renaissance-movie-lens_0
[2024-11-08T15:55:17.327Z] Running test renaissance-movie-lens_0 ...
[2024-11-08T15:55:17.327Z] ===============================================
[2024-11-08T15:55:17.327Z] renaissance-movie-lens_0 Start Time: Fri Nov 8 09:55:17 2024 Epoch Time (ms): 1731081317073
[2024-11-08T15:55:17.327Z] variation: NoOptions
[2024-11-08T15:55:17.327Z] JVM_OPTIONS:
[2024-11-08T15:55:17.327Z] { \
[2024-11-08T15:55:17.327Z] echo ""; echo "TEST SETUP:"; \
[2024-11-08T15:55:17.327Z] echo "Nothing to be done for setup."; \
[2024-11-08T15:55:17.327Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17310806949971/renaissance-movie-lens_0"; \
[2024-11-08T15:55:17.327Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17310806949971/renaissance-movie-lens_0"; \
[2024-11-08T15:55:17.327Z] echo ""; echo "TESTING:"; \
[2024-11-08T15:55:17.327Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/jdkbinary/j2sdk-image/jdk-17.0.14+2/bin/..//bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17310806949971/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-08T15:55:17.327Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17310806949971/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-08T15:55:17.327Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-08T15:55:17.327Z] echo "Nothing to be done for teardown."; \
[2024-11-08T15:55:17.327Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17310806949971/TestTargetResult";
[2024-11-08T15:55:17.327Z]
[2024-11-08T15:55:17.327Z] TEST SETUP:
[2024-11-08T15:55:17.327Z] Nothing to be done for setup.
[2024-11-08T15:55:17.327Z]
[2024-11-08T15:55:17.327Z] TESTING:
[2024-11-08T15:55:20.385Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-08T15:55:21.795Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2024-11-08T15:55:24.853Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-08T15:55:25.539Z] Training: 60056, validation: 20285, test: 19854
[2024-11-08T15:55:25.539Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-08T15:55:25.539Z] GC before operation: completed in 48.281 ms, heap usage 87.338 MB -> 37.770 MB.
[2024-11-08T15:55:33.168Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:55:36.255Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:55:39.347Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:55:42.434Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:55:43.877Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:55:46.093Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:55:47.509Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:55:48.926Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:55:49.627Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:55:49.627Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:55:49.627Z] Movies recommended for you:
[2024-11-08T15:55:49.627Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:55:49.627Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:55:49.627Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (24364.674 ms) ======
[2024-11-08T15:55:49.627Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-08T15:55:49.627Z] GC before operation: completed in 96.747 ms, heap usage 511.316 MB -> 56.888 MB.
[2024-11-08T15:55:52.763Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:55:55.852Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:55:58.093Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:56:00.369Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:56:02.598Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:56:03.287Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:56:05.521Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:56:06.940Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:56:06.940Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:56:06.940Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:56:06.940Z] Movies recommended for you:
[2024-11-08T15:56:06.940Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:56:06.940Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:56:06.940Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17404.151 ms) ======
[2024-11-08T15:56:06.940Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-08T15:56:06.940Z] GC before operation: completed in 57.838 ms, heap usage 156.966 MB -> 51.489 MB.
[2024-11-08T15:56:10.769Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:56:12.969Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:56:15.185Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:56:18.245Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:56:19.684Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:56:21.132Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:56:22.569Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:56:24.000Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:56:24.000Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:56:24.000Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:56:24.682Z] Movies recommended for you:
[2024-11-08T15:56:24.682Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:56:24.682Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:56:24.682Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17230.194 ms) ======
[2024-11-08T15:56:24.682Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-08T15:56:24.682Z] GC before operation: completed in 66.143 ms, heap usage 103.560 MB -> 54.213 MB.
[2024-11-08T15:56:26.896Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:56:29.101Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:56:31.328Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:56:33.580Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:56:35.009Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:56:36.455Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:56:37.872Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:56:39.283Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:56:39.962Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:56:39.962Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:56:39.962Z] Movies recommended for you:
[2024-11-08T15:56:39.962Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:56:39.962Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:56:39.962Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (15459.571 ms) ======
[2024-11-08T15:56:39.962Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-08T15:56:39.962Z] GC before operation: completed in 59.088 ms, heap usage 280.243 MB -> 55.647 MB.
[2024-11-08T15:56:42.192Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:56:44.398Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:56:46.636Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:56:48.849Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:56:50.259Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:56:51.700Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:56:52.389Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:56:53.802Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:56:54.489Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:56:54.489Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:56:54.489Z] Movies recommended for you:
[2024-11-08T15:56:54.489Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:56:54.489Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:56:54.489Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (14500.915 ms) ======
[2024-11-08T15:56:54.489Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-08T15:56:54.489Z] GC before operation: completed in 89.259 ms, heap usage 323.147 MB -> 52.524 MB.
[2024-11-08T15:56:57.592Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:56:59.858Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:57:01.286Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:57:03.482Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:57:04.891Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:57:06.835Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:57:07.522Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:57:08.987Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:57:09.669Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:57:09.669Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:57:09.669Z] Movies recommended for you:
[2024-11-08T15:57:09.669Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:57:09.669Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:57:09.669Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (14980.915 ms) ======
[2024-11-08T15:57:09.669Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-08T15:57:09.669Z] GC before operation: completed in 63.223 ms, heap usage 360.849 MB -> 52.550 MB.
[2024-11-08T15:57:11.880Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:57:14.084Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:57:16.300Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:57:18.509Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:57:19.922Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:57:21.333Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:57:22.780Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:57:24.245Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:57:24.245Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:57:24.245Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:57:24.245Z] Movies recommended for you:
[2024-11-08T15:57:24.245Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:57:24.245Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:57:24.245Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (14570.871 ms) ======
[2024-11-08T15:57:24.245Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-08T15:57:24.245Z] GC before operation: completed in 60.304 ms, heap usage 337.292 MB -> 52.767 MB.
[2024-11-08T15:57:26.539Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:57:28.748Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:57:30.948Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:57:33.169Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:57:34.596Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:57:36.009Z] RMSE (validation) = 1.117495376637101 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:57:37.413Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:57:38.830Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:57:38.830Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:57:38.830Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:57:38.830Z] Movies recommended for you:
[2024-11-08T15:57:38.830Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:57:38.830Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:57:38.830Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (14840.950 ms) ======
[2024-11-08T15:57:38.830Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-08T15:57:38.830Z] GC before operation: completed in 59.739 ms, heap usage 314.084 MB -> 53.034 MB.
[2024-11-08T15:57:41.905Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:57:44.139Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:57:46.353Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:57:48.580Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:57:49.275Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:57:50.704Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:57:52.127Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:57:53.548Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:57:54.225Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:57:54.225Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:57:54.225Z] Movies recommended for you:
[2024-11-08T15:57:54.225Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:57:54.225Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:57:54.225Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (14982.114 ms) ======
[2024-11-08T15:57:54.225Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-08T15:57:54.225Z] GC before operation: completed in 55.716 ms, heap usage 326.484 MB -> 52.914 MB.
[2024-11-08T15:57:56.432Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:57:58.643Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:58:00.875Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:58:03.094Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:58:04.513Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:58:05.936Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:58:07.372Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:58:08.790Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:58:08.790Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:58:08.790Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:58:08.790Z] Movies recommended for you:
[2024-11-08T15:58:08.790Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:58:08.790Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:58:08.790Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14914.868 ms) ======
[2024-11-08T15:58:08.790Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-08T15:58:09.468Z] GC before operation: completed in 63.705 ms, heap usage 216.607 MB -> 52.886 MB.
[2024-11-08T15:58:11.696Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:58:13.914Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:58:16.673Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:58:18.877Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:58:20.305Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:58:21.730Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:58:23.154Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:58:23.842Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:58:24.528Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:58:24.528Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:58:24.528Z] Movies recommended for you:
[2024-11-08T15:58:24.528Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:58:24.528Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:58:24.528Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15263.927 ms) ======
[2024-11-08T15:58:24.528Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-08T15:58:24.528Z] GC before operation: completed in 65.125 ms, heap usage 104.867 MB -> 55.821 MB.
[2024-11-08T15:58:26.742Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:58:28.952Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:58:31.188Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:58:33.409Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:58:34.828Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:58:36.260Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:58:37.672Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:58:39.109Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:58:39.109Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:58:39.110Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:58:39.799Z] Movies recommended for you:
[2024-11-08T15:58:39.799Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:58:39.799Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:58:39.799Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14980.675 ms) ======
[2024-11-08T15:58:39.799Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-08T15:58:39.799Z] GC before operation: completed in 87.235 ms, heap usage 155.566 MB -> 52.799 MB.
[2024-11-08T15:58:42.002Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:58:44.228Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:58:46.447Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:58:48.669Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:58:50.095Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:58:51.514Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:58:52.963Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:58:54.394Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:58:54.395Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:58:54.395Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:58:55.085Z] Movies recommended for you:
[2024-11-08T15:58:55.085Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:58:55.085Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:58:55.085Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15190.635 ms) ======
[2024-11-08T15:58:55.085Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-08T15:58:55.085Z] GC before operation: completed in 82.370 ms, heap usage 321.991 MB -> 53.061 MB.
[2024-11-08T15:58:57.317Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:58:59.513Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:59:01.747Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:59:03.984Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:59:05.410Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:59:06.820Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:59:08.247Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:59:09.678Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:59:09.678Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:59:09.678Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:59:09.678Z] Movies recommended for you:
[2024-11-08T15:59:09.678Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:59:09.678Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:59:09.678Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15003.427 ms) ======
[2024-11-08T15:59:09.678Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-08T15:59:09.678Z] GC before operation: completed in 61.682 ms, heap usage 295.491 MB -> 52.929 MB.
[2024-11-08T15:59:12.760Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:59:14.987Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:59:17.188Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:59:18.941Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:59:20.359Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:59:21.801Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:59:23.220Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:59:24.631Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:59:24.631Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:59:24.631Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:59:24.631Z] Movies recommended for you:
[2024-11-08T15:59:24.631Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:59:24.631Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:59:24.631Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14713.273 ms) ======
[2024-11-08T15:59:24.631Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-08T15:59:24.631Z] GC before operation: completed in 94.775 ms, heap usage 286.377 MB -> 53.108 MB.
[2024-11-08T15:59:26.847Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:59:29.084Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:59:31.310Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:59:33.552Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:59:34.978Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:59:36.392Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:59:37.808Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:59:39.216Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:59:39.216Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:59:39.216Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:59:39.893Z] Movies recommended for you:
[2024-11-08T15:59:39.893Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:59:39.893Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:59:39.893Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14891.541 ms) ======
[2024-11-08T15:59:39.893Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-08T15:59:39.893Z] GC before operation: completed in 55.900 ms, heap usage 77.832 MB -> 53.120 MB.
[2024-11-08T15:59:42.100Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:59:45.191Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:59:46.631Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:59:48.840Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:59:50.287Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:59:51.698Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:59:53.128Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:59:54.560Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:59:54.560Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:59:54.560Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:59:55.246Z] Movies recommended for you:
[2024-11-08T15:59:55.247Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:59:55.247Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:59:55.247Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (15318.812 ms) ======
[2024-11-08T15:59:55.247Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-08T15:59:55.247Z] GC before operation: completed in 72.050 ms, heap usage 1.211 GB -> 60.609 MB.
[2024-11-08T15:59:57.582Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T16:00:00.662Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T16:00:02.868Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T16:00:05.943Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T16:00:07.354Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T16:00:08.766Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T16:00:10.978Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T16:00:12.427Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T16:00:12.427Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T16:00:12.427Z] The best model improves the baseline by 14.43%.
[2024-11-08T16:00:12.427Z] Movies recommended for you:
[2024-11-08T16:00:12.427Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T16:00:12.427Z] There is no way to check that no silent failure occurred.
[2024-11-08T16:00:12.427Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (17359.630 ms) ======
[2024-11-08T16:00:12.427Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-08T16:00:12.427Z] GC before operation: completed in 70.366 ms, heap usage 501.192 MB -> 57.583 MB.
[2024-11-08T16:00:15.508Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T16:00:17.708Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T16:00:19.922Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T16:00:22.135Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T16:00:23.574Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T16:00:24.694Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T16:00:26.198Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T16:00:27.636Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T16:00:27.636Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T16:00:27.636Z] The best model improves the baseline by 14.43%.
[2024-11-08T16:00:27.636Z] Movies recommended for you:
[2024-11-08T16:00:27.636Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T16:00:27.636Z] There is no way to check that no silent failure occurred.
[2024-11-08T16:00:27.636Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (15466.483 ms) ======
[2024-11-08T16:00:27.636Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-08T16:00:28.317Z] GC before operation: completed in 65.025 ms, heap usage 338.555 MB -> 57.366 MB.
[2024-11-08T16:00:30.519Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T16:00:32.756Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T16:00:34.994Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T16:00:37.204Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T16:00:38.619Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T16:00:40.044Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T16:00:41.496Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T16:00:42.184Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T16:00:42.865Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T16:00:42.865Z] The best model improves the baseline by 14.43%.
[2024-11-08T16:00:42.865Z] Movies recommended for you:
[2024-11-08T16:00:42.865Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T16:00:42.865Z] There is no way to check that no silent failure occurred.
[2024-11-08T16:00:42.865Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14741.648 ms) ======
[2024-11-08T16:00:43.565Z] -----------------------------------
[2024-11-08T16:00:43.565Z] renaissance-movie-lens_0_PASSED
[2024-11-08T16:00:43.565Z] -----------------------------------
[2024-11-08T16:00:43.565Z]
[2024-11-08T16:00:43.565Z] TEST TEARDOWN:
[2024-11-08T16:00:43.565Z] Nothing to be done for teardown.
[2024-11-08T16:00:44.242Z] renaissance-movie-lens_0 Finish Time: Fri Nov 8 10:00:43 2024 Epoch Time (ms): 1731081643551