[2024-08-22T08:21:39.078Z] Running test renaissance-movie-lens_0 ... [2024-08-22T08:21:39.078Z] =============================================== [2024-08-22T08:21:39.381Z] renaissance-movie-lens_0 Start Time: Thu Aug 22 08:21:39 2024 Epoch Time (ms): 1724314899116 [2024-08-22T08:21:39.693Z] variation: NoOptions [2024-08-22T08:21:39.693Z] JVM_OPTIONS: [2024-08-22T08:21:39.693Z] { \ [2024-08-22T08:21:39.693Z] echo ""; echo "TEST SETUP:"; \ [2024-08-22T08:21:39.693Z] echo "Nothing to be done for setup."; \ [2024-08-22T08:21:39.693Z] mkdir -p "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_1724313576892\\renaissance-movie-lens_0"; \ [2024-08-22T08:21:39.693Z] cd "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_1724313576892\\renaissance-movie-lens_0"; \ [2024-08-22T08:21:39.693Z] echo ""; echo "TESTING:"; \ [2024-08-22T08:21:39.693Z] "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_1724313576892\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2024-08-22T08:21:39.693Z] 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_1724313576892\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-22T08:21:39.693Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-22T08:21:39.693Z] echo "Nothing to be done for teardown."; \ [2024-08-22T08:21:39.693Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_1724313576892\\TestTargetResult"; [2024-08-22T08:21:40.006Z] [2024-08-22T08:21:40.006Z] TEST SETUP: [2024-08-22T08:21:40.006Z] Nothing to be done for setup. [2024-08-22T08:21:40.006Z] [2024-08-22T08:21:40.006Z] TESTING: [2024-08-22T08:21:52.798Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-22T08:21:52.798Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-08-22T08:21:56.555Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-22T08:21:56.555Z] Training: 60056, validation: 20285, test: 19854 [2024-08-22T08:21:56.555Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-22T08:21:56.555Z] GC before operation: completed in 63.771 ms, heap usage 86.574 MB -> 36.924 MB. [2024-08-22T08:22:09.529Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:22:16.575Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:22:25.272Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:22:32.312Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:22:35.956Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:22:40.559Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:22:45.149Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:22:48.783Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:22:49.492Z] 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. [2024-08-22T08:22:49.492Z] The best model improves the baseline by 14.52%. [2024-08-22T08:22:49.492Z] Movies recommended for you: [2024-08-22T08:22:49.492Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:22:49.492Z] There is no way to check that no silent failure occurred. [2024-08-22T08:22:49.492Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (53144.294 ms) ====== [2024-08-22T08:22:49.492Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-22T08:22:49.809Z] GC before operation: completed in 94.332 ms, heap usage 263.569 MB -> 47.444 MB. [2024-08-22T08:22:56.934Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:23:03.979Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:23:12.636Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:23:18.364Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:23:22.967Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:23:26.588Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:23:31.176Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:23:34.796Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:23:35.202Z] 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. [2024-08-22T08:23:35.202Z] The best model improves the baseline by 14.52%. [2024-08-22T08:23:35.202Z] Movies recommended for you: [2024-08-22T08:23:35.202Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:23:35.202Z] There is no way to check that no silent failure occurred. [2024-08-22T08:23:35.202Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (45520.290 ms) ====== [2024-08-22T08:23:35.202Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-22T08:23:35.202Z] GC before operation: completed in 94.947 ms, heap usage 238.918 MB -> 52.822 MB. [2024-08-22T08:23:43.834Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:23:50.886Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:23:57.909Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:24:04.955Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:24:08.646Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:24:13.210Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:24:16.942Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:24:21.517Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:24:21.517Z] 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. [2024-08-22T08:24:21.517Z] The best model improves the baseline by 14.52%. [2024-08-22T08:24:21.517Z] Movies recommended for you: [2024-08-22T08:24:21.517Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:24:21.517Z] There is no way to check that no silent failure occurred. [2024-08-22T08:24:21.517Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (46242.122 ms) ====== [2024-08-22T08:24:21.517Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-22T08:24:21.517Z] GC before operation: completed in 85.095 ms, heap usage 94.718 MB -> 49.752 MB. [2024-08-22T08:24:30.154Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:24:37.225Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:24:44.305Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:24:51.352Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:24:55.002Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:24:59.604Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:25:03.266Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:25:07.857Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:25:07.857Z] 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. [2024-08-22T08:25:07.857Z] The best model improves the baseline by 14.52%. [2024-08-22T08:25:07.857Z] Movies recommended for you: [2024-08-22T08:25:07.857Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:25:07.857Z] There is no way to check that no silent failure occurred. [2024-08-22T08:25:07.857Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (46332.150 ms) ====== [2024-08-22T08:25:07.857Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-22T08:25:07.857Z] GC before operation: completed in 86.810 ms, heap usage 187.797 MB -> 50.161 MB. [2024-08-22T08:25:14.915Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:25:23.575Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:25:30.665Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:25:37.708Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:25:41.358Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:25:44.983Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:25:49.567Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:25:54.148Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:25:54.148Z] 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. [2024-08-22T08:25:54.148Z] The best model improves the baseline by 14.52%. [2024-08-22T08:25:54.148Z] Movies recommended for you: [2024-08-22T08:25:54.148Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:25:54.148Z] There is no way to check that no silent failure occurred. [2024-08-22T08:25:54.148Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (46236.445 ms) ====== [2024-08-22T08:25:54.148Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-22T08:25:54.452Z] GC before operation: completed in 86.515 ms, heap usage 95.361 MB -> 50.268 MB. [2024-08-22T08:26:03.170Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:26:10.214Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:26:17.258Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:26:24.316Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:26:27.983Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:26:32.546Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:26:36.234Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:26:40.817Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:26:40.817Z] 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. [2024-08-22T08:26:40.817Z] The best model improves the baseline by 14.52%. [2024-08-22T08:26:40.817Z] Movies recommended for you: [2024-08-22T08:26:40.817Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:26:40.817Z] There is no way to check that no silent failure occurred. [2024-08-22T08:26:40.817Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (46369.806 ms) ====== [2024-08-22T08:26:40.817Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-22T08:26:40.817Z] GC before operation: completed in 89.206 ms, heap usage 173.620 MB -> 50.287 MB. [2024-08-22T08:26:47.853Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:26:54.901Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:27:01.976Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:27:09.014Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:27:12.653Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:27:16.311Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:27:20.911Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:27:24.578Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:27:24.937Z] 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. [2024-08-22T08:27:24.937Z] The best model improves the baseline by 14.52%. [2024-08-22T08:27:24.937Z] Movies recommended for you: [2024-08-22T08:27:24.937Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:27:24.937Z] There is no way to check that no silent failure occurred. [2024-08-22T08:27:24.937Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (44262.239 ms) ====== [2024-08-22T08:27:24.937Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-22T08:27:25.260Z] GC before operation: completed in 80.840 ms, heap usage 97.126 MB -> 52.142 MB. [2024-08-22T08:27:33.904Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:27:39.673Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:27:48.308Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:27:53.998Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:27:58.580Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:28:02.206Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:28:05.823Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:28:10.387Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:28:10.387Z] 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. [2024-08-22T08:28:10.387Z] The best model improves the baseline by 14.52%. [2024-08-22T08:28:10.387Z] Movies recommended for you: [2024-08-22T08:28:10.387Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:28:10.387Z] There is no way to check that no silent failure occurred. [2024-08-22T08:28:10.387Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (45248.683 ms) ====== [2024-08-22T08:28:10.387Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-22T08:28:10.387Z] GC before operation: completed in 89.542 ms, heap usage 261.489 MB -> 50.771 MB. [2024-08-22T08:28:17.440Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:28:24.477Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:28:31.576Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:28:38.620Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:28:42.256Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:28:46.849Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:28:50.484Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:28:54.113Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:28:54.514Z] 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. [2024-08-22T08:28:54.514Z] The best model improves the baseline by 14.52%. [2024-08-22T08:28:54.514Z] Movies recommended for you: [2024-08-22T08:28:54.514Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:28:54.514Z] There is no way to check that no silent failure occurred. [2024-08-22T08:28:54.514Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (44023.701 ms) ====== [2024-08-22T08:28:54.514Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-22T08:28:54.514Z] GC before operation: completed in 92.398 ms, heap usage 229.873 MB -> 53.799 MB. [2024-08-22T08:29:03.159Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:29:08.881Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:29:17.567Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:29:23.269Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:29:26.898Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:29:31.465Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:29:35.152Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:29:39.779Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:29:39.779Z] 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. [2024-08-22T08:29:39.779Z] The best model improves the baseline by 14.52%. [2024-08-22T08:29:39.779Z] Movies recommended for you: [2024-08-22T08:29:39.779Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:29:39.779Z] There is no way to check that no silent failure occurred. [2024-08-22T08:29:39.779Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (45090.778 ms) ====== [2024-08-22T08:29:39.779Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-22T08:29:39.779Z] GC before operation: completed in 89.531 ms, heap usage 233.864 MB -> 50.650 MB. [2024-08-22T08:29:48.453Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:29:55.541Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:30:02.595Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:30:09.630Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:30:13.269Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:30:17.859Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:30:22.434Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:30:26.072Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:30:26.072Z] 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. [2024-08-22T08:30:26.415Z] The best model improves the baseline by 14.52%. [2024-08-22T08:30:26.415Z] Movies recommended for you: [2024-08-22T08:30:26.415Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:30:26.415Z] There is no way to check that no silent failure occurred. [2024-08-22T08:30:26.415Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (46626.645 ms) ====== [2024-08-22T08:30:26.415Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-22T08:30:26.415Z] GC before operation: completed in 88.447 ms, heap usage 211.074 MB -> 50.380 MB. [2024-08-22T08:30:33.460Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:30:42.117Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:30:49.160Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:30:54.881Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:30:59.448Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:31:03.106Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:31:07.773Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:31:11.392Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:31:12.087Z] 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. [2024-08-22T08:31:12.087Z] The best model improves the baseline by 14.52%. [2024-08-22T08:31:12.417Z] Movies recommended for you: [2024-08-22T08:31:12.417Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:31:12.417Z] There is no way to check that no silent failure occurred. [2024-08-22T08:31:12.417Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (45789.471 ms) ====== [2024-08-22T08:31:12.417Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-22T08:31:12.417Z] GC before operation: completed in 86.783 ms, heap usage 110.700 MB -> 50.491 MB. [2024-08-22T08:31:19.518Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:31:28.150Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:31:35.211Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:31:42.254Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:31:45.880Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:31:50.455Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:31:55.033Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:31:58.640Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:31:58.960Z] 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. [2024-08-22T08:31:58.960Z] The best model improves the baseline by 14.52%. [2024-08-22T08:31:59.290Z] Movies recommended for you: [2024-08-22T08:31:59.290Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:31:59.290Z] There is no way to check that no silent failure occurred. [2024-08-22T08:31:59.290Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (46784.098 ms) ====== [2024-08-22T08:31:59.290Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-22T08:31:59.290Z] GC before operation: completed in 90.145 ms, heap usage 191.473 MB -> 50.731 MB. [2024-08-22T08:32:06.335Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:32:14.951Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:32:22.065Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:32:29.092Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:32:32.721Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:32:37.286Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:32:41.833Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:32:45.465Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:32:45.465Z] 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. [2024-08-22T08:32:45.465Z] The best model improves the baseline by 14.52%. [2024-08-22T08:32:45.465Z] Movies recommended for you: [2024-08-22T08:32:45.465Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:32:45.465Z] There is no way to check that no silent failure occurred. [2024-08-22T08:32:45.465Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (46319.076 ms) ====== [2024-08-22T08:32:45.465Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-22T08:32:45.778Z] GC before operation: completed in 99.775 ms, heap usage 200.381 MB -> 53.816 MB. [2024-08-22T08:32:52.805Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:32:59.849Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:33:08.489Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:33:14.179Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:33:18.794Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:33:22.460Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:33:26.073Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:33:30.664Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:33:30.664Z] 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. [2024-08-22T08:33:30.664Z] The best model improves the baseline by 14.52%. [2024-08-22T08:33:30.664Z] Movies recommended for you: [2024-08-22T08:33:30.664Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:33:30.664Z] There is no way to check that no silent failure occurred. [2024-08-22T08:33:30.664Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (44924.347 ms) ====== [2024-08-22T08:33:30.664Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-22T08:33:30.664Z] GC before operation: completed in 98.867 ms, heap usage 328.382 MB -> 52.967 MB. [2024-08-22T08:33:37.715Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:33:44.764Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:33:51.838Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:33:58.880Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:34:02.566Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:34:06.322Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:34:10.879Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:34:14.497Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:34:14.815Z] 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. [2024-08-22T08:34:15.157Z] The best model improves the baseline by 14.52%. [2024-08-22T08:34:15.157Z] Movies recommended for you: [2024-08-22T08:34:15.157Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:34:15.157Z] There is no way to check that no silent failure occurred. [2024-08-22T08:34:15.157Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (44451.931 ms) ====== [2024-08-22T08:34:15.157Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-22T08:34:15.157Z] GC before operation: completed in 105.495 ms, heap usage 134.637 MB -> 53.910 MB. [2024-08-22T08:34:23.777Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:34:30.823Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:34:39.456Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:34:45.154Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:34:49.786Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:34:53.402Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:34:57.977Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:35:01.694Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:35:01.694Z] 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. [2024-08-22T08:35:01.694Z] The best model improves the baseline by 14.52%. [2024-08-22T08:35:01.694Z] Movies recommended for you: [2024-08-22T08:35:01.694Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:35:01.694Z] There is no way to check that no silent failure occurred. [2024-08-22T08:35:01.694Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (46384.824 ms) ====== [2024-08-22T08:35:01.694Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-22T08:35:01.694Z] GC before operation: completed in 92.919 ms, heap usage 267.489 MB -> 53.828 MB. [2024-08-22T08:35:08.794Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:35:17.422Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:35:24.478Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:35:30.217Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:35:34.798Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:35:38.417Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:35:42.973Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:35:46.668Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:35:46.668Z] 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. [2024-08-22T08:35:46.668Z] The best model improves the baseline by 14.52%. [2024-08-22T08:35:46.668Z] Movies recommended for you: [2024-08-22T08:35:46.668Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:35:46.668Z] There is no way to check that no silent failure occurred. [2024-08-22T08:35:46.668Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (44913.211 ms) ====== [2024-08-22T08:35:46.668Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-22T08:35:46.668Z] GC before operation: completed in 104.367 ms, heap usage 190.064 MB -> 53.818 MB. [2024-08-22T08:35:53.717Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:36:00.791Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:36:09.461Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:36:15.183Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:36:19.755Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:36:23.361Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:36:26.984Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:36:30.602Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:36:31.293Z] 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. [2024-08-22T08:36:31.293Z] The best model improves the baseline by 14.52%. [2024-08-22T08:36:31.293Z] Movies recommended for you: [2024-08-22T08:36:31.293Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:36:31.293Z] There is no way to check that no silent failure occurred. [2024-08-22T08:36:31.293Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (44646.260 ms) ====== [2024-08-22T08:36:31.293Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-22T08:36:31.620Z] GC before operation: completed in 92.054 ms, heap usage 219.669 MB -> 54.068 MB. [2024-08-22T08:36:38.729Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T08:36:45.776Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T08:36:54.450Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T08:37:01.480Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T08:37:05.124Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T08:37:08.742Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T08:37:13.320Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T08:37:17.912Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T08:37:17.913Z] 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. [2024-08-22T08:37:17.913Z] The best model improves the baseline by 14.52%. [2024-08-22T08:37:17.913Z] Movies recommended for you: [2024-08-22T08:37:17.913Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T08:37:17.913Z] There is no way to check that no silent failure occurred. [2024-08-22T08:37:17.913Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (46401.546 ms) ====== [2024-08-22T08:37:18.229Z] ----------------------------------- [2024-08-22T08:37:18.229Z] renaissance-movie-lens_0_PASSED [2024-08-22T08:37:18.229Z] ----------------------------------- [2024-08-22T08:37:18.889Z] [2024-08-22T08:37:18.889Z] TEST TEARDOWN: [2024-08-22T08:37:18.889Z] Nothing to be done for teardown. [2024-08-22T08:37:19.194Z] renaissance-movie-lens_0 Finish Time: Thu Aug 22 08:37:18 2024 Epoch Time (ms): 1724315838892