renaissance-movie-lens_0
[2024-08-16T19:56:14.146Z] Running test renaissance-movie-lens_0 ...
[2024-08-16T19:56:14.146Z] ===============================================
[2024-08-16T19:56:14.146Z] renaissance-movie-lens_0 Start Time: Fri Aug 16 19:56:13 2024 Epoch Time (ms): 1723838173447
[2024-08-16T19:56:14.146Z] variation: NoOptions
[2024-08-16T19:56:14.146Z] JVM_OPTIONS:
[2024-08-16T19:56:14.146Z] { \
[2024-08-16T19:56:14.146Z] echo ""; echo "TEST SETUP:"; \
[2024-08-16T19:56:14.146Z] echo "Nothing to be done for setup."; \
[2024-08-16T19:56:14.146Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17238371767414/renaissance-movie-lens_0"; \
[2024-08-16T19:56:14.146Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17238371767414/renaissance-movie-lens_0"; \
[2024-08-16T19:56:14.146Z] echo ""; echo "TESTING:"; \
[2024-08-16T19:56:14.146Z] "/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_17238371767414/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-16T19:56:14.146Z] 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_17238371767414/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-16T19:56:14.146Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-16T19:56:14.146Z] echo "Nothing to be done for teardown."; \
[2024-08-16T19:56:14.146Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17238371767414/TestTargetResult";
[2024-08-16T19:56:14.146Z]
[2024-08-16T19:56:14.146Z] TEST SETUP:
[2024-08-16T19:56:14.146Z] Nothing to be done for setup.
[2024-08-16T19:56:14.146Z]
[2024-08-16T19:56:14.146Z] TESTING:
[2024-08-16T19:56:18.583Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-16T19:56:21.996Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 24) threads.
[2024-08-16T19:56:25.414Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-16T19:56:25.414Z] Training: 60056, validation: 20285, test: 19854
[2024-08-16T19:56:25.414Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-16T19:56:25.414Z] GC before operation: completed in 59.895 ms, heap usage 146.641 MB -> 38.096 MB.
[2024-08-16T19:56:32.257Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:56:35.664Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:56:39.083Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:56:42.495Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:56:44.954Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:56:46.540Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:56:49.013Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:56:50.602Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:56:50.602Z] 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.
[2024-08-16T19:56:51.368Z] The best model improves the baseline by 14.43%.
[2024-08-16T19:56:51.368Z] Movies recommended for you:
[2024-08-16T19:56:51.368Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:56:51.368Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:56:51.368Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (25495.393 ms) ======
[2024-08-16T19:56:51.368Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-16T19:56:51.368Z] GC before operation: completed in 114.037 ms, heap usage 307.652 MB -> 51.341 MB.
[2024-08-16T19:56:54.776Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:56:58.185Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:57:01.593Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:57:04.047Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:57:06.507Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:57:08.085Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:57:10.550Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:57:12.141Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:57:12.141Z] 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.
[2024-08-16T19:57:12.141Z] The best model improves the baseline by 14.43%.
[2024-08-16T19:57:12.141Z] Movies recommended for you:
[2024-08-16T19:57:12.141Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:57:12.141Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:57:12.141Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (21211.514 ms) ======
[2024-08-16T19:57:12.141Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-16T19:57:12.906Z] GC before operation: completed in 116.728 ms, heap usage 619.075 MB -> 55.238 MB.
[2024-08-16T19:57:15.378Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:57:18.783Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:57:22.200Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:57:25.606Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:57:27.188Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:57:28.773Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:57:31.254Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:57:32.858Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:57:32.859Z] 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.
[2024-08-16T19:57:32.859Z] The best model improves the baseline by 14.43%.
[2024-08-16T19:57:32.859Z] Movies recommended for you:
[2024-08-16T19:57:32.859Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:57:32.859Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:57:32.859Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (20557.749 ms) ======
[2024-08-16T19:57:32.859Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-16T19:57:33.628Z] GC before operation: completed in 113.608 ms, heap usage 484.547 MB -> 52.292 MB.
[2024-08-16T19:57:36.095Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:57:39.507Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:57:42.936Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:57:45.401Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:57:47.876Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:57:49.480Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:57:51.070Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:57:52.665Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:57:53.432Z] 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.
[2024-08-16T19:57:53.432Z] The best model improves the baseline by 14.43%.
[2024-08-16T19:57:53.432Z] Movies recommended for you:
[2024-08-16T19:57:53.432Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:57:53.432Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:57:53.432Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (20114.575 ms) ======
[2024-08-16T19:57:53.432Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-16T19:57:53.432Z] GC before operation: completed in 151.779 ms, heap usage 292.293 MB -> 52.535 MB.
[2024-08-16T19:57:56.852Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:57:59.327Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:58:02.755Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:58:06.162Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:58:07.745Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:58:09.330Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:58:11.820Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:58:13.402Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:58:13.402Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-16T19:58:13.402Z] The best model improves the baseline by 14.43%.
[2024-08-16T19:58:13.402Z] Movies recommended for you:
[2024-08-16T19:58:13.402Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:58:13.402Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:58:13.402Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (20058.062 ms) ======
[2024-08-16T19:58:13.402Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-16T19:58:13.402Z] GC before operation: completed in 117.760 ms, heap usage 363.557 MB -> 52.701 MB.
[2024-08-16T19:58:16.809Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:58:20.209Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:58:22.664Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:58:26.070Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:58:27.651Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:58:29.230Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:58:31.697Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:58:33.856Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:58:33.856Z] 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.
[2024-08-16T19:58:33.856Z] The best model improves the baseline by 14.43%.
[2024-08-16T19:58:33.856Z] Movies recommended for you:
[2024-08-16T19:58:33.856Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:58:33.856Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:58:33.856Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (20062.595 ms) ======
[2024-08-16T19:58:33.856Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-16T19:58:33.856Z] GC before operation: completed in 118.848 ms, heap usage 477.719 MB -> 52.721 MB.
[2024-08-16T19:58:36.841Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:58:40.260Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:58:42.727Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:58:46.136Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:58:47.726Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:58:49.316Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:58:51.779Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:58:53.366Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:58:54.134Z] 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.
[2024-08-16T19:58:54.134Z] The best model improves the baseline by 14.43%.
[2024-08-16T19:58:54.134Z] Movies recommended for you:
[2024-08-16T19:58:54.134Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:58:54.134Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:58:54.134Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (20015.434 ms) ======
[2024-08-16T19:58:54.134Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-16T19:58:54.134Z] GC before operation: completed in 107.737 ms, heap usage 509.458 MB -> 56.169 MB.
[2024-08-16T19:58:57.544Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:59:00.014Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:59:03.419Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:59:05.916Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:59:08.391Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:59:09.972Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:59:11.558Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:59:13.145Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:59:13.921Z] 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.
[2024-08-16T19:59:13.921Z] The best model improves the baseline by 14.43%.
[2024-08-16T19:59:13.921Z] Movies recommended for you:
[2024-08-16T19:59:13.921Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:59:13.921Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:59:13.921Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (19856.099 ms) ======
[2024-08-16T19:59:13.921Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-16T19:59:13.921Z] GC before operation: completed in 113.650 ms, heap usage 271.731 MB -> 53.009 MB.
[2024-08-16T19:59:17.342Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:59:19.802Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:59:23.210Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:59:26.633Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:59:28.221Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:59:29.803Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:59:31.397Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:59:33.864Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:59:33.864Z] 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.
[2024-08-16T19:59:33.864Z] The best model improves the baseline by 14.43%.
[2024-08-16T19:59:33.864Z] Movies recommended for you:
[2024-08-16T19:59:33.864Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:59:33.864Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:59:33.864Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (19937.053 ms) ======
[2024-08-16T19:59:33.864Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-16T19:59:33.864Z] GC before operation: completed in 120.467 ms, heap usage 310.682 MB -> 52.874 MB.
[2024-08-16T19:59:37.308Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:59:39.945Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:59:43.349Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:59:45.815Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:59:48.294Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:59:49.876Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:59:51.462Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:59:53.246Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:59:54.054Z] 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.
[2024-08-16T19:59:54.054Z] The best model improves the baseline by 14.43%.
[2024-08-16T19:59:54.054Z] Movies recommended for you:
[2024-08-16T19:59:54.054Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:59:54.054Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:59:54.054Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (19945.880 ms) ======
[2024-08-16T19:59:54.054Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-16T19:59:54.054Z] GC before operation: completed in 121.890 ms, heap usage 536.395 MB -> 56.380 MB.
[2024-08-16T19:59:57.457Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:59:59.913Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T20:00:03.325Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T20:00:05.799Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T20:00:08.259Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T20:00:09.841Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T20:00:11.420Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T20:00:13.877Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T20:00:13.877Z] 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.
[2024-08-16T20:00:13.877Z] The best model improves the baseline by 14.43%.
[2024-08-16T20:00:13.877Z] Movies recommended for you:
[2024-08-16T20:00:13.877Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T20:00:13.877Z] There is no way to check that no silent failure occurred.
[2024-08-16T20:00:13.877Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (19850.077 ms) ======
[2024-08-16T20:00:13.877Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-16T20:00:13.877Z] GC before operation: completed in 109.326 ms, heap usage 541.883 MB -> 56.089 MB.
[2024-08-16T20:00:17.286Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T20:00:19.741Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T20:00:23.139Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T20:00:26.552Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T20:00:28.147Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T20:00:29.723Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T20:00:31.309Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T20:00:33.760Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T20:00:33.761Z] 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.
[2024-08-16T20:00:33.761Z] The best model improves the baseline by 14.43%.
[2024-08-16T20:00:33.761Z] Movies recommended for you:
[2024-08-16T20:00:33.761Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T20:00:33.761Z] There is no way to check that no silent failure occurred.
[2024-08-16T20:00:33.761Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (19840.969 ms) ======
[2024-08-16T20:00:33.761Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-16T20:00:33.761Z] GC before operation: completed in 119.563 ms, heap usage 219.716 MB -> 52.847 MB.
[2024-08-16T20:00:37.194Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T20:00:40.622Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T20:00:43.075Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T20:00:46.475Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T20:00:48.081Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T20:00:49.658Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T20:00:52.118Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T20:00:53.701Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T20:00:53.701Z] 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.
[2024-08-16T20:00:53.701Z] The best model improves the baseline by 14.43%.
[2024-08-16T20:00:53.701Z] Movies recommended for you:
[2024-08-16T20:00:53.701Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T20:00:53.701Z] There is no way to check that no silent failure occurred.
[2024-08-16T20:00:53.701Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (19816.380 ms) ======
[2024-08-16T20:00:53.701Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-16T20:00:53.701Z] GC before operation: completed in 126.862 ms, heap usage 604.193 MB -> 56.539 MB.
[2024-08-16T20:00:57.108Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T20:01:00.691Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T20:01:03.161Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T20:01:05.620Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T20:01:08.098Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T20:01:09.775Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T20:01:11.360Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T20:01:12.945Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T20:01:13.710Z] 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.
[2024-08-16T20:01:13.710Z] The best model improves the baseline by 14.43%.
[2024-08-16T20:01:13.710Z] Movies recommended for you:
[2024-08-16T20:01:13.710Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T20:01:13.710Z] There is no way to check that no silent failure occurred.
[2024-08-16T20:01:13.710Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (19736.707 ms) ======
[2024-08-16T20:01:13.710Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-16T20:01:13.710Z] GC before operation: completed in 108.390 ms, heap usage 382.604 MB -> 52.814 MB.
[2024-08-16T20:01:17.119Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T20:01:19.580Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T20:01:22.980Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T20:01:26.390Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T20:01:27.977Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T20:01:29.557Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T20:01:31.139Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T20:01:32.730Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T20:01:33.501Z] 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.
[2024-08-16T20:01:33.501Z] The best model improves the baseline by 14.43%.
[2024-08-16T20:01:33.501Z] Movies recommended for you:
[2024-08-16T20:01:33.501Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T20:01:33.501Z] There is no way to check that no silent failure occurred.
[2024-08-16T20:01:33.501Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (19764.343 ms) ======
[2024-08-16T20:01:33.501Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-16T20:01:33.501Z] GC before operation: completed in 117.458 ms, heap usage 270.529 MB -> 52.948 MB.
[2024-08-16T20:01:36.905Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T20:01:40.308Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T20:01:42.769Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T20:01:46.186Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T20:01:47.781Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T20:01:49.375Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T20:01:50.959Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T20:01:53.421Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T20:01:53.421Z] 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.
[2024-08-16T20:01:53.421Z] The best model improves the baseline by 14.43%.
[2024-08-16T20:01:53.421Z] Movies recommended for you:
[2024-08-16T20:01:53.421Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T20:01:53.421Z] There is no way to check that no silent failure occurred.
[2024-08-16T20:01:53.421Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (19777.872 ms) ======
[2024-08-16T20:01:53.421Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-16T20:01:53.421Z] GC before operation: completed in 152.812 ms, heap usage 562.176 MB -> 56.459 MB.
[2024-08-16T20:01:56.827Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T20:01:59.289Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T20:02:02.692Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T20:02:06.103Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T20:02:07.692Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T20:02:09.285Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T20:02:11.047Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T20:02:12.644Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T20:02:13.410Z] 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.
[2024-08-16T20:02:13.410Z] The best model improves the baseline by 14.43%.
[2024-08-16T20:02:13.410Z] Movies recommended for you:
[2024-08-16T20:02:13.410Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T20:02:13.410Z] There is no way to check that no silent failure occurred.
[2024-08-16T20:02:13.410Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (19644.836 ms) ======
[2024-08-16T20:02:13.410Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-16T20:02:13.410Z] GC before operation: completed in 119.089 ms, heap usage 657.252 MB -> 56.365 MB.
[2024-08-16T20:02:16.817Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T20:02:19.273Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T20:02:22.686Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T20:02:25.150Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T20:02:27.622Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T20:02:29.220Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T20:02:30.802Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T20:02:32.396Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T20:02:33.161Z] 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.
[2024-08-16T20:02:33.161Z] The best model improves the baseline by 14.43%.
[2024-08-16T20:02:33.161Z] Movies recommended for you:
[2024-08-16T20:02:33.161Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T20:02:33.162Z] There is no way to check that no silent failure occurred.
[2024-08-16T20:02:33.162Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (19730.842 ms) ======
[2024-08-16T20:02:33.162Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-16T20:02:33.162Z] GC before operation: completed in 120.386 ms, heap usage 234.902 MB -> 52.915 MB.
[2024-08-16T20:02:36.570Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T20:02:39.026Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T20:02:42.431Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T20:02:44.891Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T20:02:47.356Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T20:02:48.942Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T20:02:50.527Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T20:02:52.990Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T20:02:52.990Z] 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.
[2024-08-16T20:02:52.990Z] The best model improves the baseline by 14.43%.
[2024-08-16T20:02:52.990Z] Movies recommended for you:
[2024-08-16T20:02:52.990Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T20:02:52.990Z] There is no way to check that no silent failure occurred.
[2024-08-16T20:02:52.990Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (19770.064 ms) ======
[2024-08-16T20:02:52.990Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-16T20:02:52.990Z] GC before operation: completed in 112.246 ms, heap usage 431.331 MB -> 53.232 MB.
[2024-08-16T20:02:56.395Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T20:02:58.856Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T20:03:02.270Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T20:03:05.712Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T20:03:07.293Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T20:03:08.874Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T20:03:10.458Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T20:03:12.044Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T20:03:12.810Z] 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.
[2024-08-16T20:03:12.810Z] The best model improves the baseline by 14.43%.
[2024-08-16T20:03:12.810Z] Movies recommended for you:
[2024-08-16T20:03:12.810Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T20:03:12.810Z] There is no way to check that no silent failure occurred.
[2024-08-16T20:03:12.810Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (19724.820 ms) ======
[2024-08-16T20:03:13.575Z] -----------------------------------
[2024-08-16T20:03:13.575Z] renaissance-movie-lens_0_PASSED
[2024-08-16T20:03:13.575Z] -----------------------------------
[2024-08-16T20:03:13.575Z]
[2024-08-16T20:03:13.575Z] TEST TEARDOWN:
[2024-08-16T20:03:13.575Z] Nothing to be done for teardown.
[2024-08-16T20:03:13.575Z] renaissance-movie-lens_0 Finish Time: Fri Aug 16 20:03:13 2024 Epoch Time (ms): 1723838593171