[2024-08-22T10:48:49.371Z] Running test renaissance-movie-lens_0 ... [2024-08-22T10:48:49.371Z] =============================================== [2024-08-22T10:48:49.371Z] renaissance-movie-lens_0 Start Time: Thu Aug 22 10:48:48 2024 Epoch Time (ms): 1724323728327 [2024-08-22T10:48:49.371Z] variation: NoOptions [2024-08-22T10:48:49.371Z] JVM_OPTIONS: [2024-08-22T10:48:49.371Z] { \ [2024-08-22T10:48:49.371Z] echo ""; echo "TEST SETUP:"; \ [2024-08-22T10:48:49.371Z] echo "Nothing to be done for setup."; \ [2024-08-22T10:48:49.371Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17243227179404/renaissance-movie-lens_0"; \ [2024-08-22T10:48:49.371Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17243227179404/renaissance-movie-lens_0"; \ [2024-08-22T10:48:49.371Z] echo ""; echo "TESTING:"; \ [2024-08-22T10:48:49.371Z] "/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_17243227179404/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-08-22T10:48:49.372Z] 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_17243227179404/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-22T10:48:49.372Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-22T10:48:49.372Z] echo "Nothing to be done for teardown."; \ [2024-08-22T10:48:49.372Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17243227179404/TestTargetResult"; [2024-08-22T10:48:49.372Z] [2024-08-22T10:48:49.372Z] TEST SETUP: [2024-08-22T10:48:49.372Z] Nothing to be done for setup. [2024-08-22T10:48:49.372Z] [2024-08-22T10:48:49.372Z] TESTING: [2024-08-22T10:48:53.856Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-22T10:48:56.341Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 24) threads. [2024-08-22T10:49:00.820Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-22T10:49:00.820Z] Training: 60056, validation: 20285, test: 19854 [2024-08-22T10:49:00.820Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-22T10:49:00.820Z] GC before operation: completed in 61.602 ms, heap usage 171.011 MB -> 38.010 MB. [2024-08-22T10:49:07.714Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T10:49:11.157Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T10:49:14.593Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T10:49:18.028Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T10:49:20.508Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T10:49:22.112Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T10:49:24.590Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T10:49:26.189Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T10:49:26.963Z] 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. [2024-08-22T10:49:26.963Z] The best model improves the baseline by 14.43%. [2024-08-22T10:49:26.963Z] Movies recommended for you: [2024-08-22T10:49:26.963Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T10:49:26.963Z] There is no way to check that no silent failure occurred. [2024-08-22T10:49:26.963Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (26366.910 ms) ====== [2024-08-22T10:49:26.963Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-22T10:49:26.963Z] GC before operation: completed in 112.536 ms, heap usage 562.183 MB -> 55.100 MB. [2024-08-22T10:49:30.412Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T10:49:33.846Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T10:49:37.287Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T10:49:40.733Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T10:49:42.348Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T10:49:44.834Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T10:49:46.432Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T10:49:48.931Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T10:49:48.932Z] 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. [2024-08-22T10:49:48.932Z] The best model improves the baseline by 14.43%. [2024-08-22T10:49:48.932Z] Movies recommended for you: [2024-08-22T10:49:48.932Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T10:49:48.932Z] There is no way to check that no silent failure occurred. [2024-08-22T10:49:48.932Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (21745.186 ms) ====== [2024-08-22T10:49:48.932Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-22T10:49:48.932Z] GC before operation: completed in 104.071 ms, heap usage 368.287 MB -> 51.817 MB. [2024-08-22T10:49:52.386Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T10:49:55.834Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T10:49:59.274Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T10:50:01.751Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T10:50:04.245Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T10:50:05.844Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T10:50:07.451Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T10:50:09.937Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T10:50:09.937Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-22T10:50:09.937Z] The best model improves the baseline by 14.43%. [2024-08-22T10:50:09.937Z] Movies recommended for you: [2024-08-22T10:50:09.937Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T10:50:09.937Z] There is no way to check that no silent failure occurred. [2024-08-22T10:50:09.937Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (20833.931 ms) ====== [2024-08-22T10:50:09.937Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-22T10:50:09.937Z] GC before operation: completed in 114.668 ms, heap usage 301.983 MB -> 52.212 MB. [2024-08-22T10:50:13.375Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T10:50:16.812Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T10:50:19.299Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T10:50:22.742Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T10:50:24.343Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T10:50:25.946Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T10:50:28.431Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T10:50:30.035Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T10:50:30.035Z] 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. [2024-08-22T10:50:30.035Z] The best model improves the baseline by 14.43%. [2024-08-22T10:50:30.817Z] Movies recommended for you: [2024-08-22T10:50:30.817Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T10:50:30.817Z] There is no way to check that no silent failure occurred. [2024-08-22T10:50:30.817Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (20424.230 ms) ====== [2024-08-22T10:50:30.817Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-22T10:50:30.817Z] GC before operation: completed in 115.319 ms, heap usage 148.650 MB -> 55.608 MB. [2024-08-22T10:50:33.289Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T10:50:36.719Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T10:50:40.255Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T10:50:42.733Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T10:50:45.222Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T10:50:46.818Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T10:50:48.420Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T10:50:50.900Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T10:50:50.900Z] 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. [2024-08-22T10:50:50.900Z] The best model improves the baseline by 14.43%. [2024-08-22T10:50:50.900Z] Movies recommended for you: [2024-08-22T10:50:50.900Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T10:50:50.900Z] There is no way to check that no silent failure occurred. [2024-08-22T10:50:50.900Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (20389.437 ms) ====== [2024-08-22T10:50:50.900Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-22T10:50:50.900Z] GC before operation: completed in 149.132 ms, heap usage 212.865 MB -> 52.614 MB. [2024-08-22T10:50:54.345Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T10:50:57.784Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T10:51:00.272Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T10:51:03.714Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T10:51:05.324Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T10:51:06.927Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T10:51:09.422Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T10:51:11.017Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T10:51:11.017Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-22T10:51:11.792Z] The best model improves the baseline by 14.43%. [2024-08-22T10:51:11.792Z] Movies recommended for you: [2024-08-22T10:51:11.792Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T10:51:11.792Z] There is no way to check that no silent failure occurred. [2024-08-22T10:51:11.792Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (20366.508 ms) ====== [2024-08-22T10:51:11.792Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-22T10:51:11.792Z] GC before operation: completed in 112.468 ms, heap usage 289.123 MB -> 52.610 MB. [2024-08-22T10:51:14.275Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T10:51:17.712Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T10:51:21.167Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T10:51:23.654Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T10:51:26.143Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T10:51:27.739Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T10:51:29.342Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T10:51:31.828Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T10:51:31.828Z] 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. [2024-08-22T10:51:31.828Z] The best model improves the baseline by 14.43%. [2024-08-22T10:51:31.828Z] Movies recommended for you: [2024-08-22T10:51:31.828Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T10:51:31.828Z] There is no way to check that no silent failure occurred. [2024-08-22T10:51:31.828Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (20180.529 ms) ====== [2024-08-22T10:51:31.828Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-22T10:51:31.828Z] GC before operation: completed in 111.491 ms, heap usage 277.565 MB -> 52.762 MB. [2024-08-22T10:51:35.262Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T10:51:37.744Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T10:51:41.180Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T10:51:44.647Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T10:51:46.257Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T10:51:47.857Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T10:51:49.463Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T10:51:51.973Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T10:51:51.973Z] 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. [2024-08-22T10:51:51.973Z] The best model improves the baseline by 14.43%. [2024-08-22T10:51:51.973Z] Movies recommended for you: [2024-08-22T10:51:51.973Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T10:51:51.973Z] There is no way to check that no silent failure occurred. [2024-08-22T10:51:51.973Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (20244.894 ms) ====== [2024-08-22T10:51:51.973Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-22T10:51:51.973Z] GC before operation: completed in 120.053 ms, heap usage 494.336 MB -> 56.492 MB. [2024-08-22T10:51:55.424Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T10:51:58.867Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T10:52:01.530Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T10:52:04.965Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T10:52:06.561Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T10:52:08.161Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T10:52:10.649Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T10:52:12.247Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T10:52:12.247Z] 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. [2024-08-22T10:52:12.247Z] The best model improves the baseline by 14.43%. [2024-08-22T10:52:12.247Z] Movies recommended for you: [2024-08-22T10:52:12.247Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T10:52:12.247Z] There is no way to check that no silent failure occurred. [2024-08-22T10:52:12.247Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (20257.165 ms) ====== [2024-08-22T10:52:12.247Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-22T10:52:13.022Z] GC before operation: completed in 113.018 ms, heap usage 467.535 MB -> 53.012 MB. [2024-08-22T10:52:15.503Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T10:52:18.937Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T10:52:22.386Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T10:52:24.882Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T10:52:27.373Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T10:52:28.970Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T10:52:30.568Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T10:52:32.179Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T10:52:32.953Z] 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. [2024-08-22T10:52:32.953Z] The best model improves the baseline by 14.43%. [2024-08-22T10:52:32.953Z] Movies recommended for you: [2024-08-22T10:52:32.953Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T10:52:32.953Z] There is no way to check that no silent failure occurred. [2024-08-22T10:52:32.953Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (20281.498 ms) ====== [2024-08-22T10:52:32.953Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-22T10:52:32.953Z] GC before operation: completed in 123.793 ms, heap usage 528.100 MB -> 56.432 MB. [2024-08-22T10:52:36.409Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T10:52:38.898Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T10:52:42.332Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T10:52:45.790Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T10:52:47.389Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T10:52:48.990Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T10:52:51.492Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T10:52:53.089Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T10:52:53.089Z] 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. [2024-08-22T10:52:53.089Z] The best model improves the baseline by 14.43%. [2024-08-22T10:52:53.089Z] Movies recommended for you: [2024-08-22T10:52:53.089Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T10:52:53.089Z] There is no way to check that no silent failure occurred. [2024-08-22T10:52:53.089Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (20222.472 ms) ====== [2024-08-22T10:52:53.089Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-22T10:52:53.089Z] GC before operation: completed in 114.022 ms, heap usage 407.780 MB -> 52.822 MB. [2024-08-22T10:52:56.526Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T10:52:59.988Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T10:53:02.471Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T10:53:05.920Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T10:53:07.521Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T10:53:09.120Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T10:53:11.606Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T10:53:13.222Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T10:53:13.222Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-22T10:53:13.222Z] The best model improves the baseline by 14.43%. [2024-08-22T10:53:13.996Z] Movies recommended for you: [2024-08-22T10:53:13.996Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T10:53:13.996Z] There is no way to check that no silent failure occurred. [2024-08-22T10:53:13.996Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (20209.152 ms) ====== [2024-08-22T10:53:13.996Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-22T10:53:13.996Z] GC before operation: completed in 117.664 ms, heap usage 826.643 MB -> 56.699 MB. [2024-08-22T10:53:16.592Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T10:53:20.046Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T10:53:23.494Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T10:53:25.975Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T10:53:27.577Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T10:53:30.073Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T10:53:31.670Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T10:53:33.288Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T10:53:34.063Z] 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. [2024-08-22T10:53:34.063Z] The best model improves the baseline by 14.43%. [2024-08-22T10:53:34.063Z] Movies recommended for you: [2024-08-22T10:53:34.063Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T10:53:34.063Z] There is no way to check that no silent failure occurred. [2024-08-22T10:53:34.063Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (20146.567 ms) ====== [2024-08-22T10:53:34.063Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-22T10:53:34.063Z] GC before operation: completed in 112.953 ms, heap usage 178.056 MB -> 53.016 MB. [2024-08-22T10:53:37.494Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T10:53:39.987Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T10:53:43.424Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T10:53:45.911Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T10:53:48.410Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T10:53:50.024Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T10:53:51.631Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T10:53:54.123Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T10:53:54.123Z] 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. [2024-08-22T10:53:54.123Z] The best model improves the baseline by 14.43%. [2024-08-22T10:53:54.123Z] Movies recommended for you: [2024-08-22T10:53:54.123Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T10:53:54.123Z] There is no way to check that no silent failure occurred. [2024-08-22T10:53:54.123Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (20152.656 ms) ====== [2024-08-22T10:53:54.123Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-22T10:53:54.123Z] GC before operation: completed in 115.710 ms, heap usage 552.260 MB -> 56.193 MB. [2024-08-22T10:53:57.582Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T10:54:00.073Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T10:54:03.510Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T10:54:06.948Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T10:54:08.547Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T10:54:10.143Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T10:54:11.741Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T10:54:14.219Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T10:54:14.219Z] 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. [2024-08-22T10:54:14.219Z] The best model improves the baseline by 14.43%. [2024-08-22T10:54:14.219Z] Movies recommended for you: [2024-08-22T10:54:14.219Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T10:54:14.219Z] There is no way to check that no silent failure occurred. [2024-08-22T10:54:14.219Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (20080.099 ms) ====== [2024-08-22T10:54:14.219Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-22T10:54:14.219Z] GC before operation: completed in 118.421 ms, heap usage 582.553 MB -> 56.447 MB. [2024-08-22T10:54:17.665Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T10:54:20.167Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T10:54:23.611Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T10:54:27.075Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T10:54:28.681Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T10:54:30.279Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T10:54:32.769Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T10:54:34.386Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T10:54:34.386Z] 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. [2024-08-22T10:54:34.386Z] The best model improves the baseline by 14.43%. [2024-08-22T10:54:34.386Z] Movies recommended for you: [2024-08-22T10:54:34.386Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T10:54:34.386Z] There is no way to check that no silent failure occurred. [2024-08-22T10:54:34.386Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (20206.044 ms) ====== [2024-08-22T10:54:34.386Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-22T10:54:35.165Z] GC before operation: completed in 157.616 ms, heap usage 225.074 MB -> 53.012 MB. [2024-08-22T10:54:37.661Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T10:54:41.121Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T10:54:44.566Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T10:54:47.048Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T10:54:48.661Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T10:54:51.166Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T10:54:52.760Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T10:54:54.506Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T10:54:55.297Z] 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. [2024-08-22T10:54:55.297Z] The best model improves the baseline by 14.43%. [2024-08-22T10:54:55.297Z] Movies recommended for you: [2024-08-22T10:54:55.297Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T10:54:55.297Z] There is no way to check that no silent failure occurred. [2024-08-22T10:54:55.297Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (20080.597 ms) ====== [2024-08-22T10:54:55.297Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-22T10:54:55.297Z] GC before operation: completed in 115.683 ms, heap usage 406.018 MB -> 52.980 MB. [2024-08-22T10:54:58.670Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T10:55:00.783Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T10:55:04.219Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T10:55:07.651Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T10:55:09.252Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T10:55:10.854Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T10:55:12.454Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T10:55:14.953Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T10:55:14.953Z] 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. [2024-08-22T10:55:14.953Z] The best model improves the baseline by 14.43%. [2024-08-22T10:55:14.953Z] Movies recommended for you: [2024-08-22T10:55:14.953Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T10:55:14.953Z] There is no way to check that no silent failure occurred. [2024-08-22T10:55:14.953Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (19891.345 ms) ====== [2024-08-22T10:55:14.953Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-22T10:55:14.953Z] GC before operation: completed in 119.021 ms, heap usage 300.655 MB -> 52.971 MB. [2024-08-22T10:55:18.402Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T10:55:20.892Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T10:55:24.338Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T10:55:26.828Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T10:55:29.317Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T10:55:30.910Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T10:55:32.503Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T10:55:34.985Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T10:55:34.985Z] 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. [2024-08-22T10:55:34.985Z] The best model improves the baseline by 14.43%. [2024-08-22T10:55:34.985Z] Movies recommended for you: [2024-08-22T10:55:34.985Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T10:55:34.985Z] There is no way to check that no silent failure occurred. [2024-08-22T10:55:34.985Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (20073.801 ms) ====== [2024-08-22T10:55:34.985Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-22T10:55:34.985Z] GC before operation: completed in 123.480 ms, heap usage 461.020 MB -> 53.258 MB. [2024-08-22T10:55:38.431Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-22T10:55:40.940Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-22T10:55:44.370Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-22T10:55:47.818Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-22T10:55:49.417Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-22T10:55:51.014Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-22T10:55:52.617Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-22T10:55:55.113Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-22T10:55:55.113Z] 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. [2024-08-22T10:55:55.113Z] The best model improves the baseline by 14.43%. [2024-08-22T10:55:55.113Z] Movies recommended for you: [2024-08-22T10:55:55.113Z] WARNING: This benchmark provides no result that can be validated. [2024-08-22T10:55:55.113Z] There is no way to check that no silent failure occurred. [2024-08-22T10:55:55.113Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (19887.122 ms) ====== [2024-08-22T10:55:55.885Z] ----------------------------------- [2024-08-22T10:55:55.885Z] renaissance-movie-lens_0_PASSED [2024-08-22T10:55:55.885Z] ----------------------------------- [2024-08-22T10:55:55.885Z] [2024-08-22T10:55:55.885Z] TEST TEARDOWN: [2024-08-22T10:55:55.885Z] Nothing to be done for teardown. [2024-08-22T10:55:55.885Z] renaissance-movie-lens_0 Finish Time: Thu Aug 22 10:55:55 2024 Epoch Time (ms): 1724324155303