renaissance-movie-lens_0
[2024-08-17T07:55:21.525Z] Running test renaissance-movie-lens_0 ...
[2024-08-17T07:55:21.525Z] ===============================================
[2024-08-17T07:55:21.525Z] renaissance-movie-lens_0 Start Time: Sat Aug 17 07:55:21 2024 Epoch Time (ms): 1723881321167
[2024-08-17T07:55:21.525Z] variation: NoOptions
[2024-08-17T07:55:21.525Z] JVM_OPTIONS:
[2024-08-17T07:55:21.525Z] { \
[2024-08-17T07:55:21.525Z] echo ""; echo "TEST SETUP:"; \
[2024-08-17T07:55:21.525Z] echo "Nothing to be done for setup."; \
[2024-08-17T07:55:21.525Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_1723880075761/renaissance-movie-lens_0"; \
[2024-08-17T07:55:21.525Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_1723880075761/renaissance-movie-lens_0"; \
[2024-08-17T07:55:21.525Z] echo ""; echo "TESTING:"; \
[2024-08-17T07:55:21.525Z] "/home/jenkins/workspace/Test_openjdk17_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_openjdk17_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_1723880075761/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-17T07:55:21.525Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_1723880075761/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-17T07:55:21.525Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-17T07:55:21.525Z] echo "Nothing to be done for teardown."; \
[2024-08-17T07:55:21.525Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_1723880075761/TestTargetResult";
[2024-08-17T07:55:21.525Z]
[2024-08-17T07:55:21.525Z] TEST SETUP:
[2024-08-17T07:55:21.525Z] Nothing to be done for setup.
[2024-08-17T07:55:21.525Z]
[2024-08-17T07:55:21.525Z] TESTING:
[2024-08-17T07:55:37.729Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-17T07:55:40.225Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 16) threads.
[2024-08-17T07:55:43.690Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-17T07:55:43.690Z] Training: 60056, validation: 20285, test: 19854
[2024-08-17T07:55:43.690Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-17T07:55:44.472Z] GC before operation: completed in 52.919 ms, heap usage 46.852 MB -> 37.748 MB.
[2024-08-17T07:55:50.132Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T07:55:52.625Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T07:55:57.133Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T07:55:59.659Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T07:56:01.274Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T07:56:03.773Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T07:56:05.385Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T07:56:07.009Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T07:56:07.792Z] 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.
[2024-08-17T07:56:07.792Z] The best model improves the baseline by 14.43%.
[2024-08-17T07:56:07.792Z] Movies recommended for you:
[2024-08-17T07:56:07.792Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T07:56:07.792Z] There is no way to check that no silent failure occurred.
[2024-08-17T07:56:07.792Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (23767.029 ms) ======
[2024-08-17T07:56:07.792Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-17T07:56:07.792Z] GC before operation: completed in 98.769 ms, heap usage 349.795 MB -> 50.521 MB.
[2024-08-17T07:56:11.254Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T07:56:13.751Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T07:56:17.216Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T07:56:20.690Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T07:56:22.307Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T07:56:23.917Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T07:56:26.603Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T07:56:27.787Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T07:56:27.787Z] 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.
[2024-08-17T07:56:27.787Z] The best model improves the baseline by 14.43%.
[2024-08-17T07:56:28.567Z] Movies recommended for you:
[2024-08-17T07:56:28.567Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T07:56:28.567Z] There is no way to check that no silent failure occurred.
[2024-08-17T07:56:28.567Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (20193.215 ms) ======
[2024-08-17T07:56:28.567Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-17T07:56:28.567Z] GC before operation: completed in 81.235 ms, heap usage 625.770 MB -> 54.775 MB.
[2024-08-17T07:56:31.087Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T07:56:33.592Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T07:56:38.241Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T07:56:40.757Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T07:56:42.373Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T07:56:43.985Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T07:56:46.487Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T07:56:48.095Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T07:56:48.095Z] 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.
[2024-08-17T07:56:48.095Z] The best model improves the baseline by 14.43%.
[2024-08-17T07:56:48.876Z] Movies recommended for you:
[2024-08-17T07:56:48.876Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T07:56:48.876Z] There is no way to check that no silent failure occurred.
[2024-08-17T07:56:48.876Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (20356.135 ms) ======
[2024-08-17T07:56:48.876Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-17T07:56:48.876Z] GC before operation: completed in 88.751 ms, heap usage 1.267 GB -> 55.945 MB.
[2024-08-17T07:56:51.381Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T07:56:53.893Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T07:56:57.355Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T07:57:00.820Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T07:57:02.435Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T07:57:04.043Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T07:57:05.653Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T07:57:07.278Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T07:57:08.066Z] 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.
[2024-08-17T07:57:08.066Z] The best model improves the baseline by 14.43%.
[2024-08-17T07:57:08.066Z] Movies recommended for you:
[2024-08-17T07:57:08.066Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T07:57:08.066Z] There is no way to check that no silent failure occurred.
[2024-08-17T07:57:08.066Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (19312.181 ms) ======
[2024-08-17T07:57:08.066Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-17T07:57:08.066Z] GC before operation: completed in 77.148 ms, heap usage 538.907 MB -> 55.248 MB.
[2024-08-17T07:57:10.565Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T07:57:13.068Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T07:57:17.584Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T07:57:20.096Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T07:57:21.919Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T07:57:23.526Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T07:57:25.138Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T07:57:26.758Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T07:57:26.758Z] 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.
[2024-08-17T07:57:26.758Z] The best model improves the baseline by 14.43%.
[2024-08-17T07:57:26.758Z] Movies recommended for you:
[2024-08-17T07:57:26.758Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T07:57:26.758Z] There is no way to check that no silent failure occurred.
[2024-08-17T07:57:26.758Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (19061.923 ms) ======
[2024-08-17T07:57:26.758Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-17T07:57:27.538Z] GC before operation: completed in 89.382 ms, heap usage 3.136 GB -> 60.698 MB.
[2024-08-17T07:57:30.049Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T07:57:32.546Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T07:57:36.015Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T07:57:38.516Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T07:57:40.125Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T07:57:41.757Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T07:57:44.254Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T07:57:45.863Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T07:57:45.863Z] 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.
[2024-08-17T07:57:45.863Z] The best model improves the baseline by 14.43%.
[2024-08-17T07:57:45.863Z] Movies recommended for you:
[2024-08-17T07:57:45.863Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T07:57:45.863Z] There is no way to check that no silent failure occurred.
[2024-08-17T07:57:45.863Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (18990.551 ms) ======
[2024-08-17T07:57:45.863Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-17T07:57:46.641Z] GC before operation: completed in 95.491 ms, heap usage 652.149 MB -> 55.392 MB.
[2024-08-17T07:57:49.430Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T07:57:51.959Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T07:57:57.620Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T07:58:00.125Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T07:58:01.742Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T07:58:03.343Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T07:58:05.849Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T07:58:07.453Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T07:58:07.453Z] 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.
[2024-08-17T07:58:07.453Z] The best model improves the baseline by 14.43%.
[2024-08-17T07:58:07.453Z] Movies recommended for you:
[2024-08-17T07:58:07.453Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T07:58:07.453Z] There is no way to check that no silent failure occurred.
[2024-08-17T07:58:07.453Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (21461.676 ms) ======
[2024-08-17T07:58:07.453Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-17T07:58:08.233Z] GC before operation: completed in 101.977 ms, heap usage 2.451 GB -> 57.160 MB.
[2024-08-17T07:58:10.739Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T07:58:13.244Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T07:58:17.767Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T07:58:20.261Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T07:58:21.867Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T07:58:23.486Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T07:58:25.096Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T07:58:26.993Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T07:58:27.935Z] 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.
[2024-08-17T07:58:27.935Z] The best model improves the baseline by 14.43%.
[2024-08-17T07:58:27.935Z] Movies recommended for you:
[2024-08-17T07:58:27.935Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T07:58:27.935Z] There is no way to check that no silent failure occurred.
[2024-08-17T07:58:27.935Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (19631.400 ms) ======
[2024-08-17T07:58:27.935Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-17T07:58:27.935Z] GC before operation: completed in 98.029 ms, heap usage 246.654 MB -> 52.482 MB.
[2024-08-17T07:58:30.435Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T07:58:32.929Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T07:58:36.552Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T07:58:39.045Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T07:58:41.558Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T07:58:43.168Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T07:58:44.774Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T07:58:46.381Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T07:58:47.167Z] 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.
[2024-08-17T07:58:47.167Z] The best model improves the baseline by 14.43%.
[2024-08-17T07:58:47.167Z] Movies recommended for you:
[2024-08-17T07:58:47.167Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T07:58:47.167Z] There is no way to check that no silent failure occurred.
[2024-08-17T07:58:47.167Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (19555.879 ms) ======
[2024-08-17T07:58:47.167Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-17T07:58:47.167Z] GC before operation: completed in 82.133 ms, heap usage 280.609 MB -> 52.285 MB.
[2024-08-17T07:58:49.668Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T07:58:52.165Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T07:58:55.620Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T07:58:59.099Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T07:59:00.728Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T07:59:01.509Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T07:59:04.002Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T07:59:05.617Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T07:59:06.395Z] 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.
[2024-08-17T07:59:06.395Z] The best model improves the baseline by 14.43%.
[2024-08-17T07:59:06.395Z] Movies recommended for you:
[2024-08-17T07:59:06.395Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T07:59:06.395Z] There is no way to check that no silent failure occurred.
[2024-08-17T07:59:06.395Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (19048.598 ms) ======
[2024-08-17T07:59:06.395Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-17T07:59:06.395Z] GC before operation: completed in 97.018 ms, heap usage 3.215 GB -> 61.060 MB.
[2024-08-17T07:59:08.895Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T07:59:11.394Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T07:59:15.921Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T07:59:18.428Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T07:59:20.036Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T07:59:20.812Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T07:59:23.322Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T07:59:24.936Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T07:59:24.936Z] 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.
[2024-08-17T07:59:24.936Z] The best model improves the baseline by 14.43%.
[2024-08-17T07:59:25.714Z] Movies recommended for you:
[2024-08-17T07:59:25.714Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T07:59:25.714Z] There is no way to check that no silent failure occurred.
[2024-08-17T07:59:25.714Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (19041.427 ms) ======
[2024-08-17T07:59:25.714Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-17T07:59:25.714Z] GC before operation: completed in 78.324 ms, heap usage 108.842 MB -> 55.289 MB.
[2024-08-17T07:59:28.209Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T07:59:30.710Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T07:59:34.170Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T07:59:37.811Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T07:59:38.595Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T07:59:40.516Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T07:59:42.152Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T07:59:43.767Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T07:59:44.549Z] 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.
[2024-08-17T07:59:44.550Z] The best model improves the baseline by 14.43%.
[2024-08-17T07:59:44.550Z] Movies recommended for you:
[2024-08-17T07:59:44.550Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T07:59:44.550Z] There is no way to check that no silent failure occurred.
[2024-08-17T07:59:44.550Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (19073.182 ms) ======
[2024-08-17T07:59:44.550Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-17T07:59:44.550Z] GC before operation: completed in 80.996 ms, heap usage 399.071 MB -> 52.318 MB.
[2024-08-17T07:59:47.049Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T07:59:49.550Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T07:59:54.074Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T07:59:55.685Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T07:59:57.301Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T07:59:58.923Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T08:00:02.392Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T08:00:04.046Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T08:00:04.823Z] 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.
[2024-08-17T08:00:04.823Z] The best model improves the baseline by 14.43%.
[2024-08-17T08:00:04.823Z] Movies recommended for you:
[2024-08-17T08:00:04.823Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T08:00:04.823Z] There is no way to check that no silent failure occurred.
[2024-08-17T08:00:04.823Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (20074.201 ms) ======
[2024-08-17T08:00:04.823Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-17T08:00:04.823Z] GC before operation: completed in 81.314 ms, heap usage 563.769 MB -> 55.880 MB.
[2024-08-17T08:00:07.314Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T08:00:09.815Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T08:00:14.323Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T08:00:16.823Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T08:00:18.440Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T08:00:20.068Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T08:00:21.702Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T08:00:23.318Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T08:00:23.318Z] 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.
[2024-08-17T08:00:23.318Z] The best model improves the baseline by 14.43%.
[2024-08-17T08:00:23.318Z] Movies recommended for you:
[2024-08-17T08:00:23.318Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T08:00:23.318Z] There is no way to check that no silent failure occurred.
[2024-08-17T08:00:23.318Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (18832.417 ms) ======
[2024-08-17T08:00:23.318Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-17T08:00:24.097Z] GC before operation: completed in 95.970 ms, heap usage 578.516 MB -> 55.609 MB.
[2024-08-17T08:00:26.593Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T08:00:29.096Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T08:00:32.555Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T08:00:35.048Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T08:00:36.655Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T08:00:38.265Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T08:00:40.758Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T08:00:42.364Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T08:00:42.364Z] 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.
[2024-08-17T08:00:42.364Z] The best model improves the baseline by 14.43%.
[2024-08-17T08:00:43.141Z] Movies recommended for you:
[2024-08-17T08:00:43.141Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T08:00:43.141Z] There is no way to check that no silent failure occurred.
[2024-08-17T08:00:43.141Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (19082.976 ms) ======
[2024-08-17T08:00:43.141Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-17T08:00:43.141Z] GC before operation: completed in 95.551 ms, heap usage 2.257 GB -> 57.270 MB.
[2024-08-17T08:00:45.862Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T08:00:48.372Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T08:00:51.835Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T08:00:54.341Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T08:00:55.965Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T08:00:57.592Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T08:01:00.091Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T08:01:01.719Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T08:01:01.719Z] 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.
[2024-08-17T08:01:01.719Z] The best model improves the baseline by 14.43%.
[2024-08-17T08:01:01.719Z] Movies recommended for you:
[2024-08-17T08:01:01.719Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T08:01:01.719Z] There is no way to check that no silent failure occurred.
[2024-08-17T08:01:01.719Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (18755.386 ms) ======
[2024-08-17T08:01:01.719Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-17T08:01:01.719Z] GC before operation: completed in 82.490 ms, heap usage 418.251 MB -> 52.477 MB.
[2024-08-17T08:01:04.226Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T08:01:06.736Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T08:01:10.191Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T08:01:13.661Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T08:01:15.285Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T08:01:16.093Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T08:01:18.612Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T08:01:20.222Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T08:01:20.222Z] 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.
[2024-08-17T08:01:20.222Z] The best model improves the baseline by 14.43%.
[2024-08-17T08:01:20.223Z] Movies recommended for you:
[2024-08-17T08:01:20.223Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T08:01:20.223Z] There is no way to check that no silent failure occurred.
[2024-08-17T08:01:20.223Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (18525.512 ms) ======
[2024-08-17T08:01:20.223Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-17T08:01:20.223Z] GC before operation: completed in 84.145 ms, heap usage 509.166 MB -> 52.414 MB.
[2024-08-17T08:01:22.720Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T08:01:25.222Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T08:01:29.741Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T08:01:32.253Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T08:01:33.887Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T08:01:35.531Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T08:01:37.143Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T08:01:38.765Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T08:01:38.765Z] 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.
[2024-08-17T08:01:38.765Z] The best model improves the baseline by 14.43%.
[2024-08-17T08:01:39.541Z] Movies recommended for you:
[2024-08-17T08:01:39.541Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T08:01:39.541Z] There is no way to check that no silent failure occurred.
[2024-08-17T08:01:39.541Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (18806.946 ms) ======
[2024-08-17T08:01:39.541Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-17T08:01:39.541Z] GC before operation: completed in 95.332 ms, heap usage 2.604 GB -> 57.269 MB.
[2024-08-17T08:01:42.044Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T08:01:44.540Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T08:01:48.004Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T08:01:50.507Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T08:01:52.126Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T08:01:53.745Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T08:01:56.772Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T08:01:57.553Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T08:01:57.553Z] 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.
[2024-08-17T08:01:57.553Z] The best model improves the baseline by 14.43%.
[2024-08-17T08:01:57.553Z] Movies recommended for you:
[2024-08-17T08:01:57.553Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T08:01:57.553Z] There is no way to check that no silent failure occurred.
[2024-08-17T08:01:57.553Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (18444.451 ms) ======
[2024-08-17T08:01:57.553Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-17T08:01:57.553Z] GC before operation: completed in 87.599 ms, heap usage 255.435 MB -> 52.492 MB.
[2024-08-17T08:02:00.061Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T08:02:03.519Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T08:02:08.026Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T08:02:10.525Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T08:02:12.136Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T08:02:13.747Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T08:02:16.255Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T08:02:17.882Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T08:02:17.882Z] 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.
[2024-08-17T08:02:17.882Z] The best model improves the baseline by 14.43%.
[2024-08-17T08:02:17.882Z] Movies recommended for you:
[2024-08-17T08:02:17.882Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T08:02:17.882Z] There is no way to check that no silent failure occurred.
[2024-08-17T08:02:17.882Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (20223.170 ms) ======
[2024-08-17T08:02:18.660Z] -----------------------------------
[2024-08-17T08:02:18.660Z] renaissance-movie-lens_0_PASSED
[2024-08-17T08:02:18.660Z] -----------------------------------
[2024-08-17T08:02:18.660Z]
[2024-08-17T08:02:18.660Z] TEST TEARDOWN:
[2024-08-17T08:02:18.660Z] Nothing to be done for teardown.
[2024-08-17T08:02:18.660Z] renaissance-movie-lens_0 Finish Time: Sat Aug 17 08:02:18 2024 Epoch Time (ms): 1723881738122