renaissance-movie-lens_0
[2025-02-05T22:30:22.275Z] Running test renaissance-movie-lens_0 ...
[2025-02-05T22:30:22.275Z] ===============================================
[2025-02-05T22:30:22.275Z] renaissance-movie-lens_0 Start Time: Wed Feb 5 17:30:22 2025 Epoch Time (ms): 1738794622180
[2025-02-05T22:30:22.275Z] variation: NoOptions
[2025-02-05T22:30:22.275Z] JVM_OPTIONS:
[2025-02-05T22:30:22.275Z] { \
[2025-02-05T22:30:22.275Z] echo ""; echo "TEST SETUP:"; \
[2025-02-05T22:30:22.275Z] echo "Nothing to be done for setup."; \
[2025-02-05T22:30:22.275Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17387942506025/renaissance-movie-lens_0"; \
[2025-02-05T22:30:22.275Z] cd "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17387942506025/renaissance-movie-lens_0"; \
[2025-02-05T22:30:22.275Z] echo ""; echo "TESTING:"; \
[2025-02-05T22:30:22.276Z] "/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_17387942506025/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-02-05T22:30:22.276Z] 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_17387942506025/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-02-05T22:30:22.276Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-02-05T22:30:22.276Z] echo "Nothing to be done for teardown."; \
[2025-02-05T22:30:22.276Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17387942506025/TestTargetResult";
[2025-02-05T22:30:22.276Z]
[2025-02-05T22:30:22.276Z] TEST SETUP:
[2025-02-05T22:30:22.276Z] Nothing to be done for setup.
[2025-02-05T22:30:22.276Z]
[2025-02-05T22:30:22.276Z] TESTING:
[2025-02-05T22:30:24.204Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-02-05T22:30:25.052Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2025-02-05T22:30:27.003Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-02-05T22:30:27.003Z] Training: 60056, validation: 20285, test: 19854
[2025-02-05T22:30:27.003Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-02-05T22:30:27.003Z] GC before operation: completed in 24.765 ms, heap usage 47.876 MB -> 36.570 MB.
[2025-02-05T22:30:29.583Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-05T22:30:31.525Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-05T22:30:32.867Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-05T22:30:34.222Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-05T22:30:35.058Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-05T22:30:35.926Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-05T22:30:36.763Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-05T22:30:37.597Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-05T22:30:37.597Z] 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.
[2025-02-05T22:30:37.597Z] The best model improves the baseline by 14.52%.
[2025-02-05T22:30:37.597Z] Movies recommended for you:
[2025-02-05T22:30:37.597Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-05T22:30:37.597Z] There is no way to check that no silent failure occurred.
[2025-02-05T22:30:37.597Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (10791.669 ms) ======
[2025-02-05T22:30:37.597Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-02-05T22:30:37.597Z] GC before operation: completed in 49.410 ms, heap usage 62.656 MB -> 46.649 MB.
[2025-02-05T22:30:38.962Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-05T22:30:40.336Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-05T22:30:41.685Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-05T22:30:43.042Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-05T22:30:43.894Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-05T22:30:45.253Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-05T22:30:45.680Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-05T22:30:46.549Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-05T22:30:46.550Z] 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.
[2025-02-05T22:30:46.940Z] The best model improves the baseline by 14.52%.
[2025-02-05T22:30:46.940Z] Movies recommended for you:
[2025-02-05T22:30:46.940Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-05T22:30:46.940Z] There is no way to check that no silent failure occurred.
[2025-02-05T22:30:46.940Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (9059.762 ms) ======
[2025-02-05T22:30:46.940Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-02-05T22:30:46.940Z] GC before operation: completed in 48.406 ms, heap usage 169.899 MB -> 48.876 MB.
[2025-02-05T22:30:48.290Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-05T22:30:49.636Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-05T22:30:50.999Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-05T22:30:51.841Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-05T22:30:52.715Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-05T22:30:53.604Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-05T22:30:54.449Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-05T22:30:55.295Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-05T22:30:55.295Z] 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.
[2025-02-05T22:30:55.295Z] The best model improves the baseline by 14.52%.
[2025-02-05T22:30:55.295Z] Movies recommended for you:
[2025-02-05T22:30:55.295Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-05T22:30:55.295Z] There is no way to check that no silent failure occurred.
[2025-02-05T22:30:55.295Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (8538.308 ms) ======
[2025-02-05T22:30:55.295Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-02-05T22:30:55.295Z] GC before operation: completed in 42.417 ms, heap usage 233.088 MB -> 49.322 MB.
[2025-02-05T22:30:56.658Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-05T22:30:58.024Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-05T22:30:59.386Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-05T22:31:00.755Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-05T22:31:01.611Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-05T22:31:02.473Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-05T22:31:03.334Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-05T22:31:04.196Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-05T22:31:04.196Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-02-05T22:31:04.196Z] The best model improves the baseline by 14.52%.
[2025-02-05T22:31:04.196Z] Movies recommended for you:
[2025-02-05T22:31:04.196Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-05T22:31:04.196Z] There is no way to check that no silent failure occurred.
[2025-02-05T22:31:04.196Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (8908.189 ms) ======
[2025-02-05T22:31:04.196Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-02-05T22:31:04.599Z] GC before operation: completed in 47.979 ms, heap usage 189.908 MB -> 49.583 MB.
[2025-02-05T22:31:05.949Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-05T22:31:07.322Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-05T22:31:09.269Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-05T22:31:10.616Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-05T22:31:11.011Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-05T22:31:11.863Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-05T22:31:12.719Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-05T22:31:13.126Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-05T22:31:13.520Z] 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.
[2025-02-05T22:31:13.520Z] The best model improves the baseline by 14.52%.
[2025-02-05T22:31:13.520Z] Movies recommended for you:
[2025-02-05T22:31:13.520Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-05T22:31:13.520Z] There is no way to check that no silent failure occurred.
[2025-02-05T22:31:13.520Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (8972.063 ms) ======
[2025-02-05T22:31:13.520Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-02-05T22:31:13.520Z] GC before operation: completed in 49.907 ms, heap usage 185.894 MB -> 49.762 MB.
[2025-02-05T22:31:14.887Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-05T22:31:16.293Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-05T22:31:17.654Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-05T22:31:19.017Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-05T22:31:20.384Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-05T22:31:20.774Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-05T22:31:21.637Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-05T22:31:22.484Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-05T22:31:22.874Z] 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.
[2025-02-05T22:31:22.874Z] The best model improves the baseline by 14.52%.
[2025-02-05T22:31:22.874Z] Movies recommended for you:
[2025-02-05T22:31:22.875Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-05T22:31:22.875Z] There is no way to check that no silent failure occurred.
[2025-02-05T22:31:22.875Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (9324.359 ms) ======
[2025-02-05T22:31:22.875Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-02-05T22:31:22.875Z] GC before operation: completed in 42.262 ms, heap usage 117.480 MB -> 49.603 MB.
[2025-02-05T22:31:24.232Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-05T22:31:26.165Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-05T22:31:27.018Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-05T22:31:28.371Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-05T22:31:29.216Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-05T22:31:29.621Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-05T22:31:30.457Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-05T22:31:31.338Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-05T22:31:31.338Z] 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.
[2025-02-05T22:31:31.338Z] The best model improves the baseline by 14.52%.
[2025-02-05T22:31:31.338Z] Movies recommended for you:
[2025-02-05T22:31:31.338Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-05T22:31:31.338Z] There is no way to check that no silent failure occurred.
[2025-02-05T22:31:31.338Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (8711.001 ms) ======
[2025-02-05T22:31:31.338Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-02-05T22:31:31.739Z] GC before operation: completed in 43.719 ms, heap usage 263.684 MB -> 49.913 MB.
[2025-02-05T22:31:33.101Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-05T22:31:33.938Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-05T22:31:35.427Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-05T22:31:36.789Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-05T22:31:37.644Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-05T22:31:38.481Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-05T22:31:38.896Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-05T22:31:39.766Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-05T22:31:39.766Z] 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.
[2025-02-05T22:31:39.766Z] The best model improves the baseline by 14.52%.
[2025-02-05T22:31:39.766Z] Movies recommended for you:
[2025-02-05T22:31:39.766Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-05T22:31:39.766Z] There is no way to check that no silent failure occurred.
[2025-02-05T22:31:39.766Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (8323.949 ms) ======
[2025-02-05T22:31:39.766Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-02-05T22:31:39.766Z] GC before operation: completed in 48.577 ms, heap usage 87.792 MB -> 50.006 MB.
[2025-02-05T22:31:41.126Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-05T22:31:43.088Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-05T22:31:43.963Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-05T22:31:45.311Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-05T22:31:46.161Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-05T22:31:46.584Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-05T22:31:47.937Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-05T22:31:48.797Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-05T22:31:48.797Z] 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.
[2025-02-05T22:31:48.797Z] The best model improves the baseline by 14.52%.
[2025-02-05T22:31:48.797Z] Movies recommended for you:
[2025-02-05T22:31:48.797Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-05T22:31:48.797Z] There is no way to check that no silent failure occurred.
[2025-02-05T22:31:48.797Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (8815.365 ms) ======
[2025-02-05T22:31:48.797Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-02-05T22:31:48.797Z] GC before operation: completed in 41.094 ms, heap usage 187.148 MB -> 49.919 MB.
[2025-02-05T22:31:50.156Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-05T22:31:51.536Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-05T22:31:53.470Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-05T22:31:54.317Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-05T22:31:54.717Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-05T22:31:55.582Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-05T22:31:56.432Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-05T22:31:57.297Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-05T22:31:57.297Z] 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.
[2025-02-05T22:31:57.297Z] The best model improves the baseline by 14.52%.
[2025-02-05T22:31:57.297Z] Movies recommended for you:
[2025-02-05T22:31:57.297Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-05T22:31:57.297Z] There is no way to check that no silent failure occurred.
[2025-02-05T22:31:57.297Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (8447.721 ms) ======
[2025-02-05T22:31:57.297Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-02-05T22:31:57.297Z] GC before operation: completed in 46.205 ms, heap usage 167.483 MB -> 50.000 MB.
[2025-02-05T22:31:58.671Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-05T22:31:59.588Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-05T22:32:00.442Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-05T22:32:01.812Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-05T22:32:02.208Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-05T22:32:03.065Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-05T22:32:03.935Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-05T22:32:04.343Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-05T22:32:04.741Z] 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.
[2025-02-05T22:32:04.741Z] The best model improves the baseline by 14.52%.
[2025-02-05T22:32:04.741Z] Movies recommended for you:
[2025-02-05T22:32:04.741Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-05T22:32:04.741Z] There is no way to check that no silent failure occurred.
[2025-02-05T22:32:04.741Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (7387.519 ms) ======
[2025-02-05T22:32:04.741Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-02-05T22:32:04.741Z] GC before operation: completed in 43.009 ms, heap usage 264.187 MB -> 49.929 MB.
[2025-02-05T22:32:06.103Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-05T22:32:07.479Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-05T22:32:08.835Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-05T22:32:10.190Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-05T22:32:11.039Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-05T22:32:11.435Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-05T22:32:12.273Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-05T22:32:13.131Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-05T22:32:13.131Z] 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.
[2025-02-05T22:32:13.131Z] The best model improves the baseline by 14.52%.
[2025-02-05T22:32:13.131Z] Movies recommended for you:
[2025-02-05T22:32:13.131Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-05T22:32:13.131Z] There is no way to check that no silent failure occurred.
[2025-02-05T22:32:13.131Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (8572.661 ms) ======
[2025-02-05T22:32:13.131Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-02-05T22:32:13.131Z] GC before operation: completed in 44.789 ms, heap usage 95.565 MB -> 49.938 MB.
[2025-02-05T22:32:15.071Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-05T22:32:16.000Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-05T22:32:17.350Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-05T22:32:18.707Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-05T22:32:19.580Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-05T22:32:20.424Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-05T22:32:21.262Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-05T22:32:22.098Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-05T22:32:22.098Z] 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.
[2025-02-05T22:32:22.098Z] The best model improves the baseline by 14.52%.
[2025-02-05T22:32:22.098Z] Movies recommended for you:
[2025-02-05T22:32:22.098Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-05T22:32:22.098Z] There is no way to check that no silent failure occurred.
[2025-02-05T22:32:22.098Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (8814.911 ms) ======
[2025-02-05T22:32:22.098Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-02-05T22:32:22.098Z] GC before operation: completed in 44.550 ms, heap usage 169.780 MB -> 50.155 MB.
[2025-02-05T22:32:23.439Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-05T22:32:24.792Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-05T22:32:26.146Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-05T22:32:27.501Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-05T22:32:28.340Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-05T22:32:29.184Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-05T22:32:29.579Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-05T22:32:30.438Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-05T22:32:30.829Z] 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.
[2025-02-05T22:32:30.829Z] The best model improves the baseline by 14.52%.
[2025-02-05T22:32:30.829Z] Movies recommended for you:
[2025-02-05T22:32:30.829Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-05T22:32:30.829Z] There is no way to check that no silent failure occurred.
[2025-02-05T22:32:30.829Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (8540.986 ms) ======
[2025-02-05T22:32:30.829Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-02-05T22:32:30.829Z] GC before operation: completed in 42.272 ms, heap usage 77.764 MB -> 49.954 MB.
[2025-02-05T22:32:32.194Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-05T22:32:33.554Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-05T22:32:34.913Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-05T22:32:36.262Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-05T22:32:36.665Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-05T22:32:37.512Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-05T22:32:38.360Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-05T22:32:39.200Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-05T22:32:39.200Z] 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.
[2025-02-05T22:32:39.200Z] The best model improves the baseline by 14.52%.
[2025-02-05T22:32:39.200Z] Movies recommended for you:
[2025-02-05T22:32:39.200Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-05T22:32:39.200Z] There is no way to check that no silent failure occurred.
[2025-02-05T22:32:39.200Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (8468.586 ms) ======
[2025-02-05T22:32:39.200Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-02-05T22:32:39.200Z] GC before operation: completed in 44.923 ms, heap usage 56.337 MB -> 50.034 MB.
[2025-02-05T22:32:40.543Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-05T22:32:41.913Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-05T22:32:43.289Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-05T22:32:44.631Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-05T22:32:45.473Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-05T22:32:45.891Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-05T22:32:46.753Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-05T22:32:47.597Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-05T22:32:47.990Z] 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.
[2025-02-05T22:32:47.990Z] The best model improves the baseline by 14.52%.
[2025-02-05T22:32:47.990Z] Movies recommended for you:
[2025-02-05T22:32:47.990Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-05T22:32:47.990Z] There is no way to check that no silent failure occurred.
[2025-02-05T22:32:47.990Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (8610.710 ms) ======
[2025-02-05T22:32:47.990Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-02-05T22:32:47.990Z] GC before operation: completed in 47.078 ms, heap usage 253.594 MB -> 50.163 MB.
[2025-02-05T22:32:49.338Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-05T22:32:50.703Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-05T22:32:52.058Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-05T22:32:53.413Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-05T22:32:54.261Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-05T22:32:55.115Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-05T22:32:55.992Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-05T22:32:56.860Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-05T22:32:56.860Z] 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.
[2025-02-05T22:32:56.860Z] The best model improves the baseline by 14.52%.
[2025-02-05T22:32:56.860Z] Movies recommended for you:
[2025-02-05T22:32:56.860Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-05T22:32:56.860Z] There is no way to check that no silent failure occurred.
[2025-02-05T22:32:56.860Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (9002.876 ms) ======
[2025-02-05T22:32:56.860Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-02-05T22:32:56.860Z] GC before operation: completed in 40.161 ms, heap usage 173.459 MB -> 49.927 MB.
[2025-02-05T22:32:58.224Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-05T22:32:59.580Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-05T22:33:00.961Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-05T22:33:01.815Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-05T22:33:02.656Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-05T22:33:03.516Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-05T22:33:04.394Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-05T22:33:04.802Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-05T22:33:05.207Z] 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.
[2025-02-05T22:33:05.207Z] The best model improves the baseline by 14.52%.
[2025-02-05T22:33:05.207Z] Movies recommended for you:
[2025-02-05T22:33:05.207Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-05T22:33:05.207Z] There is no way to check that no silent failure occurred.
[2025-02-05T22:33:05.207Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (8192.062 ms) ======
[2025-02-05T22:33:05.207Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-02-05T22:33:05.207Z] GC before operation: completed in 45.462 ms, heap usage 197.279 MB -> 50.114 MB.
[2025-02-05T22:33:06.580Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-05T22:33:07.949Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-05T22:33:09.307Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-05T22:33:10.659Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-05T22:33:11.061Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-05T22:33:11.917Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-05T22:33:12.772Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-05T22:33:13.625Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-05T22:33:13.625Z] 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.
[2025-02-05T22:33:13.625Z] The best model improves the baseline by 14.52%.
[2025-02-05T22:33:13.625Z] Movies recommended for you:
[2025-02-05T22:33:13.625Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-05T22:33:13.625Z] There is no way to check that no silent failure occurred.
[2025-02-05T22:33:13.625Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (8528.744 ms) ======
[2025-02-05T22:33:13.625Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-02-05T22:33:13.625Z] GC before operation: completed in 49.147 ms, heap usage 175.618 MB -> 50.262 MB.
[2025-02-05T22:33:15.563Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-05T22:33:16.409Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-05T22:33:17.783Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-05T22:33:19.141Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-05T22:33:19.994Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-05T22:33:20.845Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-05T22:33:21.698Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-05T22:33:22.550Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-05T22:33:22.550Z] 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.
[2025-02-05T22:33:22.550Z] The best model improves the baseline by 14.52%.
[2025-02-05T22:33:22.550Z] Movies recommended for you:
[2025-02-05T22:33:22.550Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-05T22:33:22.550Z] There is no way to check that no silent failure occurred.
[2025-02-05T22:33:22.550Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (8890.028 ms) ======
[2025-02-05T22:33:22.943Z] -----------------------------------
[2025-02-05T22:33:22.943Z] renaissance-movie-lens_0_PASSED
[2025-02-05T22:33:22.943Z] -----------------------------------
[2025-02-05T22:33:22.943Z]
[2025-02-05T22:33:22.943Z] TEST TEARDOWN:
[2025-02-05T22:33:22.943Z] Nothing to be done for teardown.
[2025-02-05T22:33:22.943Z] renaissance-movie-lens_0 Finish Time: Wed Feb 5 17:33:22 2025 Epoch Time (ms): 1738794802753