renaissance-movie-lens_0
[2025-03-04T21:59:11.820Z] Running test renaissance-movie-lens_0 ...
[2025-03-04T21:59:12.601Z] ===============================================
[2025-03-04T21:59:12.601Z] renaissance-movie-lens_0 Start Time: Tue Mar 4 21:59:11 2025 Epoch Time (ms): 1741125551746
[2025-03-04T21:59:12.601Z] variation: NoOptions
[2025-03-04T21:59:12.601Z] JVM_OPTIONS:
[2025-03-04T21:59:12.601Z] { \
[2025-03-04T21:59:12.601Z] echo ""; echo "TEST SETUP:"; \
[2025-03-04T21:59:12.601Z] echo "Nothing to be done for setup."; \
[2025-03-04T21:59:12.601Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17411244387155/renaissance-movie-lens_0"; \
[2025-03-04T21:59:12.601Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17411244387155/renaissance-movie-lens_0"; \
[2025-03-04T21:59:12.601Z] echo ""; echo "TESTING:"; \
[2025-03-04T21:59:12.601Z] "/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_17411244387155/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-03-04T21:59:12.601Z] 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_17411244387155/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-03-04T21:59:12.601Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-03-04T21:59:12.601Z] echo "Nothing to be done for teardown."; \
[2025-03-04T21:59:12.601Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17411244387155/TestTargetResult";
[2025-03-04T21:59:12.601Z]
[2025-03-04T21:59:12.601Z] TEST SETUP:
[2025-03-04T21:59:12.601Z] Nothing to be done for setup.
[2025-03-04T21:59:12.601Z]
[2025-03-04T21:59:12.601Z] TESTING:
[2025-03-04T21:59:17.105Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-03-04T21:59:20.565Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 24) threads.
[2025-03-04T21:59:27.529Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-03-04T21:59:27.529Z] Training: 60056, validation: 20285, test: 19854
[2025-03-04T21:59:27.529Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-03-04T21:59:27.529Z] GC before operation: completed in 235.160 ms, heap usage 41.815 MB -> 25.960 MB.
[2025-03-04T21:59:35.900Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T21:59:41.554Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T21:59:47.237Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T21:59:50.791Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T21:59:54.260Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T21:59:56.764Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T21:59:59.256Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:00:02.734Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:00:02.734Z] 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.
[2025-03-04T22:00:02.735Z] The best model improves the baseline by 14.43%.
[2025-03-04T22:00:02.735Z] Movies recommended for you:
[2025-03-04T22:00:02.735Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:00:02.735Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:00:02.735Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (35192.345 ms) ======
[2025-03-04T22:00:02.735Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-03-04T22:00:03.527Z] GC before operation: completed in 347.107 ms, heap usage 131.160 MB -> 42.562 MB.
[2025-03-04T22:00:07.499Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:00:12.025Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:00:16.585Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:00:21.134Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:00:22.787Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:00:25.331Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:00:30.426Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:00:30.426Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:00:31.294Z] 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.
[2025-03-04T22:00:31.294Z] The best model improves the baseline by 14.43%.
[2025-03-04T22:00:31.294Z] Movies recommended for you:
[2025-03-04T22:00:31.294Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:00:31.294Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:00:31.294Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (27947.308 ms) ======
[2025-03-04T22:00:31.294Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-03-04T22:00:31.294Z] GC before operation: completed in 225.712 ms, heap usage 347.258 MB -> 50.099 MB.
[2025-03-04T22:00:35.855Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:00:39.333Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:00:44.066Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:00:48.580Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:00:51.109Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:00:52.720Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:00:55.213Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:00:57.713Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:00:58.495Z] 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.
[2025-03-04T22:00:58.495Z] The best model improves the baseline by 14.43%.
[2025-03-04T22:00:58.495Z] Movies recommended for you:
[2025-03-04T22:00:58.495Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:00:58.495Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:00:58.495Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (26935.961 ms) ======
[2025-03-04T22:00:58.495Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-03-04T22:00:58.495Z] GC before operation: completed in 209.610 ms, heap usage 331.042 MB -> 58.013 MB.
[2025-03-04T22:01:04.355Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:01:06.884Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:01:11.766Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:01:15.226Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:01:17.731Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:01:20.247Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:01:25.133Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:01:25.133Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:01:25.133Z] 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.
[2025-03-04T22:01:25.133Z] The best model improves the baseline by 14.43%.
[2025-03-04T22:01:25.133Z] Movies recommended for you:
[2025-03-04T22:01:25.133Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:01:25.133Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:01:25.133Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (26944.882 ms) ======
[2025-03-04T22:01:25.133Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-03-04T22:01:25.912Z] GC before operation: completed in 253.148 ms, heap usage 288.729 MB -> 51.017 MB.
[2025-03-04T22:01:29.406Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:01:33.956Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:01:38.459Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:01:42.975Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:01:44.588Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:01:49.224Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:01:50.001Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:01:52.503Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:01:52.503Z] 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.
[2025-03-04T22:01:52.503Z] The best model improves the baseline by 14.43%.
[2025-03-04T22:01:52.503Z] Movies recommended for you:
[2025-03-04T22:01:52.503Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:01:52.503Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:01:52.503Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (26987.987 ms) ======
[2025-03-04T22:01:52.503Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-03-04T22:01:53.280Z] GC before operation: completed in 237.105 ms, heap usage 407.235 MB -> 74.562 MB.
[2025-03-04T22:01:59.464Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:02:01.075Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:02:05.226Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:02:09.734Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:02:12.265Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:02:14.768Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:02:16.406Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:02:23.345Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:02:23.345Z] 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.
[2025-03-04T22:02:23.345Z] The best model improves the baseline by 14.43%.
[2025-03-04T22:02:23.345Z] Movies recommended for you:
[2025-03-04T22:02:23.345Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:02:23.345Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:02:23.345Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (26642.252 ms) ======
[2025-03-04T22:02:23.345Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-03-04T22:02:23.345Z] GC before operation: completed in 257.827 ms, heap usage 249.403 MB -> 54.669 MB.
[2025-03-04T22:02:28.240Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:02:29.057Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:02:32.604Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:02:37.117Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:02:39.713Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:02:41.327Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:02:44.028Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:02:46.539Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:02:46.539Z] 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.
[2025-03-04T22:02:46.539Z] The best model improves the baseline by 14.43%.
[2025-03-04T22:02:47.319Z] Movies recommended for you:
[2025-03-04T22:02:47.319Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:02:47.319Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:02:47.319Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (27110.649 ms) ======
[2025-03-04T22:02:47.319Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-03-04T22:02:47.319Z] GC before operation: completed in 228.302 ms, heap usage 410.241 MB -> 58.993 MB.
[2025-03-04T22:02:51.915Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:02:55.381Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:02:59.877Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:03:04.432Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:03:06.053Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:03:08.607Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:03:11.119Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:03:13.734Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:03:13.734Z] 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.
[2025-03-04T22:03:13.734Z] The best model improves the baseline by 14.43%.
[2025-03-04T22:03:14.617Z] Movies recommended for you:
[2025-03-04T22:03:14.617Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:03:14.617Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:03:14.617Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (27051.925 ms) ======
[2025-03-04T22:03:14.617Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-03-04T22:03:14.617Z] GC before operation: completed in 259.587 ms, heap usage 253.132 MB -> 54.950 MB.
[2025-03-04T22:03:19.130Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:03:22.612Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:03:27.197Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:03:31.740Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:03:33.348Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:03:35.847Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:03:38.346Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:03:40.850Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:03:40.850Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2025-03-04T22:03:40.850Z] The best model improves the baseline by 14.43%.
[2025-03-04T22:03:40.850Z] Movies recommended for you:
[2025-03-04T22:03:40.850Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:03:40.850Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:03:40.850Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (26578.677 ms) ======
[2025-03-04T22:03:40.850Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-03-04T22:03:41.630Z] GC before operation: completed in 184.518 ms, heap usage 161.406 MB -> 73.674 MB.
[2025-03-04T22:03:45.125Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:03:49.624Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:03:54.226Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:03:58.265Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:03:59.874Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:04:02.379Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:04:04.951Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:04:07.453Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:04:07.453Z] 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.
[2025-03-04T22:04:07.453Z] The best model improves the baseline by 14.43%.
[2025-03-04T22:04:08.231Z] Movies recommended for you:
[2025-03-04T22:04:08.231Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:04:08.231Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:04:08.231Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (26628.958 ms) ======
[2025-03-04T22:04:08.231Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-03-04T22:04:08.231Z] GC before operation: completed in 311.800 ms, heap usage 312.301 MB -> 51.708 MB.
[2025-03-04T22:04:12.757Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:04:16.219Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:04:20.728Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:04:25.236Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:04:26.844Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:04:29.358Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:04:31.906Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:04:34.455Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:04:34.455Z] 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.
[2025-03-04T22:04:34.455Z] The best model improves the baseline by 14.43%.
[2025-03-04T22:04:34.455Z] Movies recommended for you:
[2025-03-04T22:04:34.455Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:04:34.455Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:04:34.455Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (26436.553 ms) ======
[2025-03-04T22:04:34.455Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-03-04T22:04:35.247Z] GC before operation: completed in 213.842 ms, heap usage 288.101 MB -> 74.055 MB.
[2025-03-04T22:04:38.761Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:04:43.334Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:04:47.884Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:04:51.355Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:04:53.853Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:04:56.355Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:04:58.855Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:05:01.361Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:05:02.156Z] 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.
[2025-03-04T22:05:02.156Z] The best model improves the baseline by 14.43%.
[2025-03-04T22:05:02.156Z] Movies recommended for you:
[2025-03-04T22:05:02.156Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:05:02.156Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:05:02.156Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (27055.452 ms) ======
[2025-03-04T22:05:02.156Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-03-04T22:05:02.156Z] GC before operation: completed in 190.020 ms, heap usage 386.999 MB -> 47.701 MB.
[2025-03-04T22:05:06.674Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:05:10.320Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:05:14.853Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:05:18.333Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:05:20.834Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:05:23.365Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:05:25.907Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:05:28.412Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:05:28.412Z] 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.
[2025-03-04T22:05:28.412Z] The best model improves the baseline by 14.43%.
[2025-03-04T22:05:28.412Z] Movies recommended for you:
[2025-03-04T22:05:28.412Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:05:28.412Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:05:28.412Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (26541.144 ms) ======
[2025-03-04T22:05:28.412Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-03-04T22:05:29.191Z] GC before operation: completed in 224.845 ms, heap usage 237.098 MB -> 74.615 MB.
[2025-03-04T22:05:32.658Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:05:37.177Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:05:41.712Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:05:45.357Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:05:47.858Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:05:50.356Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:05:52.881Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:05:55.398Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:05:55.398Z] 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.
[2025-03-04T22:05:55.398Z] The best model improves the baseline by 14.43%.
[2025-03-04T22:05:55.398Z] Movies recommended for you:
[2025-03-04T22:05:55.398Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:05:55.398Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:05:55.398Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (26913.933 ms) ======
[2025-03-04T22:05:55.398Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-03-04T22:05:56.178Z] GC before operation: completed in 179.850 ms, heap usage 343.237 MB -> 51.322 MB.
[2025-03-04T22:06:00.705Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:06:04.204Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:06:08.831Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:06:12.294Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:06:14.823Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:06:17.326Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:06:19.847Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:06:24.092Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:06:24.092Z] 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.
[2025-03-04T22:06:24.092Z] The best model improves the baseline by 14.43%.
[2025-03-04T22:06:24.092Z] Movies recommended for you:
[2025-03-04T22:06:24.092Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:06:24.092Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:06:24.092Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (26525.301 ms) ======
[2025-03-04T22:06:24.092Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-03-04T22:06:24.092Z] GC before operation: completed in 216.336 ms, heap usage 347.231 MB -> 74.418 MB.
[2025-03-04T22:06:26.593Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:06:31.134Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:06:35.650Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:06:39.125Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:06:41.637Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:06:44.138Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:06:46.636Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:06:49.160Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:06:49.943Z] 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.
[2025-03-04T22:06:49.943Z] The best model improves the baseline by 14.43%.
[2025-03-04T22:06:49.943Z] Movies recommended for you:
[2025-03-04T22:06:49.943Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:06:49.943Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:06:49.943Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (27037.646 ms) ======
[2025-03-04T22:06:49.943Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-03-04T22:06:49.943Z] GC before operation: completed in 179.771 ms, heap usage 271.302 MB -> 55.129 MB.
[2025-03-04T22:06:54.506Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:06:58.015Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:07:02.570Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:07:07.085Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:07:09.593Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:07:11.205Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:07:14.663Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:07:16.287Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:07:17.065Z] 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.
[2025-03-04T22:07:17.065Z] The best model improves the baseline by 14.43%.
[2025-03-04T22:07:17.065Z] Movies recommended for you:
[2025-03-04T22:07:17.065Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:07:17.065Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:07:17.065Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (27065.539 ms) ======
[2025-03-04T22:07:17.065Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-03-04T22:07:17.065Z] GC before operation: completed in 164.802 ms, heap usage 391.845 MB -> 51.840 MB.
[2025-03-04T22:07:21.579Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:07:26.099Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:07:29.558Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:07:34.065Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:07:36.593Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:07:39.119Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:07:42.000Z] RMSE (validation) = 0.9275717388537592 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:07:47.309Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:07:47.309Z] 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.
[2025-03-04T22:07:47.309Z] The best model improves the baseline by 14.43%.
[2025-03-04T22:07:47.309Z] Movies recommended for you:
[2025-03-04T22:07:47.309Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:07:47.309Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:07:47.309Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (27214.148 ms) ======
[2025-03-04T22:07:47.309Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-03-04T22:07:47.309Z] GC before operation: completed in 203.592 ms, heap usage 214.132 MB -> 51.444 MB.
[2025-03-04T22:07:52.880Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:07:52.880Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:07:57.507Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:08:02.024Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:08:03.636Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:08:06.161Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:08:08.656Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:08:11.163Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:08:11.163Z] 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.
[2025-03-04T22:08:11.163Z] The best model improves the baseline by 14.43%.
[2025-03-04T22:08:11.943Z] Movies recommended for you:
[2025-03-04T22:08:11.943Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:08:11.943Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:08:11.943Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (27098.313 ms) ======
[2025-03-04T22:08:11.943Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-03-04T22:08:11.943Z] GC before operation: completed in 169.951 ms, heap usage 241.767 MB -> 48.633 MB.
[2025-03-04T22:08:16.460Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:08:19.936Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:08:24.467Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:08:28.975Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:08:31.473Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:08:33.082Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:08:35.604Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:08:38.106Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:08:38.885Z] 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.
[2025-03-04T22:08:38.885Z] The best model improves the baseline by 14.43%.
[2025-03-04T22:08:38.885Z] Movies recommended for you:
[2025-03-04T22:08:38.885Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:08:38.885Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:08:38.885Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (26835.154 ms) ======
[2025-03-04T22:08:40.495Z] -----------------------------------
[2025-03-04T22:08:40.495Z] renaissance-movie-lens_0_PASSED
[2025-03-04T22:08:40.495Z] -----------------------------------
[2025-03-04T22:08:40.495Z]
[2025-03-04T22:08:40.495Z] TEST TEARDOWN:
[2025-03-04T22:08:40.495Z] Nothing to be done for teardown.
[2025-03-04T22:08:40.495Z] renaissance-movie-lens_0 Finish Time: Tue Mar 4 22:08:40 2025 Epoch Time (ms): 1741126120065