renaissance-movie-lens_0
[2024-11-07T23:50:56.333Z] Running test renaissance-movie-lens_0 ...
[2024-11-07T23:50:56.333Z] ===============================================
[2024-11-07T23:50:56.333Z] renaissance-movie-lens_0 Start Time: Thu Nov 7 23:50:56 2024 Epoch Time (ms): 1731023456048
[2024-11-07T23:50:56.333Z] variation: NoOptions
[2024-11-07T23:50:56.333Z] JVM_OPTIONS:
[2024-11-07T23:50:56.333Z] { \
[2024-11-07T23:50:56.333Z] echo ""; echo "TEST SETUP:"; \
[2024-11-07T23:50:56.333Z] echo "Nothing to be done for setup."; \
[2024-11-07T23:50:56.333Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17310222975035/renaissance-movie-lens_0"; \
[2024-11-07T23:50:56.333Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17310222975035/renaissance-movie-lens_0"; \
[2024-11-07T23:50:56.333Z] echo ""; echo "TESTING:"; \
[2024-11-07T23:50:56.333Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/jdkbinary/j2sdk-image/bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17310222975035/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-07T23:50:56.333Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17310222975035/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-07T23:50:56.333Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-07T23:50:56.333Z] echo "Nothing to be done for teardown."; \
[2024-11-07T23:50:56.333Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17310222975035/TestTargetResult";
[2024-11-07T23:50:56.333Z]
[2024-11-07T23:50:56.333Z] TEST SETUP:
[2024-11-07T23:50:56.333Z] Nothing to be done for setup.
[2024-11-07T23:50:56.333Z]
[2024-11-07T23:50:56.333Z] TESTING:
[2024-11-07T23:51:00.362Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-07T23:51:04.395Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2024-11-07T23:51:10.911Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-07T23:51:11.834Z] Training: 60056, validation: 20285, test: 19854
[2024-11-07T23:51:11.834Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-07T23:51:11.834Z] GC before operation: completed in 248.017 ms, heap usage 249.917 MB -> 29.425 MB.
[2024-11-07T23:51:21.348Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:51:26.572Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:51:32.153Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:51:36.189Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:51:38.088Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:51:41.184Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:51:43.083Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:51:46.011Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:51:46.933Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-07T23:51:46.934Z] The best model improves the baseline by 14.43%.
[2024-11-07T23:51:46.934Z] Movies recommended for you:
[2024-11-07T23:51:46.934Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:51:46.934Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:51:46.934Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (35118.326 ms) ======
[2024-11-07T23:51:46.934Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-07T23:51:47.857Z] GC before operation: completed in 362.575 ms, heap usage 1.037 GB -> 55.221 MB.
[2024-11-07T23:51:50.788Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:51:54.823Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:51:58.895Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:52:02.934Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:52:04.831Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:52:06.730Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:52:09.668Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:52:11.692Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:52:12.615Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-07T23:52:12.615Z] The best model improves the baseline by 14.43%.
[2024-11-07T23:52:12.615Z] Movies recommended for you:
[2024-11-07T23:52:12.615Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:52:12.615Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:52:12.615Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (25095.997 ms) ======
[2024-11-07T23:52:12.615Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-07T23:52:12.615Z] GC before operation: completed in 287.780 ms, heap usage 515.919 MB -> 49.318 MB.
[2024-11-07T23:52:16.647Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:52:19.595Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:52:23.633Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:52:26.557Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:52:28.450Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:52:30.344Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:52:32.922Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:52:34.822Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:52:34.822Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-07T23:52:34.822Z] The best model improves the baseline by 14.43%.
[2024-11-07T23:52:34.822Z] Movies recommended for you:
[2024-11-07T23:52:34.822Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:52:34.822Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:52:34.822Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (22133.357 ms) ======
[2024-11-07T23:52:34.822Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-07T23:52:34.822Z] GC before operation: completed in 262.320 ms, heap usage 329.797 MB -> 49.506 MB.
[2024-11-07T23:52:38.859Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:52:41.803Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:52:44.735Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:52:47.662Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:52:49.556Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:52:51.452Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:52:54.380Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:52:56.280Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:52:56.280Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-07T23:52:56.280Z] The best model improves the baseline by 14.43%.
[2024-11-07T23:52:56.280Z] Movies recommended for you:
[2024-11-07T23:52:56.280Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:52:56.280Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:52:56.280Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (21427.904 ms) ======
[2024-11-07T23:52:56.280Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-07T23:52:57.205Z] GC before operation: completed in 257.431 ms, heap usage 1.384 GB -> 53.869 MB.
[2024-11-07T23:53:00.136Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:53:03.065Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:53:06.009Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:53:10.047Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:53:11.941Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:53:13.841Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:53:15.746Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:53:17.642Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:53:17.642Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-07T23:53:18.565Z] The best model improves the baseline by 14.43%.
[2024-11-07T23:53:18.565Z] Movies recommended for you:
[2024-11-07T23:53:18.565Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:53:18.565Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:53:18.565Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (21396.427 ms) ======
[2024-11-07T23:53:18.565Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-07T23:53:18.565Z] GC before operation: completed in 281.684 ms, heap usage 1.309 GB -> 54.625 MB.
[2024-11-07T23:53:21.494Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:53:24.423Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:53:28.457Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:53:31.384Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:53:33.594Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:53:35.491Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:53:37.391Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:53:39.303Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:53:40.228Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-07T23:53:40.228Z] The best model improves the baseline by 14.43%.
[2024-11-07T23:53:40.228Z] Movies recommended for you:
[2024-11-07T23:53:40.228Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:53:40.228Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:53:40.228Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (21541.999 ms) ======
[2024-11-07T23:53:40.228Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-07T23:53:40.228Z] GC before operation: completed in 255.590 ms, heap usage 1.314 GB -> 57.308 MB.
[2024-11-07T23:53:43.163Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:53:47.201Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:53:50.133Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:53:53.059Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:53:54.955Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:53:56.852Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:53:59.785Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:54:01.678Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:54:01.678Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-07T23:54:01.678Z] The best model improves the baseline by 14.43%.
[2024-11-07T23:54:01.678Z] Movies recommended for you:
[2024-11-07T23:54:01.678Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:54:01.678Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:54:01.678Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (21699.995 ms) ======
[2024-11-07T23:54:01.678Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-07T23:54:02.598Z] GC before operation: completed in 224.227 ms, heap usage 154.023 MB -> 45.878 MB.
[2024-11-07T23:54:05.527Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:54:08.453Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:54:11.564Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:54:14.492Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:54:17.456Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:54:19.353Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:54:21.251Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:54:23.167Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:54:24.089Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-07T23:54:24.089Z] The best model improves the baseline by 14.43%.
[2024-11-07T23:54:24.089Z] Movies recommended for you:
[2024-11-07T23:54:24.089Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:54:24.089Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:54:24.089Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (21692.080 ms) ======
[2024-11-07T23:54:24.089Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-07T23:54:24.089Z] GC before operation: completed in 239.102 ms, heap usage 117.397 MB -> 51.632 MB.
[2024-11-07T23:54:27.016Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:54:31.056Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:54:34.653Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:54:36.548Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:54:38.439Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:54:40.333Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:54:42.228Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:54:45.155Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:54:45.155Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-07T23:54:45.155Z] The best model improves the baseline by 14.43%.
[2024-11-07T23:54:45.155Z] Movies recommended for you:
[2024-11-07T23:54:45.155Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:54:45.155Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:54:45.155Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (21250.197 ms) ======
[2024-11-07T23:54:45.155Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-07T23:54:46.077Z] GC before operation: completed in 250.851 ms, heap usage 167.478 MB -> 46.089 MB.
[2024-11-07T23:54:49.011Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:54:51.945Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:54:54.871Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:54:57.816Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:55:00.783Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:55:02.677Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:55:04.579Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:55:06.472Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:55:07.394Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-07T23:55:07.394Z] The best model improves the baseline by 14.43%.
[2024-11-07T23:55:07.394Z] Movies recommended for you:
[2024-11-07T23:55:07.394Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:55:07.394Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:55:07.394Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (21516.656 ms) ======
[2024-11-07T23:55:07.394Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-07T23:55:07.394Z] GC before operation: completed in 283.401 ms, heap usage 1.269 GB -> 59.642 MB.
[2024-11-07T23:55:10.320Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:55:13.259Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:55:16.204Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:55:20.239Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:55:21.158Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:55:23.054Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:55:25.983Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:55:26.904Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:55:27.827Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-07T23:55:27.827Z] The best model improves the baseline by 14.43%.
[2024-11-07T23:55:27.827Z] Movies recommended for you:
[2024-11-07T23:55:27.827Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:55:27.827Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:55:27.827Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (20456.972 ms) ======
[2024-11-07T23:55:27.827Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-07T23:55:27.827Z] GC before operation: completed in 223.631 ms, heap usage 184.673 MB -> 46.015 MB.
[2024-11-07T23:55:30.753Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:55:34.780Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:55:37.359Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:55:40.283Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:55:42.172Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:55:44.066Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:55:45.967Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:55:47.945Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:55:48.866Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-07T23:55:48.866Z] The best model improves the baseline by 14.43%.
[2024-11-07T23:55:48.866Z] Movies recommended for you:
[2024-11-07T23:55:48.866Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:55:48.866Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:55:48.866Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (20717.320 ms) ======
[2024-11-07T23:55:48.866Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-07T23:55:48.866Z] GC before operation: completed in 214.490 ms, heap usage 108.815 MB -> 50.056 MB.
[2024-11-07T23:55:51.787Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:55:55.870Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:55:58.794Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:56:01.842Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:56:03.737Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:56:05.640Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:56:07.534Z] RMSE (validation) = 0.9275717388537592 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:56:09.429Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:56:10.515Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-07T23:56:10.515Z] The best model improves the baseline by 14.43%.
[2024-11-07T23:56:10.515Z] Movies recommended for you:
[2024-11-07T23:56:10.515Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:56:10.515Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:56:10.515Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (20992.858 ms) ======
[2024-11-07T23:56:10.515Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-07T23:56:10.515Z] GC before operation: completed in 222.664 ms, heap usage 142.694 MB -> 46.306 MB.
[2024-11-07T23:56:13.444Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:56:16.372Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:56:19.299Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:56:22.232Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:56:24.131Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:56:26.026Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:56:28.952Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:56:30.856Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:56:30.856Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-07T23:56:30.856Z] The best model improves the baseline by 14.43%.
[2024-11-07T23:56:30.856Z] Movies recommended for you:
[2024-11-07T23:56:30.856Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:56:30.856Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:56:30.856Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (20783.702 ms) ======
[2024-11-07T23:56:30.856Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-07T23:56:31.781Z] GC before operation: completed in 267.079 ms, heap usage 1.283 GB -> 54.608 MB.
[2024-11-07T23:56:34.714Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:56:37.643Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:56:40.544Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:56:43.471Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:56:45.366Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:56:47.261Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:56:49.155Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:56:51.050Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:56:51.972Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-07T23:56:51.972Z] The best model improves the baseline by 14.43%.
[2024-11-07T23:56:51.972Z] Movies recommended for you:
[2024-11-07T23:56:51.972Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:56:51.972Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:56:51.972Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (20597.004 ms) ======
[2024-11-07T23:56:51.972Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-07T23:56:51.972Z] GC before operation: completed in 257.345 ms, heap usage 1.296 GB -> 54.549 MB.
[2024-11-07T23:56:54.903Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:56:58.948Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:57:01.872Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:57:04.800Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:57:06.698Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:57:08.596Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:57:10.516Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:57:12.414Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:57:13.338Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-07T23:57:13.338Z] The best model improves the baseline by 14.43%.
[2024-11-07T23:57:13.338Z] Movies recommended for you:
[2024-11-07T23:57:13.338Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:57:13.338Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:57:13.338Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (21076.210 ms) ======
[2024-11-07T23:57:13.338Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-07T23:57:13.338Z] GC before operation: completed in 255.445 ms, heap usage 1.342 GB -> 54.800 MB.
[2024-11-07T23:57:16.270Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:57:20.309Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:57:23.249Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:57:26.178Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:57:28.073Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:57:29.967Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:57:31.864Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:57:33.758Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:57:34.681Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-07T23:57:34.681Z] The best model improves the baseline by 14.43%.
[2024-11-07T23:57:34.681Z] Movies recommended for you:
[2024-11-07T23:57:34.681Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:57:34.681Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:57:34.681Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (20972.926 ms) ======
[2024-11-07T23:57:34.681Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-07T23:57:34.681Z] GC before operation: completed in 256.737 ms, heap usage 151.746 MB -> 46.170 MB.
[2024-11-07T23:57:38.709Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:57:42.310Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:57:44.209Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:57:47.149Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:57:49.049Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:57:50.946Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:57:52.843Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:57:54.737Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:57:55.660Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-07T23:57:55.660Z] The best model improves the baseline by 14.43%.
[2024-11-07T23:57:55.660Z] Movies recommended for you:
[2024-11-07T23:57:55.660Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:57:55.660Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:57:55.660Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (20967.131 ms) ======
[2024-11-07T23:57:55.660Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-07T23:57:55.660Z] GC before operation: completed in 264.616 ms, heap usage 1.307 GB -> 54.846 MB.
[2024-11-07T23:57:59.693Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:58:02.620Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:58:05.546Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:58:08.474Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:58:10.493Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:58:12.394Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:58:14.289Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:58:16.187Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:58:17.108Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-07T23:58:17.108Z] The best model improves the baseline by 14.43%.
[2024-11-07T23:58:17.108Z] Movies recommended for you:
[2024-11-07T23:58:17.108Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:58:17.108Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:58:17.108Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (21189.695 ms) ======
[2024-11-07T23:58:17.108Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-07T23:58:17.108Z] GC before operation: completed in 227.795 ms, heap usage 164.712 MB -> 49.274 MB.
[2024-11-07T23:58:21.135Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:58:24.069Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:58:26.995Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:58:29.923Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:58:31.819Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:58:33.712Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:58:36.636Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:58:38.533Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:58:38.533Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-11-07T23:58:38.533Z] The best model improves the baseline by 14.43%.
[2024-11-07T23:58:38.533Z] Movies recommended for you:
[2024-11-07T23:58:38.533Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:58:38.533Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:58:38.533Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (21450.967 ms) ======
[2024-11-07T23:58:40.422Z] -----------------------------------
[2024-11-07T23:58:40.422Z] renaissance-movie-lens_0_PASSED
[2024-11-07T23:58:40.422Z] -----------------------------------
[2024-11-07T23:58:40.422Z]
[2024-11-07T23:58:40.422Z] TEST TEARDOWN:
[2024-11-07T23:58:40.422Z] Nothing to be done for teardown.
[2024-11-07T23:58:40.422Z] renaissance-movie-lens_0 Finish Time: Thu Nov 7 23:58:40 2024 Epoch Time (ms): 1731023920286