renaissance-movie-lens_0
[2024-08-01T05:36:55.338Z] Running test renaissance-movie-lens_0 ...
[2024-08-01T05:36:55.338Z] ===============================================
[2024-08-01T05:36:55.338Z] renaissance-movie-lens_0 Start Time: Thu Aug 1 05:36:55 2024 Epoch Time (ms): 1722490615237
[2024-08-01T05:36:55.338Z] variation: NoOptions
[2024-08-01T05:36:56.104Z] JVM_OPTIONS:
[2024-08-01T05:36:56.104Z] { \
[2024-08-01T05:36:56.104Z] echo ""; echo "TEST SETUP:"; \
[2024-08-01T05:36:56.104Z] echo "Nothing to be done for setup."; \
[2024-08-01T05:36:56.104Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17224897626000/renaissance-movie-lens_0"; \
[2024-08-01T05:36:56.104Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17224897626000/renaissance-movie-lens_0"; \
[2024-08-01T05:36:56.104Z] echo ""; echo "TESTING:"; \
[2024-08-01T05:36:56.104Z] "/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_17224897626000/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-01T05:36:56.104Z] 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_17224897626000/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-01T05:36:56.104Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-01T05:36:56.104Z] echo "Nothing to be done for teardown."; \
[2024-08-01T05:36:56.104Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17224897626000/TestTargetResult";
[2024-08-01T05:36:56.104Z]
[2024-08-01T05:36:56.104Z] TEST SETUP:
[2024-08-01T05:36:56.104Z] Nothing to be done for setup.
[2024-08-01T05:36:56.104Z]
[2024-08-01T05:36:56.104Z] TESTING:
[2024-08-01T05:37:00.553Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-01T05:37:02.136Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 24) threads.
[2024-08-01T05:37:05.546Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-01T05:37:05.546Z] Training: 60056, validation: 20285, test: 19854
[2024-08-01T05:37:05.546Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-01T05:37:05.546Z] GC before operation: completed in 56.429 ms, heap usage 275.994 MB -> 37.750 MB.
[2024-08-01T05:37:11.157Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:37:13.618Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:37:17.036Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:37:20.475Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:37:22.077Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:37:24.545Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:37:26.142Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:37:27.726Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:37:28.492Z] 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.
[2024-08-01T05:37:28.493Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:37:28.493Z] Movies recommended for you:
[2024-08-01T05:37:28.493Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:37:28.493Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:37:28.493Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (22801.975 ms) ======
[2024-08-01T05:37:28.493Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-01T05:37:28.493Z] GC before operation: completed in 75.658 ms, heap usage 136.200 MB -> 48.415 MB.
[2024-08-01T05:37:30.985Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:37:34.391Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:37:36.904Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:37:39.362Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:37:40.940Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:37:42.528Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:37:44.285Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:37:45.868Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:37:46.647Z] 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.
[2024-08-01T05:37:46.647Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:37:46.647Z] Movies recommended for you:
[2024-08-01T05:37:46.647Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:37:46.647Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:37:46.647Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17999.386 ms) ======
[2024-08-01T05:37:46.647Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-01T05:37:46.647Z] GC before operation: completed in 94.649 ms, heap usage 1.846 GB -> 57.370 MB.
[2024-08-01T05:37:49.116Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:37:52.562Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:37:55.033Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:37:58.450Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:37:59.217Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:38:01.672Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:38:03.261Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:38:04.029Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:38:04.793Z] 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.
[2024-08-01T05:38:04.793Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:38:04.793Z] Movies recommended for you:
[2024-08-01T05:38:04.793Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:38:04.793Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:38:04.793Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (18342.996 ms) ======
[2024-08-01T05:38:04.793Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-01T05:38:04.793Z] GC before operation: completed in 86.342 ms, heap usage 1.973 GB -> 56.549 MB.
[2024-08-01T05:38:07.254Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:38:10.664Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:38:14.075Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:38:16.535Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:38:18.118Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:38:19.709Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:38:21.296Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:38:22.929Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:38:22.929Z] 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.
[2024-08-01T05:38:23.694Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:38:23.694Z] Movies recommended for you:
[2024-08-01T05:38:23.694Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:38:23.694Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:38:23.694Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (18519.815 ms) ======
[2024-08-01T05:38:23.694Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-01T05:38:23.694Z] GC before operation: completed in 90.070 ms, heap usage 1.727 GB -> 60.542 MB.
[2024-08-01T05:38:26.159Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:38:28.618Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:38:32.022Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:38:34.485Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:38:36.073Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:38:37.667Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:38:39.273Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:38:40.857Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:38:40.857Z] 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.
[2024-08-01T05:38:40.857Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:38:40.857Z] Movies recommended for you:
[2024-08-01T05:38:40.857Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:38:40.857Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:38:40.857Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (17404.466 ms) ======
[2024-08-01T05:38:40.857Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-01T05:38:40.857Z] GC before operation: completed in 94.363 ms, heap usage 2.555 GB -> 59.024 MB.
[2024-08-01T05:38:44.287Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:38:46.762Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:38:49.225Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:38:51.794Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:38:53.377Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:38:54.976Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:38:56.562Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:38:58.166Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:38:58.166Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-01T05:38:58.943Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:38:58.943Z] Movies recommended for you:
[2024-08-01T05:38:58.943Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:38:58.943Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:38:58.943Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (17638.948 ms) ======
[2024-08-01T05:38:58.943Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-01T05:38:58.943Z] GC before operation: completed in 95.249 ms, heap usage 1.080 GB -> 58.788 MB.
[2024-08-01T05:39:01.403Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:39:03.861Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:39:07.274Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:39:08.868Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:39:10.448Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:39:12.038Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:39:14.501Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:39:15.267Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:39:16.031Z] 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.
[2024-08-01T05:39:16.031Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:39:16.031Z] Movies recommended for you:
[2024-08-01T05:39:16.031Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:39:16.031Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:39:16.032Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (17281.536 ms) ======
[2024-08-01T05:39:16.032Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-01T05:39:16.032Z] GC before operation: completed in 98.308 ms, heap usage 1.360 GB -> 59.299 MB.
[2024-08-01T05:39:19.453Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:39:21.913Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:39:24.372Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:39:26.843Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:39:28.451Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:39:30.044Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:39:32.506Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:39:34.086Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:39:34.086Z] 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.
[2024-08-01T05:39:34.086Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:39:34.086Z] Movies recommended for you:
[2024-08-01T05:39:34.086Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:39:34.086Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:39:34.086Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (17915.786 ms) ======
[2024-08-01T05:39:34.086Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-01T05:39:34.086Z] GC before operation: completed in 90.905 ms, heap usage 1.917 GB -> 57.492 MB.
[2024-08-01T05:39:37.492Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:39:39.965Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:39:42.431Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:39:44.895Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:39:46.475Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:39:48.064Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:39:49.653Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:39:51.332Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:39:51.332Z] 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.
[2024-08-01T05:39:51.332Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:39:51.332Z] Movies recommended for you:
[2024-08-01T05:39:51.332Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:39:51.332Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:39:51.332Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (17476.291 ms) ======
[2024-08-01T05:39:51.332Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-01T05:39:52.109Z] GC before operation: completed in 98.148 ms, heap usage 1.202 GB -> 56.819 MB.
[2024-08-01T05:39:54.567Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:39:57.031Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:40:00.453Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:40:02.923Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:40:04.504Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:40:06.105Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:40:07.690Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:40:08.461Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:40:09.227Z] 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.
[2024-08-01T05:40:09.227Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:40:09.227Z] Movies recommended for you:
[2024-08-01T05:40:09.227Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:40:09.227Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:40:09.227Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (17511.416 ms) ======
[2024-08-01T05:40:09.227Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-01T05:40:09.227Z] GC before operation: completed in 93.999 ms, heap usage 1.800 GB -> 57.398 MB.
[2024-08-01T05:40:11.687Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:40:15.099Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:40:17.555Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:40:20.011Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:40:21.610Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:40:23.193Z] RMSE (validation) = 1.117495376637101 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:40:24.778Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:40:26.368Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:40:26.368Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-01T05:40:26.368Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:40:26.368Z] Movies recommended for you:
[2024-08-01T05:40:26.368Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:40:26.368Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:40:26.368Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (17143.904 ms) ======
[2024-08-01T05:40:26.368Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-01T05:40:26.368Z] GC before operation: completed in 89.365 ms, heap usage 1.922 GB -> 61.845 MB.
[2024-08-01T05:40:30.864Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:40:31.810Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:40:35.184Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:40:37.120Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:40:38.700Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:40:40.287Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:40:41.871Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:40:43.471Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:40:43.471Z] 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.
[2024-08-01T05:40:43.471Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:40:43.471Z] Movies recommended for you:
[2024-08-01T05:40:43.471Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:40:43.471Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:40:43.471Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (17249.988 ms) ======
[2024-08-01T05:40:43.471Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-01T05:40:44.238Z] GC before operation: completed in 93.098 ms, heap usage 1.338 GB -> 58.847 MB.
[2024-08-01T05:40:46.710Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:40:49.182Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:40:51.786Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:40:55.199Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:40:55.963Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:40:57.546Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:40:59.128Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:41:00.710Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:41:01.476Z] 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.
[2024-08-01T05:41:01.476Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:41:01.476Z] Movies recommended for you:
[2024-08-01T05:41:01.476Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:41:01.476Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:41:01.476Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (17487.838 ms) ======
[2024-08-01T05:41:01.476Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-01T05:41:01.476Z] GC before operation: completed in 82.132 ms, heap usage 192.687 MB -> 55.850 MB.
[2024-08-01T05:41:03.937Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:41:06.401Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:41:09.819Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:41:12.286Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:41:13.869Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:41:14.650Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:41:16.239Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:41:17.838Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:41:18.604Z] 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.
[2024-08-01T05:41:18.604Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:41:18.604Z] Movies recommended for you:
[2024-08-01T05:41:18.604Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:41:18.604Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:41:18.604Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (16999.617 ms) ======
[2024-08-01T05:41:18.604Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-01T05:41:18.604Z] GC before operation: completed in 97.503 ms, heap usage 1.912 GB -> 59.039 MB.
[2024-08-01T05:41:21.069Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:41:23.530Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:41:26.950Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:41:29.444Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:41:30.210Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:41:31.802Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:41:33.384Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:41:34.970Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:41:35.737Z] 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.
[2024-08-01T05:41:35.738Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:41:35.738Z] Movies recommended for you:
[2024-08-01T05:41:35.738Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:41:35.738Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:41:35.738Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (16939.783 ms) ======
[2024-08-01T05:41:35.738Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-01T05:41:35.738Z] GC before operation: completed in 95.055 ms, heap usage 1.927 GB -> 59.664 MB.
[2024-08-01T05:41:38.204Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:41:40.682Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:41:44.092Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:41:46.555Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:41:48.142Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:41:49.727Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:41:51.341Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:41:52.941Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:41:52.941Z] 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.
[2024-08-01T05:41:52.941Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:41:52.941Z] Movies recommended for you:
[2024-08-01T05:41:52.941Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:41:52.941Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:41:52.941Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (17493.218 ms) ======
[2024-08-01T05:41:52.941Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-01T05:41:52.941Z] GC before operation: completed in 90.797 ms, heap usage 1.422 GB -> 59.856 MB.
[2024-08-01T05:41:56.363Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:41:58.821Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:42:02.237Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:42:04.699Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:42:06.281Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:42:07.886Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:42:09.472Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:42:11.069Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:42:11.844Z] 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.
[2024-08-01T05:42:11.844Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:42:11.844Z] Movies recommended for you:
[2024-08-01T05:42:11.844Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:42:11.844Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:42:11.844Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (18432.282 ms) ======
[2024-08-01T05:42:11.844Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-01T05:42:11.844Z] GC before operation: completed in 84.230 ms, heap usage 412.671 MB -> 53.686 MB.
[2024-08-01T05:42:15.262Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:42:17.740Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:42:20.207Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:42:22.665Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:42:24.257Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:42:25.837Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:42:27.427Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:42:29.018Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:42:29.785Z] 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.
[2024-08-01T05:42:29.785Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:42:29.785Z] Movies recommended for you:
[2024-08-01T05:42:29.785Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:42:29.785Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:42:29.785Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (17890.228 ms) ======
[2024-08-01T05:42:29.785Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-01T05:42:29.785Z] GC before operation: completed in 91.932 ms, heap usage 1.992 GB -> 59.241 MB.
[2024-08-01T05:42:32.242Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:42:35.647Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:42:38.103Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:42:40.562Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:42:42.152Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:42:43.740Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:42:45.504Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:42:47.090Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:42:47.090Z] 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.
[2024-08-01T05:42:47.090Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:42:47.857Z] Movies recommended for you:
[2024-08-01T05:42:47.857Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:42:47.857Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:42:47.857Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (17787.852 ms) ======
[2024-08-01T05:42:47.857Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-01T05:42:47.857Z] GC before operation: completed in 87.105 ms, heap usage 215.467 MB -> 52.612 MB.
[2024-08-01T05:42:50.323Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T05:42:53.733Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T05:42:56.200Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T05:42:59.619Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T05:43:01.200Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T05:43:02.784Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T05:43:04.370Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T05:43:05.962Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T05:43:06.739Z] 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.
[2024-08-01T05:43:06.739Z] The best model improves the baseline by 14.43%.
[2024-08-01T05:43:06.739Z] Movies recommended for you:
[2024-08-01T05:43:06.739Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T05:43:06.739Z] There is no way to check that no silent failure occurred.
[2024-08-01T05:43:06.739Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (18956.049 ms) ======
[2024-08-01T05:43:07.505Z] -----------------------------------
[2024-08-01T05:43:07.505Z] renaissance-movie-lens_0_PASSED
[2024-08-01T05:43:07.505Z] -----------------------------------
[2024-08-01T05:43:07.505Z]
[2024-08-01T05:43:07.505Z] TEST TEARDOWN:
[2024-08-01T05:43:07.505Z] Nothing to be done for teardown.
[2024-08-01T05:43:07.505Z] renaissance-movie-lens_0 Finish Time: Thu Aug 1 05:43:06 2024 Epoch Time (ms): 1722490986805