renaissance-movie-lens_0
[2024-08-10T22:10:06.813Z] Running test renaissance-movie-lens_0 ...
[2024-08-10T22:10:06.813Z] ===============================================
[2024-08-10T22:10:06.813Z] renaissance-movie-lens_0 Start Time: Sat Aug 10 22:10:05 2024 Epoch Time (ms): 1723327805968
[2024-08-10T22:10:06.813Z] variation: NoOptions
[2024-08-10T22:10:06.813Z] JVM_OPTIONS:
[2024-08-10T22:10:06.813Z] { \
[2024-08-10T22:10:06.813Z] echo ""; echo "TEST SETUP:"; \
[2024-08-10T22:10:06.813Z] echo "Nothing to be done for setup."; \
[2024-08-10T22:10:06.813Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17233267741116/renaissance-movie-lens_0"; \
[2024-08-10T22:10:06.813Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17233267741116/renaissance-movie-lens_0"; \
[2024-08-10T22:10:06.813Z] echo ""; echo "TESTING:"; \
[2024-08-10T22:10:06.813Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix_testList_0/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_openjdk11_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17233267741116/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-10T22:10:06.813Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17233267741116/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-10T22:10:06.813Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-10T22:10:06.813Z] echo "Nothing to be done for teardown."; \
[2024-08-10T22:10:06.813Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17233267741116/TestTargetResult";
[2024-08-10T22:10:06.813Z]
[2024-08-10T22:10:06.813Z] TEST SETUP:
[2024-08-10T22:10:06.813Z] Nothing to be done for setup.
[2024-08-10T22:10:06.813Z]
[2024-08-10T22:10:06.813Z] TESTING:
[2024-08-10T22:10:11.265Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-10T22:10:13.741Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 24) threads.
[2024-08-10T22:10:18.194Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-10T22:10:18.194Z] Training: 60056, validation: 20285, test: 19854
[2024-08-10T22:10:18.194Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-10T22:10:18.194Z] GC before operation: completed in 60.540 ms, heap usage 111.631 MB -> 38.075 MB.
[2024-08-10T22:10:25.059Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T22:10:28.894Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T22:10:33.362Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T22:10:36.781Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T22:10:38.375Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T22:10:40.847Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T22:10:42.435Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T22:10:44.898Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T22:10:44.898Z] 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.
[2024-08-10T22:10:44.898Z] The best model improves the baseline by 14.43%.
[2024-08-10T22:10:45.664Z] Movies recommended for you:
[2024-08-10T22:10:45.665Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T22:10:45.665Z] There is no way to check that no silent failure occurred.
[2024-08-10T22:10:45.665Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (26835.661 ms) ======
[2024-08-10T22:10:45.665Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-10T22:10:45.665Z] GC before operation: completed in 103.281 ms, heap usage 96.509 MB -> 53.210 MB.
[2024-08-10T22:10:49.076Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T22:10:52.496Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T22:10:55.919Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T22:10:59.342Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T22:11:00.936Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T22:11:03.401Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T22:11:04.986Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T22:11:07.475Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T22:11:07.475Z] 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.
[2024-08-10T22:11:07.475Z] The best model improves the baseline by 14.43%.
[2024-08-10T22:11:07.475Z] Movies recommended for you:
[2024-08-10T22:11:07.475Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T22:11:07.475Z] There is no way to check that no silent failure occurred.
[2024-08-10T22:11:07.475Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (22229.819 ms) ======
[2024-08-10T22:11:07.475Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-10T22:11:07.475Z] GC before operation: completed in 127.169 ms, heap usage 515.147 MB -> 55.219 MB.
[2024-08-10T22:11:10.896Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T22:11:14.311Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T22:11:17.732Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T22:11:21.165Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T22:11:22.754Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T22:11:24.340Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T22:11:26.818Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T22:11:28.420Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T22:11:29.188Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T22:11:29.188Z] The best model improves the baseline by 14.43%.
[2024-08-10T22:11:29.188Z] Movies recommended for you:
[2024-08-10T22:11:29.188Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T22:11:29.188Z] There is no way to check that no silent failure occurred.
[2024-08-10T22:11:29.188Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (21256.898 ms) ======
[2024-08-10T22:11:29.188Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-10T22:11:29.188Z] GC before operation: completed in 111.005 ms, heap usage 310.455 MB -> 52.210 MB.
[2024-08-10T22:11:32.603Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T22:11:36.025Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T22:11:38.489Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T22:11:41.905Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T22:11:43.490Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T22:11:45.614Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T22:11:48.094Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T22:11:49.683Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T22:11:49.683Z] 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.
[2024-08-10T22:11:49.683Z] The best model improves the baseline by 14.43%.
[2024-08-10T22:11:50.452Z] Movies recommended for you:
[2024-08-10T22:11:50.452Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T22:11:50.452Z] There is no way to check that no silent failure occurred.
[2024-08-10T22:11:50.452Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (20970.069 ms) ======
[2024-08-10T22:11:50.452Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-10T22:11:50.452Z] GC before operation: completed in 149.472 ms, heap usage 473.915 MB -> 52.646 MB.
[2024-08-10T22:11:53.881Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T22:11:56.355Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T22:11:59.769Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T22:12:03.200Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T22:12:04.795Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T22:12:06.382Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T22:12:08.865Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T22:12:10.467Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T22:12:11.237Z] 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.
[2024-08-10T22:12:11.237Z] The best model improves the baseline by 14.43%.
[2024-08-10T22:12:11.237Z] Movies recommended for you:
[2024-08-10T22:12:11.237Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T22:12:11.237Z] There is no way to check that no silent failure occurred.
[2024-08-10T22:12:11.237Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (20702.935 ms) ======
[2024-08-10T22:12:11.237Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-10T22:12:11.237Z] GC before operation: completed in 119.046 ms, heap usage 516.819 MB -> 56.117 MB.
[2024-08-10T22:12:14.659Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T22:12:17.135Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T22:12:20.555Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T22:12:23.976Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T22:12:25.564Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T22:12:27.173Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T22:12:29.654Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T22:12:31.250Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T22:12:32.017Z] 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.
[2024-08-10T22:12:32.017Z] The best model improves the baseline by 14.43%.
[2024-08-10T22:12:32.017Z] Movies recommended for you:
[2024-08-10T22:12:32.017Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T22:12:32.017Z] There is no way to check that no silent failure occurred.
[2024-08-10T22:12:32.017Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (20733.540 ms) ======
[2024-08-10T22:12:32.017Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-10T22:12:32.017Z] GC before operation: completed in 120.485 ms, heap usage 280.225 MB -> 52.611 MB.
[2024-08-10T22:12:35.438Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T22:12:37.907Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T22:12:41.326Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T22:12:44.857Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T22:12:46.444Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T22:12:48.040Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T22:12:50.523Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T22:12:52.124Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T22:12:52.891Z] 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.
[2024-08-10T22:12:52.891Z] The best model improves the baseline by 14.43%.
[2024-08-10T22:12:52.891Z] Movies recommended for you:
[2024-08-10T22:12:52.891Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T22:12:52.891Z] There is no way to check that no silent failure occurred.
[2024-08-10T22:12:52.891Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (20724.728 ms) ======
[2024-08-10T22:12:52.891Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-10T22:12:52.891Z] GC before operation: completed in 124.049 ms, heap usage 577.435 MB -> 56.216 MB.
[2024-08-10T22:12:56.313Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T22:12:58.949Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T22:13:02.367Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T22:13:05.394Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T22:13:06.989Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T22:13:09.455Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T22:13:11.039Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T22:13:12.646Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T22:13:13.413Z] 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.
[2024-08-10T22:13:13.413Z] The best model improves the baseline by 14.43%.
[2024-08-10T22:13:13.413Z] Movies recommended for you:
[2024-08-10T22:13:13.413Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T22:13:13.413Z] There is no way to check that no silent failure occurred.
[2024-08-10T22:13:13.413Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (20698.820 ms) ======
[2024-08-10T22:13:13.413Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-10T22:13:13.413Z] GC before operation: completed in 111.173 ms, heap usage 433.125 MB -> 53.182 MB.
[2024-08-10T22:13:16.840Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T22:13:20.262Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T22:13:22.734Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T22:13:26.159Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T22:13:27.754Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T22:13:30.222Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T22:13:31.819Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T22:13:33.405Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T22:13:34.173Z] 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.
[2024-08-10T22:13:34.173Z] The best model improves the baseline by 14.43%.
[2024-08-10T22:13:34.173Z] Movies recommended for you:
[2024-08-10T22:13:34.173Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T22:13:34.173Z] There is no way to check that no silent failure occurred.
[2024-08-10T22:13:34.173Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (20622.900 ms) ======
[2024-08-10T22:13:34.173Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-10T22:13:34.173Z] GC before operation: completed in 123.547 ms, heap usage 256.809 MB -> 52.869 MB.
[2024-08-10T22:13:37.590Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T22:13:41.021Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T22:13:43.513Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T22:13:46.927Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T22:13:48.520Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T22:13:50.990Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T22:13:52.579Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T22:13:54.169Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T22:13:54.937Z] 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.
[2024-08-10T22:13:54.937Z] The best model improves the baseline by 14.43%.
[2024-08-10T22:13:54.937Z] Movies recommended for you:
[2024-08-10T22:13:54.937Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T22:13:54.937Z] There is no way to check that no silent failure occurred.
[2024-08-10T22:13:54.937Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (20652.738 ms) ======
[2024-08-10T22:13:54.937Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-10T22:13:54.937Z] GC before operation: completed in 117.270 ms, heap usage 386.096 MB -> 52.994 MB.
[2024-08-10T22:13:58.361Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T22:14:01.792Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T22:14:04.253Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T22:14:07.674Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T22:14:09.267Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T22:14:11.744Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T22:14:13.329Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T22:14:14.917Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T22:14:15.686Z] 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.
[2024-08-10T22:14:15.687Z] The best model improves the baseline by 14.43%.
[2024-08-10T22:14:15.687Z] Movies recommended for you:
[2024-08-10T22:14:15.687Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T22:14:15.687Z] There is no way to check that no silent failure occurred.
[2024-08-10T22:14:15.687Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (20466.754 ms) ======
[2024-08-10T22:14:15.687Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-10T22:14:15.687Z] GC before operation: completed in 124.646 ms, heap usage 454.625 MB -> 52.792 MB.
[2024-08-10T22:14:19.124Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T22:14:21.947Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T22:14:25.364Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T22:14:28.803Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T22:14:30.396Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T22:14:31.979Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T22:14:34.465Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T22:14:36.069Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T22:14:36.069Z] 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.
[2024-08-10T22:14:36.069Z] The best model improves the baseline by 14.43%.
[2024-08-10T22:14:36.841Z] Movies recommended for you:
[2024-08-10T22:14:36.841Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T22:14:36.841Z] There is no way to check that no silent failure occurred.
[2024-08-10T22:14:36.841Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (20760.175 ms) ======
[2024-08-10T22:14:36.841Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-10T22:14:36.841Z] GC before operation: completed in 144.936 ms, heap usage 263.826 MB -> 52.854 MB.
[2024-08-10T22:14:40.262Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T22:14:42.724Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T22:14:46.142Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T22:14:49.555Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T22:14:51.149Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T22:14:52.736Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T22:14:55.204Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T22:14:56.805Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T22:14:56.805Z] 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.
[2024-08-10T22:14:56.805Z] The best model improves the baseline by 14.43%.
[2024-08-10T22:14:56.805Z] Movies recommended for you:
[2024-08-10T22:14:56.805Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T22:14:56.805Z] There is no way to check that no silent failure occurred.
[2024-08-10T22:14:56.805Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (20491.449 ms) ======
[2024-08-10T22:14:56.805Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-10T22:14:57.571Z] GC before operation: completed in 114.431 ms, heap usage 613.735 MB -> 56.544 MB.
[2024-08-10T22:15:00.036Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T22:15:03.447Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T22:15:06.863Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T22:15:09.329Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T22:15:11.804Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T22:15:13.389Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T22:15:15.859Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T22:15:17.449Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T22:15:17.449Z] 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.
[2024-08-10T22:15:17.449Z] The best model improves the baseline by 14.43%.
[2024-08-10T22:15:17.449Z] Movies recommended for you:
[2024-08-10T22:15:17.449Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T22:15:17.449Z] There is no way to check that no silent failure occurred.
[2024-08-10T22:15:17.449Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (20516.120 ms) ======
[2024-08-10T22:15:17.449Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-10T22:15:18.217Z] GC before operation: completed in 114.360 ms, heap usage 530.696 MB -> 56.210 MB.
[2024-08-10T22:15:20.682Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T22:15:24.118Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T22:15:27.557Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T22:15:30.021Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T22:15:32.494Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T22:15:34.079Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T22:15:35.674Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T22:15:38.149Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T22:15:38.149Z] 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.
[2024-08-10T22:15:38.149Z] The best model improves the baseline by 14.43%.
[2024-08-10T22:15:38.149Z] Movies recommended for you:
[2024-08-10T22:15:38.149Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T22:15:38.149Z] There is no way to check that no silent failure occurred.
[2024-08-10T22:15:38.149Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (20428.743 ms) ======
[2024-08-10T22:15:38.149Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-10T22:15:38.149Z] GC before operation: completed in 115.811 ms, heap usage 315.014 MB -> 53.027 MB.
[2024-08-10T22:15:41.987Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T22:15:44.450Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T22:15:47.925Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T22:15:51.359Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T22:15:52.949Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T22:15:54.537Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T22:15:57.018Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T22:15:58.604Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T22:15:58.604Z] 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.
[2024-08-10T22:15:59.377Z] The best model improves the baseline by 14.43%.
[2024-08-10T22:15:59.377Z] Movies recommended for you:
[2024-08-10T22:15:59.377Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T22:15:59.377Z] There is no way to check that no silent failure occurred.
[2024-08-10T22:15:59.377Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (20690.283 ms) ======
[2024-08-10T22:15:59.377Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-10T22:15:59.377Z] GC before operation: completed in 122.367 ms, heap usage 568.202 MB -> 56.484 MB.
[2024-08-10T22:16:02.794Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T22:16:05.260Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T22:16:08.685Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T22:16:12.108Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T22:16:13.707Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T22:16:15.305Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T22:16:16.895Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T22:16:19.395Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T22:16:19.395Z] 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.
[2024-08-10T22:16:19.395Z] The best model improves the baseline by 14.43%.
[2024-08-10T22:16:19.395Z] Movies recommended for you:
[2024-08-10T22:16:19.395Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T22:16:19.395Z] There is no way to check that no silent failure occurred.
[2024-08-10T22:16:19.395Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (20417.911 ms) ======
[2024-08-10T22:16:19.395Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-10T22:16:20.164Z] GC before operation: completed in 152.352 ms, heap usage 538.347 MB -> 56.331 MB.
[2024-08-10T22:16:22.638Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T22:16:26.085Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T22:16:29.527Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T22:16:32.005Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T22:16:34.471Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T22:16:36.068Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T22:16:37.659Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T22:16:40.139Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T22:16:40.139Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T22:16:40.139Z] The best model improves the baseline by 14.43%.
[2024-08-10T22:16:40.139Z] Movies recommended for you:
[2024-08-10T22:16:40.139Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T22:16:40.139Z] There is no way to check that no silent failure occurred.
[2024-08-10T22:16:40.139Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (20462.008 ms) ======
[2024-08-10T22:16:40.139Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-10T22:16:40.139Z] GC before operation: completed in 120.194 ms, heap usage 277.215 MB -> 52.948 MB.
[2024-08-10T22:16:43.559Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T22:16:46.991Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T22:16:50.408Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T22:16:52.878Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T22:16:54.478Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T22:16:56.946Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T22:16:58.536Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T22:17:00.125Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T22:17:00.893Z] 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.
[2024-08-10T22:17:00.893Z] The best model improves the baseline by 14.43%.
[2024-08-10T22:17:00.893Z] Movies recommended for you:
[2024-08-10T22:17:00.893Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T22:17:00.893Z] There is no way to check that no silent failure occurred.
[2024-08-10T22:17:00.893Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (20479.196 ms) ======
[2024-08-10T22:17:00.893Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-10T22:17:00.893Z] GC before operation: completed in 122.267 ms, heap usage 356.870 MB -> 53.209 MB.
[2024-08-10T22:17:04.302Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T22:17:07.721Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T22:17:10.184Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T22:17:13.603Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T22:17:15.190Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T22:17:16.775Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T22:17:19.261Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T22:17:20.853Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T22:17:21.621Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T22:17:21.621Z] The best model improves the baseline by 14.43%.
[2024-08-10T22:17:21.621Z] Movies recommended for you:
[2024-08-10T22:17:21.621Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T22:17:21.621Z] There is no way to check that no silent failure occurred.
[2024-08-10T22:17:21.621Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (20545.523 ms) ======
[2024-08-10T22:17:22.390Z] -----------------------------------
[2024-08-10T22:17:22.390Z] renaissance-movie-lens_0_PASSED
[2024-08-10T22:17:22.390Z] -----------------------------------
[2024-08-10T22:17:22.390Z]
[2024-08-10T22:17:22.390Z] TEST TEARDOWN:
[2024-08-10T22:17:22.390Z] Nothing to be done for teardown.
[2024-08-10T22:17:22.390Z] renaissance-movie-lens_0 Finish Time: Sat Aug 10 22:17:21 2024 Epoch Time (ms): 1723328241745