renaissance-movie-lens_0
[2024-11-21T02:53:48.667Z] Running test renaissance-movie-lens_0 ...
[2024-11-21T02:53:48.667Z] ===============================================
[2024-11-21T02:53:48.667Z] renaissance-movie-lens_0 Start Time: Thu Nov 21 02:53:47 2024 Epoch Time (ms): 1732157627509
[2024-11-21T02:53:48.667Z] variation: NoOptions
[2024-11-21T02:53:48.667Z] JVM_OPTIONS:
[2024-11-21T02:53:48.667Z] { \
[2024-11-21T02:53:48.667Z] echo ""; echo "TEST SETUP:"; \
[2024-11-21T02:53:48.667Z] echo "Nothing to be done for setup."; \
[2024-11-21T02:53:48.667Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17321566156705/renaissance-movie-lens_0"; \
[2024-11-21T02:53:48.667Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17321566156705/renaissance-movie-lens_0"; \
[2024-11-21T02:53:48.667Z] echo ""; echo "TESTING:"; \
[2024-11-21T02:53:48.667Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix/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/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17321566156705/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-21T02:53:48.667Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17321566156705/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-21T02:53:48.667Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-21T02:53:48.667Z] echo "Nothing to be done for teardown."; \
[2024-11-21T02:53:48.667Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17321566156705/TestTargetResult";
[2024-11-21T02:53:48.667Z]
[2024-11-21T02:53:48.667Z] TEST SETUP:
[2024-11-21T02:53:48.667Z] Nothing to be done for setup.
[2024-11-21T02:53:48.667Z]
[2024-11-21T02:53:48.667Z] TESTING:
[2024-11-21T02:53:53.076Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-21T02:53:55.524Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 24) threads.
[2024-11-21T02:53:59.945Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-21T02:53:59.945Z] Training: 60056, validation: 20285, test: 19854
[2024-11-21T02:53:59.945Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-21T02:53:59.945Z] GC before operation: completed in 66.767 ms, heap usage 142.396 MB -> 37.970 MB.
[2024-11-21T02:54:06.749Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T02:54:10.286Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T02:54:14.679Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T02:54:18.060Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T02:54:19.623Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T02:54:22.058Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T02:54:24.493Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T02:54:26.056Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T02:54:26.814Z] 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.
[2024-11-21T02:54:26.814Z] The best model improves the baseline by 14.43%.
[2024-11-21T02:54:26.814Z] Movies recommended for you:
[2024-11-21T02:54:26.814Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T02:54:26.814Z] There is no way to check that no silent failure occurred.
[2024-11-21T02:54:26.814Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (26448.915 ms) ======
[2024-11-21T02:54:26.814Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-21T02:54:26.814Z] GC before operation: completed in 101.826 ms, heap usage 138.021 MB -> 51.198 MB.
[2024-11-21T02:54:30.181Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T02:54:33.626Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T02:54:37.003Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T02:54:40.386Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T02:54:41.955Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T02:54:43.518Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T02:54:45.947Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T02:54:47.528Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T02:54:48.285Z] 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.
[2024-11-21T02:54:48.285Z] The best model improves the baseline by 14.43%.
[2024-11-21T02:54:48.285Z] Movies recommended for you:
[2024-11-21T02:54:48.285Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T02:54:48.285Z] There is no way to check that no silent failure occurred.
[2024-11-21T02:54:48.285Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (21568.293 ms) ======
[2024-11-21T02:54:48.285Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-21T02:54:48.285Z] GC before operation: completed in 123.649 ms, heap usage 525.319 MB -> 55.195 MB.
[2024-11-21T02:54:51.680Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T02:54:55.074Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T02:54:58.446Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T02:55:00.875Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T02:55:03.303Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T02:55:04.874Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T02:55:06.434Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T02:55:08.873Z] RMSE (validation) = 0.9001440981626696 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T02:55:08.873Z] 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.
[2024-11-21T02:55:08.873Z] The best model improves the baseline by 14.43%.
[2024-11-21T02:55:08.873Z] Movies recommended for you:
[2024-11-21T02:55:08.873Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T02:55:08.873Z] There is no way to check that no silent failure occurred.
[2024-11-21T02:55:08.873Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (20612.634 ms) ======
[2024-11-21T02:55:08.873Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-21T02:55:08.873Z] GC before operation: completed in 113.084 ms, heap usage 124.498 MB -> 52.046 MB.
[2024-11-21T02:55:12.243Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T02:55:15.635Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T02:55:19.019Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T02:55:21.449Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T02:55:24.086Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T02:55:25.651Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T02:55:27.224Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T02:55:28.795Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T02:55:29.554Z] 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.
[2024-11-21T02:55:29.554Z] The best model improves the baseline by 14.43%.
[2024-11-21T02:55:29.554Z] Movies recommended for you:
[2024-11-21T02:55:29.554Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T02:55:29.554Z] There is no way to check that no silent failure occurred.
[2024-11-21T02:55:29.554Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (20445.996 ms) ======
[2024-11-21T02:55:29.554Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-21T02:55:29.554Z] GC before operation: completed in 115.979 ms, heap usage 549.096 MB -> 55.872 MB.
[2024-11-21T02:55:32.965Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T02:55:36.336Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T02:55:38.775Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T02:55:42.152Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T02:55:43.721Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T02:55:46.153Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T02:55:47.723Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T02:55:49.295Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T02:55:50.075Z] 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.
[2024-11-21T02:55:50.075Z] The best model improves the baseline by 14.43%.
[2024-11-21T02:55:50.075Z] Movies recommended for you:
[2024-11-21T02:55:50.075Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T02:55:50.075Z] There is no way to check that no silent failure occurred.
[2024-11-21T02:55:50.075Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (20278.576 ms) ======
[2024-11-21T02:55:50.075Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-21T02:55:50.075Z] GC before operation: completed in 117.340 ms, heap usage 347.759 MB -> 52.709 MB.
[2024-11-21T02:55:53.450Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T02:55:55.900Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T02:55:59.318Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T02:56:02.686Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T02:56:04.254Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T02:56:05.821Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T02:56:08.249Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T02:56:09.816Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T02:56:10.573Z] 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.
[2024-11-21T02:56:10.573Z] The best model improves the baseline by 14.43%.
[2024-11-21T02:56:10.573Z] Movies recommended for you:
[2024-11-21T02:56:10.573Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T02:56:10.573Z] There is no way to check that no silent failure occurred.
[2024-11-21T02:56:10.573Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (20261.943 ms) ======
[2024-11-21T02:56:10.573Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-21T02:56:10.573Z] GC before operation: completed in 104.896 ms, heap usage 351.207 MB -> 52.650 MB.
[2024-11-21T02:56:13.952Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T02:56:17.326Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T02:56:19.762Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T02:56:23.153Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T02:56:24.718Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T02:56:26.283Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T02:56:28.720Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T02:56:30.285Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T02:56:31.043Z] 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.
[2024-11-21T02:56:31.044Z] The best model improves the baseline by 14.43%.
[2024-11-21T02:56:31.044Z] Movies recommended for you:
[2024-11-21T02:56:31.044Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T02:56:31.044Z] There is no way to check that no silent failure occurred.
[2024-11-21T02:56:31.044Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (20327.730 ms) ======
[2024-11-21T02:56:31.044Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-21T02:56:31.044Z] GC before operation: completed in 108.747 ms, heap usage 385.474 MB -> 52.808 MB.
[2024-11-21T02:56:34.426Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T02:56:36.863Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T02:56:40.415Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T02:56:42.862Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T02:56:45.314Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T02:56:46.879Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T02:56:49.321Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T02:56:50.894Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T02:56:50.894Z] 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.
[2024-11-21T02:56:50.894Z] The best model improves the baseline by 14.43%.
[2024-11-21T02:56:50.894Z] Movies recommended for you:
[2024-11-21T02:56:50.894Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T02:56:50.894Z] There is no way to check that no silent failure occurred.
[2024-11-21T02:56:50.894Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (20221.447 ms) ======
[2024-11-21T02:56:50.894Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-21T02:56:51.650Z] GC before operation: completed in 109.220 ms, heap usage 374.654 MB -> 53.093 MB.
[2024-11-21T02:56:54.078Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T02:56:57.461Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T02:57:01.014Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T02:57:03.452Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T02:57:05.897Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T02:57:07.462Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T02:57:09.906Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T02:57:11.472Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T02:57:11.472Z] 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.
[2024-11-21T02:57:11.472Z] The best model improves the baseline by 14.43%.
[2024-11-21T02:57:12.230Z] Movies recommended for you:
[2024-11-21T02:57:12.230Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T02:57:12.230Z] There is no way to check that no silent failure occurred.
[2024-11-21T02:57:12.230Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (20586.415 ms) ======
[2024-11-21T02:57:12.230Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-21T02:57:12.230Z] GC before operation: completed in 154.526 ms, heap usage 298.287 MB -> 52.901 MB.
[2024-11-21T02:57:15.609Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T02:57:18.041Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T02:57:21.419Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T02:57:24.801Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T02:57:26.378Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T02:57:27.961Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T02:57:30.423Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T02:57:31.987Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T02:57:31.987Z] 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.
[2024-11-21T02:57:31.987Z] The best model improves the baseline by 14.43%.
[2024-11-21T02:57:31.987Z] Movies recommended for you:
[2024-11-21T02:57:31.987Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T02:57:31.987Z] There is no way to check that no silent failure occurred.
[2024-11-21T02:57:31.987Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (20151.900 ms) ======
[2024-11-21T02:57:31.987Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-21T02:57:31.987Z] GC before operation: completed in 120.615 ms, heap usage 530.034 MB -> 56.414 MB.
[2024-11-21T02:57:35.363Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T02:57:38.731Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T02:57:41.170Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T02:57:44.538Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T02:57:46.117Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T02:57:48.569Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T02:57:50.135Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T02:57:51.762Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T02:57:52.518Z] 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.
[2024-11-21T02:57:52.518Z] The best model improves the baseline by 14.43%.
[2024-11-21T02:57:52.518Z] Movies recommended for you:
[2024-11-21T02:57:52.518Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T02:57:52.518Z] There is no way to check that no silent failure occurred.
[2024-11-21T02:57:52.518Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (20157.601 ms) ======
[2024-11-21T02:57:52.518Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-21T02:57:52.518Z] GC before operation: completed in 106.741 ms, heap usage 371.764 MB -> 52.742 MB.
[2024-11-21T02:57:55.897Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T02:57:59.273Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T02:58:01.714Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T02:58:05.087Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T02:58:06.657Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T02:58:08.219Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T02:58:10.662Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T02:58:12.230Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T02:58:12.987Z] 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.
[2024-11-21T02:58:12.987Z] The best model improves the baseline by 14.43%.
[2024-11-21T02:58:12.987Z] Movies recommended for you:
[2024-11-21T02:58:12.987Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T02:58:12.987Z] There is no way to check that no silent failure occurred.
[2024-11-21T02:58:12.987Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (20294.130 ms) ======
[2024-11-21T02:58:12.987Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-21T02:58:12.987Z] GC before operation: completed in 111.283 ms, heap usage 451.984 MB -> 53.034 MB.
[2024-11-21T02:58:16.365Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T02:58:18.799Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T02:58:22.176Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T02:58:25.554Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T02:58:27.120Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T02:58:28.684Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T02:58:31.117Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T02:58:32.682Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T02:58:32.682Z] 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.
[2024-11-21T02:58:32.682Z] The best model improves the baseline by 14.43%.
[2024-11-21T02:58:32.682Z] Movies recommended for you:
[2024-11-21T02:58:32.682Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T02:58:32.682Z] There is no way to check that no silent failure occurred.
[2024-11-21T02:58:32.682Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (20049.075 ms) ======
[2024-11-21T02:58:32.682Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-21T02:58:33.436Z] GC before operation: completed in 117.067 ms, heap usage 551.120 MB -> 56.521 MB.
[2024-11-21T02:58:35.877Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T02:58:39.254Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T02:58:42.625Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T02:58:45.065Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T02:58:47.491Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T02:58:49.053Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T02:58:50.618Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T02:58:53.057Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T02:58:53.057Z] 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.
[2024-11-21T02:58:53.057Z] The best model improves the baseline by 14.43%.
[2024-11-21T02:58:53.057Z] Movies recommended for you:
[2024-11-21T02:58:53.057Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T02:58:53.057Z] There is no way to check that no silent failure occurred.
[2024-11-21T02:58:53.057Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (20089.423 ms) ======
[2024-11-21T02:58:53.057Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-21T02:58:53.057Z] GC before operation: completed in 125.008 ms, heap usage 550.716 MB -> 56.242 MB.
[2024-11-21T02:58:56.430Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T02:58:59.798Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T02:59:02.228Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T02:59:05.607Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T02:59:07.519Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T02:59:09.127Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T02:59:10.690Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T02:59:13.124Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T02:59:13.124Z] 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.
[2024-11-21T02:59:13.124Z] The best model improves the baseline by 14.43%.
[2024-11-21T02:59:13.124Z] Movies recommended for you:
[2024-11-21T02:59:13.124Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T02:59:13.124Z] There is no way to check that no silent failure occurred.
[2024-11-21T02:59:13.124Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (19842.911 ms) ======
[2024-11-21T02:59:13.124Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-21T02:59:13.124Z] GC before operation: completed in 117.190 ms, heap usage 311.167 MB -> 53.054 MB.
[2024-11-21T02:59:16.503Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T02:59:19.877Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T02:59:22.307Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T02:59:25.674Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T02:59:27.247Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T02:59:28.813Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T02:59:31.256Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T02:59:32.822Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T02:59:32.823Z] 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.
[2024-11-21T02:59:33.579Z] The best model improves the baseline by 14.43%.
[2024-11-21T02:59:33.579Z] Movies recommended for you:
[2024-11-21T02:59:33.579Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T02:59:33.579Z] There is no way to check that no silent failure occurred.
[2024-11-21T02:59:33.579Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (20005.566 ms) ======
[2024-11-21T02:59:33.579Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-21T02:59:33.579Z] GC before operation: completed in 118.410 ms, heap usage 507.142 MB -> 56.507 MB.
[2024-11-21T02:59:36.010Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T02:59:39.383Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T02:59:42.752Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T02:59:45.187Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T02:59:47.627Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T02:59:49.197Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T02:59:50.765Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T02:59:53.203Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T02:59:53.203Z] 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.
[2024-11-21T02:59:53.203Z] The best model improves the baseline by 14.43%.
[2024-11-21T02:59:53.203Z] Movies recommended for you:
[2024-11-21T02:59:53.203Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T02:59:53.203Z] There is no way to check that no silent failure occurred.
[2024-11-21T02:59:53.203Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (19802.670 ms) ======
[2024-11-21T02:59:53.203Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-21T02:59:53.203Z] GC before operation: completed in 114.893 ms, heap usage 248.814 MB -> 52.907 MB.
[2024-11-21T02:59:56.585Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T02:59:59.962Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T03:00:02.399Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T03:00:05.775Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T03:00:07.348Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T03:00:08.926Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T03:00:11.363Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T03:00:12.936Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T03:00:12.936Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-11-21T03:00:13.692Z] The best model improves the baseline by 14.43%.
[2024-11-21T03:00:13.692Z] Movies recommended for you:
[2024-11-21T03:00:13.692Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T03:00:13.692Z] There is no way to check that no silent failure occurred.
[2024-11-21T03:00:13.692Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (20070.566 ms) ======
[2024-11-21T03:00:13.692Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-21T03:00:13.692Z] GC before operation: completed in 121.717 ms, heap usage 705.069 MB -> 56.528 MB.
[2024-11-21T03:00:17.083Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T03:00:19.526Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T03:00:23.096Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T03:00:25.543Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T03:00:27.113Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T03:00:29.561Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T03:00:31.126Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T03:00:32.722Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T03:00:33.481Z] 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.
[2024-11-21T03:00:33.481Z] The best model improves the baseline by 14.43%.
[2024-11-21T03:00:33.481Z] Movies recommended for you:
[2024-11-21T03:00:33.481Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T03:00:33.481Z] There is no way to check that no silent failure occurred.
[2024-11-21T03:00:33.481Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (19830.607 ms) ======
[2024-11-21T03:00:33.481Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-21T03:00:33.481Z] GC before operation: completed in 119.373 ms, heap usage 311.600 MB -> 53.223 MB.
[2024-11-21T03:00:36.849Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T03:00:39.295Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T03:00:42.676Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T03:00:46.073Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T03:00:47.651Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T03:00:49.214Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T03:00:51.653Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T03:00:53.222Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T03:00:53.222Z] 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.
[2024-11-21T03:00:53.222Z] The best model improves the baseline by 14.43%.
[2024-11-21T03:00:53.222Z] Movies recommended for you:
[2024-11-21T03:00:53.222Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T03:00:53.222Z] There is no way to check that no silent failure occurred.
[2024-11-21T03:00:53.223Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (19976.860 ms) ======
[2024-11-21T03:00:53.978Z] -----------------------------------
[2024-11-21T03:00:53.978Z] renaissance-movie-lens_0_PASSED
[2024-11-21T03:00:53.978Z] -----------------------------------
[2024-11-21T03:00:53.978Z]
[2024-11-21T03:00:53.978Z] TEST TEARDOWN:
[2024-11-21T03:00:53.978Z] Nothing to be done for teardown.
[2024-11-21T03:00:53.978Z] renaissance-movie-lens_0 Finish Time: Thu Nov 21 03:00:53 2024 Epoch Time (ms): 1732158053690