renaissance-movie-lens_0
[2024-08-08T03:34:02.038Z] Running test renaissance-movie-lens_0 ...
[2024-08-08T03:34:02.038Z] ===============================================
[2024-08-08T03:34:02.038Z] renaissance-movie-lens_0 Start Time: Wed Aug 7 22:34:01 2024 Epoch Time (ms): 1723088041833
[2024-08-08T03:34:02.038Z] variation: NoOptions
[2024-08-08T03:34:02.038Z] JVM_OPTIONS:
[2024-08-08T03:34:02.038Z] { \
[2024-08-08T03:34:02.038Z] echo ""; echo "TEST SETUP:"; \
[2024-08-08T03:34:02.038Z] echo "Nothing to be done for setup."; \
[2024-08-08T03:34:02.038Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17230871299812/renaissance-movie-lens_0"; \
[2024-08-08T03:34:02.038Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17230871299812/renaissance-movie-lens_0"; \
[2024-08-08T03:34:02.038Z] echo ""; echo "TESTING:"; \
[2024-08-08T03:34:02.038Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/jdkbinary/j2sdk-image/jdk-11.0.25+2/bin/..//bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_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_17230871299812/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-08T03:34:02.038Z] 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_17230871299812/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-08T03:34:02.038Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-08T03:34:02.038Z] echo "Nothing to be done for teardown."; \
[2024-08-08T03:34:02.038Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17230871299812/TestTargetResult";
[2024-08-08T03:34:02.038Z]
[2024-08-08T03:34:02.038Z] TEST SETUP:
[2024-08-08T03:34:02.038Z] Nothing to be done for setup.
[2024-08-08T03:34:02.038Z]
[2024-08-08T03:34:02.038Z] TESTING:
[2024-08-08T03:34:05.079Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-08T03:34:07.249Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2024-08-08T03:34:10.295Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-08T03:34:10.968Z] Training: 60056, validation: 20285, test: 19854
[2024-08-08T03:34:10.968Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-08T03:34:10.968Z] GC before operation: completed in 144.623 ms, heap usage 52.124 MB -> 37.174 MB.
[2024-08-08T03:34:20.069Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T03:34:24.035Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T03:34:27.491Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T03:34:30.523Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T03:34:32.695Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T03:34:34.874Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T03:34:36.271Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T03:34:39.321Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T03:34:39.321Z] 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.
[2024-08-08T03:34:39.321Z] The best model improves the baseline by 14.43%.
[2024-08-08T03:34:39.321Z] Movies recommended for you:
[2024-08-08T03:34:39.321Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T03:34:39.321Z] There is no way to check that no silent failure occurred.
[2024-08-08T03:34:39.321Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (28539.448 ms) ======
[2024-08-08T03:34:39.321Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-08T03:34:39.321Z] GC before operation: completed in 139.176 ms, heap usage 151.606 MB -> 49.372 MB.
[2024-08-08T03:34:43.311Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T03:34:46.352Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T03:34:49.380Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T03:34:52.510Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T03:34:53.918Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T03:34:56.084Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T03:34:57.514Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T03:34:59.768Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T03:34:59.768Z] 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.
[2024-08-08T03:35:00.435Z] The best model improves the baseline by 14.43%.
[2024-08-08T03:35:00.435Z] Movies recommended for you:
[2024-08-08T03:35:00.435Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T03:35:00.435Z] There is no way to check that no silent failure occurred.
[2024-08-08T03:35:00.435Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (20610.972 ms) ======
[2024-08-08T03:35:00.435Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-08T03:35:00.435Z] GC before operation: completed in 115.570 ms, heap usage 152.210 MB -> 50.891 MB.
[2024-08-08T03:35:03.565Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T03:35:07.544Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T03:35:09.731Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T03:35:12.775Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T03:35:14.953Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T03:35:16.347Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T03:35:17.867Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T03:35:20.080Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T03:35:20.080Z] 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.
[2024-08-08T03:35:20.080Z] The best model improves the baseline by 14.43%.
[2024-08-08T03:35:20.080Z] Movies recommended for you:
[2024-08-08T03:35:20.080Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T03:35:20.080Z] There is no way to check that no silent failure occurred.
[2024-08-08T03:35:20.080Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (19782.177 ms) ======
[2024-08-08T03:35:20.080Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-08T03:35:20.080Z] GC before operation: completed in 132.138 ms, heap usage 489.804 MB -> 54.811 MB.
[2024-08-08T03:35:23.105Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T03:35:26.136Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T03:35:28.325Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T03:35:31.357Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T03:35:32.758Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T03:35:34.159Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T03:35:36.342Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T03:35:37.760Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T03:35:37.760Z] 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.
[2024-08-08T03:35:37.760Z] The best model improves the baseline by 14.43%.
[2024-08-08T03:35:38.437Z] Movies recommended for you:
[2024-08-08T03:35:38.437Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T03:35:38.437Z] There is no way to check that no silent failure occurred.
[2024-08-08T03:35:38.437Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (17852.729 ms) ======
[2024-08-08T03:35:38.437Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-08T03:35:38.437Z] GC before operation: completed in 144.010 ms, heap usage 102.080 MB -> 53.838 MB.
[2024-08-08T03:35:41.492Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T03:35:43.682Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T03:35:46.719Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T03:35:49.796Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T03:35:51.200Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T03:35:52.596Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T03:35:54.837Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T03:35:56.241Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T03:35:56.241Z] 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.
[2024-08-08T03:35:56.241Z] The best model improves the baseline by 14.43%.
[2024-08-08T03:35:56.241Z] Movies recommended for you:
[2024-08-08T03:35:56.241Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T03:35:56.241Z] There is no way to check that no silent failure occurred.
[2024-08-08T03:35:56.241Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (18273.718 ms) ======
[2024-08-08T03:35:56.241Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-08T03:35:56.909Z] GC before operation: completed in 123.301 ms, heap usage 178.681 MB -> 51.806 MB.
[2024-08-08T03:36:00.021Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T03:36:02.196Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T03:36:05.226Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T03:36:07.406Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T03:36:09.596Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T03:36:11.003Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T03:36:12.407Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T03:36:14.581Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T03:36:14.581Z] 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.
[2024-08-08T03:36:14.581Z] The best model improves the baseline by 14.43%.
[2024-08-08T03:36:14.581Z] Movies recommended for you:
[2024-08-08T03:36:14.581Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T03:36:14.581Z] There is no way to check that no silent failure occurred.
[2024-08-08T03:36:14.581Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (17910.879 ms) ======
[2024-08-08T03:36:14.581Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-08T03:36:14.581Z] GC before operation: completed in 143.736 ms, heap usage 337.214 MB -> 51.892 MB.
[2024-08-08T03:36:17.610Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T03:36:19.801Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T03:36:22.823Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T03:36:25.450Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T03:36:26.842Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T03:36:28.237Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T03:36:30.423Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T03:36:31.825Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T03:36:31.825Z] 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.
[2024-08-08T03:36:31.825Z] The best model improves the baseline by 14.43%.
[2024-08-08T03:36:31.825Z] Movies recommended for you:
[2024-08-08T03:36:31.825Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T03:36:31.825Z] There is no way to check that no silent failure occurred.
[2024-08-08T03:36:31.825Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (17393.075 ms) ======
[2024-08-08T03:36:31.825Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-08T03:36:32.498Z] GC before operation: completed in 132.005 ms, heap usage 84.092 MB -> 53.079 MB.
[2024-08-08T03:36:35.547Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T03:36:37.721Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T03:36:40.792Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T03:36:42.991Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T03:36:45.162Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T03:36:46.572Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T03:36:47.982Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T03:36:50.172Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T03:36:50.172Z] 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.
[2024-08-08T03:36:50.172Z] The best model improves the baseline by 14.43%.
[2024-08-08T03:36:50.172Z] Movies recommended for you:
[2024-08-08T03:36:50.172Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T03:36:50.172Z] There is no way to check that no silent failure occurred.
[2024-08-08T03:36:50.172Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (17932.129 ms) ======
[2024-08-08T03:36:50.172Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-08T03:36:50.172Z] GC before operation: completed in 130.307 ms, heap usage 438.699 MB -> 52.392 MB.
[2024-08-08T03:36:53.211Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T03:36:55.403Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T03:36:58.438Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T03:37:00.634Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T03:37:02.813Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T03:37:04.206Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T03:37:05.705Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T03:37:07.131Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T03:37:07.799Z] 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.
[2024-08-08T03:37:07.799Z] The best model improves the baseline by 14.43%.
[2024-08-08T03:37:07.799Z] Movies recommended for you:
[2024-08-08T03:37:07.799Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T03:37:07.799Z] There is no way to check that no silent failure occurred.
[2024-08-08T03:37:07.799Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (17418.179 ms) ======
[2024-08-08T03:37:07.799Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-08T03:37:07.799Z] GC before operation: completed in 126.592 ms, heap usage 100.910 MB -> 54.446 MB.
[2024-08-08T03:37:10.822Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T03:37:12.998Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T03:37:16.038Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T03:37:18.220Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T03:37:19.613Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T03:37:21.788Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T03:37:23.180Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T03:37:24.579Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T03:37:25.246Z] 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.
[2024-08-08T03:37:25.247Z] The best model improves the baseline by 14.43%.
[2024-08-08T03:37:25.247Z] Movies recommended for you:
[2024-08-08T03:37:25.247Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T03:37:25.247Z] There is no way to check that no silent failure occurred.
[2024-08-08T03:37:25.247Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (17450.490 ms) ======
[2024-08-08T03:37:25.247Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-08T03:37:25.247Z] GC before operation: completed in 130.582 ms, heap usage 448.666 MB -> 52.360 MB.
[2024-08-08T03:37:28.305Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T03:37:31.332Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T03:37:33.528Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T03:37:36.556Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T03:37:37.957Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T03:37:39.367Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T03:37:40.777Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T03:37:42.978Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T03:37:42.978Z] 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.
[2024-08-08T03:37:42.978Z] The best model improves the baseline by 14.43%.
[2024-08-08T03:37:42.978Z] Movies recommended for you:
[2024-08-08T03:37:42.978Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T03:37:42.978Z] There is no way to check that no silent failure occurred.
[2024-08-08T03:37:42.978Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (17642.706 ms) ======
[2024-08-08T03:37:42.978Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-08T03:37:42.978Z] GC before operation: completed in 135.177 ms, heap usage 327.562 MB -> 51.957 MB.
[2024-08-08T03:37:46.017Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T03:37:49.050Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T03:37:51.235Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T03:37:53.441Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T03:37:55.619Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T03:37:57.009Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T03:37:58.409Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T03:38:00.597Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T03:38:00.597Z] 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.
[2024-08-08T03:38:00.597Z] The best model improves the baseline by 14.43%.
[2024-08-08T03:38:00.597Z] Movies recommended for you:
[2024-08-08T03:38:00.597Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T03:38:00.597Z] There is no way to check that no silent failure occurred.
[2024-08-08T03:38:00.597Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (17449.196 ms) ======
[2024-08-08T03:38:00.597Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-08T03:38:00.597Z] GC before operation: completed in 132.017 ms, heap usage 296.532 MB -> 52.145 MB.
[2024-08-08T03:38:03.626Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T03:38:05.868Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T03:38:08.914Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T03:38:11.987Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T03:38:13.395Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T03:38:14.808Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T03:38:16.995Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T03:38:18.402Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T03:38:18.402Z] 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.
[2024-08-08T03:38:18.402Z] The best model improves the baseline by 14.43%.
[2024-08-08T03:38:19.069Z] Movies recommended for you:
[2024-08-08T03:38:19.069Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T03:38:19.069Z] There is no way to check that no silent failure occurred.
[2024-08-08T03:38:19.069Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (18023.469 ms) ======
[2024-08-08T03:38:19.069Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-08T03:38:19.069Z] GC before operation: completed in 135.166 ms, heap usage 389.149 MB -> 52.376 MB.
[2024-08-08T03:38:22.138Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T03:38:24.316Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T03:38:27.353Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T03:38:29.534Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T03:38:31.727Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T03:38:33.116Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T03:38:34.746Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T03:38:36.171Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T03:38:36.171Z] 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.
[2024-08-08T03:38:36.171Z] The best model improves the baseline by 14.43%.
[2024-08-08T03:38:36.845Z] Movies recommended for you:
[2024-08-08T03:38:36.845Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T03:38:36.845Z] There is no way to check that no silent failure occurred.
[2024-08-08T03:38:36.845Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (17564.205 ms) ======
[2024-08-08T03:38:36.845Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-08T03:38:36.845Z] GC before operation: completed in 139.227 ms, heap usage 304.862 MB -> 52.024 MB.
[2024-08-08T03:38:39.041Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T03:38:42.073Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T03:38:44.278Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T03:38:47.334Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T03:38:48.725Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T03:38:50.134Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T03:38:51.637Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T03:38:53.806Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T03:38:53.806Z] 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.
[2024-08-08T03:38:53.806Z] The best model improves the baseline by 14.43%.
[2024-08-08T03:38:53.806Z] Movies recommended for you:
[2024-08-08T03:38:53.806Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T03:38:53.806Z] There is no way to check that no silent failure occurred.
[2024-08-08T03:38:53.806Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (17167.069 ms) ======
[2024-08-08T03:38:53.806Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-08T03:38:53.806Z] GC before operation: completed in 141.808 ms, heap usage 303.248 MB -> 52.271 MB.
[2024-08-08T03:38:56.823Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T03:38:58.995Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T03:39:02.020Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T03:39:04.203Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T03:39:06.401Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T03:39:07.802Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T03:39:09.201Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T03:39:11.392Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T03:39:11.392Z] 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.
[2024-08-08T03:39:11.392Z] The best model improves the baseline by 14.43%.
[2024-08-08T03:39:11.392Z] Movies recommended for you:
[2024-08-08T03:39:11.392Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T03:39:11.392Z] There is no way to check that no silent failure occurred.
[2024-08-08T03:39:11.392Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (17524.842 ms) ======
[2024-08-08T03:39:11.392Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-08T03:39:11.392Z] GC before operation: completed in 140.422 ms, heap usage 105.418 MB -> 54.758 MB.
[2024-08-08T03:39:14.424Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T03:39:17.448Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T03:39:19.625Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T03:39:21.815Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T03:39:24.004Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T03:39:25.407Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T03:39:26.807Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T03:39:28.228Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T03:39:28.895Z] 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.
[2024-08-08T03:39:28.895Z] The best model improves the baseline by 14.43%.
[2024-08-08T03:39:28.895Z] Movies recommended for you:
[2024-08-08T03:39:28.895Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T03:39:28.895Z] There is no way to check that no silent failure occurred.
[2024-08-08T03:39:28.895Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (17166.718 ms) ======
[2024-08-08T03:39:28.895Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-08T03:39:28.895Z] GC before operation: completed in 163.919 ms, heap usage 172.106 MB -> 52.037 MB.
[2024-08-08T03:39:31.936Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T03:39:34.114Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T03:39:37.142Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T03:39:39.748Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T03:39:41.161Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T03:39:42.556Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T03:39:44.743Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T03:39:46.143Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T03:39:46.143Z] 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.
[2024-08-08T03:39:46.143Z] The best model improves the baseline by 14.43%.
[2024-08-08T03:39:46.143Z] Movies recommended for you:
[2024-08-08T03:39:46.143Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T03:39:46.143Z] There is no way to check that no silent failure occurred.
[2024-08-08T03:39:46.143Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (17466.718 ms) ======
[2024-08-08T03:39:46.143Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-08T03:39:46.811Z] GC before operation: completed in 133.645 ms, heap usage 89.835 MB -> 52.725 MB.
[2024-08-08T03:39:49.849Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T03:39:52.031Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T03:39:55.053Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T03:39:57.239Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T03:39:58.643Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T03:40:00.036Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T03:40:02.209Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T03:40:03.631Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T03:40:03.631Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-08T03:40:03.631Z] The best model improves the baseline by 14.43%.
[2024-08-08T03:40:04.304Z] Movies recommended for you:
[2024-08-08T03:40:04.304Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T03:40:04.304Z] There is no way to check that no silent failure occurred.
[2024-08-08T03:40:04.304Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (17444.895 ms) ======
[2024-08-08T03:40:04.304Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-08T03:40:04.304Z] GC before operation: completed in 134.749 ms, heap usage 295.624 MB -> 52.446 MB.
[2024-08-08T03:40:07.364Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T03:40:09.540Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T03:40:12.595Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T03:40:14.781Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T03:40:16.178Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T03:40:17.736Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T03:40:19.901Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T03:40:21.296Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T03:40:21.963Z] 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.
[2024-08-08T03:40:21.963Z] The best model improves the baseline by 14.43%.
[2024-08-08T03:40:21.963Z] Movies recommended for you:
[2024-08-08T03:40:21.963Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T03:40:21.963Z] There is no way to check that no silent failure occurred.
[2024-08-08T03:40:21.963Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (17708.316 ms) ======
[2024-08-08T03:40:23.355Z] -----------------------------------
[2024-08-08T03:40:23.355Z] renaissance-movie-lens_0_PASSED
[2024-08-08T03:40:23.355Z] -----------------------------------
[2024-08-08T03:40:23.355Z]
[2024-08-08T03:40:23.355Z] TEST TEARDOWN:
[2024-08-08T03:40:23.355Z] Nothing to be done for teardown.
[2024-08-08T03:40:23.355Z] renaissance-movie-lens_0 Finish Time: Wed Aug 7 22:40:22 2024 Epoch Time (ms): 1723088422621