renaissance-movie-lens_0
[2024-08-07T21:08:57.795Z] Running test renaissance-movie-lens_0 ...
[2024-08-07T21:08:57.795Z] ===============================================
[2024-08-07T21:08:57.796Z] renaissance-movie-lens_0 Start Time: Wed Aug 7 17:08:57 2024 Epoch Time (ms): 1723064937509
[2024-08-07T21:08:57.796Z] variation: NoOptions
[2024-08-07T21:08:57.796Z] JVM_OPTIONS:
[2024-08-07T21:08:57.796Z] { \
[2024-08-07T21:08:57.796Z] echo ""; echo "TEST SETUP:"; \
[2024-08-07T21:08:57.796Z] echo "Nothing to be done for setup."; \
[2024-08-07T21:08:57.796Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../TKG/output_17230646171882/renaissance-movie-lens_0"; \
[2024-08-07T21:08:57.796Z] cd "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../TKG/output_17230646171882/renaissance-movie-lens_0"; \
[2024-08-07T21:08:57.796Z] echo ""; echo "TESTING:"; \
[2024-08-07T21:08:57.796Z] "/Users/admin/workspace/workspace/Test_openjdk17_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_openjdk17_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../TKG/output_17230646171882/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-07T21:08:57.796Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../TKG/output_17230646171882/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-07T21:08:57.796Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-07T21:08:57.796Z] echo "Nothing to be done for teardown."; \
[2024-08-07T21:08:57.796Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../TKG/output_17230646171882/TestTargetResult";
[2024-08-07T21:08:57.796Z]
[2024-08-07T21:08:57.796Z] TEST SETUP:
[2024-08-07T21:08:57.796Z] Nothing to be done for setup.
[2024-08-07T21:08:57.796Z]
[2024-08-07T21:08:57.796Z] TESTING:
[2024-08-07T21:08:59.541Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-07T21:09:00.302Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2024-08-07T21:09:02.070Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-07T21:09:02.070Z] Training: 60056, validation: 20285, test: 19854
[2024-08-07T21:09:02.070Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-07T21:09:02.070Z] GC before operation: completed in 19.154 ms, heap usage 95.102 MB -> 36.859 MB.
[2024-08-07T21:09:05.237Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:09:06.465Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:09:08.216Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:09:09.987Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:09:10.788Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:09:11.551Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:09:12.777Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:09:13.566Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:09:13.566Z] 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.
[2024-08-07T21:09:13.566Z] The best model improves the baseline by 14.52%.
[2024-08-07T21:09:13.566Z] Movies recommended for you:
[2024-08-07T21:09:13.566Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:09:13.566Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:09:13.566Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (11722.249 ms) ======
[2024-08-07T21:09:13.566Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-07T21:09:13.919Z] GC before operation: completed in 34.021 ms, heap usage 77.764 MB -> 53.304 MB.
[2024-08-07T21:09:15.143Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:09:16.356Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:09:17.607Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:09:18.835Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:09:19.592Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:09:20.353Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:09:21.580Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:09:21.964Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:09:22.315Z] 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.
[2024-08-07T21:09:22.315Z] The best model improves the baseline by 14.52%.
[2024-08-07T21:09:22.315Z] Movies recommended for you:
[2024-08-07T21:09:22.315Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:09:22.315Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:09:22.315Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (8451.548 ms) ======
[2024-08-07T21:09:22.315Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-07T21:09:22.315Z] GC before operation: completed in 42.899 ms, heap usage 263.901 MB -> 49.210 MB.
[2024-08-07T21:09:23.536Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:09:25.296Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:09:26.514Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:09:27.743Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:09:28.496Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:09:29.267Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:09:30.028Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:09:31.260Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:09:31.260Z] 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.
[2024-08-07T21:09:31.260Z] The best model improves the baseline by 14.52%.
[2024-08-07T21:09:31.260Z] Movies recommended for you:
[2024-08-07T21:09:31.260Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:09:31.260Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:09:31.260Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (9000.621 ms) ======
[2024-08-07T21:09:31.260Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-07T21:09:31.260Z] GC before operation: completed in 36.706 ms, heap usage 169.527 MB -> 49.445 MB.
[2024-08-07T21:09:32.484Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:09:33.704Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:09:35.477Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:09:36.693Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:09:37.458Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:09:38.225Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:09:39.000Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:09:39.429Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:09:39.795Z] 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.
[2024-08-07T21:09:39.795Z] The best model improves the baseline by 14.52%.
[2024-08-07T21:09:39.795Z] Movies recommended for you:
[2024-08-07T21:09:39.795Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:09:39.795Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:09:39.795Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (8441.745 ms) ======
[2024-08-07T21:09:39.795Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-07T21:09:39.795Z] GC before operation: completed in 35.116 ms, heap usage 203.937 MB -> 49.734 MB.
[2024-08-07T21:09:41.020Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:09:42.239Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:09:43.577Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:09:44.801Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:09:45.555Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:09:46.308Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:09:47.071Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:09:47.836Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:09:47.836Z] 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.
[2024-08-07T21:09:47.836Z] The best model improves the baseline by 14.52%.
[2024-08-07T21:09:48.190Z] Movies recommended for you:
[2024-08-07T21:09:48.190Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:09:48.190Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:09:48.190Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (8253.868 ms) ======
[2024-08-07T21:09:48.190Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-07T21:09:48.190Z] GC before operation: completed in 29.844 ms, heap usage 125.850 MB -> 50.069 MB.
[2024-08-07T21:09:49.432Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:09:50.664Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:09:51.887Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:09:53.150Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:09:53.509Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:09:54.267Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:09:55.600Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:09:55.952Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:09:55.952Z] 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.
[2024-08-07T21:09:55.952Z] The best model improves the baseline by 14.52%.
[2024-08-07T21:09:56.311Z] Movies recommended for you:
[2024-08-07T21:09:56.311Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:09:56.311Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:09:56.311Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (8104.098 ms) ======
[2024-08-07T21:09:56.311Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-07T21:09:56.311Z] GC before operation: completed in 32.560 ms, heap usage 74.725 MB -> 49.929 MB.
[2024-08-07T21:09:57.525Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:09:58.760Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:09:59.983Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:10:01.244Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:10:02.011Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:10:02.799Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:10:03.578Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:10:04.347Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:10:04.347Z] 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.
[2024-08-07T21:10:04.347Z] The best model improves the baseline by 14.52%.
[2024-08-07T21:10:04.347Z] Movies recommended for you:
[2024-08-07T21:10:04.347Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:10:04.347Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:10:04.347Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (8097.189 ms) ======
[2024-08-07T21:10:04.347Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-07T21:10:04.347Z] GC before operation: completed in 30.999 ms, heap usage 261.231 MB -> 50.337 MB.
[2024-08-07T21:10:05.577Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:10:06.801Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:10:08.029Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:10:09.279Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:10:10.502Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:10:10.861Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:10:12.112Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:10:12.464Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:10:12.819Z] 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.
[2024-08-07T21:10:12.819Z] The best model improves the baseline by 14.52%.
[2024-08-07T21:10:12.819Z] Movies recommended for you:
[2024-08-07T21:10:12.819Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:10:12.819Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:10:12.819Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (8490.501 ms) ======
[2024-08-07T21:10:12.819Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-07T21:10:12.819Z] GC before operation: completed in 29.488 ms, heap usage 188.592 MB -> 50.507 MB.
[2024-08-07T21:10:14.075Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:10:15.334Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:10:16.545Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:10:17.765Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:10:18.535Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:10:19.305Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:10:20.085Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:10:20.854Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:10:20.854Z] 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.
[2024-08-07T21:10:20.854Z] The best model improves the baseline by 14.52%.
[2024-08-07T21:10:20.854Z] Movies recommended for you:
[2024-08-07T21:10:20.854Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:10:20.854Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:10:20.854Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (8176.747 ms) ======
[2024-08-07T21:10:20.854Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-07T21:10:21.210Z] GC before operation: completed in 29.326 ms, heap usage 158.194 MB -> 50.367 MB.
[2024-08-07T21:10:22.451Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:10:23.695Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:10:24.912Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:10:26.139Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:10:26.913Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:10:27.672Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:10:28.435Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:10:29.195Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:10:29.195Z] 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.
[2024-08-07T21:10:29.195Z] The best model improves the baseline by 14.52%.
[2024-08-07T21:10:29.195Z] Movies recommended for you:
[2024-08-07T21:10:29.195Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:10:29.195Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:10:29.545Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (8324.677 ms) ======
[2024-08-07T21:10:29.545Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-07T21:10:29.545Z] GC before operation: completed in 31.019 ms, heap usage 189.807 MB -> 50.304 MB.
[2024-08-07T21:10:30.762Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:10:31.973Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:10:33.211Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:10:34.433Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:10:35.187Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:10:35.948Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:10:36.726Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:10:37.095Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:10:37.446Z] 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.
[2024-08-07T21:10:37.446Z] The best model improves the baseline by 14.52%.
[2024-08-07T21:10:37.446Z] Movies recommended for you:
[2024-08-07T21:10:37.446Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:10:37.446Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:10:37.446Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (7961.524 ms) ======
[2024-08-07T21:10:37.446Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-07T21:10:37.446Z] GC before operation: completed in 32.503 ms, heap usage 126.305 MB -> 50.076 MB.
[2024-08-07T21:10:38.672Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:10:39.901Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:10:41.126Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:10:42.344Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:10:43.096Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:10:43.853Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:10:44.618Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:10:45.395Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:10:45.395Z] 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.
[2024-08-07T21:10:45.395Z] The best model improves the baseline by 14.52%.
[2024-08-07T21:10:45.752Z] Movies recommended for you:
[2024-08-07T21:10:45.752Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:10:45.752Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:10:45.752Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (8195.416 ms) ======
[2024-08-07T21:10:45.752Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-07T21:10:45.752Z] GC before operation: completed in 39.178 ms, heap usage 70.776 MB -> 50.232 MB.
[2024-08-07T21:10:47.015Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:10:47.771Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:10:49.013Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:10:50.246Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:10:51.008Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:10:51.780Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:10:52.552Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:10:53.306Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:10:53.306Z] 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.
[2024-08-07T21:10:53.306Z] The best model improves the baseline by 14.52%.
[2024-08-07T21:10:53.306Z] Movies recommended for you:
[2024-08-07T21:10:53.306Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:10:53.306Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:10:53.306Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (7719.642 ms) ======
[2024-08-07T21:10:53.306Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-07T21:10:53.306Z] GC before operation: completed in 42.616 ms, heap usage 76.282 MB -> 50.376 MB.
[2024-08-07T21:10:54.547Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:10:55.793Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:10:57.030Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:10:58.264Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:10:58.626Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:10:59.384Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:11:00.652Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:11:01.005Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:11:01.005Z] 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.
[2024-08-07T21:11:01.005Z] The best model improves the baseline by 14.52%.
[2024-08-07T21:11:01.365Z] Movies recommended for you:
[2024-08-07T21:11:01.365Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:11:01.365Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:11:01.365Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (7821.730 ms) ======
[2024-08-07T21:11:01.365Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-07T21:11:01.365Z] GC before operation: completed in 35.811 ms, heap usage 77.138 MB -> 50.061 MB.
[2024-08-07T21:11:02.612Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:11:03.850Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:11:05.079Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:11:06.298Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:11:07.092Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:11:07.847Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:11:08.652Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:11:09.006Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:11:09.356Z] 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.
[2024-08-07T21:11:09.356Z] The best model improves the baseline by 14.52%.
[2024-08-07T21:11:09.356Z] Movies recommended for you:
[2024-08-07T21:11:09.356Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:11:09.356Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:11:09.356Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (8103.885 ms) ======
[2024-08-07T21:11:09.356Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-07T21:11:09.356Z] GC before operation: completed in 37.918 ms, heap usage 89.793 MB -> 53.163 MB.
[2024-08-07T21:11:10.579Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:11:11.342Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:11:12.568Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:11:13.790Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:11:14.154Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:11:14.908Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:11:15.665Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:11:16.447Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:11:16.447Z] 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.
[2024-08-07T21:11:16.447Z] The best model improves the baseline by 14.52%.
[2024-08-07T21:11:16.447Z] Movies recommended for you:
[2024-08-07T21:11:16.447Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:11:16.447Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:11:16.447Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (6991.865 ms) ======
[2024-08-07T21:11:16.447Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-07T21:11:16.447Z] GC before operation: completed in 31.832 ms, heap usage 198.807 MB -> 50.581 MB.
[2024-08-07T21:11:17.711Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:11:18.932Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:11:20.167Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:11:21.387Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:11:22.179Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:11:22.527Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:11:23.300Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:11:24.081Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:11:24.436Z] 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.
[2024-08-07T21:11:24.436Z] The best model improves the baseline by 14.52%.
[2024-08-07T21:11:24.436Z] Movies recommended for you:
[2024-08-07T21:11:24.436Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:11:24.436Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:11:24.436Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (7968.233 ms) ======
[2024-08-07T21:11:24.436Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-07T21:11:24.436Z] GC before operation: completed in 32.178 ms, heap usage 255.478 MB -> 50.402 MB.
[2024-08-07T21:11:25.663Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:11:26.920Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:11:28.141Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:11:29.363Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:11:30.114Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:11:30.879Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:11:31.655Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:11:32.414Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:11:32.769Z] 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.
[2024-08-07T21:11:32.769Z] The best model improves the baseline by 14.52%.
[2024-08-07T21:11:32.769Z] Movies recommended for you:
[2024-08-07T21:11:32.769Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:11:32.769Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:11:32.770Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (8330.102 ms) ======
[2024-08-07T21:11:32.770Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-07T21:11:32.770Z] GC before operation: completed in 32.102 ms, heap usage 173.412 MB -> 50.417 MB.
[2024-08-07T21:11:33.995Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:11:35.215Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:11:36.443Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:11:37.660Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:11:38.421Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:11:39.174Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:11:40.403Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:11:40.752Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:11:41.113Z] 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.
[2024-08-07T21:11:41.113Z] The best model improves the baseline by 14.52%.
[2024-08-07T21:11:41.113Z] Movies recommended for you:
[2024-08-07T21:11:41.113Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:11:41.113Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:11:41.113Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (8282.018 ms) ======
[2024-08-07T21:11:41.113Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-07T21:11:41.113Z] GC before operation: completed in 35.146 ms, heap usage 145.950 MB -> 50.433 MB.
[2024-08-07T21:11:42.343Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-07T21:11:43.603Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-07T21:11:44.828Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-07T21:11:46.052Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-07T21:11:46.420Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-07T21:11:47.185Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-07T21:11:47.947Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-07T21:11:48.707Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-07T21:11:48.707Z] 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.
[2024-08-07T21:11:49.057Z] The best model improves the baseline by 14.52%.
[2024-08-07T21:11:49.057Z] Movies recommended for you:
[2024-08-07T21:11:49.057Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-07T21:11:49.057Z] There is no way to check that no silent failure occurred.
[2024-08-07T21:11:49.057Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (7850.389 ms) ======
[2024-08-07T21:11:49.446Z] -----------------------------------
[2024-08-07T21:11:49.446Z] renaissance-movie-lens_0_PASSED
[2024-08-07T21:11:49.446Z] -----------------------------------
[2024-08-07T21:11:49.446Z]
[2024-08-07T21:11:49.446Z] TEST TEARDOWN:
[2024-08-07T21:11:49.446Z] Nothing to be done for teardown.
[2024-08-07T21:11:49.446Z] renaissance-movie-lens_0 Finish Time: Wed Aug 7 17:11:49 2024 Epoch Time (ms): 1723065109086