[2024-12-07T13:32:33.266Z] Running test renaissance-movie-lens_0 ... [2024-12-07T13:32:33.266Z] =============================================== [2024-12-07T13:32:33.266Z] renaissance-movie-lens_0 Start Time: Sat Dec 7 13:32:32 2024 Epoch Time (ms): 1733578352766 [2024-12-07T13:32:33.266Z] variation: NoOptions [2024-12-07T13:32:33.266Z] JVM_OPTIONS: [2024-12-07T13:32:33.266Z] { \ [2024-12-07T13:32:33.266Z] echo ""; echo "TEST SETUP:"; \ [2024-12-07T13:32:33.266Z] echo "Nothing to be done for setup."; \ [2024-12-07T13:32:33.266Z] mkdir -p "/Users/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17335776558922/renaissance-movie-lens_0"; \ [2024-12-07T13:32:33.266Z] cd "/Users/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17335776558922/renaissance-movie-lens_0"; \ [2024-12-07T13:32:33.266Z] echo ""; echo "TESTING:"; \ [2024-12-07T13:32:33.266Z] "/Users/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/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_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17335776558922/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-12-07T13:32:33.266Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/..; rm -f -r "/Users/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17335776558922/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-12-07T13:32:33.266Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-12-07T13:32:33.266Z] echo "Nothing to be done for teardown."; \ [2024-12-07T13:32:33.266Z] } 2>&1 | tee -a "/Users/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17335776558922/TestTargetResult"; [2024-12-07T13:32:33.266Z] [2024-12-07T13:32:33.266Z] TEST SETUP: [2024-12-07T13:32:33.266Z] Nothing to be done for setup. [2024-12-07T13:32:33.266Z] [2024-12-07T13:32:33.266Z] TESTING: [2024-12-07T13:32:37.243Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-12-07T13:32:39.015Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads. [2024-12-07T13:32:42.991Z] Got 100004 ratings from 671 users on 9066 movies. [2024-12-07T13:32:42.991Z] Training: 60056, validation: 20285, test: 19854 [2024-12-07T13:32:42.991Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-12-07T13:32:42.991Z] GC before operation: completed in 53.202 ms, heap usage 175.168 MB -> 37.305 MB. [2024-12-07T13:33:11.210Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-07T13:33:30.760Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-07T13:33:59.039Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-07T13:34:15.318Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-07T13:34:28.798Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-07T13:34:39.961Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-07T13:34:56.228Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-07T13:35:05.434Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-07T13:35:05.799Z] 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. [2024-12-07T13:35:05.799Z] The best model improves the baseline by 14.43%. [2024-12-07T13:35:05.799Z] Movies recommended for you: [2024-12-07T13:35:05.799Z] WARNING: This benchmark provides no result that can be validated. [2024-12-07T13:35:05.799Z] There is no way to check that no silent failure occurred. [2024-12-07T13:35:05.799Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (143009.733 ms) ====== [2024-12-07T13:35:05.799Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-12-07T13:35:06.163Z] GC before operation: completed in 163.866 ms, heap usage 682.242 MB -> 52.103 MB. [2024-12-07T13:35:34.427Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-07T13:35:57.962Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-07T13:36:26.222Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-07T13:36:45.797Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-07T13:36:59.305Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-07T13:37:08.511Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-07T13:37:24.790Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-07T13:37:35.956Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-07T13:37:35.956Z] 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. [2024-12-07T13:37:35.956Z] The best model improves the baseline by 14.43%. [2024-12-07T13:37:35.956Z] Movies recommended for you: [2024-12-07T13:37:35.956Z] WARNING: This benchmark provides no result that can be validated. [2024-12-07T13:37:35.956Z] There is no way to check that no silent failure occurred. [2024-12-07T13:37:35.956Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (149044.907 ms) ====== [2024-12-07T13:37:35.956Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-12-07T13:37:35.956Z] GC before operation: completed in 222.532 ms, heap usage 350.424 MB -> 78.204 MB. [2024-12-07T13:37:59.456Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-07T13:38:22.973Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-07T13:38:51.195Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-07T13:39:10.760Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-07T13:39:24.262Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-07T13:39:35.434Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-07T13:39:48.932Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-07T13:40:00.085Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-07T13:40:00.442Z] 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. [2024-12-07T13:40:00.442Z] The best model improves the baseline by 14.43%. [2024-12-07T13:40:00.442Z] Movies recommended for you: [2024-12-07T13:40:00.442Z] WARNING: This benchmark provides no result that can be validated. [2024-12-07T13:40:00.442Z] There is no way to check that no silent failure occurred. [2024-12-07T13:40:00.442Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (145169.310 ms) ====== [2024-12-07T13:40:00.442Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-12-07T13:40:00.807Z] GC before operation: completed in 164.626 ms, heap usage 374.878 MB -> 57.252 MB. [2024-12-07T13:40:24.320Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-07T13:40:52.554Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-07T13:41:16.170Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-07T13:41:39.677Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-07T13:41:50.892Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-07T13:42:02.029Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-07T13:42:18.271Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-07T13:42:29.402Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-07T13:42:29.402Z] 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. [2024-12-07T13:42:29.402Z] The best model improves the baseline by 14.43%. [2024-12-07T13:42:29.402Z] Movies recommended for you: [2024-12-07T13:42:29.402Z] WARNING: This benchmark provides no result that can be validated. [2024-12-07T13:42:29.402Z] There is no way to check that no silent failure occurred. [2024-12-07T13:42:29.402Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (147958.149 ms) ====== [2024-12-07T13:42:29.402Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-12-07T13:42:29.402Z] GC before operation: completed in 314.523 ms, heap usage 939.445 MB -> 57.597 MB. [2024-12-07T13:42:52.914Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-07T13:43:16.401Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-07T13:43:44.590Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-07T13:44:08.068Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-07T13:44:19.203Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-07T13:44:28.383Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-07T13:44:44.672Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-07T13:44:55.819Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-07T13:44:55.819Z] 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. [2024-12-07T13:44:55.819Z] The best model improves the baseline by 14.43%. [2024-12-07T13:44:55.819Z] Movies recommended for you: [2024-12-07T13:44:55.819Z] WARNING: This benchmark provides no result that can be validated. [2024-12-07T13:44:55.819Z] There is no way to check that no silent failure occurred. [2024-12-07T13:44:55.819Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (146322.546 ms) ====== [2024-12-07T13:44:55.819Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-12-07T13:44:55.819Z] GC before operation: completed in 162.241 ms, heap usage 282.159 MB -> 55.320 MB. [2024-12-07T13:45:19.428Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-07T13:45:47.668Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-07T13:46:15.889Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-07T13:46:42.360Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-07T13:47:03.574Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-07T13:47:12.772Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-07T13:47:29.033Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-07T13:47:40.203Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-07T13:47:40.970Z] 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. [2024-12-07T13:47:40.970Z] The best model improves the baseline by 14.43%. [2024-12-07T13:47:40.970Z] Movies recommended for you: [2024-12-07T13:47:40.970Z] WARNING: This benchmark provides no result that can be validated. [2024-12-07T13:47:40.970Z] There is no way to check that no silent failure occurred. [2024-12-07T13:47:40.970Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (165571.063 ms) ====== [2024-12-07T13:47:40.970Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-12-07T13:47:41.328Z] GC before operation: completed in 199.324 ms, heap usage 553.412 MB -> 55.312 MB. [2024-12-07T13:48:09.564Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-07T13:48:37.823Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-07T13:49:06.075Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-07T13:49:29.602Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-07T13:49:40.783Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-07T13:49:54.295Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-07T13:50:10.551Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-07T13:50:24.049Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-07T13:50:24.049Z] 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. [2024-12-07T13:50:24.049Z] The best model improves the baseline by 14.43%. [2024-12-07T13:50:24.049Z] Movies recommended for you: [2024-12-07T13:50:24.049Z] WARNING: This benchmark provides no result that can be validated. [2024-12-07T13:50:24.049Z] There is no way to check that no silent failure occurred. [2024-12-07T13:50:24.049Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (161791.795 ms) ====== [2024-12-07T13:50:24.049Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-12-07T13:50:24.049Z] GC before operation: completed in 175.001 ms, heap usage 359.459 MB -> 57.839 MB. [2024-12-07T13:50:52.291Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-07T13:51:15.843Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-07T13:51:44.116Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-07T13:52:03.693Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-07T13:52:14.912Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-07T13:52:26.083Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-07T13:52:39.585Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-07T13:52:50.756Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-07T13:52:50.756Z] 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. [2024-12-07T13:52:50.756Z] The best model improves the baseline by 14.43%. [2024-12-07T13:52:51.126Z] Movies recommended for you: [2024-12-07T13:52:51.126Z] WARNING: This benchmark provides no result that can be validated. [2024-12-07T13:52:51.126Z] There is no way to check that no silent failure occurred. [2024-12-07T13:52:51.126Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (147794.967 ms) ====== [2024-12-07T13:52:51.126Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-12-07T13:52:51.126Z] GC before operation: completed in 135.113 ms, heap usage 609.956 MB -> 56.955 MB. [2024-12-07T13:53:14.668Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-07T13:53:38.217Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-07T13:54:12.114Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-07T13:54:31.714Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-07T13:54:45.232Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-07T13:54:56.417Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-07T13:55:12.692Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-07T13:55:21.912Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-07T13:55:22.268Z] 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. [2024-12-07T13:55:22.268Z] The best model improves the baseline by 14.43%. [2024-12-07T13:55:22.268Z] Movies recommended for you: [2024-12-07T13:55:22.268Z] WARNING: This benchmark provides no result that can be validated. [2024-12-07T13:55:22.268Z] There is no way to check that no silent failure occurred. [2024-12-07T13:55:22.268Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (151253.498 ms) ====== [2024-12-07T13:55:22.268Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-12-07T13:55:22.626Z] GC before operation: completed in 150.328 ms, heap usage 232.300 MB -> 55.498 MB. [2024-12-07T13:55:46.191Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-07T13:56:09.762Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-07T13:56:43.702Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-07T13:57:07.213Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-07T13:57:18.385Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-07T13:57:29.548Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-07T13:57:45.828Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-07T13:57:59.362Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-07T13:57:59.362Z] 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. [2024-12-07T13:57:59.362Z] The best model improves the baseline by 14.43%. [2024-12-07T13:57:59.362Z] Movies recommended for you: [2024-12-07T13:57:59.362Z] WARNING: This benchmark provides no result that can be validated. [2024-12-07T13:57:59.362Z] There is no way to check that no silent failure occurred. [2024-12-07T13:57:59.362Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (156059.720 ms) ====== [2024-12-07T13:57:59.362Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-12-07T13:57:59.362Z] GC before operation: completed in 138.499 ms, heap usage 647.551 MB -> 55.688 MB. [2024-12-07T13:58:27.587Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-07T13:58:51.117Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-07T13:59:19.350Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-07T13:59:38.941Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-07T13:59:52.448Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-07T14:00:03.655Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-07T14:00:19.940Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-07T14:00:29.174Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-07T14:00:29.174Z] 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. [2024-12-07T14:00:29.174Z] The best model improves the baseline by 14.43%. [2024-12-07T14:00:29.174Z] Movies recommended for you: [2024-12-07T14:00:29.174Z] WARNING: This benchmark provides no result that can be validated. [2024-12-07T14:00:29.174Z] There is no way to check that no silent failure occurred. [2024-12-07T14:00:29.174Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (150300.610 ms) ====== [2024-12-07T14:00:29.174Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-12-07T14:00:29.174Z] GC before operation: completed in 159.214 ms, heap usage 733.933 MB -> 55.391 MB. [2024-12-07T14:00:52.746Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-07T14:01:16.298Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-07T14:01:44.552Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-07T14:02:08.080Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-07T14:02:21.561Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-07T14:02:32.713Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-07T14:02:48.973Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-07T14:03:00.139Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-07T14:03:00.139Z] 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. [2024-12-07T14:03:00.139Z] The best model improves the baseline by 14.43%. [2024-12-07T14:03:00.139Z] Movies recommended for you: [2024-12-07T14:03:00.139Z] WARNING: This benchmark provides no result that can be validated. [2024-12-07T14:03:00.139Z] There is no way to check that no silent failure occurred. [2024-12-07T14:03:00.139Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (151116.294 ms) ====== [2024-12-07T14:03:00.139Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-12-07T14:03:00.499Z] GC before operation: completed in 148.805 ms, heap usage 352.329 MB -> 55.595 MB. [2024-12-07T14:03:24.056Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-07T14:03:47.605Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-07T14:04:15.938Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-07T14:04:35.517Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-07T14:04:49.014Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-07T14:05:00.198Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-07T14:05:16.468Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-07T14:05:25.688Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-07T14:05:25.689Z] 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. [2024-12-07T14:05:25.689Z] The best model improves the baseline by 14.43%. [2024-12-07T14:05:25.689Z] Movies recommended for you: [2024-12-07T14:05:25.689Z] WARNING: This benchmark provides no result that can be validated. [2024-12-07T14:05:25.689Z] There is no way to check that no silent failure occurred. [2024-12-07T14:05:25.689Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (145294.615 ms) ====== [2024-12-07T14:05:25.689Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-12-07T14:05:25.689Z] GC before operation: completed in 180.771 ms, heap usage 770.621 MB -> 55.781 MB. [2024-12-07T14:05:49.211Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-07T14:06:17.474Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-07T14:06:45.719Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-07T14:07:05.334Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-07T14:07:18.917Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-07T14:07:28.236Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-07T14:07:44.501Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-07T14:07:55.665Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-07T14:07:55.665Z] 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. [2024-12-07T14:07:55.665Z] The best model improves the baseline by 14.43%. [2024-12-07T14:07:55.665Z] Movies recommended for you: [2024-12-07T14:07:55.665Z] WARNING: This benchmark provides no result that can be validated. [2024-12-07T14:07:55.665Z] There is no way to check that no silent failure occurred. [2024-12-07T14:07:55.665Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (148913.911 ms) ====== [2024-12-07T14:07:55.665Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-12-07T14:07:55.665Z] GC before operation: completed in 142.284 ms, heap usage 326.133 MB -> 55.499 MB. [2024-12-07T14:08:19.179Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-07T14:08:42.702Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-07T14:09:11.031Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-07T14:09:30.601Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-07T14:09:44.089Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-07T14:09:57.579Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-07T14:10:13.838Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-07T14:10:23.034Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-07T14:10:23.034Z] 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. [2024-12-07T14:10:23.034Z] The best model improves the baseline by 14.43%. [2024-12-07T14:10:23.397Z] Movies recommended for you: [2024-12-07T14:10:23.397Z] WARNING: This benchmark provides no result that can be validated. [2024-12-07T14:10:23.397Z] There is no way to check that no silent failure occurred. [2024-12-07T14:10:23.397Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (148385.894 ms) ====== [2024-12-07T14:10:23.397Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-12-07T14:10:23.397Z] GC before operation: completed in 167.904 ms, heap usage 189.746 MB -> 55.556 MB. [2024-12-07T14:10:51.622Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-07T14:11:15.169Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-07T14:11:57.887Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-07T14:12:14.154Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-07T14:12:27.653Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-07T14:12:38.825Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-07T14:12:55.107Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-07T14:13:06.270Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-07T14:13:06.270Z] 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. [2024-12-07T14:13:06.270Z] The best model improves the baseline by 14.43%. [2024-12-07T14:13:06.270Z] Movies recommended for you: [2024-12-07T14:13:06.270Z] WARNING: This benchmark provides no result that can be validated. [2024-12-07T14:13:06.270Z] There is no way to check that no silent failure occurred. [2024-12-07T14:13:06.270Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (162214.409 ms) ====== [2024-12-07T14:13:06.270Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-12-07T14:13:06.270Z] GC before operation: completed in 251.368 ms, heap usage 462.652 MB -> 59.499 MB. [2024-12-07T14:13:38.876Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-07T14:14:07.108Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-07T14:14:35.363Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-07T14:14:51.656Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-07T14:15:05.160Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-07T14:15:16.325Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-07T14:15:32.629Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-07T14:15:41.837Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-07T14:15:42.196Z] 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. [2024-12-07T14:15:42.196Z] The best model improves the baseline by 14.43%. [2024-12-07T14:15:42.196Z] Movies recommended for you: [2024-12-07T14:15:42.196Z] WARNING: This benchmark provides no result that can be validated. [2024-12-07T14:15:42.196Z] There is no way to check that no silent failure occurred. [2024-12-07T14:15:42.196Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (156289.075 ms) ====== [2024-12-07T14:15:42.196Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-12-07T14:15:42.554Z] GC before operation: completed in 162.591 ms, heap usage 644.899 MB -> 57.991 MB. [2024-12-07T14:16:06.083Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-07T14:16:34.353Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-07T14:17:02.598Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-07T14:17:26.116Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-07T14:17:39.616Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-07T14:17:50.813Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-07T14:18:10.394Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-07T14:18:19.621Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-07T14:18:19.621Z] 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. [2024-12-07T14:18:19.621Z] The best model improves the baseline by 14.43%. [2024-12-07T14:18:19.978Z] Movies recommended for you: [2024-12-07T14:18:19.978Z] WARNING: This benchmark provides no result that can be validated. [2024-12-07T14:18:19.978Z] There is no way to check that no silent failure occurred. [2024-12-07T14:18:19.978Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (157423.987 ms) ====== [2024-12-07T14:18:19.978Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-12-07T14:18:19.978Z] GC before operation: completed in 170.885 ms, heap usage 131.158 MB -> 55.448 MB. [2024-12-07T14:18:48.240Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-07T14:19:16.489Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-07T14:19:44.747Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-07T14:20:08.258Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-07T14:20:21.772Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-07T14:20:30.984Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-07T14:20:47.238Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-07T14:20:58.400Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-07T14:20:58.400Z] 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. [2024-12-07T14:20:58.400Z] The best model improves the baseline by 14.43%. [2024-12-07T14:20:58.400Z] Movies recommended for you: [2024-12-07T14:20:58.400Z] WARNING: This benchmark provides no result that can be validated. [2024-12-07T14:20:58.400Z] There is no way to check that no silent failure occurred. [2024-12-07T14:20:58.400Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (157596.897 ms) ====== [2024-12-07T14:20:58.400Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-12-07T14:20:58.400Z] GC before operation: completed in 165.545 ms, heap usage 286.863 MB -> 55.802 MB. [2024-12-07T14:21:21.932Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-07T14:21:50.161Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-07T14:22:18.391Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-07T14:22:45.011Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-07T14:22:59.258Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-07T14:23:10.443Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-07T14:23:26.738Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-07T14:23:40.247Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-07T14:23:40.247Z] 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. [2024-12-07T14:23:40.247Z] The best model improves the baseline by 14.43%. [2024-12-07T14:23:40.247Z] Movies recommended for you: [2024-12-07T14:23:40.247Z] WARNING: This benchmark provides no result that can be validated. [2024-12-07T14:23:40.247Z] There is no way to check that no silent failure occurred. [2024-12-07T14:23:40.247Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (161150.061 ms) ====== [2024-12-07T14:23:40.247Z] ----------------------------------- [2024-12-07T14:23:40.247Z] renaissance-movie-lens_0_PASSED [2024-12-07T14:23:40.247Z] ----------------------------------- [2024-12-07T14:23:40.247Z] [2024-12-07T14:23:40.247Z] TEST TEARDOWN: [2024-12-07T14:23:40.247Z] Nothing to be done for teardown. [2024-12-07T14:23:40.247Z] renaissance-movie-lens_0 Finish Time: Sat Dec 7 14:23:39 2024 Epoch Time (ms): 1733581419789