[2024-11-25T04:49:34.870Z] Running test renaissance-movie-lens_0 ... [2024-11-25T04:49:34.870Z] =============================================== [2024-11-25T04:49:34.870Z] renaissance-movie-lens_0 Start Time: Mon Nov 25 04:49:34 2024 Epoch Time (ms): 1732510174806 [2024-11-25T04:49:35.206Z] variation: NoOptions [2024-11-25T04:49:35.206Z] JVM_OPTIONS: [2024-11-25T04:49:35.206Z] { \ [2024-11-25T04:49:35.206Z] echo ""; echo "TEST SETUP:"; \ [2024-11-25T04:49:35.206Z] echo "Nothing to be done for setup."; \ [2024-11-25T04:49:35.206Z] mkdir -p "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17325089071198\\renaissance-movie-lens_0"; \ [2024-11-25T04:49:35.206Z] cd "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17325089071198\\renaissance-movie-lens_0"; \ [2024-11-25T04:49:35.206Z] echo ""; echo "TESTING:"; \ [2024-11-25T04:49:35.206Z] "c:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/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 "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17325089071198\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2024-11-25T04:49:35.206Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17325089071198\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-11-25T04:49:35.206Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-11-25T04:49:35.206Z] echo "Nothing to be done for teardown."; \ [2024-11-25T04:49:35.206Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17325089071198\\TestTargetResult"; [2024-11-25T04:49:35.206Z] [2024-11-25T04:49:35.206Z] TEST SETUP: [2024-11-25T04:49:35.206Z] Nothing to be done for setup. [2024-11-25T04:49:35.206Z] [2024-11-25T04:49:35.206Z] TESTING: [2024-11-25T04:49:45.911Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-11-25T04:49:47.540Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-11-25T04:49:50.596Z] Got 100004 ratings from 671 users on 9066 movies. [2024-11-25T04:49:50.596Z] Training: 60056, validation: 20285, test: 19854 [2024-11-25T04:49:50.596Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-11-25T04:49:50.938Z] GC before operation: completed in 71.057 ms, heap usage 101.339 MB -> 36.939 MB. [2024-11-25T04:50:04.152Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T04:50:11.347Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T04:50:20.187Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T04:50:26.029Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T04:50:30.739Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T04:50:34.454Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T04:50:39.152Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T04:50:42.913Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T04:50:42.913Z] 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. [2024-11-25T04:50:42.913Z] The best model improves the baseline by 14.52%. [2024-11-25T04:50:43.241Z] Movies recommended for you: [2024-11-25T04:50:43.241Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T04:50:43.242Z] There is no way to check that no silent failure occurred. [2024-11-25T04:50:43.242Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (52441.177 ms) ====== [2024-11-25T04:50:43.242Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-11-25T04:50:43.242Z] GC before operation: completed in 108.722 ms, heap usage 215.907 MB -> 48.672 MB. [2024-11-25T04:50:50.490Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T04:50:57.695Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T04:51:06.487Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T04:51:12.300Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T04:51:16.028Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T04:51:19.752Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T04:51:23.479Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T04:51:28.231Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T04:51:28.231Z] 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. [2024-11-25T04:51:28.231Z] The best model improves the baseline by 14.52%. [2024-11-25T04:51:28.231Z] Movies recommended for you: [2024-11-25T04:51:28.231Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T04:51:28.231Z] There is no way to check that no silent failure occurred. [2024-11-25T04:51:28.231Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (44851.249 ms) ====== [2024-11-25T04:51:28.231Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-11-25T04:51:28.231Z] GC before operation: completed in 91.098 ms, heap usage 213.743 MB -> 52.805 MB. [2024-11-25T04:51:35.450Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T04:51:42.662Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T04:51:49.825Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T04:51:55.640Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T04:51:59.389Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T04:52:03.135Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T04:52:07.803Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T04:52:10.702Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T04:52:11.407Z] 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. [2024-11-25T04:52:11.408Z] The best model improves the baseline by 14.52%. [2024-11-25T04:52:11.408Z] Movies recommended for you: [2024-11-25T04:52:11.408Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T04:52:11.408Z] There is no way to check that no silent failure occurred. [2024-11-25T04:52:11.408Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (43234.533 ms) ====== [2024-11-25T04:52:11.408Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-11-25T04:52:11.748Z] GC before operation: completed in 95.278 ms, heap usage 90.382 MB -> 54.140 MB. [2024-11-25T04:52:18.921Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T04:52:26.091Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T04:52:33.263Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T04:52:39.084Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T04:52:42.798Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T04:52:46.510Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T04:52:50.215Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T04:52:53.923Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T04:52:54.254Z] 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. [2024-11-25T04:52:54.254Z] The best model improves the baseline by 14.52%. [2024-11-25T04:52:54.624Z] Movies recommended for you: [2024-11-25T04:52:54.624Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T04:52:54.624Z] There is no way to check that no silent failure occurred. [2024-11-25T04:52:54.624Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (42969.438 ms) ====== [2024-11-25T04:52:54.624Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-11-25T04:52:54.624Z] GC before operation: completed in 90.240 ms, heap usage 184.211 MB -> 53.429 MB. [2024-11-25T04:53:01.844Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T04:53:09.038Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T04:53:16.222Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T04:53:22.040Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T04:53:25.760Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T04:53:30.464Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T04:53:34.183Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T04:53:37.094Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T04:53:37.802Z] 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. [2024-11-25T04:53:37.802Z] The best model improves the baseline by 14.52%. [2024-11-25T04:53:37.802Z] Movies recommended for you: [2024-11-25T04:53:37.802Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T04:53:37.802Z] There is no way to check that no silent failure occurred. [2024-11-25T04:53:37.802Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (43204.738 ms) ====== [2024-11-25T04:53:37.802Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-11-25T04:53:37.802Z] GC before operation: completed in 91.624 ms, heap usage 123.522 MB -> 52.463 MB. [2024-11-25T04:53:44.987Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T04:53:52.173Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T04:53:59.377Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T04:54:05.217Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T04:54:09.914Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T04:54:13.634Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T04:54:17.353Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T04:54:21.080Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T04:54:21.080Z] 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. [2024-11-25T04:54:21.080Z] The best model improves the baseline by 14.52%. [2024-11-25T04:54:21.408Z] Movies recommended for you: [2024-11-25T04:54:21.408Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T04:54:21.408Z] There is no way to check that no silent failure occurred. [2024-11-25T04:54:21.408Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (43397.786 ms) ====== [2024-11-25T04:54:21.408Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-11-25T04:54:21.408Z] GC before operation: completed in 86.786 ms, heap usage 197.702 MB -> 53.477 MB. [2024-11-25T04:54:28.625Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T04:54:35.816Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T04:54:41.662Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T04:54:48.845Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T04:54:51.753Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T04:54:55.480Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T04:54:59.198Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T04:55:02.972Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T04:55:03.307Z] 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. [2024-11-25T04:55:03.307Z] The best model improves the baseline by 14.52%. [2024-11-25T04:55:03.637Z] Movies recommended for you: [2024-11-25T04:55:03.637Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T04:55:03.637Z] There is no way to check that no silent failure occurred. [2024-11-25T04:55:03.637Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (42158.065 ms) ====== [2024-11-25T04:55:03.637Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-11-25T04:55:03.637Z] GC before operation: completed in 91.388 ms, heap usage 316.969 MB -> 52.361 MB. [2024-11-25T04:55:10.840Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T04:55:18.026Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T04:55:25.234Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T04:55:31.064Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T04:55:35.765Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T04:55:38.683Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T04:55:43.378Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T04:55:46.300Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T04:55:47.004Z] 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. [2024-11-25T04:55:47.004Z] The best model improves the baseline by 14.52%. [2024-11-25T04:55:47.004Z] Movies recommended for you: [2024-11-25T04:55:47.004Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T04:55:47.004Z] There is no way to check that no silent failure occurred. [2024-11-25T04:55:47.004Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (43335.338 ms) ====== [2024-11-25T04:55:47.004Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-11-25T04:55:47.004Z] GC before operation: completed in 85.063 ms, heap usage 213.971 MB -> 50.709 MB. [2024-11-25T04:55:54.223Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T04:56:00.063Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T04:56:07.268Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T04:56:14.476Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T04:56:18.219Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T04:56:21.953Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T04:56:25.701Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T04:56:29.441Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T04:56:29.777Z] 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. [2024-11-25T04:56:29.777Z] The best model improves the baseline by 14.52%. [2024-11-25T04:56:29.777Z] Movies recommended for you: [2024-11-25T04:56:29.777Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T04:56:29.777Z] There is no way to check that no silent failure occurred. [2024-11-25T04:56:29.777Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (42693.673 ms) ====== [2024-11-25T04:56:29.777Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-11-25T04:56:29.777Z] GC before operation: completed in 85.771 ms, heap usage 132.625 MB -> 50.484 MB. [2024-11-25T04:56:37.009Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T04:56:44.209Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T04:56:51.405Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T04:56:57.242Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T04:57:00.982Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T04:57:05.664Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T04:57:09.440Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T04:57:13.162Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T04:57:13.495Z] 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. [2024-11-25T04:57:13.495Z] The best model improves the baseline by 14.52%. [2024-11-25T04:57:13.495Z] Movies recommended for you: [2024-11-25T04:57:13.495Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T04:57:13.495Z] There is no way to check that no silent failure occurred. [2024-11-25T04:57:13.495Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (43648.891 ms) ====== [2024-11-25T04:57:13.495Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-11-25T04:57:13.495Z] GC before operation: completed in 82.033 ms, heap usage 191.679 MB -> 50.668 MB. [2024-11-25T04:57:20.681Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T04:57:26.526Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T04:57:33.703Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T04:57:40.908Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T04:57:43.842Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T04:57:48.529Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T04:57:52.240Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T04:57:55.968Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T04:57:55.968Z] 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. [2024-11-25T04:57:56.303Z] The best model improves the baseline by 14.52%. [2024-11-25T04:57:56.303Z] Movies recommended for you: [2024-11-25T04:57:56.303Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T04:57:56.303Z] There is no way to check that no silent failure occurred. [2024-11-25T04:57:56.303Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (42667.226 ms) ====== [2024-11-25T04:57:56.303Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-11-25T04:57:56.303Z] GC before operation: completed in 82.698 ms, heap usage 189.041 MB -> 50.383 MB. [2024-11-25T04:58:03.494Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T04:58:10.685Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T04:58:17.897Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T04:58:23.722Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T04:58:27.439Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T04:58:31.193Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T04:58:34.991Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T04:58:38.720Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T04:58:39.050Z] 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. [2024-11-25T04:58:39.050Z] The best model improves the baseline by 14.52%. [2024-11-25T04:58:39.381Z] Movies recommended for you: [2024-11-25T04:58:39.381Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T04:58:39.381Z] There is no way to check that no silent failure occurred. [2024-11-25T04:58:39.382Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (43009.663 ms) ====== [2024-11-25T04:58:39.382Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-11-25T04:58:39.382Z] GC before operation: completed in 79.095 ms, heap usage 94.865 MB -> 51.180 MB. [2024-11-25T04:58:48.181Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T04:58:54.023Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T04:59:01.207Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T04:59:08.409Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T04:59:11.319Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T04:59:16.025Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T04:59:19.795Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T04:59:23.507Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T04:59:23.864Z] 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. [2024-11-25T04:59:23.864Z] The best model improves the baseline by 14.52%. [2024-11-25T04:59:23.864Z] Movies recommended for you: [2024-11-25T04:59:23.864Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T04:59:23.864Z] There is no way to check that no silent failure occurred. [2024-11-25T04:59:23.864Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (44521.850 ms) ====== [2024-11-25T04:59:23.864Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-11-25T04:59:24.207Z] GC before operation: completed in 97.725 ms, heap usage 101.954 MB -> 50.663 MB. [2024-11-25T04:59:31.416Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T04:59:37.245Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T04:59:44.419Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T04:59:51.605Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T04:59:54.527Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T04:59:58.260Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T05:00:02.939Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T05:00:06.699Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T05:00:06.699Z] 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. [2024-11-25T05:00:06.699Z] The best model improves the baseline by 14.52%. [2024-11-25T05:00:06.699Z] Movies recommended for you: [2024-11-25T05:00:06.699Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T05:00:06.699Z] There is no way to check that no silent failure occurred. [2024-11-25T05:00:06.699Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (42748.793 ms) ====== [2024-11-25T05:00:06.699Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-11-25T05:00:07.054Z] GC before operation: completed in 82.199 ms, heap usage 141.317 MB -> 50.409 MB. [2024-11-25T05:00:14.248Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T05:00:21.475Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T05:00:28.676Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T05:00:34.514Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T05:00:38.239Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T05:00:41.962Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T05:00:46.657Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T05:00:49.562Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T05:00:50.269Z] 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. [2024-11-25T05:00:50.269Z] The best model improves the baseline by 14.52%. [2024-11-25T05:00:50.269Z] Movies recommended for you: [2024-11-25T05:00:50.269Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T05:00:50.269Z] There is no way to check that no silent failure occurred. [2024-11-25T05:00:50.269Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (43379.400 ms) ====== [2024-11-25T05:00:50.269Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-11-25T05:00:50.269Z] GC before operation: completed in 82.614 ms, heap usage 101.278 MB -> 50.577 MB. [2024-11-25T05:00:57.462Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T05:01:04.625Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T05:01:10.449Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T05:01:17.607Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T05:01:21.327Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T05:01:25.090Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T05:01:28.844Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T05:01:32.562Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T05:01:32.939Z] 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. [2024-11-25T05:01:32.939Z] The best model improves the baseline by 14.52%. [2024-11-25T05:01:33.286Z] Movies recommended for you: [2024-11-25T05:01:33.286Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T05:01:33.286Z] There is no way to check that no silent failure occurred. [2024-11-25T05:01:33.286Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (42792.446 ms) ====== [2024-11-25T05:01:33.286Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-11-25T05:01:33.286Z] GC before operation: completed in 81.368 ms, heap usage 156.750 MB -> 50.722 MB. [2024-11-25T05:01:40.465Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T05:01:47.663Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T05:01:54.917Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T05:02:00.729Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T05:02:04.543Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T05:02:08.264Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T05:02:12.970Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T05:02:16.724Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T05:02:16.724Z] 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. [2024-11-25T05:02:16.724Z] The best model improves the baseline by 14.52%. [2024-11-25T05:02:17.053Z] Movies recommended for you: [2024-11-25T05:02:17.053Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T05:02:17.053Z] There is no way to check that no silent failure occurred. [2024-11-25T05:02:17.053Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (43782.344 ms) ====== [2024-11-25T05:02:17.053Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-11-25T05:02:17.053Z] GC before operation: completed in 85.974 ms, heap usage 92.166 MB -> 50.491 MB. [2024-11-25T05:02:24.246Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T05:02:31.436Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T05:02:38.613Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T05:02:44.438Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T05:02:48.177Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T05:02:51.903Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T05:02:56.605Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T05:03:00.336Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T05:03:00.336Z] 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. [2024-11-25T05:03:00.336Z] The best model improves the baseline by 14.52%. [2024-11-25T05:03:00.668Z] Movies recommended for you: [2024-11-25T05:03:00.668Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T05:03:00.668Z] There is no way to check that no silent failure occurred. [2024-11-25T05:03:00.668Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (43431.139 ms) ====== [2024-11-25T05:03:00.668Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-11-25T05:03:00.668Z] GC before operation: completed in 84.721 ms, heap usage 113.094 MB -> 50.571 MB. [2024-11-25T05:03:07.843Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T05:03:15.025Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T05:03:22.200Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T05:03:28.030Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T05:03:31.771Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T05:03:35.492Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T05:03:39.229Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T05:03:42.991Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T05:03:42.991Z] 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. [2024-11-25T05:03:42.991Z] The best model improves the baseline by 14.52%. [2024-11-25T05:03:42.991Z] Movies recommended for you: [2024-11-25T05:03:42.991Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T05:03:42.991Z] There is no way to check that no silent failure occurred. [2024-11-25T05:03:42.991Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (42456.233 ms) ====== [2024-11-25T05:03:42.991Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-11-25T05:03:43.333Z] GC before operation: completed in 94.006 ms, heap usage 135.980 MB -> 54.078 MB. [2024-11-25T05:03:50.512Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-25T05:03:56.348Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-25T05:04:05.143Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-25T05:04:11.007Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-25T05:04:14.748Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-25T05:04:18.478Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-25T05:04:22.211Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-25T05:04:25.931Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-25T05:04:26.624Z] 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. [2024-11-25T05:04:26.624Z] The best model improves the baseline by 14.52%. [2024-11-25T05:04:26.625Z] Movies recommended for you: [2024-11-25T05:04:26.625Z] WARNING: This benchmark provides no result that can be validated. [2024-11-25T05:04:26.625Z] There is no way to check that no silent failure occurred. [2024-11-25T05:04:26.625Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (43519.633 ms) ====== [2024-11-25T05:04:27.322Z] ----------------------------------- [2024-11-25T05:04:27.322Z] renaissance-movie-lens_0_PASSED [2024-11-25T05:04:27.322Z] ----------------------------------- [2024-11-25T05:04:28.006Z] [2024-11-25T05:04:28.007Z] TEST TEARDOWN: [2024-11-25T05:04:28.007Z] Nothing to be done for teardown. [2024-11-25T05:04:28.007Z] renaissance-movie-lens_0 Finish Time: Mon Nov 25 05:04:27 2024 Epoch Time (ms): 1732511067736