renaissance-movie-lens_0
[2024-08-16T21:25:44.308Z] Running test renaissance-movie-lens_0 ...
[2024-08-16T21:25:44.308Z] ===============================================
[2024-08-16T21:25:44.308Z] renaissance-movie-lens_0 Start Time: Fri Aug 16 16:25:43 2024 Epoch Time (ms): 1723843543857
[2024-08-16T21:25:44.308Z] variation: NoOptions
[2024-08-16T21:25:44.308Z] JVM_OPTIONS:
[2024-08-16T21:25:44.308Z] { \
[2024-08-16T21:25:44.308Z] echo ""; echo "TEST SETUP:"; \
[2024-08-16T21:25:44.308Z] echo "Nothing to be done for setup."; \
[2024-08-16T21:25:44.308Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17238428998059/renaissance-movie-lens_0"; \
[2024-08-16T21:25:44.308Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17238428998059/renaissance-movie-lens_0"; \
[2024-08-16T21:25:44.308Z] echo ""; echo "TESTING:"; \
[2024-08-16T21:25:44.308Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux_testList_0/jdkbinary/j2sdk-image/jdk-17.0.13+3/bin/..//bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17238428998059/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-16T21:25:44.308Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17238428998059/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-16T21:25:44.308Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-16T21:25:44.308Z] echo "Nothing to be done for teardown."; \
[2024-08-16T21:25:44.308Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17238428998059/TestTargetResult";
[2024-08-16T21:25:44.308Z]
[2024-08-16T21:25:44.308Z] TEST SETUP:
[2024-08-16T21:25:44.308Z] Nothing to be done for setup.
[2024-08-16T21:25:44.308Z]
[2024-08-16T21:25:44.308Z] TESTING:
[2024-08-16T21:25:47.375Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-16T21:25:48.784Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2024-08-16T21:25:51.863Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-16T21:25:52.999Z] Training: 60056, validation: 20285, test: 19854
[2024-08-16T21:25:52.999Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-16T21:25:52.999Z] GC before operation: completed in 62.336 ms, heap usage 54.807 MB -> 37.748 MB.
[2024-08-16T21:25:59.271Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T21:26:03.370Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T21:26:06.426Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T21:26:09.512Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T21:26:10.929Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T21:26:12.354Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T21:26:14.617Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T21:26:16.074Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T21:26:16.074Z] 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.
[2024-08-16T21:26:16.755Z] The best model improves the baseline by 14.43%.
[2024-08-16T21:26:16.755Z] Movies recommended for you:
[2024-08-16T21:26:16.755Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T21:26:16.755Z] There is no way to check that no silent failure occurred.
[2024-08-16T21:26:16.755Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (24182.390 ms) ======
[2024-08-16T21:26:16.755Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-16T21:26:16.755Z] GC before operation: completed in 108.506 ms, heap usage 496.910 MB -> 52.696 MB.
[2024-08-16T21:26:19.836Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T21:26:22.938Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T21:26:25.152Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T21:26:28.252Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T21:26:29.676Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T21:26:31.111Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T21:26:32.545Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T21:26:34.759Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T21:26:34.759Z] 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.
[2024-08-16T21:26:34.759Z] The best model improves the baseline by 14.43%.
[2024-08-16T21:26:34.759Z] Movies recommended for you:
[2024-08-16T21:26:34.759Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T21:26:34.759Z] There is no way to check that no silent failure occurred.
[2024-08-16T21:26:34.759Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (18196.320 ms) ======
[2024-08-16T21:26:34.759Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-16T21:26:34.759Z] GC before operation: completed in 78.494 ms, heap usage 435.704 MB -> 51.607 MB.
[2024-08-16T21:26:37.912Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T21:26:41.044Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T21:26:43.258Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T21:26:46.343Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T21:26:47.766Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T21:26:49.185Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T21:26:51.359Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T21:26:52.050Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T21:26:52.050Z] 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.
[2024-08-16T21:26:52.737Z] The best model improves the baseline by 14.43%.
[2024-08-16T21:26:52.737Z] Movies recommended for you:
[2024-08-16T21:26:52.737Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T21:26:52.737Z] There is no way to check that no silent failure occurred.
[2024-08-16T21:26:52.737Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17553.919 ms) ======
[2024-08-16T21:26:52.737Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-16T21:26:52.737Z] GC before operation: completed in 80.138 ms, heap usage 327.090 MB -> 51.997 MB.
[2024-08-16T21:26:55.839Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T21:26:57.282Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T21:27:00.395Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T21:27:01.817Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T21:27:03.248Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T21:27:04.659Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T21:27:06.087Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T21:27:07.525Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T21:27:08.212Z] 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.
[2024-08-16T21:27:08.212Z] The best model improves the baseline by 14.43%.
[2024-08-16T21:27:08.212Z] Movies recommended for you:
[2024-08-16T21:27:08.212Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T21:27:08.212Z] There is no way to check that no silent failure occurred.
[2024-08-16T21:27:08.212Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (15519.689 ms) ======
[2024-08-16T21:27:08.212Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-16T21:27:08.212Z] GC before operation: completed in 55.790 ms, heap usage 594.855 MB -> 55.795 MB.
[2024-08-16T21:27:11.319Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T21:27:12.759Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T21:27:15.863Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T21:27:18.074Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T21:27:19.494Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T21:27:20.902Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T21:27:22.313Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T21:27:23.721Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T21:27:23.721Z] 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.
[2024-08-16T21:27:23.721Z] The best model improves the baseline by 14.43%.
[2024-08-16T21:27:23.721Z] Movies recommended for you:
[2024-08-16T21:27:23.721Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T21:27:23.721Z] There is no way to check that no silent failure occurred.
[2024-08-16T21:27:23.721Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15805.742 ms) ======
[2024-08-16T21:27:23.721Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-16T21:27:23.721Z] GC before operation: completed in 53.338 ms, heap usage 445.150 MB -> 52.563 MB.
[2024-08-16T21:27:26.788Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T21:27:29.005Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T21:27:31.236Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T21:27:33.454Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T21:27:34.897Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T21:27:36.310Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T21:27:37.734Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T21:27:39.155Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T21:27:39.155Z] 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.
[2024-08-16T21:27:39.155Z] The best model improves the baseline by 14.43%.
[2024-08-16T21:27:39.836Z] Movies recommended for you:
[2024-08-16T21:27:39.836Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T21:27:39.836Z] There is no way to check that no silent failure occurred.
[2024-08-16T21:27:39.836Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15519.265 ms) ======
[2024-08-16T21:27:39.836Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-16T21:27:39.836Z] GC before operation: completed in 80.062 ms, heap usage 78.957 MB -> 55.755 MB.
[2024-08-16T21:27:42.062Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T21:27:45.158Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T21:27:47.357Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T21:27:49.588Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T21:27:50.272Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T21:27:51.693Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T21:27:53.687Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T21:27:54.368Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T21:27:55.049Z] 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.
[2024-08-16T21:27:55.049Z] The best model improves the baseline by 14.43%.
[2024-08-16T21:27:55.049Z] Movies recommended for you:
[2024-08-16T21:27:55.049Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T21:27:55.049Z] There is no way to check that no silent failure occurred.
[2024-08-16T21:27:55.049Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15393.849 ms) ======
[2024-08-16T21:27:55.049Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-16T21:27:55.049Z] GC before operation: completed in 61.869 ms, heap usage 250.627 MB -> 52.540 MB.
[2024-08-16T21:27:58.133Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T21:27:59.578Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T21:28:01.839Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T21:28:04.070Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T21:28:05.504Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T21:28:06.926Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T21:28:08.359Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T21:28:09.790Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T21:28:09.790Z] 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.
[2024-08-16T21:28:09.790Z] The best model improves the baseline by 14.43%.
[2024-08-16T21:28:10.472Z] Movies recommended for you:
[2024-08-16T21:28:10.472Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T21:28:10.472Z] There is no way to check that no silent failure occurred.
[2024-08-16T21:28:10.472Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15034.956 ms) ======
[2024-08-16T21:28:10.472Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-16T21:28:10.472Z] GC before operation: completed in 84.101 ms, heap usage 307.633 MB -> 52.833 MB.
[2024-08-16T21:28:12.687Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T21:28:14.909Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T21:28:17.141Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T21:28:19.365Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T21:28:20.790Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T21:28:22.223Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T21:28:23.658Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T21:28:25.092Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T21:28:25.092Z] 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.
[2024-08-16T21:28:25.092Z] The best model improves the baseline by 14.43%.
[2024-08-16T21:28:25.771Z] Movies recommended for you:
[2024-08-16T21:28:25.771Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T21:28:25.771Z] There is no way to check that no silent failure occurred.
[2024-08-16T21:28:25.771Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15274.737 ms) ======
[2024-08-16T21:28:25.771Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-16T21:28:25.771Z] GC before operation: completed in 63.854 ms, heap usage 236.889 MB -> 52.627 MB.
[2024-08-16T21:28:27.998Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T21:28:30.218Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T21:28:32.436Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T21:28:34.649Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T21:28:36.114Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T21:28:37.527Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T21:28:38.935Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T21:28:40.367Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T21:28:40.367Z] 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.
[2024-08-16T21:28:40.367Z] The best model improves the baseline by 14.43%.
[2024-08-16T21:28:40.367Z] Movies recommended for you:
[2024-08-16T21:28:40.367Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T21:28:40.367Z] There is no way to check that no silent failure occurred.
[2024-08-16T21:28:40.367Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15065.957 ms) ======
[2024-08-16T21:28:40.367Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-16T21:28:41.045Z] GC before operation: completed in 96.823 ms, heap usage 433.571 MB -> 52.875 MB.
[2024-08-16T21:28:43.259Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T21:28:45.474Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T21:28:47.934Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T21:28:50.162Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T21:28:51.575Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T21:28:52.993Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T21:28:54.423Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T21:28:55.855Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T21:28:55.855Z] 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.
[2024-08-16T21:28:55.855Z] The best model improves the baseline by 14.43%.
[2024-08-16T21:28:55.855Z] Movies recommended for you:
[2024-08-16T21:28:55.855Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T21:28:55.855Z] There is no way to check that no silent failure occurred.
[2024-08-16T21:28:55.855Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15269.581 ms) ======
[2024-08-16T21:28:55.855Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-16T21:28:55.855Z] GC before operation: completed in 66.701 ms, heap usage 660.997 MB -> 55.982 MB.
[2024-08-16T21:28:58.099Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T21:29:00.322Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T21:29:02.569Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T21:29:04.777Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T21:29:06.216Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T21:29:07.639Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T21:29:09.056Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T21:29:10.490Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T21:29:11.171Z] 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.
[2024-08-16T21:29:11.171Z] The best model improves the baseline by 14.43%.
[2024-08-16T21:29:11.171Z] Movies recommended for you:
[2024-08-16T21:29:11.171Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T21:29:11.171Z] There is no way to check that no silent failure occurred.
[2024-08-16T21:29:11.171Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14973.519 ms) ======
[2024-08-16T21:29:11.171Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-16T21:29:11.171Z] GC before operation: completed in 75.851 ms, heap usage 522.797 MB -> 56.105 MB.
[2024-08-16T21:29:13.394Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T21:29:15.596Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T21:29:18.684Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T21:29:20.900Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T21:29:21.592Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T21:29:23.004Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T21:29:24.435Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T21:29:25.910Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T21:29:26.613Z] 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.
[2024-08-16T21:29:26.613Z] The best model improves the baseline by 14.43%.
[2024-08-16T21:29:26.613Z] Movies recommended for you:
[2024-08-16T21:29:26.613Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T21:29:26.613Z] There is no way to check that no silent failure occurred.
[2024-08-16T21:29:26.613Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15423.330 ms) ======
[2024-08-16T21:29:26.613Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-16T21:29:26.613Z] GC before operation: completed in 62.983 ms, heap usage 500.263 MB -> 56.355 MB.
[2024-08-16T21:29:29.714Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T21:29:31.152Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T21:29:34.215Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T21:29:36.446Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T21:29:37.858Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T21:29:39.270Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T21:29:40.693Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T21:29:42.109Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T21:29:42.109Z] 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.
[2024-08-16T21:29:42.109Z] The best model improves the baseline by 14.43%.
[2024-08-16T21:29:42.109Z] Movies recommended for you:
[2024-08-16T21:29:42.109Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T21:29:42.109Z] There is no way to check that no silent failure occurred.
[2024-08-16T21:29:42.109Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15573.326 ms) ======
[2024-08-16T21:29:42.109Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-16T21:29:42.109Z] GC before operation: completed in 59.763 ms, heap usage 402.466 MB -> 55.892 MB.
[2024-08-16T21:29:45.775Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T21:29:47.208Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T21:29:49.454Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T21:29:51.671Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T21:29:52.370Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T21:29:53.790Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T21:29:55.211Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T21:29:56.626Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T21:29:57.303Z] 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.
[2024-08-16T21:29:57.303Z] The best model improves the baseline by 14.43%.
[2024-08-16T21:29:57.303Z] Movies recommended for you:
[2024-08-16T21:29:57.303Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T21:29:57.303Z] There is no way to check that no silent failure occurred.
[2024-08-16T21:29:57.303Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14881.582 ms) ======
[2024-08-16T21:29:57.303Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-16T21:29:57.303Z] GC before operation: completed in 96.843 ms, heap usage 273.458 MB -> 52.762 MB.
[2024-08-16T21:29:59.517Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T21:30:01.846Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T21:30:04.071Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T21:30:06.279Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T21:30:07.697Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T21:30:09.125Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T21:30:10.580Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T21:30:12.021Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T21:30:12.021Z] 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.
[2024-08-16T21:30:12.021Z] The best model improves the baseline by 14.43%.
[2024-08-16T21:30:12.021Z] Movies recommended for you:
[2024-08-16T21:30:12.021Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T21:30:12.021Z] There is no way to check that no silent failure occurred.
[2024-08-16T21:30:12.021Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15076.613 ms) ======
[2024-08-16T21:30:12.021Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-16T21:30:12.704Z] GC before operation: completed in 91.785 ms, heap usage 403.479 MB -> 52.870 MB.
[2024-08-16T21:30:14.897Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T21:30:17.094Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T21:30:19.318Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T21:30:21.534Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T21:30:22.950Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T21:30:24.377Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T21:30:25.800Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T21:30:27.220Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T21:30:27.220Z] 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.
[2024-08-16T21:30:27.220Z] The best model improves the baseline by 14.43%.
[2024-08-16T21:30:27.220Z] Movies recommended for you:
[2024-08-16T21:30:27.220Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T21:30:27.220Z] There is no way to check that no silent failure occurred.
[2024-08-16T21:30:27.220Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (15057.076 ms) ======
[2024-08-16T21:30:27.220Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-16T21:30:27.220Z] GC before operation: completed in 95.219 ms, heap usage 563.189 MB -> 56.134 MB.
[2024-08-16T21:30:30.334Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T21:30:32.552Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T21:30:34.761Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T21:30:37.025Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T21:30:37.710Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T21:30:39.134Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T21:30:40.552Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T21:30:42.406Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T21:30:42.406Z] 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.
[2024-08-16T21:30:42.406Z] The best model improves the baseline by 14.43%.
[2024-08-16T21:30:42.406Z] Movies recommended for you:
[2024-08-16T21:30:42.406Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T21:30:42.406Z] There is no way to check that no silent failure occurred.
[2024-08-16T21:30:42.406Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14921.527 ms) ======
[2024-08-16T21:30:42.406Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-16T21:30:42.406Z] GC before operation: completed in 84.206 ms, heap usage 384.318 MB -> 52.776 MB.
[2024-08-16T21:30:44.639Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T21:30:46.841Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T21:30:49.067Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T21:30:51.308Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T21:30:52.747Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T21:30:54.162Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T21:30:55.588Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T21:30:57.004Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T21:30:57.005Z] 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.
[2024-08-16T21:30:57.687Z] The best model improves the baseline by 14.43%.
[2024-08-16T21:30:57.687Z] Movies recommended for you:
[2024-08-16T21:30:57.687Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T21:30:57.687Z] There is no way to check that no silent failure occurred.
[2024-08-16T21:30:57.687Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14931.646 ms) ======
[2024-08-16T21:30:57.687Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-16T21:30:57.687Z] GC before operation: completed in 60.649 ms, heap usage 538.977 MB -> 56.459 MB.
[2024-08-16T21:30:59.908Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T21:31:02.130Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T21:31:04.347Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T21:31:06.555Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T21:31:08.001Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T21:31:09.413Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T21:31:10.829Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T21:31:12.255Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T21:31:12.936Z] 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.
[2024-08-16T21:31:12.936Z] The best model improves the baseline by 14.43%.
[2024-08-16T21:31:12.936Z] Movies recommended for you:
[2024-08-16T21:31:12.936Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T21:31:12.936Z] There is no way to check that no silent failure occurred.
[2024-08-16T21:31:12.936Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (15230.113 ms) ======
[2024-08-16T21:31:14.343Z] -----------------------------------
[2024-08-16T21:31:14.343Z] renaissance-movie-lens_0_PASSED
[2024-08-16T21:31:14.343Z] -----------------------------------
[2024-08-16T21:31:14.343Z]
[2024-08-16T21:31:14.343Z] TEST TEARDOWN:
[2024-08-16T21:31:14.343Z] Nothing to be done for teardown.
[2024-08-16T21:31:14.343Z] renaissance-movie-lens_0 Finish Time: Fri Aug 16 16:31:13 2024 Epoch Time (ms): 1723843873629