renaissance-movie-lens_0
[2024-11-08T15:19:28.546Z] Running test renaissance-movie-lens_0 ...
[2024-11-08T15:19:28.546Z] ===============================================
[2024-11-08T15:19:28.546Z] renaissance-movie-lens_0 Start Time: Fri Nov 8 15:19:27 2024 Epoch Time (ms): 1731079167722
[2024-11-08T15:19:28.546Z] variation: NoOptions
[2024-11-08T15:19:28.546Z] JVM_OPTIONS:
[2024-11-08T15:19:28.546Z] { \
[2024-11-08T15:19:28.546Z] echo ""; echo "TEST SETUP:"; \
[2024-11-08T15:19:28.546Z] echo "Nothing to be done for setup."; \
[2024-11-08T15:19:28.546Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17310781315454/renaissance-movie-lens_0"; \
[2024-11-08T15:19:28.546Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17310781315454/renaissance-movie-lens_0"; \
[2024-11-08T15:19:28.546Z] echo ""; echo "TESTING:"; \
[2024-11-08T15:19:28.546Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17310781315454/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-08T15:19:28.546Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17310781315454/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-08T15:19:28.546Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-08T15:19:28.547Z] echo "Nothing to be done for teardown."; \
[2024-11-08T15:19:28.547Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17310781315454/TestTargetResult";
[2024-11-08T15:19:28.547Z]
[2024-11-08T15:19:28.547Z] TEST SETUP:
[2024-11-08T15:19:28.547Z] Nothing to be done for setup.
[2024-11-08T15:19:28.547Z]
[2024-11-08T15:19:28.547Z] TESTING:
[2024-11-08T15:19:32.150Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-08T15:19:36.179Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2024-11-08T15:19:42.715Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-08T15:19:43.635Z] Training: 60056, validation: 20285, test: 19854
[2024-11-08T15:19:43.635Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-08T15:19:43.635Z] GC before operation: completed in 96.681 ms, heap usage 73.447 MB -> 39.334 MB.
[2024-11-08T15:19:54.902Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:20:00.121Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:20:04.148Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:20:08.174Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:20:11.097Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:20:12.989Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:20:15.919Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:20:17.811Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:20:18.732Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:20:18.732Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:20:18.732Z] Movies recommended for you:
[2024-11-08T15:20:18.732Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:20:18.732Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:20:18.732Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (35318.338 ms) ======
[2024-11-08T15:20:18.732Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-08T15:20:18.732Z] GC before operation: completed in 109.983 ms, heap usage 601.226 MB -> 57.729 MB.
[2024-11-08T15:20:22.762Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:20:26.794Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:20:30.832Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:20:33.432Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:20:36.362Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:20:38.257Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:20:40.148Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:20:42.039Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:20:42.961Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:20:42.961Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:20:42.961Z] Movies recommended for you:
[2024-11-08T15:20:42.961Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:20:42.961Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:20:42.961Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (23951.911 ms) ======
[2024-11-08T15:20:42.962Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-08T15:20:42.962Z] GC before operation: completed in 133.152 ms, heap usage 363.148 MB -> 53.186 MB.
[2024-11-08T15:20:45.886Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:20:49.921Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:20:52.875Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:20:55.801Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:20:57.695Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:20:59.595Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:21:01.490Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:21:03.385Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:21:04.308Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:21:04.308Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:21:04.308Z] Movies recommended for you:
[2024-11-08T15:21:04.308Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:21:04.308Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:21:04.308Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (21440.400 ms) ======
[2024-11-08T15:21:04.308Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-08T15:21:04.308Z] GC before operation: completed in 107.547 ms, heap usage 608.027 MB -> 57.042 MB.
[2024-11-08T15:21:07.237Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:21:10.163Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:21:13.088Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:21:16.015Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:21:17.911Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:21:19.803Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:21:21.705Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:21:23.600Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:21:23.600Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:21:23.600Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:21:23.600Z] Movies recommended for you:
[2024-11-08T15:21:23.600Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:21:23.600Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:21:23.600Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (19459.778 ms) ======
[2024-11-08T15:21:23.600Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-08T15:21:23.600Z] GC before operation: completed in 99.760 ms, heap usage 321.774 MB -> 53.773 MB.
[2024-11-08T15:21:26.864Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:21:29.790Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:21:32.720Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:21:35.644Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:21:37.538Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:21:38.460Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:21:40.351Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:21:42.246Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:21:43.166Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:21:43.166Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:21:43.166Z] Movies recommended for you:
[2024-11-08T15:21:43.166Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:21:43.166Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:21:43.166Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (19154.066 ms) ======
[2024-11-08T15:21:43.166Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-08T15:21:43.166Z] GC before operation: completed in 111.779 ms, heap usage 355.726 MB -> 54.081 MB.
[2024-11-08T15:21:46.088Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:21:49.011Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:21:51.934Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:21:54.861Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:21:56.753Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:21:57.676Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:21:59.570Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:22:01.481Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:22:02.403Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:22:02.403Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:22:02.403Z] Movies recommended for you:
[2024-11-08T15:22:02.403Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:22:02.403Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:22:02.403Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (19023.093 ms) ======
[2024-11-08T15:22:02.403Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-08T15:22:02.403Z] GC before operation: completed in 101.966 ms, heap usage 307.169 MB -> 54.162 MB.
[2024-11-08T15:22:05.332Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:22:08.260Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:22:11.198Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:22:13.092Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:22:15.164Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:22:17.201Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:22:19.134Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:22:21.700Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:22:21.700Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:22:21.700Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:22:21.700Z] Movies recommended for you:
[2024-11-08T15:22:21.700Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:22:21.700Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:22:21.700Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (18729.015 ms) ======
[2024-11-08T15:22:21.700Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-08T15:22:21.700Z] GC before operation: completed in 102.430 ms, heap usage 305.955 MB -> 54.203 MB.
[2024-11-08T15:22:24.627Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:22:26.520Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:22:29.449Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:22:32.375Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:22:34.268Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:22:35.188Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:22:37.083Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:22:38.980Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:22:39.904Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:22:39.904Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:22:39.904Z] Movies recommended for you:
[2024-11-08T15:22:39.904Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:22:39.904Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:22:39.904Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (18518.571 ms) ======
[2024-11-08T15:22:39.904Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-08T15:22:39.904Z] GC before operation: completed in 113.737 ms, heap usage 364.960 MB -> 54.534 MB.
[2024-11-08T15:22:42.831Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:22:45.759Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:22:48.684Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:22:50.579Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:22:52.473Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:22:54.367Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:22:56.271Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:22:58.165Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:22:58.165Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:22:58.165Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:22:58.165Z] Movies recommended for you:
[2024-11-08T15:22:58.165Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:22:58.165Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:22:58.165Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (18679.437 ms) ======
[2024-11-08T15:22:58.165Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-08T15:22:59.086Z] GC before operation: completed in 105.368 ms, heap usage 306.175 MB -> 54.370 MB.
[2024-11-08T15:23:02.017Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:23:03.911Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:23:06.835Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:23:09.766Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:23:11.670Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:23:13.568Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:23:15.461Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:23:17.095Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:23:17.095Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:23:17.095Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:23:17.095Z] Movies recommended for you:
[2024-11-08T15:23:17.095Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:23:17.095Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:23:17.095Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (18709.984 ms) ======
[2024-11-08T15:23:17.095Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-08T15:23:17.095Z] GC before operation: completed in 104.961 ms, heap usage 307.522 MB -> 54.413 MB.
[2024-11-08T15:23:20.022Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:23:23.020Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:23:25.946Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:23:28.876Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:23:29.797Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:23:31.698Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:23:33.594Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:23:35.491Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:23:35.491Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:23:35.491Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:23:36.414Z] Movies recommended for you:
[2024-11-08T15:23:36.414Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:23:36.414Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:23:36.414Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (18576.612 ms) ======
[2024-11-08T15:23:36.414Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-08T15:23:36.414Z] GC before operation: completed in 105.709 ms, heap usage 357.917 MB -> 54.118 MB.
[2024-11-08T15:23:39.340Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:23:42.265Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:23:44.160Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:23:47.091Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:23:48.989Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:23:50.881Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:23:52.772Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:23:54.663Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:23:54.663Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:23:54.663Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:23:54.663Z] Movies recommended for you:
[2024-11-08T15:23:54.663Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:23:54.663Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:23:54.663Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (18597.024 ms) ======
[2024-11-08T15:23:54.663Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-08T15:23:54.663Z] GC before operation: completed in 103.426 ms, heap usage 307.364 MB -> 54.381 MB.
[2024-11-08T15:23:57.584Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:24:00.503Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:24:03.435Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:24:06.363Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:24:07.284Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:24:09.183Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:24:11.768Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:24:13.665Z] RMSE (validation) = 0.9001440981626696 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:24:13.665Z] 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.
[2024-11-08T15:24:13.665Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:24:13.665Z] Movies recommended for you:
[2024-11-08T15:24:13.665Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:24:13.665Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:24:13.665Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (18903.742 ms) ======
[2024-11-08T15:24:13.665Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-08T15:24:13.665Z] GC before operation: completed in 109.240 ms, heap usage 307.145 MB -> 54.507 MB.
[2024-11-08T15:24:16.744Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:24:19.708Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:24:22.641Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:24:24.536Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:24:26.430Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:24:28.325Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:24:30.217Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:24:32.108Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:24:32.108Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:24:32.108Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:24:32.108Z] Movies recommended for you:
[2024-11-08T15:24:32.108Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:24:32.108Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:24:32.108Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (18467.284 ms) ======
[2024-11-08T15:24:32.108Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-08T15:24:32.108Z] GC before operation: completed in 107.181 ms, heap usage 307.032 MB -> 54.409 MB.
[2024-11-08T15:24:36.134Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:24:38.045Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:24:41.015Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:24:43.941Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:24:45.834Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:24:47.728Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:24:48.649Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:24:50.541Z] RMSE (validation) = 0.9001440981626696 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:24:51.464Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:24:51.464Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:24:51.464Z] Movies recommended for you:
[2024-11-08T15:24:51.464Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:24:51.464Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:24:51.464Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (18928.413 ms) ======
[2024-11-08T15:24:51.464Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-08T15:24:51.464Z] GC before operation: completed in 103.295 ms, heap usage 393.709 MB -> 54.510 MB.
[2024-11-08T15:24:54.389Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:24:57.319Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:25:00.249Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:25:02.809Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:25:04.711Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:25:05.633Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:25:07.553Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:25:09.446Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:25:10.368Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:25:10.368Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:25:10.368Z] Movies recommended for you:
[2024-11-08T15:25:10.368Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:25:10.368Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:25:10.368Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (18742.801 ms) ======
[2024-11-08T15:25:10.368Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-08T15:25:10.368Z] GC before operation: completed in 109.579 ms, heap usage 652.716 MB -> 58.107 MB.
[2024-11-08T15:25:13.288Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:25:16.398Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:25:18.292Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:25:21.251Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:25:23.147Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:25:25.040Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:25:26.929Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:25:27.849Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:25:28.772Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:25:28.772Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:25:28.772Z] Movies recommended for you:
[2024-11-08T15:25:28.772Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:25:28.772Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:25:28.772Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (18422.331 ms) ======
[2024-11-08T15:25:28.772Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-08T15:25:28.772Z] GC before operation: completed in 108.760 ms, heap usage 196.775 MB -> 54.314 MB.
[2024-11-08T15:25:31.692Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:25:34.616Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:25:37.574Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:25:39.476Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:25:41.370Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:25:43.264Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:25:45.299Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:25:47.205Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:25:47.205Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:25:47.205Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:25:47.205Z] Movies recommended for you:
[2024-11-08T15:25:47.205Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:25:47.205Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:25:47.205Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (18573.145 ms) ======
[2024-11-08T15:25:47.205Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-08T15:25:47.205Z] GC before operation: completed in 106.873 ms, heap usage 304.814 MB -> 54.457 MB.
[2024-11-08T15:25:50.127Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:25:53.049Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:25:55.987Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:25:58.253Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:26:00.151Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:26:02.048Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:26:03.999Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:26:04.921Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:26:05.841Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:26:05.841Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:26:05.841Z] Movies recommended for you:
[2024-11-08T15:26:05.841Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:26:05.841Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:26:05.842Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (18351.730 ms) ======
[2024-11-08T15:26:05.842Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-08T15:26:05.842Z] GC before operation: completed in 108.172 ms, heap usage 418.632 MB -> 54.640 MB.
[2024-11-08T15:26:08.769Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T15:26:11.695Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T15:26:14.625Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T15:26:16.572Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T15:26:18.466Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T15:26:20.360Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T15:26:22.254Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T15:26:24.147Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T15:26:24.147Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-08T15:26:24.147Z] The best model improves the baseline by 14.43%.
[2024-11-08T15:26:24.147Z] Movies recommended for you:
[2024-11-08T15:26:24.147Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T15:26:24.147Z] There is no way to check that no silent failure occurred.
[2024-11-08T15:26:24.147Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (18398.298 ms) ======
[2024-11-08T15:26:26.042Z] -----------------------------------
[2024-11-08T15:26:26.042Z] renaissance-movie-lens_0_PASSED
[2024-11-08T15:26:26.042Z] -----------------------------------
[2024-11-08T15:26:26.042Z]
[2024-11-08T15:26:26.042Z] TEST TEARDOWN:
[2024-11-08T15:26:26.042Z] Nothing to be done for teardown.
[2024-11-08T15:26:26.042Z] renaissance-movie-lens_0 Finish Time: Fri Nov 8 15:26:25 2024 Epoch Time (ms): 1731079585724