renaissance-movie-lens_0
[2024-08-28T21:01:08.995Z] Running test renaissance-movie-lens_0 ...
[2024-08-28T21:01:08.995Z] ===============================================
[2024-08-28T21:01:08.995Z] renaissance-movie-lens_0 Start Time: Wed Aug 28 17:01:08 2024 Epoch Time (ms): 1724878868660
[2024-08-28T21:01:08.995Z] variation: NoOptions
[2024-08-28T21:01:08.995Z] JVM_OPTIONS:
[2024-08-28T21:01:08.995Z] { \
[2024-08-28T21:01:08.995Z] echo ""; echo "TEST SETUP:"; \
[2024-08-28T21:01:08.995Z] echo "Nothing to be done for setup."; \
[2024-08-28T21:01:08.995Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_1724878409841/renaissance-movie-lens_0"; \
[2024-08-28T21:01:08.995Z] cd "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_1724878409841/renaissance-movie-lens_0"; \
[2024-08-28T21:01:08.995Z] echo ""; echo "TESTING:"; \
[2024-08-28T21:01:08.995Z] "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/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/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_1724878409841/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-28T21:01:08.995Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_1724878409841/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-28T21:01:08.995Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-28T21:01:08.995Z] echo "Nothing to be done for teardown."; \
[2024-08-28T21:01:08.995Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_1724878409841/TestTargetResult";
[2024-08-28T21:01:08.995Z]
[2024-08-28T21:01:08.995Z] TEST SETUP:
[2024-08-28T21:01:08.995Z] Nothing to be done for setup.
[2024-08-28T21:01:08.995Z]
[2024-08-28T21:01:08.995Z] TESTING:
[2024-08-28T21:01:10.809Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-28T21:01:11.166Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2024-08-28T21:01:12.442Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-28T21:01:12.442Z] Training: 60056, validation: 20285, test: 19854
[2024-08-28T21:01:12.442Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-28T21:01:12.442Z] GC before operation: completed in 25.223 ms, heap usage 79.712 MB -> 36.570 MB.
[2024-08-28T21:01:14.859Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:01:16.632Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:01:18.415Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:01:19.185Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:01:19.992Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:01:20.757Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:01:21.547Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:01:22.310Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:01:22.664Z] 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.
[2024-08-28T21:01:22.664Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:01:22.664Z] Movies recommended for you:
[2024-08-28T21:01:22.664Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:01:22.664Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:01:22.664Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (10008.443 ms) ======
[2024-08-28T21:01:22.664Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-28T21:01:22.664Z] GC before operation: completed in 43.352 ms, heap usage 68.179 MB -> 49.785 MB.
[2024-08-28T21:01:23.914Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:01:25.183Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:01:26.423Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:01:27.671Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:01:28.454Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:01:29.254Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:01:30.040Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:01:30.825Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:01:30.825Z] 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.
[2024-08-28T21:01:30.826Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:01:30.826Z] Movies recommended for you:
[2024-08-28T21:01:30.826Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:01:30.826Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:01:30.826Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (8302.534 ms) ======
[2024-08-28T21:01:30.826Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-28T21:01:31.185Z] GC before operation: completed in 39.814 ms, heap usage 188.687 MB -> 48.952 MB.
[2024-08-28T21:01:32.420Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:01:33.275Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:01:34.529Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:01:35.784Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:01:36.549Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:01:37.315Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:01:38.083Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:01:38.869Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:01:38.869Z] 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.
[2024-08-28T21:01:38.869Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:01:38.869Z] Movies recommended for you:
[2024-08-28T21:01:38.869Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:01:38.869Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:01:38.869Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (7907.812 ms) ======
[2024-08-28T21:01:38.869Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-28T21:01:38.869Z] GC before operation: completed in 38.764 ms, heap usage 171.253 MB -> 49.209 MB.
[2024-08-28T21:01:40.107Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:01:41.353Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:01:42.588Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:01:43.357Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:01:44.134Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:01:44.903Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:01:45.675Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:01:46.044Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:01:46.410Z] 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.
[2024-08-28T21:01:46.410Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:01:46.410Z] Movies recommended for you:
[2024-08-28T21:01:46.410Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:01:46.410Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:01:46.410Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (7416.491 ms) ======
[2024-08-28T21:01:46.410Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-28T21:01:46.410Z] GC before operation: completed in 48.825 ms, heap usage 165.826 MB -> 49.518 MB.
[2024-08-28T21:01:47.663Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:01:48.439Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:01:49.696Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:01:50.939Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:01:51.309Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:01:52.110Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:01:52.903Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:01:53.675Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:01:53.675Z] 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.
[2024-08-28T21:01:53.675Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:01:53.675Z] Movies recommended for you:
[2024-08-28T21:01:53.675Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:01:53.675Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:01:53.675Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (7326.306 ms) ======
[2024-08-28T21:01:53.675Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-28T21:01:53.675Z] GC before operation: completed in 46.289 ms, heap usage 167.759 MB -> 49.823 MB.
[2024-08-28T21:01:54.936Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:01:56.195Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:01:56.979Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:01:58.257Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:01:58.616Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:01:59.385Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:02:00.166Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:02:00.542Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:02:00.900Z] 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.
[2024-08-28T21:02:00.900Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:02:00.900Z] Movies recommended for you:
[2024-08-28T21:02:00.900Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:02:00.900Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:02:00.900Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (6996.233 ms) ======
[2024-08-28T21:02:00.900Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-28T21:02:00.900Z] GC before operation: completed in 42.754 ms, heap usage 383.887 MB -> 53.073 MB.
[2024-08-28T21:02:02.144Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:02:03.389Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:02:04.633Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:02:05.410Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:02:06.195Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:02:06.970Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:02:07.765Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:02:08.548Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:02:08.904Z] 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.
[2024-08-28T21:02:08.904Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:02:08.904Z] Movies recommended for you:
[2024-08-28T21:02:08.904Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:02:08.904Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:02:08.904Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (7952.666 ms) ======
[2024-08-28T21:02:08.904Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-28T21:02:08.904Z] GC before operation: completed in 40.220 ms, heap usage 262.966 MB -> 49.912 MB.
[2024-08-28T21:02:10.145Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:02:10.919Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:02:12.167Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:02:13.407Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:02:13.765Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:02:14.550Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:02:15.332Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:02:16.107Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:02:16.107Z] 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.
[2024-08-28T21:02:16.107Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:02:16.107Z] Movies recommended for you:
[2024-08-28T21:02:16.107Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:02:16.107Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:02:16.107Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (7197.284 ms) ======
[2024-08-28T21:02:16.107Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-28T21:02:16.107Z] GC before operation: completed in 41.620 ms, heap usage 308.405 MB -> 50.212 MB.
[2024-08-28T21:02:17.396Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:02:18.638Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:02:19.417Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:02:20.654Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:02:21.453Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:02:22.258Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:02:23.035Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:02:23.388Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:02:23.754Z] 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.
[2024-08-28T21:02:23.754Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:02:23.754Z] Movies recommended for you:
[2024-08-28T21:02:23.754Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:02:23.754Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:02:23.754Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (7620.735 ms) ======
[2024-08-28T21:02:23.754Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-28T21:02:23.754Z] GC before operation: completed in 39.826 ms, heap usage 237.098 MB -> 50.100 MB.
[2024-08-28T21:02:25.006Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:02:26.266Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:02:27.519Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:02:28.291Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:02:29.060Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:02:29.842Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:02:30.226Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:02:31.012Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:02:31.370Z] 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.
[2024-08-28T21:02:31.370Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:02:31.370Z] Movies recommended for you:
[2024-08-28T21:02:31.370Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:02:31.370Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:02:31.370Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (7524.835 ms) ======
[2024-08-28T21:02:31.370Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-28T21:02:31.370Z] GC before operation: completed in 38.536 ms, heap usage 237.574 MB -> 50.163 MB.
[2024-08-28T21:02:32.622Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:02:33.389Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:02:34.633Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:02:35.405Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:02:36.168Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:02:36.951Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:02:37.311Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:02:38.082Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:02:38.082Z] 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.
[2024-08-28T21:02:38.082Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:02:38.082Z] Movies recommended for you:
[2024-08-28T21:02:38.082Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:02:38.082Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:02:38.082Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (6708.748 ms) ======
[2024-08-28T21:02:38.082Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-28T21:02:38.082Z] GC before operation: completed in 39.291 ms, heap usage 172.307 MB -> 49.806 MB.
[2024-08-28T21:02:39.362Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:02:40.623Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:02:41.393Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:02:42.232Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:02:42.995Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:02:43.768Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:02:44.129Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:02:44.898Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:02:44.898Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-28T21:02:44.898Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:02:44.898Z] Movies recommended for you:
[2024-08-28T21:02:44.898Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:02:44.898Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:02:44.898Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (6871.283 ms) ======
[2024-08-28T21:02:44.898Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-28T21:02:44.898Z] GC before operation: completed in 39.371 ms, heap usage 121.766 MB -> 49.832 MB.
[2024-08-28T21:02:46.146Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:02:46.920Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:02:48.143Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:02:48.925Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:02:49.291Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:02:50.068Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:02:50.849Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:02:51.636Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:02:51.636Z] 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.
[2024-08-28T21:02:51.636Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:02:51.636Z] Movies recommended for you:
[2024-08-28T21:02:51.636Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:02:51.636Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:02:51.636Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (6614.788 ms) ======
[2024-08-28T21:02:51.636Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-28T21:02:51.636Z] GC before operation: completed in 42.962 ms, heap usage 77.228 MB -> 50.240 MB.
[2024-08-28T21:02:52.891Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:02:53.659Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:02:55.503Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:02:56.275Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:02:57.048Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:02:57.830Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:02:58.599Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:02:58.976Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:02:59.342Z] 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.
[2024-08-28T21:02:59.342Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:02:59.342Z] Movies recommended for you:
[2024-08-28T21:02:59.342Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:02:59.342Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:02:59.342Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (7601.580 ms) ======
[2024-08-28T21:02:59.342Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-28T21:02:59.342Z] GC before operation: completed in 42.265 ms, heap usage 186.598 MB -> 49.886 MB.
[2024-08-28T21:03:00.620Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:03:01.393Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:03:02.666Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:03:03.917Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:03:04.283Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:03:05.078Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:03:05.861Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:03:06.249Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:03:06.613Z] 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.
[2024-08-28T21:03:06.613Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:03:06.613Z] Movies recommended for you:
[2024-08-28T21:03:06.613Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:03:06.613Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:03:06.613Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (7291.544 ms) ======
[2024-08-28T21:03:06.613Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-28T21:03:06.613Z] GC before operation: completed in 51.133 ms, heap usage 260.590 MB -> 50.075 MB.
[2024-08-28T21:03:07.867Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:03:09.132Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:03:09.906Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:03:11.147Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:03:11.911Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:03:12.681Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:03:13.450Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:03:14.220Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:03:14.220Z] 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.
[2024-08-28T21:03:14.220Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:03:14.220Z] Movies recommended for you:
[2024-08-28T21:03:14.220Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:03:14.220Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:03:14.220Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (7541.790 ms) ======
[2024-08-28T21:03:14.220Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-28T21:03:14.220Z] GC before operation: completed in 39.982 ms, heap usage 219.855 MB -> 50.217 MB.
[2024-08-28T21:03:15.461Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:03:16.708Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:03:17.940Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:03:18.729Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:03:19.503Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:03:20.279Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:03:21.047Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:03:21.815Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:03:21.815Z] 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.
[2024-08-28T21:03:21.815Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:03:21.815Z] Movies recommended for you:
[2024-08-28T21:03:21.815Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:03:21.815Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:03:21.815Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (7728.349 ms) ======
[2024-08-28T21:03:21.815Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-28T21:03:21.815Z] GC before operation: completed in 40.077 ms, heap usage 233.231 MB -> 50.080 MB.
[2024-08-28T21:03:23.106Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:03:24.359Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:03:25.130Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:03:26.369Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:03:27.143Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:03:27.907Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:03:28.677Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:03:29.058Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:03:29.434Z] 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.
[2024-08-28T21:03:29.434Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:03:29.434Z] Movies recommended for you:
[2024-08-28T21:03:29.434Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:03:29.434Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:03:29.434Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (7417.280 ms) ======
[2024-08-28T21:03:29.434Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-28T21:03:29.434Z] GC before operation: completed in 43.383 ms, heap usage 168.355 MB -> 50.049 MB.
[2024-08-28T21:03:30.762Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:03:31.521Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:03:33.317Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:03:34.106Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:03:34.876Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:03:35.660Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:03:36.430Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:03:37.199Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:03:37.199Z] 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.
[2024-08-28T21:03:37.199Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:03:37.562Z] Movies recommended for you:
[2024-08-28T21:03:37.562Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:03:37.562Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:03:37.562Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (7976.749 ms) ======
[2024-08-28T21:03:37.562Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-28T21:03:37.562Z] GC before operation: completed in 47.510 ms, heap usage 229.614 MB -> 50.248 MB.
[2024-08-28T21:03:38.797Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:03:40.066Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:03:40.863Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:03:42.103Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:03:42.871Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:03:43.702Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:03:44.484Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:03:44.844Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:03:44.844Z] 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.
[2024-08-28T21:03:44.844Z] The best model improves the baseline by 14.52%.
[2024-08-28T21:03:44.844Z] Movies recommended for you:
[2024-08-28T21:03:44.844Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:03:44.844Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:03:44.844Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (7572.172 ms) ======
[2024-08-28T21:03:45.200Z] -----------------------------------
[2024-08-28T21:03:45.200Z] renaissance-movie-lens_0_PASSED
[2024-08-28T21:03:45.200Z] -----------------------------------
[2024-08-28T21:03:45.200Z]
[2024-08-28T21:03:45.200Z] TEST TEARDOWN:
[2024-08-28T21:03:45.200Z] Nothing to be done for teardown.
[2024-08-28T21:03:45.200Z] renaissance-movie-lens_0 Finish Time: Wed Aug 28 17:03:44 2024 Epoch Time (ms): 1724879024973