renaissance-movie-lens_0
[2025-01-07T23:05:21.742Z] Running test renaissance-movie-lens_0 ...
[2025-01-07T23:05:21.742Z] ===============================================
[2025-01-07T23:05:21.742Z] renaissance-movie-lens_0 Start Time: Tue Jan 7 23:05:18 2025 Epoch Time (ms): 1736291118806
[2025-01-07T23:05:21.742Z] variation: NoOptions
[2025-01-07T23:05:21.742Z] JVM_OPTIONS:
[2025-01-07T23:05:21.742Z] { \
[2025-01-07T23:05:21.742Z] echo ""; echo "TEST SETUP:"; \
[2025-01-07T23:05:21.742Z] echo "Nothing to be done for setup."; \
[2025-01-07T23:05:21.742Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17362860363845/renaissance-movie-lens_0"; \
[2025-01-07T23:05:21.742Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17362860363845/renaissance-movie-lens_0"; \
[2025-01-07T23:05:21.742Z] echo ""; echo "TESTING:"; \
[2025-01-07T23:05:21.742Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/jdkbinary/j2sdk-image/bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17362860363845/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-01-07T23:05:21.742Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17362860363845/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-01-07T23:05:21.742Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-01-07T23:05:21.742Z] echo "Nothing to be done for teardown."; \
[2025-01-07T23:05:21.742Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17362860363845/TestTargetResult";
[2025-01-07T23:05:21.742Z]
[2025-01-07T23:05:21.742Z] TEST SETUP:
[2025-01-07T23:05:21.742Z] Nothing to be done for setup.
[2025-01-07T23:05:21.742Z]
[2025-01-07T23:05:21.742Z] TESTING:
[2025-01-07T23:05:31.559Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-01-07T23:05:43.255Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-01-07T23:06:05.800Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-01-07T23:06:06.708Z] Training: 60056, validation: 20285, test: 19854
[2025-01-07T23:06:06.708Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-01-07T23:06:07.476Z] GC before operation: completed in 1081.395 ms, heap usage 36.523 MB -> 27.186 MB.
[2025-01-07T23:06:43.094Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-07T23:06:54.920Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-07T23:07:08.888Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-07T23:07:22.594Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-07T23:07:29.523Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-07T23:07:37.057Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-07T23:07:46.916Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-07T23:07:56.759Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-07T23:07:58.331Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-01-07T23:07:58.331Z] The best model improves the baseline by 14.52%.
[2025-01-07T23:07:59.107Z] Movies recommended for you:
[2025-01-07T23:07:59.107Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-07T23:07:59.107Z] There is no way to check that no silent failure occurred.
[2025-01-07T23:07:59.107Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (111977.902 ms) ======
[2025-01-07T23:07:59.107Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-01-07T23:08:01.628Z] GC before operation: completed in 2494.133 ms, heap usage 393.927 MB -> 49.394 MB.
[2025-01-07T23:08:15.522Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-07T23:08:29.427Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-07T23:08:43.239Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-07T23:08:54.914Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-07T23:09:03.235Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-07T23:09:10.083Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-07T23:09:21.939Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-07T23:09:30.831Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-07T23:09:32.419Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-01-07T23:09:32.419Z] The best model improves the baseline by 14.52%.
[2025-01-07T23:09:33.179Z] Movies recommended for you:
[2025-01-07T23:09:33.180Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-07T23:09:33.180Z] There is no way to check that no silent failure occurred.
[2025-01-07T23:09:33.180Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (91055.819 ms) ======
[2025-01-07T23:09:33.180Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-01-07T23:09:33.938Z] GC before operation: completed in 1302.693 ms, heap usage 311.897 MB -> 42.327 MB.
[2025-01-07T23:09:47.738Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-07T23:09:59.416Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-07T23:10:13.176Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-07T23:10:25.053Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-07T23:10:33.494Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-07T23:10:42.017Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-07T23:10:52.117Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-07T23:10:59.098Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-07T23:11:00.691Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-01-07T23:11:00.691Z] The best model improves the baseline by 14.52%.
[2025-01-07T23:11:01.458Z] Movies recommended for you:
[2025-01-07T23:11:01.458Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-07T23:11:01.458Z] There is no way to check that no silent failure occurred.
[2025-01-07T23:11:01.459Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (86935.367 ms) ======
[2025-01-07T23:11:01.459Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-01-07T23:11:02.237Z] GC before operation: completed in 1165.244 ms, heap usage 533.814 MB -> 48.330 MB.
[2025-01-07T23:11:16.602Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-07T23:11:32.726Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-07T23:11:48.955Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-07T23:12:05.049Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-07T23:12:14.955Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-07T23:12:24.926Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-07T23:12:34.916Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-07T23:12:43.370Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-07T23:12:45.000Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-01-07T23:12:45.000Z] The best model improves the baseline by 14.52%.
[2025-01-07T23:12:45.794Z] Movies recommended for you:
[2025-01-07T23:12:45.794Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-07T23:12:45.794Z] There is no way to check that no silent failure occurred.
[2025-01-07T23:12:45.794Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (103364.859 ms) ======
[2025-01-07T23:12:45.794Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-01-07T23:12:46.575Z] GC before operation: completed in 806.311 ms, heap usage 485.140 MB -> 46.813 MB.
[2025-01-07T23:12:58.360Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-07T23:13:12.744Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-07T23:13:26.724Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-07T23:13:40.433Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-07T23:13:47.281Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-07T23:13:57.241Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-07T23:14:05.795Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-07T23:14:14.238Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-07T23:14:15.051Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-01-07T23:14:15.051Z] The best model improves the baseline by 14.52%.
[2025-01-07T23:14:15.826Z] Movies recommended for you:
[2025-01-07T23:14:15.826Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-07T23:14:15.826Z] There is no way to check that no silent failure occurred.
[2025-01-07T23:14:15.826Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (89174.738 ms) ======
[2025-01-07T23:14:15.826Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-01-07T23:14:16.614Z] GC before operation: completed in 708.445 ms, heap usage 403.653 MB -> 46.946 MB.
[2025-01-07T23:14:30.503Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-07T23:14:44.396Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-07T23:14:58.861Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-07T23:15:12.815Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-07T23:15:19.792Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-07T23:15:28.245Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-07T23:15:36.719Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-07T23:15:45.071Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-07T23:15:45.850Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-01-07T23:15:46.622Z] The best model improves the baseline by 14.52%.
[2025-01-07T23:15:46.622Z] Movies recommended for you:
[2025-01-07T23:15:46.622Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-07T23:15:46.622Z] There is no way to check that no silent failure occurred.
[2025-01-07T23:15:46.622Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (90266.961 ms) ======
[2025-01-07T23:15:46.622Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-01-07T23:15:48.218Z] GC before operation: completed in 1196.103 ms, heap usage 421.949 MB -> 46.840 MB.
[2025-01-07T23:15:59.918Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-07T23:16:11.866Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-07T23:16:25.773Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-07T23:16:36.456Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-07T23:16:43.403Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-07T23:16:50.305Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-07T23:16:57.296Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-07T23:17:04.284Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-07T23:17:06.796Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-01-07T23:17:06.796Z] The best model improves the baseline by 14.52%.
[2025-01-07T23:17:06.796Z] Movies recommended for you:
[2025-01-07T23:17:06.796Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-07T23:17:06.796Z] There is no way to check that no silent failure occurred.
[2025-01-07T23:17:06.796Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (78865.052 ms) ======
[2025-01-07T23:17:06.796Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-01-07T23:17:07.566Z] GC before operation: completed in 979.701 ms, heap usage 482.661 MB -> 52.754 MB.
[2025-01-07T23:17:19.450Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-07T23:17:33.377Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-07T23:17:47.385Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-07T23:17:59.238Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-07T23:18:06.268Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-07T23:18:13.866Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-07T23:18:22.366Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-07T23:18:29.394Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-07T23:18:31.017Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-01-07T23:18:31.017Z] The best model improves the baseline by 14.52%.
[2025-01-07T23:18:31.814Z] Movies recommended for you:
[2025-01-07T23:18:31.814Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-07T23:18:31.814Z] There is no way to check that no silent failure occurred.
[2025-01-07T23:18:31.814Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (84024.045 ms) ======
[2025-01-07T23:18:31.814Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-01-07T23:18:32.587Z] GC before operation: completed in 860.289 ms, heap usage 269.116 MB -> 43.655 MB.
[2025-01-07T23:18:46.393Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-07T23:19:00.153Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-07T23:19:13.993Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-07T23:19:23.983Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-07T23:19:32.399Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-07T23:19:39.232Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-07T23:19:47.503Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-07T23:19:55.767Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-07T23:19:56.531Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-01-07T23:19:56.531Z] The best model improves the baseline by 14.52%.
[2025-01-07T23:19:57.295Z] Movies recommended for you:
[2025-01-07T23:19:57.295Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-07T23:19:57.295Z] There is no way to check that no silent failure occurred.
[2025-01-07T23:19:57.295Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (84465.264 ms) ======
[2025-01-07T23:19:57.295Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-01-07T23:19:58.059Z] GC before operation: completed in 955.885 ms, heap usage 444.108 MB -> 47.172 MB.
[2025-01-07T23:20:10.281Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-07T23:20:22.189Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-07T23:20:36.183Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-07T23:20:48.054Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-07T23:20:55.099Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-07T23:21:04.436Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-07T23:21:11.620Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-07T23:21:19.998Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-07T23:21:21.598Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-01-07T23:21:21.598Z] The best model improves the baseline by 14.52%.
[2025-01-07T23:21:21.598Z] Movies recommended for you:
[2025-01-07T23:21:21.598Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-07T23:21:21.598Z] There is no way to check that no silent failure occurred.
[2025-01-07T23:21:21.598Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (83887.435 ms) ======
[2025-01-07T23:21:21.598Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-01-07T23:21:23.197Z] GC before operation: completed in 1216.681 ms, heap usage 396.262 MB -> 47.250 MB.
[2025-01-07T23:21:36.966Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-07T23:21:48.728Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-07T23:22:02.631Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-07T23:22:14.480Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-07T23:22:22.874Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-07T23:22:29.828Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-07T23:22:45.013Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-07T23:22:46.590Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-07T23:22:48.171Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-01-07T23:22:48.171Z] The best model improves the baseline by 14.52%.
[2025-01-07T23:22:48.949Z] Movies recommended for you:
[2025-01-07T23:22:48.949Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-07T23:22:48.949Z] There is no way to check that no silent failure occurred.
[2025-01-07T23:22:48.949Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (85436.931 ms) ======
[2025-01-07T23:22:48.949Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-01-07T23:22:49.738Z] GC before operation: completed in 809.888 ms, heap usage 410.304 MB -> 48.478 MB.
[2025-01-07T23:23:03.610Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-07T23:23:15.568Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-07T23:23:29.380Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-07T23:23:41.300Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-07T23:23:49.805Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-07T23:23:58.273Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-07T23:24:07.186Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-07T23:24:14.305Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-07T23:24:15.978Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-01-07T23:24:15.978Z] The best model improves the baseline by 14.52%.
[2025-01-07T23:24:16.750Z] Movies recommended for you:
[2025-01-07T23:24:16.750Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-07T23:24:16.750Z] There is no way to check that no silent failure occurred.
[2025-01-07T23:24:16.750Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (86995.708 ms) ======
[2025-01-07T23:24:16.751Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-01-07T23:24:17.535Z] GC before operation: completed in 810.607 ms, heap usage 404.067 MB -> 47.288 MB.
[2025-01-07T23:24:29.375Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-07T23:24:43.435Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-07T23:24:55.424Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-07T23:25:07.384Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-07T23:25:15.789Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-07T23:25:22.767Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-07T23:25:32.817Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-07T23:25:41.793Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-07T23:25:44.262Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-01-07T23:25:44.262Z] The best model improves the baseline by 14.52%.
[2025-01-07T23:25:44.262Z] Movies recommended for you:
[2025-01-07T23:25:44.262Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-07T23:25:44.262Z] There is no way to check that no silent failure occurred.
[2025-01-07T23:25:44.262Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (87389.738 ms) ======
[2025-01-07T23:25:44.262Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-01-07T23:25:45.876Z] GC before operation: completed in 937.218 ms, heap usage 433.723 MB -> 48.854 MB.
[2025-01-07T23:25:59.786Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-07T23:26:13.726Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-07T23:26:29.741Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-07T23:26:41.630Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-07T23:26:51.748Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-07T23:27:00.291Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-07T23:27:08.758Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-07T23:27:17.186Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-07T23:27:18.777Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-01-07T23:27:18.777Z] The best model improves the baseline by 14.52%.
[2025-01-07T23:27:19.570Z] Movies recommended for you:
[2025-01-07T23:27:19.570Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-07T23:27:19.570Z] There is no way to check that no silent failure occurred.
[2025-01-07T23:27:19.570Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (93671.579 ms) ======
[2025-01-07T23:27:19.570Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-01-07T23:27:20.342Z] GC before operation: completed in 872.415 ms, heap usage 391.083 MB -> 47.032 MB.
[2025-01-07T23:27:32.035Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-07T23:27:45.938Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-07T23:27:57.949Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-07T23:28:07.858Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-07T23:28:16.245Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-07T23:28:23.770Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-07T23:28:29.528Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-07T23:28:38.031Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-07T23:28:39.694Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-01-07T23:28:39.694Z] The best model improves the baseline by 14.52%.
[2025-01-07T23:28:39.694Z] Movies recommended for you:
[2025-01-07T23:28:39.694Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-07T23:28:39.694Z] There is no way to check that no silent failure occurred.
[2025-01-07T23:28:39.694Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (79789.949 ms) ======
[2025-01-07T23:28:39.694Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-01-07T23:28:40.491Z] GC before operation: completed in 607.778 ms, heap usage 404.435 MB -> 47.256 MB.
[2025-01-07T23:28:52.364Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-07T23:29:04.409Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-07T23:29:16.278Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-07T23:29:28.247Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-07T23:29:35.261Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-07T23:29:42.260Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-07T23:29:49.781Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-07T23:29:56.759Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-07T23:29:57.558Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-01-07T23:29:58.329Z] The best model improves the baseline by 14.52%.
[2025-01-07T23:29:58.329Z] Movies recommended for you:
[2025-01-07T23:29:58.329Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-07T23:29:58.329Z] There is no way to check that no silent failure occurred.
[2025-01-07T23:29:58.329Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (77915.307 ms) ======
[2025-01-07T23:29:58.329Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-01-07T23:29:59.953Z] GC before operation: completed in 1076.112 ms, heap usage 393.496 MB -> 47.347 MB.
[2025-01-07T23:30:11.793Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-07T23:30:21.887Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-07T23:30:35.805Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-07T23:30:47.609Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-07T23:30:53.357Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-07T23:30:59.037Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-07T23:31:06.154Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-07T23:31:11.956Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-07T23:31:12.743Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-01-07T23:31:13.550Z] The best model improves the baseline by 14.52%.
[2025-01-07T23:31:13.550Z] Movies recommended for you:
[2025-01-07T23:31:13.550Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-07T23:31:13.550Z] There is no way to check that no silent failure occurred.
[2025-01-07T23:31:13.550Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (74030.040 ms) ======
[2025-01-07T23:31:13.550Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-01-07T23:31:15.149Z] GC before operation: completed in 1422.329 ms, heap usage 409.861 MB -> 44.052 MB.
[2025-01-07T23:31:25.203Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-07T23:31:37.031Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-07T23:31:48.813Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-07T23:31:58.849Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-07T23:32:07.267Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-07T23:32:14.231Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-07T23:32:24.434Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-07T23:32:33.179Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-07T23:32:33.964Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-01-07T23:32:33.964Z] The best model improves the baseline by 14.52%.
[2025-01-07T23:32:34.733Z] Movies recommended for you:
[2025-01-07T23:32:34.733Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-07T23:32:34.733Z] There is no way to check that no silent failure occurred.
[2025-01-07T23:32:34.733Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (79389.109 ms) ======
[2025-01-07T23:32:34.733Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-01-07T23:32:36.346Z] GC before operation: completed in 1923.332 ms, heap usage 412.654 MB -> 44.006 MB.
[2025-01-07T23:32:50.186Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-07T23:33:02.014Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-07T23:33:16.053Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-07T23:33:29.857Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-07T23:33:38.208Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-07T23:33:46.455Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-07T23:33:56.869Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-07T23:34:03.949Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-07T23:34:06.441Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-01-07T23:34:06.441Z] The best model improves the baseline by 14.52%.
[2025-01-07T23:34:06.441Z] Movies recommended for you:
[2025-01-07T23:34:06.441Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-07T23:34:06.441Z] There is no way to check that no silent failure occurred.
[2025-01-07T23:34:06.441Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (90313.907 ms) ======
[2025-01-07T23:34:06.441Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-01-07T23:34:08.031Z] GC before operation: completed in 1579.459 ms, heap usage 400.906 MB -> 44.399 MB.
[2025-01-07T23:34:21.794Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-07T23:34:35.566Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-07T23:34:49.233Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-07T23:35:03.174Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-07T23:35:10.053Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-07T23:35:19.028Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-07T23:35:26.093Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-07T23:35:34.552Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-07T23:35:36.196Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-01-07T23:35:37.027Z] The best model improves the baseline by 14.52%.
[2025-01-07T23:35:37.831Z] Movies recommended for you:
[2025-01-07T23:35:37.831Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-07T23:35:37.831Z] There is no way to check that no silent failure occurred.
[2025-01-07T23:35:37.831Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (89261.661 ms) ======
[2025-01-07T23:35:41.346Z] -----------------------------------
[2025-01-07T23:35:41.346Z] renaissance-movie-lens_0_PASSED
[2025-01-07T23:35:41.346Z] -----------------------------------
[2025-01-07T23:35:41.346Z]
[2025-01-07T23:35:41.346Z] TEST TEARDOWN:
[2025-01-07T23:35:41.346Z] Nothing to be done for teardown.
[2025-01-07T23:35:41.346Z] renaissance-movie-lens_0 Finish Time: Tue Jan 7 23:35:40 2025 Epoch Time (ms): 1736292940471