renaissance-movie-lens_0
[2024-09-05T21:12:19.736Z] Running test renaissance-movie-lens_0 ...
[2024-09-05T21:12:19.736Z] ===============================================
[2024-09-05T21:12:19.736Z] renaissance-movie-lens_0 Start Time: Thu Sep 5 21:12:18 2024 Epoch Time (ms): 1725570738234
[2024-09-05T21:12:19.736Z] variation: NoOptions
[2024-09-05T21:12:19.736Z] JVM_OPTIONS:
[2024-09-05T21:12:19.736Z] { \
[2024-09-05T21:12:19.736Z] echo ""; echo "TEST SETUP:"; \
[2024-09-05T21:12:19.736Z] echo "Nothing to be done for setup."; \
[2024-09-05T21:12:19.736Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17255696153005/renaissance-movie-lens_0"; \
[2024-09-05T21:12:19.736Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17255696153005/renaissance-movie-lens_0"; \
[2024-09-05T21:12:19.736Z] echo ""; echo "TESTING:"; \
[2024-09-05T21:12:19.736Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/jdkbinary/j2sdk-image/bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17255696153005/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-09-05T21:12:19.736Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17255696153005/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-09-05T21:12:19.736Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-09-05T21:12:19.736Z] echo "Nothing to be done for teardown."; \
[2024-09-05T21:12:19.736Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17255696153005/TestTargetResult";
[2024-09-05T21:12:19.736Z]
[2024-09-05T21:12:19.736Z] TEST SETUP:
[2024-09-05T21:12:19.736Z] Nothing to be done for setup.
[2024-09-05T21:12:19.736Z]
[2024-09-05T21:12:19.736Z] TESTING:
[2024-09-05T21:12:24.107Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-09-05T21:12:27.468Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 24) threads.
[2024-09-05T21:12:34.233Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-09-05T21:12:34.233Z] Training: 60056, validation: 20285, test: 19854
[2024-09-05T21:12:34.233Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-09-05T21:12:34.233Z] GC before operation: completed in 270.675 ms, heap usage 234.668 MB -> 26.639 MB.
[2024-09-05T21:12:43.967Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:12:48.355Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:12:53.878Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:12:58.262Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:13:00.680Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:13:03.104Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:13:06.464Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:13:08.898Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:13:08.898Z] 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.
[2024-09-05T21:13:08.898Z] The best model improves the baseline by 14.43%.
[2024-09-05T21:13:08.898Z] Movies recommended for you:
[2024-09-05T21:13:08.898Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:13:08.898Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:13:08.898Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (34972.866 ms) ======
[2024-09-05T21:13:08.898Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-09-05T21:13:09.649Z] GC before operation: completed in 374.709 ms, heap usage 96.884 MB -> 49.620 MB.
[2024-09-05T21:13:14.055Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:13:18.440Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:13:22.820Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:13:27.191Z] RMSE (validation) = 1.0045407704488025 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:13:29.625Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:13:33.006Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:13:35.439Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:13:38.043Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:13:38.043Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-09-05T21:13:38.043Z] The best model improves the baseline by 14.43%.
[2024-09-05T21:13:38.043Z] Movies recommended for you:
[2024-09-05T21:13:38.043Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:13:38.043Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:13:38.043Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (28457.799 ms) ======
[2024-09-05T21:13:38.043Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-09-05T21:13:38.043Z] GC before operation: completed in 261.521 ms, heap usage 126.114 MB -> 47.107 MB.
[2024-09-05T21:13:42.421Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:13:46.793Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:13:51.164Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:13:55.537Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:13:57.960Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:14:00.382Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:14:02.809Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:14:05.233Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:14:05.233Z] 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.
[2024-09-05T21:14:05.233Z] The best model improves the baseline by 14.43%.
[2024-09-05T21:14:05.233Z] Movies recommended for you:
[2024-09-05T21:14:05.233Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:14:05.233Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:14:05.233Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (27193.964 ms) ======
[2024-09-05T21:14:05.233Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-09-05T21:14:05.984Z] GC before operation: completed in 208.328 ms, heap usage 98.509 MB -> 42.426 MB.
[2024-09-05T21:14:10.366Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:14:13.720Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:14:18.099Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:14:22.482Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:14:24.926Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:14:27.345Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:14:29.779Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:14:32.226Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:14:32.226Z] 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.
[2024-09-05T21:14:32.226Z] The best model improves the baseline by 14.43%.
[2024-09-05T21:14:32.226Z] Movies recommended for you:
[2024-09-05T21:14:32.226Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:14:32.226Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:14:32.226Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (26829.570 ms) ======
[2024-09-05T21:14:32.226Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-09-05T21:14:32.977Z] GC before operation: completed in 187.375 ms, heap usage 202.078 MB -> 43.246 MB.
[2024-09-05T21:14:37.368Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:14:40.734Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:14:45.294Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:14:49.700Z] RMSE (validation) = 1.0045407704488025 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:14:52.124Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:14:53.680Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:14:57.041Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:14:58.615Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:14:59.384Z] 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.
[2024-09-05T21:14:59.384Z] The best model improves the baseline by 14.43%.
[2024-09-05T21:14:59.384Z] Movies recommended for you:
[2024-09-05T21:14:59.384Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:14:59.384Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:14:59.384Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (26726.524 ms) ======
[2024-09-05T21:14:59.384Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-09-05T21:14:59.384Z] GC before operation: completed in 226.472 ms, heap usage 282.204 MB -> 45.994 MB.
[2024-09-05T21:15:03.762Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:15:08.147Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:15:12.536Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:15:16.933Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:15:18.486Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:15:20.919Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:15:23.337Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:15:25.754Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:15:26.505Z] 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.
[2024-09-05T21:15:26.506Z] The best model improves the baseline by 14.43%.
[2024-09-05T21:15:26.506Z] Movies recommended for you:
[2024-09-05T21:15:26.506Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:15:26.506Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:15:26.506Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (26787.111 ms) ======
[2024-09-05T21:15:26.506Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-09-05T21:15:26.506Z] GC before operation: completed in 218.011 ms, heap usage 158.335 MB -> 46.506 MB.
[2024-09-05T21:15:30.885Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:15:35.274Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:15:38.674Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:15:43.066Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:15:45.495Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:15:47.929Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:15:50.355Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:15:52.969Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:15:52.969Z] 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.
[2024-09-05T21:15:52.969Z] The best model improves the baseline by 14.43%.
[2024-09-05T21:15:52.969Z] Movies recommended for you:
[2024-09-05T21:15:52.969Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:15:52.969Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:15:52.969Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (26313.997 ms) ======
[2024-09-05T21:15:52.969Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-09-05T21:15:52.969Z] GC before operation: completed in 167.522 ms, heap usage 195.013 MB -> 47.425 MB.
[2024-09-05T21:15:57.356Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:16:01.737Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:16:06.114Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:16:10.484Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:16:12.928Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:16:15.365Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:16:17.788Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:16:20.205Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:16:20.205Z] 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.
[2024-09-05T21:16:20.205Z] The best model improves the baseline by 14.43%.
[2024-09-05T21:16:20.205Z] Movies recommended for you:
[2024-09-05T21:16:20.205Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:16:20.205Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:16:20.205Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (27298.454 ms) ======
[2024-09-05T21:16:20.205Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-09-05T21:16:20.959Z] GC before operation: completed in 209.856 ms, heap usage 294.546 MB -> 55.381 MB.
[2024-09-05T21:16:25.333Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:16:28.720Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:16:33.101Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:16:37.530Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:16:39.963Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:16:42.386Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:16:44.812Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:16:47.251Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:16:48.011Z] 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.
[2024-09-05T21:16:48.011Z] The best model improves the baseline by 14.43%.
[2024-09-05T21:16:48.011Z] Movies recommended for you:
[2024-09-05T21:16:48.011Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:16:48.011Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:16:48.011Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (27419.210 ms) ======
[2024-09-05T21:16:48.011Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-09-05T21:16:48.011Z] GC before operation: completed in 198.322 ms, heap usage 232.339 MB -> 47.245 MB.
[2024-09-05T21:16:52.402Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:16:56.789Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:17:01.184Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:17:06.022Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:17:08.475Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:17:10.901Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:17:13.326Z] RMSE (validation) = 0.9275717388537592 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:17:15.753Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:17:15.753Z] 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.
[2024-09-05T21:17:15.753Z] The best model improves the baseline by 14.43%.
[2024-09-05T21:17:15.753Z] Movies recommended for you:
[2024-09-05T21:17:15.753Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:17:15.753Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:17:15.753Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (27494.599 ms) ======
[2024-09-05T21:17:15.753Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-09-05T21:17:15.753Z] GC before operation: completed in 302.454 ms, heap usage 345.749 MB -> 62.711 MB.
[2024-09-05T21:17:20.131Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:17:24.511Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:17:28.893Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:17:33.284Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:17:35.714Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:17:38.136Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:17:40.556Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:17:42.976Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:17:43.730Z] 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.
[2024-09-05T21:17:43.730Z] The best model improves the baseline by 14.43%.
[2024-09-05T21:17:43.731Z] Movies recommended for you:
[2024-09-05T21:17:43.731Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:17:43.731Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:17:43.731Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (27504.657 ms) ======
[2024-09-05T21:17:43.731Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-09-05T21:17:43.731Z] GC before operation: completed in 195.644 ms, heap usage 230.873 MB -> 54.441 MB.
[2024-09-05T21:17:48.112Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:17:52.488Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:17:56.871Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:18:01.252Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:18:03.675Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:18:06.096Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:18:08.550Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:18:11.925Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:18:11.925Z] 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.
[2024-09-05T21:18:11.925Z] The best model improves the baseline by 14.43%.
[2024-09-05T21:18:11.925Z] Movies recommended for you:
[2024-09-05T21:18:11.925Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:18:11.925Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:18:11.925Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (28087.950 ms) ======
[2024-09-05T21:18:11.925Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-09-05T21:18:11.925Z] GC before operation: completed in 185.627 ms, heap usage 125.640 MB -> 47.089 MB.
[2024-09-05T21:18:16.325Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:18:20.699Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:18:25.080Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:18:29.477Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:18:31.921Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:18:34.364Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:18:36.790Z] RMSE (validation) = 0.9275717388537592 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:18:39.381Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:18:39.381Z] 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.
[2024-09-05T21:18:39.381Z] The best model improves the baseline by 14.43%.
[2024-09-05T21:18:39.381Z] Movies recommended for you:
[2024-09-05T21:18:39.381Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:18:39.381Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:18:39.381Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (27591.160 ms) ======
[2024-09-05T21:18:39.381Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-09-05T21:18:40.132Z] GC before operation: completed in 253.886 ms, heap usage 335.726 MB -> 74.888 MB.
[2024-09-05T21:18:44.525Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:18:48.949Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:18:53.322Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:18:57.695Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:19:00.116Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:19:02.548Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:19:04.992Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:19:07.424Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:19:07.424Z] 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.
[2024-09-05T21:19:07.424Z] The best model improves the baseline by 14.43%.
[2024-09-05T21:19:08.184Z] Movies recommended for you:
[2024-09-05T21:19:08.184Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:19:08.184Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:19:08.184Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (27886.410 ms) ======
[2024-09-05T21:19:08.184Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-09-05T21:19:08.184Z] GC before operation: completed in 194.290 ms, heap usage 357.630 MB -> 47.600 MB.
[2024-09-05T21:19:12.559Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:19:16.949Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:19:21.335Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:19:25.897Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:19:27.465Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:19:30.820Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:19:33.247Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:19:35.668Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:19:35.668Z] 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.
[2024-09-05T21:19:35.668Z] The best model improves the baseline by 14.43%.
[2024-09-05T21:19:35.668Z] Movies recommended for you:
[2024-09-05T21:19:35.668Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:19:35.668Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:19:35.668Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (27724.136 ms) ======
[2024-09-05T21:19:35.668Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-09-05T21:19:35.668Z] GC before operation: completed in 202.011 ms, heap usage 222.206 MB -> 74.287 MB.
[2024-09-05T21:19:41.177Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:19:44.554Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:19:50.069Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:19:53.421Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:19:55.835Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:19:59.220Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:20:01.655Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:20:04.087Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:20:04.087Z] 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.
[2024-09-05T21:20:04.087Z] The best model improves the baseline by 14.43%.
[2024-09-05T21:20:04.087Z] Movies recommended for you:
[2024-09-05T21:20:04.087Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:20:04.087Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:20:04.087Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (28259.318 ms) ======
[2024-09-05T21:20:04.087Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-09-05T21:20:04.087Z] GC before operation: completed in 234.682 ms, heap usage 274.623 MB -> 55.435 MB.
[2024-09-05T21:20:08.470Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:20:12.842Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:20:17.221Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:20:21.615Z] RMSE (validation) = 1.0045407704488025 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:20:24.056Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:20:26.480Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:20:28.913Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:20:31.336Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:20:32.088Z] 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.
[2024-09-05T21:20:32.088Z] The best model improves the baseline by 14.43%.
[2024-09-05T21:20:32.088Z] Movies recommended for you:
[2024-09-05T21:20:32.088Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:20:32.088Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:20:32.088Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (27540.650 ms) ======
[2024-09-05T21:20:32.088Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-09-05T21:20:32.088Z] GC before operation: completed in 274.164 ms, heap usage 180.928 MB -> 74.326 MB.
[2024-09-05T21:20:36.569Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:20:40.956Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:20:45.330Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:20:49.720Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:20:52.137Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:20:54.593Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:20:57.008Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:20:59.470Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:20:59.471Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-09-05T21:20:59.471Z] The best model improves the baseline by 14.43%.
[2024-09-05T21:21:00.224Z] Movies recommended for you:
[2024-09-05T21:21:00.224Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:21:00.224Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:21:00.224Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (27681.810 ms) ======
[2024-09-05T21:21:00.224Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-09-05T21:21:00.224Z] GC before operation: completed in 278.459 ms, heap usage 502.289 MB -> 75.041 MB.
[2024-09-05T21:21:04.609Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:21:08.991Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:21:13.373Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:21:17.792Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:21:20.208Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:21:22.623Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:21:25.083Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:21:27.532Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:21:27.532Z] 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.
[2024-09-05T21:21:27.532Z] The best model improves the baseline by 14.43%.
[2024-09-05T21:21:27.532Z] Movies recommended for you:
[2024-09-05T21:21:27.532Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:21:27.532Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:21:27.532Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (27624.035 ms) ======
[2024-09-05T21:21:27.532Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-09-05T21:21:28.283Z] GC before operation: completed in 217.143 ms, heap usage 403.489 MB -> 74.756 MB.
[2024-09-05T21:21:32.657Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:21:37.059Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:21:41.437Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:21:45.993Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:21:48.411Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:21:50.826Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:21:53.247Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:21:55.661Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:21:55.661Z] 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.
[2024-09-05T21:21:55.661Z] The best model improves the baseline by 14.43%.
[2024-09-05T21:21:56.412Z] Movies recommended for you:
[2024-09-05T21:21:56.412Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:21:56.412Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:21:56.412Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (28085.981 ms) ======
[2024-09-05T21:21:57.966Z] -----------------------------------
[2024-09-05T21:21:57.966Z] renaissance-movie-lens_0_PASSED
[2024-09-05T21:21:57.966Z] -----------------------------------
[2024-09-05T21:21:57.966Z]
[2024-09-05T21:21:57.966Z] TEST TEARDOWN:
[2024-09-05T21:21:57.966Z] Nothing to be done for teardown.
[2024-09-05T21:21:57.966Z] renaissance-movie-lens_0 Finish Time: Thu Sep 5 21:21:57 2024 Epoch Time (ms): 1725571317672