renaissance-movie-lens_0
[2024-08-16T16:09:15.482Z] Running test renaissance-movie-lens_0 ...
[2024-08-16T16:09:15.482Z] ===============================================
[2024-08-16T16:09:15.482Z] renaissance-movie-lens_0 Start Time: Fri Aug 16 12:09:14 2024 Epoch Time (ms): 1723824554824
[2024-08-16T16:09:15.482Z] variation: NoOptions
[2024-08-16T16:09:15.482Z] JVM_OPTIONS:
[2024-08-16T16:09:15.482Z] { \
[2024-08-16T16:09:15.482Z] echo ""; echo "TEST SETUP:"; \
[2024-08-16T16:09:15.482Z] echo "Nothing to be done for setup."; \
[2024-08-16T16:09:15.482Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../TKG/output_17238242051455/renaissance-movie-lens_0"; \
[2024-08-16T16:09:15.482Z] cd "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../TKG/output_17238242051455/renaissance-movie-lens_0"; \
[2024-08-16T16:09:15.482Z] echo ""; echo "TESTING:"; \
[2024-08-16T16:09:15.482Z] "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac_testList_0/jdkbinary/j2sdk-image/Contents/Home/bin/..//bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../TKG/output_17238242051455/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-16T16:09:15.482Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../TKG/output_17238242051455/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-16T16:09:15.482Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-16T16:09:15.482Z] echo "Nothing to be done for teardown."; \
[2024-08-16T16:09:15.482Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../TKG/output_17238242051455/TestTargetResult";
[2024-08-16T16:09:15.482Z]
[2024-08-16T16:09:15.482Z] TEST SETUP:
[2024-08-16T16:09:15.482Z] Nothing to be done for setup.
[2024-08-16T16:09:15.482Z]
[2024-08-16T16:09:15.482Z] TESTING:
[2024-08-16T16:09:16.694Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-16T16:09:17.448Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2024-08-16T16:09:19.216Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-16T16:09:19.216Z] Training: 60056, validation: 20285, test: 19854
[2024-08-16T16:09:19.216Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-16T16:09:19.216Z] GC before operation: completed in 26.411 ms, heap usage 85.383 MB -> 36.576 MB.
[2024-08-16T16:09:22.343Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:09:23.562Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:09:25.310Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:09:26.527Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:09:27.300Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:09:28.054Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:09:28.813Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:09:29.595Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:09:29.946Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T16:09:29.946Z] The best model improves the baseline by 14.52%.
[2024-08-16T16:09:29.946Z] Movies recommended for you:
[2024-08-16T16:09:29.946Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:09:29.946Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:09:29.946Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (10780.116 ms) ======
[2024-08-16T16:09:29.946Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-16T16:09:29.946Z] GC before operation: completed in 42.607 ms, heap usage 359.663 MB -> 51.759 MB.
[2024-08-16T16:09:31.175Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:09:32.406Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:09:34.175Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:09:34.960Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:09:35.735Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:09:36.487Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:09:37.250Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:09:38.013Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:09:38.013Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T16:09:38.013Z] The best model improves the baseline by 14.52%.
[2024-08-16T16:09:38.013Z] Movies recommended for you:
[2024-08-16T16:09:38.013Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:09:38.013Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:09:38.013Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (8239.822 ms) ======
[2024-08-16T16:09:38.013Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-16T16:09:38.365Z] GC before operation: completed in 40.009 ms, heap usage 110.410 MB -> 48.877 MB.
[2024-08-16T16:09:39.592Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:09:40.807Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:09:42.049Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:09:43.618Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:09:43.972Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:09:45.191Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:09:45.952Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:09:46.718Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:09:46.718Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T16:09:46.718Z] The best model improves the baseline by 14.52%.
[2024-08-16T16:09:46.718Z] Movies recommended for you:
[2024-08-16T16:09:46.718Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:09:46.718Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:09:46.718Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (8621.038 ms) ======
[2024-08-16T16:09:46.718Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-16T16:09:46.718Z] GC before operation: completed in 38.618 ms, heap usage 158.135 MB -> 49.203 MB.
[2024-08-16T16:09:47.943Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:09:49.270Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:09:50.516Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:09:51.742Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:09:52.496Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:09:53.253Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:09:54.022Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:09:54.806Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:09:54.806Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T16:09:54.806Z] The best model improves the baseline by 14.52%.
[2024-08-16T16:09:55.160Z] Movies recommended for you:
[2024-08-16T16:09:55.160Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:09:55.160Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:09:55.160Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (8143.671 ms) ======
[2024-08-16T16:09:55.161Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-16T16:09:55.161Z] GC before operation: completed in 52.614 ms, heap usage 234.848 MB -> 49.589 MB.
[2024-08-16T16:09:56.387Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:09:57.610Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:09:58.844Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:10:00.613Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:10:00.978Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:10:01.787Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:10:02.563Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:10:03.346Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:10:03.346Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T16:10:03.346Z] The best model improves the baseline by 14.52%.
[2024-08-16T16:10:03.346Z] Movies recommended for you:
[2024-08-16T16:10:03.346Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:10:03.346Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:10:03.346Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (8414.437 ms) ======
[2024-08-16T16:10:03.346Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-16T16:10:03.346Z] GC before operation: completed in 46.253 ms, heap usage 163.944 MB -> 49.730 MB.
[2024-08-16T16:10:05.145Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:10:05.907Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:10:07.128Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:10:08.374Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:10:09.149Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:10:09.919Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:10:10.731Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:10:11.481Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:10:11.481Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T16:10:11.481Z] The best model improves the baseline by 14.52%.
[2024-08-16T16:10:11.481Z] Movies recommended for you:
[2024-08-16T16:10:11.481Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:10:11.481Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:10:11.481Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (8114.051 ms) ======
[2024-08-16T16:10:11.481Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-16T16:10:11.833Z] GC before operation: completed in 39.484 ms, heap usage 159.618 MB -> 49.624 MB.
[2024-08-16T16:10:13.051Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:10:14.270Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:10:15.641Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:10:16.412Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:10:17.181Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:10:17.945Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:10:18.731Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:10:19.496Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:10:19.845Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T16:10:19.845Z] The best model improves the baseline by 14.52%.
[2024-08-16T16:10:19.845Z] Movies recommended for you:
[2024-08-16T16:10:19.845Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:10:19.845Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:10:19.845Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (8068.675 ms) ======
[2024-08-16T16:10:19.845Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-16T16:10:19.845Z] GC before operation: completed in 40.703 ms, heap usage 192.093 MB -> 49.771 MB.
[2024-08-16T16:10:21.092Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:10:22.324Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:10:24.078Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:10:25.343Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:10:26.592Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:10:26.944Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:10:28.237Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:10:29.064Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:10:29.064Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T16:10:29.064Z] The best model improves the baseline by 14.52%.
[2024-08-16T16:10:29.064Z] Movies recommended for you:
[2024-08-16T16:10:29.064Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:10:29.064Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:10:29.064Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (9340.405 ms) ======
[2024-08-16T16:10:29.064Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-16T16:10:29.064Z] GC before operation: completed in 60.511 ms, heap usage 81.247 MB -> 50.113 MB.
[2024-08-16T16:10:30.894Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:10:32.119Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:10:33.902Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:10:35.134Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:10:36.370Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:10:37.125Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:10:38.367Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:10:39.136Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:10:39.496Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T16:10:39.496Z] The best model improves the baseline by 14.52%.
[2024-08-16T16:10:39.496Z] Movies recommended for you:
[2024-08-16T16:10:39.496Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:10:39.496Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:10:39.496Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (10220.641 ms) ======
[2024-08-16T16:10:39.496Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-16T16:10:39.496Z] GC before operation: completed in 54.454 ms, heap usage 129.941 MB -> 49.818 MB.
[2024-08-16T16:10:40.740Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:10:42.503Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:10:43.758Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:10:45.516Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:10:46.275Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:10:47.102Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:10:48.334Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:10:49.155Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:10:49.155Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T16:10:49.155Z] The best model improves the baseline by 14.52%.
[2024-08-16T16:10:49.155Z] Movies recommended for you:
[2024-08-16T16:10:49.155Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:10:49.155Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:10:49.155Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (9788.307 ms) ======
[2024-08-16T16:10:49.155Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-16T16:10:49.155Z] GC before operation: completed in 49.310 ms, heap usage 257.195 MB -> 50.033 MB.
[2024-08-16T16:10:51.109Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:10:52.395Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:10:54.161Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:10:55.480Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:10:56.722Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:10:57.498Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:10:58.864Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:10:59.648Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:10:59.648Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T16:10:59.648Z] The best model improves the baseline by 14.52%.
[2024-08-16T16:10:59.648Z] Movies recommended for you:
[2024-08-16T16:10:59.648Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:10:59.648Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:10:59.648Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (10487.847 ms) ======
[2024-08-16T16:10:59.648Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-16T16:10:59.999Z] GC before operation: completed in 56.750 ms, heap usage 139.403 MB -> 49.672 MB.
[2024-08-16T16:11:01.234Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:11:03.018Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:11:04.294Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:11:05.531Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:11:06.290Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:11:07.550Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:11:08.324Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:11:09.211Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:11:09.211Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T16:11:09.211Z] The best model improves the baseline by 14.52%.
[2024-08-16T16:11:09.211Z] Movies recommended for you:
[2024-08-16T16:11:09.211Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:11:09.211Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:11:09.211Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (9445.997 ms) ======
[2024-08-16T16:11:09.211Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-16T16:11:09.211Z] GC before operation: completed in 57.496 ms, heap usage 77.341 MB -> 52.613 MB.
[2024-08-16T16:11:11.009Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:11:12.345Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:11:13.605Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:11:15.368Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:11:16.152Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:11:16.920Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:11:17.676Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:11:18.438Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:11:18.810Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T16:11:18.810Z] The best model improves the baseline by 14.52%.
[2024-08-16T16:11:18.810Z] Movies recommended for you:
[2024-08-16T16:11:18.810Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:11:18.810Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:11:18.810Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (9423.029 ms) ======
[2024-08-16T16:11:18.810Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-16T16:11:18.810Z] GC before operation: completed in 50.114 ms, heap usage 121.149 MB -> 50.099 MB.
[2024-08-16T16:11:20.573Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:11:21.860Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:11:23.652Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:11:25.043Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:11:25.403Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:11:26.639Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:11:27.390Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:11:28.156Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:11:28.157Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T16:11:28.157Z] The best model improves the baseline by 14.52%.
[2024-08-16T16:11:28.508Z] Movies recommended for you:
[2024-08-16T16:11:28.508Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:11:28.508Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:11:28.508Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (9542.807 ms) ======
[2024-08-16T16:11:28.508Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-16T16:11:28.508Z] GC before operation: completed in 61.691 ms, heap usage 190.271 MB -> 49.917 MB.
[2024-08-16T16:11:29.809Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:11:31.034Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:11:32.270Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:11:33.516Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:11:34.285Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:11:35.037Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:11:35.788Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:11:37.005Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:11:37.005Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T16:11:37.005Z] The best model improves the baseline by 14.52%.
[2024-08-16T16:11:37.005Z] Movies recommended for you:
[2024-08-16T16:11:37.005Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:11:37.005Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:11:37.006Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (8602.333 ms) ======
[2024-08-16T16:11:37.006Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-16T16:11:37.006Z] GC before operation: completed in 63.783 ms, heap usage 319.492 MB -> 50.230 MB.
[2024-08-16T16:11:38.383Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:11:40.139Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:11:41.375Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:11:43.133Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:11:43.885Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:11:44.637Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:11:45.859Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:11:46.647Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:11:46.647Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T16:11:46.647Z] The best model improves the baseline by 14.52%.
[2024-08-16T16:11:47.000Z] Movies recommended for you:
[2024-08-16T16:11:47.000Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:11:47.000Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:11:47.000Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (9763.624 ms) ======
[2024-08-16T16:11:47.000Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-16T16:11:47.000Z] GC before operation: completed in 61.807 ms, heap usage 228.336 MB -> 50.210 MB.
[2024-08-16T16:11:48.778Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:11:50.013Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:11:51.259Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:11:52.475Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:11:53.722Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:11:54.475Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:11:55.257Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:11:56.042Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:11:56.408Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T16:11:56.408Z] The best model improves the baseline by 14.52%.
[2024-08-16T16:11:56.408Z] Movies recommended for you:
[2024-08-16T16:11:56.408Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:11:56.408Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:11:56.408Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (9455.719 ms) ======
[2024-08-16T16:11:56.408Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-16T16:11:56.408Z] GC before operation: completed in 50.691 ms, heap usage 252.310 MB -> 50.051 MB.
[2024-08-16T16:11:58.186Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:11:59.491Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:12:01.271Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:12:02.506Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:12:03.281Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:12:04.529Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:12:05.326Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:12:06.086Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:12:06.087Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T16:12:06.087Z] The best model improves the baseline by 14.52%.
[2024-08-16T16:12:06.087Z] Movies recommended for you:
[2024-08-16T16:12:06.087Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:12:06.087Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:12:06.087Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (9748.399 ms) ======
[2024-08-16T16:12:06.087Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-16T16:12:06.087Z] GC before operation: completed in 43.745 ms, heap usage 200.625 MB -> 50.057 MB.
[2024-08-16T16:12:07.910Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:12:09.141Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:12:10.918Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:12:12.278Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:12:13.499Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:12:14.280Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:12:15.062Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:12:16.303Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:12:16.303Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T16:12:16.303Z] The best model improves the baseline by 14.52%.
[2024-08-16T16:12:16.303Z] Movies recommended for you:
[2024-08-16T16:12:16.303Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:12:16.303Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:12:16.303Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (10122.692 ms) ======
[2024-08-16T16:12:16.303Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-16T16:12:16.303Z] GC before operation: completed in 45.014 ms, heap usage 189.599 MB -> 50.223 MB.
[2024-08-16T16:12:17.533Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T16:12:19.342Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T16:12:20.238Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T16:12:21.470Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T16:12:22.697Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T16:12:23.478Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T16:12:24.230Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T16:12:24.978Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T16:12:24.978Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-16T16:12:24.978Z] The best model improves the baseline by 14.52%.
[2024-08-16T16:12:24.978Z] Movies recommended for you:
[2024-08-16T16:12:24.978Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T16:12:24.978Z] There is no way to check that no silent failure occurred.
[2024-08-16T16:12:24.978Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (8731.537 ms) ======
[2024-08-16T16:12:25.338Z] -----------------------------------
[2024-08-16T16:12:25.338Z] renaissance-movie-lens_0_PASSED
[2024-08-16T16:12:25.338Z] -----------------------------------
[2024-08-16T16:12:25.338Z]
[2024-08-16T16:12:25.338Z] TEST TEARDOWN:
[2024-08-16T16:12:25.338Z] Nothing to be done for teardown.
[2024-08-16T16:12:25.338Z] renaissance-movie-lens_0 Finish Time: Fri Aug 16 12:12:25 2024 Epoch Time (ms): 1723824745058