommended for you: [2024-08-14T21:43:06.545Z] WARNING: This benchmark provides no result that can be validated. [2024-08-14T21:43:06.545Z] There is no way to check that no silent failure occurred. [2024-08-14T21:43:06.545Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (13473.127 ms) ====== [2024-08-14T21:43:06.545Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-14T21:43:06.545Z] GC before operation: completed in 89.281 ms, heap usage 318.865 MB -> 50.225 MB. [2024-08-14T21:43:08.461Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-14T21:43:10.373Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-14T21:43:13.326Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-14T21:43:14.257Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-14T21:43:16.179Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-14T21:43:17.116Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-14T21:43:18.048Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-14T21:43:19.960Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-14T21:43:19.960Z] 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. [2024-08-14T21:43:19.960Z] The best model improves the baseline by 14.52%. [2024-08-14T21:43:19.960Z] Movies recommended for you: [2024-08-14T21:43:19.960Z] WARNING: This benchmark provides no result that can be validated. [2024-08-14T21:43:19.960Z] There is no way to check that no silent failure occurred. [2024-08-14T21:43:19.960Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (13562.005 ms) ====== [2024-08-14T21:43:19.960Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-14T21:43:19.960Z] GC before operation: completed in 82.037 ms, heap usage 203.557 MB -> 50.202 MB. [2024-08-14T21:43:21.882Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-14T21:43:23.795Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-14T21:43:25.708Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-14T21:43:27.621Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-14T21:43:29.534Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-14T21:43:30.470Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-14T21:43:31.401Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-14T21:43:33.313Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-14T21:43:33.313Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-14T21:43:33.313Z] The best model improves the baseline by 14.52%. [2024-08-14T21:43:33.313Z] Movies recommended for you: [2024-08-14T21:43:33.313Z] WARNING: This benchmark provides no result that can be validated. [2024-08-14T21:43:33.313Z] There is no way to check that no silent failure occurred. [2024-08-14T21:43:33.313Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (13326.735 ms) ====== [2024-08-14T21:43:33.313Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-14T21:43:33.313Z] GC before operation: completed in 80.916 ms, heap usage 107.806 MB -> 50.314 MB. [2024-08-14T21:43:36.264Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-14T21:43:38.177Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-14T21:43:40.085Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-14T21:43:41.997Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-14T21:43:42.928Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-14T21:43:43.859Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-14T21:43:45.773Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-14T21:43:46.703Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-14T21:43:46.703Z] 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. [2024-08-14T21:43:46.703Z] The best model improves the baseline by 14.52%. [2024-08-14T21:43:46.703Z] Movies recommended for you: [2024-08-14T21:43:46.703Z] WARNING: This benchmark provides no result that can be validated. [2024-08-14T21:43:46.703Z] There is no way to check that no silent failure occurred. [2024-08-14T21:43:46.703Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (13572.711 ms) ====== [2024-08-14T21:43:47.637Z] ----------------------------------- [2024-08-14T21:43:47.637Z] renaissance-movie-lens_0_PASSED [2024-08-14T21:43:47.637Z] ----------------------------------- [2024-08-14T21:43:47.637Z] [2024-08-14T21:43:47.637Z] TEST TEARDOWN: [2024-08-14T21:43:47.637Z] Nothing to be done for teardown. [2024-08-14T21:43:47.637Z] renaissance-movie-lens_0 Finish Time: Wed Aug 14 21:43:46 2024 Epoch Time (ms): 1723671827001