[2024-08-17T03:44:45.775Z] Running test renaissance-movie-lens_0 ... [2024-08-17T03:44:45.775Z] =============================================== [2024-08-17T03:44:46.455Z] renaissance-movie-lens_0 Start Time: Fri Aug 16 22:44:45 2024 Epoch Time (ms): 1723866285741 [2024-08-17T03:44:46.455Z] variation: NoOptions [2024-08-17T03:44:46.455Z] JVM_OPTIONS: [2024-08-17T03:44:46.455Z] { \ [2024-08-17T03:44:46.456Z] echo ""; echo "TEST SETUP:"; \ [2024-08-17T03:44:46.456Z] echo "Nothing to be done for setup."; \ [2024-08-17T03:44:46.456Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17238653631865/renaissance-movie-lens_0"; \ [2024-08-17T03:44:46.456Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17238653631865/renaissance-movie-lens_0"; \ [2024-08-17T03:44:46.456Z] echo ""; echo "TESTING:"; \ [2024-08-17T03:44:46.456Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/jdkbinary/j2sdk-image/jdk-11.0.25+3/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_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17238653631865/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-08-17T03:44:46.456Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17238653631865/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-17T03:44:46.456Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-17T03:44:46.456Z] echo "Nothing to be done for teardown."; \ [2024-08-17T03:44:46.456Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17238653631865/TestTargetResult"; [2024-08-17T03:44:46.456Z] [2024-08-17T03:44:46.456Z] TEST SETUP: [2024-08-17T03:44:46.456Z] Nothing to be done for setup. [2024-08-17T03:44:46.456Z] [2024-08-17T03:44:46.456Z] TESTING: [2024-08-17T03:44:49.517Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-17T03:44:50.926Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads. [2024-08-17T03:44:54.956Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-17T03:44:54.956Z] Training: 60056, validation: 20285, test: 19854 [2024-08-17T03:44:54.956Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-17T03:44:54.956Z] GC before operation: completed in 67.940 ms, heap usage 67.755 MB -> 37.241 MB. [2024-08-17T03:45:03.026Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T03:45:07.100Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T03:45:11.163Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T03:45:14.279Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T03:45:16.493Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T03:45:17.911Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T03:45:20.123Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T03:45:21.558Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T03:45:22.247Z] 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. [2024-08-17T03:45:22.247Z] The best model improves the baseline by 14.43%. [2024-08-17T03:45:22.247Z] Movies recommended for you: [2024-08-17T03:45:22.247Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T03:45:22.247Z] There is no way to check that no silent failure occurred. [2024-08-17T03:45:22.247Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (27168.470 ms) ====== [2024-08-17T03:45:22.248Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-17T03:45:22.248Z] GC before operation: completed in 147.414 ms, heap usage 102.067 MB -> 48.109 MB. [2024-08-17T03:45:26.276Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T03:45:29.357Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T03:45:32.451Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T03:45:34.685Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T03:45:36.898Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T03:45:38.325Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T03:45:40.551Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T03:45:42.764Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T03:45:43.464Z] 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. [2024-08-17T03:45:43.464Z] The best model improves the baseline by 14.43%. [2024-08-17T03:45:43.464Z] Movies recommended for you: [2024-08-17T03:45:43.464Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T03:45:43.464Z] There is no way to check that no silent failure occurred. [2024-08-17T03:45:43.464Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (20985.148 ms) ====== [2024-08-17T03:45:43.464Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-17T03:45:43.464Z] GC before operation: completed in 145.669 ms, heap usage 206.356 MB -> 50.968 MB. [2024-08-17T03:45:46.541Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T03:45:49.604Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T03:45:52.674Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T03:45:55.441Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T03:45:56.858Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T03:45:58.272Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T03:46:00.508Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T03:46:02.737Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T03:46:02.737Z] 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. [2024-08-17T03:46:02.737Z] The best model improves the baseline by 14.43%. [2024-08-17T03:46:02.737Z] Movies recommended for you: [2024-08-17T03:46:02.737Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T03:46:02.737Z] There is no way to check that no silent failure occurred. [2024-08-17T03:46:02.737Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (19320.349 ms) ====== [2024-08-17T03:46:02.737Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-17T03:46:02.737Z] GC before operation: completed in 151.486 ms, heap usage 478.591 MB -> 54.807 MB. [2024-08-17T03:46:05.803Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T03:46:08.895Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T03:46:11.143Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T03:46:14.213Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T03:46:15.626Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T03:46:17.059Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T03:46:19.286Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T03:46:20.717Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T03:46:21.405Z] 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. [2024-08-17T03:46:21.405Z] The best model improves the baseline by 14.43%. [2024-08-17T03:46:21.405Z] Movies recommended for you: [2024-08-17T03:46:21.405Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T03:46:21.405Z] There is no way to check that no silent failure occurred. [2024-08-17T03:46:21.405Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (18340.952 ms) ====== [2024-08-17T03:46:21.405Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-17T03:46:21.405Z] GC before operation: completed in 129.556 ms, heap usage 437.572 MB -> 51.834 MB. [2024-08-17T03:46:24.496Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T03:46:26.722Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T03:46:29.826Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T03:46:32.041Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T03:46:34.261Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T03:46:35.677Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T03:46:37.101Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T03:46:39.311Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T03:46:39.311Z] 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. [2024-08-17T03:46:39.311Z] The best model improves the baseline by 14.43%. [2024-08-17T03:46:39.311Z] Movies recommended for you: [2024-08-17T03:46:39.311Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T03:46:39.311Z] There is no way to check that no silent failure occurred. [2024-08-17T03:46:39.311Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (18077.059 ms) ====== [2024-08-17T03:46:39.311Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-17T03:46:39.990Z] GC before operation: completed in 157.349 ms, heap usage 226.850 MB -> 55.103 MB. [2024-08-17T03:46:42.214Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T03:46:45.309Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T03:46:47.550Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T03:46:50.661Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T03:46:51.821Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T03:46:54.055Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T03:46:55.488Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T03:46:56.901Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T03:46:56.901Z] 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. [2024-08-17T03:46:56.901Z] The best model improves the baseline by 14.43%. [2024-08-17T03:46:57.578Z] Movies recommended for you: [2024-08-17T03:46:57.578Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T03:46:57.578Z] There is no way to check that no silent failure occurred. [2024-08-17T03:46:57.578Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (17559.945 ms) ====== [2024-08-17T03:46:57.578Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-17T03:46:57.578Z] GC before operation: completed in 138.079 ms, heap usage 391.060 MB -> 51.902 MB. [2024-08-17T03:46:59.819Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T03:47:02.899Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T03:47:05.116Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T03:47:08.207Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T03:47:09.625Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T03:47:11.048Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T03:47:12.482Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T03:47:14.705Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T03:47:14.705Z] 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. [2024-08-17T03:47:14.705Z] The best model improves the baseline by 14.43%. [2024-08-17T03:47:14.705Z] Movies recommended for you: [2024-08-17T03:47:14.705Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T03:47:14.705Z] There is no way to check that no silent failure occurred. [2024-08-17T03:47:14.705Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (17228.577 ms) ====== [2024-08-17T03:47:14.705Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-17T03:47:14.705Z] GC before operation: completed in 127.247 ms, heap usage 87.758 MB -> 52.665 MB. [2024-08-17T03:47:17.767Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T03:47:19.997Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T03:47:23.121Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T03:47:25.336Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T03:47:26.757Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T03:47:28.185Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T03:47:29.644Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T03:47:31.068Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T03:47:31.767Z] 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. [2024-08-17T03:47:31.767Z] The best model improves the baseline by 14.43%. [2024-08-17T03:47:31.767Z] Movies recommended for you: [2024-08-17T03:47:31.767Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T03:47:31.767Z] There is no way to check that no silent failure occurred. [2024-08-17T03:47:31.767Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (16907.305 ms) ====== [2024-08-17T03:47:31.767Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-17T03:47:31.767Z] GC before operation: completed in 134.801 ms, heap usage 389.622 MB -> 52.357 MB. [2024-08-17T03:47:34.873Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T03:47:37.091Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T03:47:40.165Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T03:47:42.375Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T03:47:43.816Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T03:47:45.661Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T03:47:47.074Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T03:47:48.512Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T03:47:49.199Z] 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. [2024-08-17T03:47:49.199Z] The best model improves the baseline by 14.43%. [2024-08-17T03:47:49.199Z] Movies recommended for you: [2024-08-17T03:47:49.199Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T03:47:49.199Z] There is no way to check that no silent failure occurred. [2024-08-17T03:47:49.199Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (17279.467 ms) ====== [2024-08-17T03:47:49.199Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-17T03:47:49.199Z] GC before operation: completed in 142.818 ms, heap usage 440.143 MB -> 52.235 MB. [2024-08-17T03:47:52.278Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T03:47:54.487Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T03:47:57.548Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T03:47:59.774Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T03:48:01.215Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T03:48:03.445Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T03:48:04.881Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T03:48:06.304Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T03:48:06.304Z] 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. [2024-08-17T03:48:06.304Z] The best model improves the baseline by 14.43%. [2024-08-17T03:48:06.304Z] Movies recommended for you: [2024-08-17T03:48:06.304Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T03:48:06.304Z] There is no way to check that no silent failure occurred. [2024-08-17T03:48:06.304Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (17331.627 ms) ====== [2024-08-17T03:48:06.304Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-17T03:48:06.994Z] GC before operation: completed in 134.889 ms, heap usage 464.523 MB -> 52.361 MB. [2024-08-17T03:48:09.216Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T03:48:12.296Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T03:48:14.499Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T03:48:17.581Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T03:48:19.014Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T03:48:20.454Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T03:48:22.691Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T03:48:24.110Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T03:48:24.110Z] 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. [2024-08-17T03:48:24.110Z] The best model improves the baseline by 14.43%. [2024-08-17T03:48:24.110Z] Movies recommended for you: [2024-08-17T03:48:24.110Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T03:48:24.110Z] There is no way to check that no silent failure occurred. [2024-08-17T03:48:24.110Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (17533.017 ms) ====== [2024-08-17T03:48:24.110Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-17T03:48:24.110Z] GC before operation: completed in 132.761 ms, heap usage 81.058 MB -> 52.628 MB. [2024-08-17T03:48:27.198Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T03:48:29.431Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T03:48:32.517Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T03:48:35.614Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T03:48:37.056Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T03:48:38.479Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T03:48:40.371Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T03:48:41.801Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T03:48:41.801Z] 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. [2024-08-17T03:48:41.801Z] The best model improves the baseline by 14.43%. [2024-08-17T03:48:41.801Z] Movies recommended for you: [2024-08-17T03:48:41.801Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T03:48:41.801Z] There is no way to check that no silent failure occurred. [2024-08-17T03:48:41.801Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (17597.945 ms) ====== [2024-08-17T03:48:41.801Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-17T03:48:41.801Z] GC before operation: completed in 1.099 ms, heap usage 120.701 MB -> 120.745 MB. [2024-08-17T03:48:44.901Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T03:48:47.124Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T03:48:50.369Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T03:48:52.573Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T03:48:54.001Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T03:48:56.223Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T03:48:57.633Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T03:48:59.063Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T03:48:59.063Z] 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. [2024-08-17T03:48:59.752Z] The best model improves the baseline by 14.43%. [2024-08-17T03:48:59.752Z] Movies recommended for you: [2024-08-17T03:48:59.752Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T03:48:59.752Z] There is no way to check that no silent failure occurred. [2024-08-17T03:48:59.752Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (17507.984 ms) ====== [2024-08-17T03:48:59.752Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-17T03:48:59.752Z] GC before operation: completed in 126.847 ms, heap usage 371.880 MB -> 52.381 MB. [2024-08-17T03:49:01.968Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T03:49:05.043Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T03:49:08.125Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T03:49:10.333Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T03:49:11.755Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T03:49:13.193Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T03:49:15.415Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T03:49:16.846Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T03:49:16.846Z] 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. [2024-08-17T03:49:16.846Z] The best model improves the baseline by 14.43%. [2024-08-17T03:49:16.846Z] Movies recommended for you: [2024-08-17T03:49:16.846Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T03:49:16.846Z] There is no way to check that no silent failure occurred. [2024-08-17T03:49:16.846Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (17361.597 ms) ====== [2024-08-17T03:49:16.846Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-17T03:49:16.846Z] GC before operation: completed in 134.595 ms, heap usage 372.879 MB -> 52.084 MB. [2024-08-17T03:49:19.941Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T03:49:22.161Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T03:49:25.267Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T03:49:27.493Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T03:49:29.026Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T03:49:30.443Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T03:49:31.892Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T03:49:34.390Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T03:49:34.390Z] 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. [2024-08-17T03:49:34.390Z] The best model improves the baseline by 14.43%. [2024-08-17T03:49:34.390Z] Movies recommended for you: [2024-08-17T03:49:34.390Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T03:49:34.390Z] There is no way to check that no silent failure occurred. [2024-08-17T03:49:34.390Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (16984.069 ms) ====== [2024-08-17T03:49:34.390Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-17T03:49:34.390Z] GC before operation: completed in 143.148 ms, heap usage 401.288 MB -> 52.321 MB. [2024-08-17T03:49:37.476Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T03:49:39.693Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T03:49:42.782Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T03:49:44.989Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T03:49:46.415Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T03:49:48.613Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T03:49:50.037Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T03:49:52.272Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T03:49:52.272Z] 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. [2024-08-17T03:49:52.272Z] The best model improves the baseline by 14.43%. [2024-08-17T03:49:52.272Z] Movies recommended for you: [2024-08-17T03:49:52.272Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T03:49:52.272Z] There is no way to check that no silent failure occurred. [2024-08-17T03:49:52.272Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (18012.304 ms) ====== [2024-08-17T03:49:52.272Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-17T03:49:52.272Z] GC before operation: completed in 134.686 ms, heap usage 119.654 MB -> 52.163 MB. [2024-08-17T03:49:55.361Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T03:49:57.589Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T03:50:00.660Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T03:50:02.880Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T03:50:04.314Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T03:50:05.737Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T03:50:07.186Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T03:50:08.613Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T03:50:09.293Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-17T03:50:09.293Z] The best model improves the baseline by 14.43%. [2024-08-17T03:50:09.293Z] Movies recommended for you: [2024-08-17T03:50:09.293Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T03:50:09.293Z] There is no way to check that no silent failure occurred. [2024-08-17T03:50:09.293Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (16805.795 ms) ====== [2024-08-17T03:50:09.293Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-17T03:50:09.293Z] GC before operation: completed in 127.877 ms, heap usage 413.498 MB -> 52.275 MB. [2024-08-17T03:50:12.363Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T03:50:14.573Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T03:50:17.653Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T03:50:19.866Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T03:50:22.082Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T03:50:23.521Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T03:50:24.938Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T03:50:26.373Z] RMSE (validation) = 0.9001440981626696 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T03:50:27.058Z] 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. [2024-08-17T03:50:27.058Z] The best model improves the baseline by 14.43%. [2024-08-17T03:50:27.058Z] Movies recommended for you: [2024-08-17T03:50:27.058Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T03:50:27.058Z] There is no way to check that no silent failure occurred. [2024-08-17T03:50:27.058Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (17518.037 ms) ====== [2024-08-17T03:50:27.058Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-17T03:50:27.058Z] GC before operation: completed in 123.721 ms, heap usage 95.344 MB -> 54.235 MB. [2024-08-17T03:50:30.399Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T03:50:32.612Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T03:50:34.848Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T03:50:37.921Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T03:50:39.337Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T03:50:40.743Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T03:50:42.161Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T03:50:43.613Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T03:50:44.322Z] 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. [2024-08-17T03:50:44.322Z] The best model improves the baseline by 14.43%. [2024-08-17T03:50:44.322Z] Movies recommended for you: [2024-08-17T03:50:44.322Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T03:50:44.322Z] There is no way to check that no silent failure occurred. [2024-08-17T03:50:44.322Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (17232.286 ms) ====== [2024-08-17T03:50:44.322Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-17T03:50:44.322Z] GC before operation: completed in 127.825 ms, heap usage 312.997 MB -> 52.416 MB. [2024-08-17T03:50:47.397Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T03:50:49.597Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T03:50:52.672Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T03:50:54.895Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T03:50:56.305Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T03:50:57.730Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T03:50:59.167Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T03:51:01.375Z] RMSE (validation) = 0.9001440981626696 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T03:51:01.375Z] 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. [2024-08-17T03:51:01.375Z] The best model improves the baseline by 14.43%. [2024-08-17T03:51:01.375Z] Movies recommended for you: [2024-08-17T03:51:01.375Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T03:51:01.375Z] There is no way to check that no silent failure occurred. [2024-08-17T03:51:01.375Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (17140.000 ms) ====== [2024-08-17T03:51:02.782Z] ----------------------------------- [2024-08-17T03:51:02.782Z] renaissance-movie-lens_0_PASSED [2024-08-17T03:51:02.782Z] ----------------------------------- [2024-08-17T03:51:02.782Z] [2024-08-17T03:51:02.782Z] TEST TEARDOWN: [2024-08-17T03:51:02.782Z] Nothing to be done for teardown. [2024-08-17T03:51:02.782Z] renaissance-movie-lens_0 Finish Time: Fri Aug 16 22:51:02 2024 Epoch Time (ms): 1723866662395