[2024-08-28T23:20:03.890Z] Running test renaissance-movie-lens_0 ... [2024-08-28T23:20:03.890Z] =============================================== [2024-08-28T23:20:03.890Z] renaissance-movie-lens_0 Start Time: Thu Aug 29 00:20:03 2024 Epoch Time (ms): 1724887203769 [2024-08-28T23:20:03.890Z] variation: NoOptions [2024-08-28T23:20:03.890Z] JVM_OPTIONS: [2024-08-28T23:20:03.890Z] { \ [2024-08-28T23:20:03.890Z] echo ""; echo "TEST SETUP:"; \ [2024-08-28T23:20:03.890Z] echo "Nothing to be done for setup."; \ [2024-08-28T23:20:03.890Z] mkdir -p "/Users/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17248768482379/renaissance-movie-lens_0"; \ [2024-08-28T23:20:03.890Z] cd "/Users/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17248768482379/renaissance-movie-lens_0"; \ [2024-08-28T23:20:03.890Z] echo ""; echo "TESTING:"; \ [2024-08-28T23:20:03.890Z] "/Users/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_0/jdkbinary/j2sdk-image/Contents/Home/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 "/Users/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17248768482379/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-08-28T23:20:03.890Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/..; rm -f -r "/Users/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17248768482379/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-28T23:20:03.890Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-28T23:20:03.890Z] echo "Nothing to be done for teardown."; \ [2024-08-28T23:20:03.890Z] } 2>&1 | tee -a "/Users/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17248768482379/TestTargetResult"; [2024-08-28T23:20:03.890Z] [2024-08-28T23:20:03.890Z] TEST SETUP: [2024-08-28T23:20:03.890Z] Nothing to be done for setup. [2024-08-28T23:20:03.890Z] [2024-08-28T23:20:03.890Z] TESTING: [2024-08-28T23:20:07.860Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-28T23:20:09.093Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads. [2024-08-28T23:20:17.898Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-28T23:20:17.898Z] Training: 60056, validation: 20285, test: 19854 [2024-08-28T23:20:17.898Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-28T23:20:17.898Z] GC before operation: completed in 44.851 ms, heap usage 84.724 MB -> 38.337 MB. [2024-08-28T23:20:41.673Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-28T23:21:01.256Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-28T23:21:24.784Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-28T23:21:41.066Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-28T23:21:52.216Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-28T23:22:01.482Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-28T23:22:14.989Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-28T23:22:22.544Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-28T23:22:22.902Z] 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. [2024-08-28T23:22:22.902Z] The best model improves the baseline by 14.43%. [2024-08-28T23:22:23.262Z] Movies recommended for you: [2024-08-28T23:22:23.262Z] WARNING: This benchmark provides no result that can be validated. [2024-08-28T23:22:23.262Z] There is no way to check that no silent failure occurred. [2024-08-28T23:22:23.262Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (130388.179 ms) ====== [2024-08-28T23:22:23.262Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-28T23:22:23.262Z] GC before operation: completed in 78.228 ms, heap usage 369.391 MB -> 74.601 MB. [2024-08-28T23:22:46.779Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-28T23:23:06.353Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-28T23:23:29.879Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-28T23:23:46.340Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-28T23:23:57.512Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-28T23:24:05.072Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-28T23:24:18.579Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-28T23:24:26.136Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-28T23:24:26.501Z] 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. [2024-08-28T23:24:26.501Z] The best model improves the baseline by 14.43%. [2024-08-28T23:24:26.501Z] Movies recommended for you: [2024-08-28T23:24:26.501Z] WARNING: This benchmark provides no result that can be validated. [2024-08-28T23:24:26.501Z] There is no way to check that no silent failure occurred. [2024-08-28T23:24:26.501Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (123352.345 ms) ====== [2024-08-28T23:24:26.501Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-28T23:24:26.501Z] GC before operation: completed in 70.881 ms, heap usage 447.392 MB -> 80.570 MB. [2024-08-28T23:24:46.096Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-28T23:25:09.612Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-28T23:25:33.132Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-28T23:25:49.393Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-28T23:26:00.569Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-28T23:26:09.771Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-28T23:26:23.260Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-28T23:26:32.465Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-28T23:26:32.465Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-28T23:26:32.465Z] The best model improves the baseline by 14.43%. [2024-08-28T23:26:32.465Z] Movies recommended for you: [2024-08-28T23:26:32.465Z] WARNING: This benchmark provides no result that can be validated. [2024-08-28T23:26:32.465Z] There is no way to check that no silent failure occurred. [2024-08-28T23:26:32.465Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (125646.342 ms) ====== [2024-08-28T23:26:32.465Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-28T23:26:32.465Z] GC before operation: completed in 67.965 ms, heap usage 406.070 MB -> 81.232 MB. [2024-08-28T23:26:56.279Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-28T23:27:15.873Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-28T23:27:39.399Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-28T23:27:52.894Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-28T23:28:04.057Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-28T23:28:13.271Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-28T23:28:24.440Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-28T23:28:33.656Z] RMSE (validation) = 0.9001440981626696 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-28T23:28:33.656Z] 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. [2024-08-28T23:28:33.656Z] The best model improves the baseline by 14.43%. [2024-08-28T23:28:33.656Z] Movies recommended for you: [2024-08-28T23:28:33.656Z] WARNING: This benchmark provides no result that can be validated. [2024-08-28T23:28:33.656Z] There is no way to check that no silent failure occurred. [2024-08-28T23:28:33.656Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (121271.363 ms) ====== [2024-08-28T23:28:33.656Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-28T23:28:33.656Z] GC before operation: completed in 78.001 ms, heap usage 1003.184 MB -> 81.445 MB. [2024-08-28T23:28:53.210Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-28T23:29:12.758Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-28T23:29:36.252Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-28T23:29:55.798Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-28T23:30:06.972Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-28T23:30:16.170Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-28T23:30:30.060Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-28T23:30:39.271Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-28T23:30:39.271Z] 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. [2024-08-28T23:30:39.271Z] The best model improves the baseline by 14.43%. [2024-08-28T23:30:39.271Z] Movies recommended for you: [2024-08-28T23:30:39.271Z] WARNING: This benchmark provides no result that can be validated. [2024-08-28T23:30:39.271Z] There is no way to check that no silent failure occurred. [2024-08-28T23:30:39.271Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (124701.147 ms) ====== [2024-08-28T23:30:39.271Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-28T23:30:39.271Z] GC before operation: completed in 73.450 ms, heap usage 198.771 MB -> 81.442 MB. [2024-08-28T23:31:03.030Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-28T23:31:22.588Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-28T23:31:46.101Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-28T23:32:02.387Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-28T23:32:11.603Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-28T23:32:20.835Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-28T23:32:34.327Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-28T23:32:41.878Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-28T23:32:41.878Z] 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. [2024-08-28T23:32:41.878Z] The best model improves the baseline by 14.43%. [2024-08-28T23:32:41.878Z] Movies recommended for you: [2024-08-28T23:32:41.878Z] WARNING: This benchmark provides no result that can be validated. [2024-08-28T23:32:41.878Z] There is no way to check that no silent failure occurred. [2024-08-28T23:32:41.878Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (123536.653 ms) ====== [2024-08-28T23:32:41.878Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-28T23:32:42.238Z] GC before operation: completed in 70.872 ms, heap usage 198.471 MB -> 81.292 MB. [2024-08-28T23:33:01.799Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-28T23:33:21.376Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-28T23:33:44.915Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-28T23:34:04.495Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-28T23:34:13.698Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-28T23:34:22.907Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-28T23:34:36.906Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-28T23:34:46.173Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-28T23:34:46.536Z] 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. [2024-08-28T23:34:46.537Z] The best model improves the baseline by 14.43%. [2024-08-28T23:34:46.537Z] Movies recommended for you: [2024-08-28T23:34:46.537Z] WARNING: This benchmark provides no result that can be validated. [2024-08-28T23:34:46.537Z] There is no way to check that no silent failure occurred. [2024-08-28T23:34:46.537Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (124593.831 ms) ====== [2024-08-28T23:34:46.537Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-28T23:34:46.894Z] GC before operation: completed in 76.436 ms, heap usage 678.361 MB -> 66.055 MB. [2024-08-28T23:35:10.392Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-28T23:35:26.674Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-28T23:35:50.217Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-28T23:36:06.493Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-28T23:36:15.713Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-28T23:36:23.271Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-28T23:36:36.795Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-28T23:36:44.368Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-28T23:36:44.740Z] 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. [2024-08-28T23:36:44.740Z] The best model improves the baseline by 14.43%. [2024-08-28T23:36:44.740Z] Movies recommended for you: [2024-08-28T23:36:44.740Z] WARNING: This benchmark provides no result that can be validated. [2024-08-28T23:36:44.740Z] There is no way to check that no silent failure occurred. [2024-08-28T23:36:44.740Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (118103.697 ms) ====== [2024-08-28T23:36:44.740Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-28T23:36:45.099Z] GC before operation: completed in 71.566 ms, heap usage 498.733 MB -> 81.890 MB. [2024-08-28T23:37:04.738Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-28T23:37:28.262Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-28T23:37:51.769Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-28T23:38:08.015Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-28T23:38:19.172Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-28T23:38:28.392Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-28T23:38:39.572Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-28T23:38:50.711Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-28T23:38:50.711Z] 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. [2024-08-28T23:38:50.711Z] The best model improves the baseline by 14.43%. [2024-08-28T23:38:50.711Z] Movies recommended for you: [2024-08-28T23:38:50.711Z] WARNING: This benchmark provides no result that can be validated. [2024-08-28T23:38:50.711Z] There is no way to check that no silent failure occurred. [2024-08-28T23:38:50.711Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (124737.297 ms) ====== [2024-08-28T23:38:50.711Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-28T23:38:50.711Z] GC before operation: completed in 64.033 ms, heap usage 230.836 MB -> 58.991 MB. [2024-08-28T23:39:14.239Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-28T23:39:33.806Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-28T23:39:53.372Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-28T23:40:12.944Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-28T23:40:20.508Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-28T23:40:29.696Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-28T23:40:43.165Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-28T23:40:50.711Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-28T23:40:50.711Z] 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. [2024-08-28T23:40:50.711Z] The best model improves the baseline by 14.43%. [2024-08-28T23:40:50.711Z] Movies recommended for you: [2024-08-28T23:40:50.711Z] WARNING: This benchmark provides no result that can be validated. [2024-08-28T23:40:50.711Z] There is no way to check that no silent failure occurred. [2024-08-28T23:40:50.711Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (120857.704 ms) ====== [2024-08-28T23:40:50.711Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-28T23:40:50.711Z] GC before operation: completed in 72.808 ms, heap usage 781.799 MB -> 81.797 MB. [2024-08-28T23:41:10.269Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-28T23:41:29.828Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-28T23:41:53.346Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-28T23:42:09.640Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-28T23:42:18.840Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-28T23:42:28.064Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-28T23:42:39.282Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-28T23:42:48.506Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-28T23:42:48.506Z] 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. [2024-08-28T23:42:48.506Z] The best model improves the baseline by 14.43%. [2024-08-28T23:42:48.506Z] Movies recommended for you: [2024-08-28T23:42:48.506Z] WARNING: This benchmark provides no result that can be validated. [2024-08-28T23:42:48.506Z] There is no way to check that no silent failure occurred. [2024-08-28T23:42:48.506Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (117407.609 ms) ====== [2024-08-28T23:42:48.506Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-28T23:42:48.506Z] GC before operation: completed in 80.811 ms, heap usage 517.219 MB -> 81.496 MB. [2024-08-28T23:43:12.016Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-28T23:43:31.594Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-28T23:43:55.116Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-28T23:44:11.429Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-28T23:44:20.640Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-28T23:44:29.855Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-28T23:44:43.359Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-28T23:44:50.912Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-28T23:44:50.912Z] 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. [2024-08-28T23:44:50.912Z] The best model improves the baseline by 14.43%. [2024-08-28T23:44:50.912Z] Movies recommended for you: [2024-08-28T23:44:50.912Z] WARNING: This benchmark provides no result that can be validated. [2024-08-28T23:44:50.912Z] There is no way to check that no silent failure occurred. [2024-08-28T23:44:50.912Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (122198.344 ms) ====== [2024-08-28T23:44:50.912Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-28T23:44:50.912Z] GC before operation: completed in 76.040 ms, heap usage 726.851 MB -> 81.773 MB. [2024-08-28T23:45:14.503Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-28T23:45:38.041Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-28T23:46:01.550Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-28T23:46:17.816Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-28T23:46:25.379Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-28T23:46:34.583Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-28T23:46:48.081Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-28T23:46:55.634Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-28T23:46:55.634Z] 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. [2024-08-28T23:46:55.634Z] The best model improves the baseline by 14.43%. [2024-08-28T23:46:55.634Z] Movies recommended for you: [2024-08-28T23:46:55.634Z] WARNING: This benchmark provides no result that can be validated. [2024-08-28T23:46:55.634Z] There is no way to check that no silent failure occurred. [2024-08-28T23:46:55.634Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (124917.222 ms) ====== [2024-08-28T23:46:55.634Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-28T23:46:55.634Z] GC before operation: completed in 71.716 ms, heap usage 135.964 MB -> 81.800 MB. [2024-08-28T23:47:15.232Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-28T23:47:34.797Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-28T23:47:58.314Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-28T23:48:14.614Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-28T23:48:25.782Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-28T23:48:43.087Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-28T23:48:54.247Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-28T23:49:03.447Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-28T23:49:03.447Z] 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. [2024-08-28T23:49:03.447Z] The best model improves the baseline by 14.43%. [2024-08-28T23:49:03.447Z] Movies recommended for you: [2024-08-28T23:49:03.447Z] WARNING: This benchmark provides no result that can be validated. [2024-08-28T23:49:03.447Z] There is no way to check that no silent failure occurred. [2024-08-28T23:49:03.447Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (128088.679 ms) ====== [2024-08-28T23:49:03.447Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-28T23:49:03.447Z] GC before operation: completed in 73.537 ms, heap usage 301.588 MB -> 74.623 MB. [2024-08-28T23:49:23.018Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-28T23:49:42.587Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-28T23:50:06.106Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-28T23:50:22.377Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-28T23:50:31.589Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-28T23:50:40.792Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-28T23:50:51.978Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-28T23:51:01.188Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-28T23:51:01.188Z] 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. [2024-08-28T23:51:01.188Z] The best model improves the baseline by 14.43%. [2024-08-28T23:51:01.188Z] Movies recommended for you: [2024-08-28T23:51:01.188Z] WARNING: This benchmark provides no result that can be validated. [2024-08-28T23:51:01.188Z] There is no way to check that no silent failure occurred. [2024-08-28T23:51:01.188Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (117699.902 ms) ====== [2024-08-28T23:51:01.188Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-28T23:51:01.188Z] GC before operation: completed in 67.674 ms, heap usage 415.766 MB -> 71.242 MB. [2024-08-28T23:51:24.919Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-28T23:51:44.494Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-28T23:52:08.121Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-28T23:52:21.612Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-28T23:52:32.770Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-28T23:52:41.971Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-28T23:52:55.458Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-28T23:53:04.680Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-28T23:53:04.680Z] 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. [2024-08-28T23:53:04.680Z] The best model improves the baseline by 14.43%. [2024-08-28T23:53:04.680Z] Movies recommended for you: [2024-08-28T23:53:04.680Z] WARNING: This benchmark provides no result that can be validated. [2024-08-28T23:53:04.680Z] There is no way to check that no silent failure occurred. [2024-08-28T23:53:04.680Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (123055.458 ms) ====== [2024-08-28T23:53:04.680Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-28T23:53:04.680Z] GC before operation: completed in 84.085 ms, heap usage 426.548 MB -> 82.139 MB. [2024-08-28T23:53:28.207Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-28T23:53:51.721Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-28T23:54:15.287Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-28T23:54:31.549Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-28T23:54:42.758Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-28T23:54:53.999Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-28T23:55:05.159Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-28T23:55:14.369Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-28T23:55:14.369Z] 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. [2024-08-28T23:55:14.369Z] The best model improves the baseline by 14.43%. [2024-08-28T23:55:14.369Z] Movies recommended for you: [2024-08-28T23:55:14.369Z] WARNING: This benchmark provides no result that can be validated. [2024-08-28T23:55:14.369Z] There is no way to check that no silent failure occurred. [2024-08-28T23:55:14.369Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (129952.076 ms) ====== [2024-08-28T23:55:14.369Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-28T23:55:14.369Z] GC before operation: completed in 74.941 ms, heap usage 709.928 MB -> 81.957 MB. [2024-08-28T23:55:42.722Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-28T23:56:02.307Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-28T23:56:21.878Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-28T23:56:38.233Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-28T23:56:49.394Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-28T23:56:56.968Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-28T23:57:10.487Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-28T23:57:18.066Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-28T23:57:18.066Z] 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. [2024-08-28T23:57:18.066Z] The best model improves the baseline by 14.43%. [2024-08-28T23:57:18.066Z] Movies recommended for you: [2024-08-28T23:57:18.066Z] WARNING: This benchmark provides no result that can be validated. [2024-08-28T23:57:18.066Z] There is no way to check that no silent failure occurred. [2024-08-28T23:57:18.066Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (123483.888 ms) ====== [2024-08-28T23:57:18.066Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-28T23:57:18.066Z] GC before operation: completed in 76.564 ms, heap usage 1.045 GB -> 82.081 MB. [2024-08-28T23:57:37.644Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-28T23:58:01.137Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-28T23:58:24.646Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-28T23:58:44.225Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-28T23:58:51.780Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-28T23:59:00.981Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-28T23:59:12.140Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-28T23:59:21.344Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-28T23:59:21.344Z] 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. [2024-08-28T23:59:21.344Z] The best model improves the baseline by 14.43%. [2024-08-28T23:59:21.344Z] Movies recommended for you: [2024-08-28T23:59:21.344Z] WARNING: This benchmark provides no result that can be validated. [2024-08-28T23:59:21.344Z] There is no way to check that no silent failure occurred. [2024-08-28T23:59:21.344Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (123420.723 ms) ====== [2024-08-28T23:59:21.344Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-28T23:59:21.701Z] GC before operation: completed in 81.552 ms, heap usage 454.106 MB -> 82.492 MB. [2024-08-28T23:59:45.268Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-29T00:00:04.853Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-29T00:00:28.363Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-29T00:00:41.846Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-29T00:00:53.001Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-29T00:01:02.217Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-29T00:01:13.388Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-29T00:01:22.598Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-29T00:01:22.598Z] 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. [2024-08-29T00:01:22.598Z] The best model improves the baseline by 14.43%. [2024-08-29T00:01:22.598Z] Movies recommended for you: [2024-08-29T00:01:22.599Z] WARNING: This benchmark provides no result that can be validated. [2024-08-29T00:01:22.599Z] There is no way to check that no silent failure occurred. [2024-08-29T00:01:22.599Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (120478.743 ms) ====== [2024-08-29T00:01:23.361Z] ----------------------------------- [2024-08-29T00:01:23.361Z] renaissance-movie-lens_0_PASSED [2024-08-29T00:01:23.361Z] ----------------------------------- [2024-08-29T00:01:23.361Z] [2024-08-29T00:01:23.361Z] TEST TEARDOWN: [2024-08-29T00:01:23.361Z] Nothing to be done for teardown. [2024-08-29T00:01:23.361Z] renaissance-movie-lens_0 Finish Time: Thu Aug 29 01:01:23 2024 Epoch Time (ms): 1724889683220