renaissance-movie-lens_0
[2024-08-14T21:42:07.348Z] Running test renaissance-movie-lens_0 ...
[2024-08-14T21:42:07.348Z] ===============================================
[2024-08-14T21:42:07.348Z] renaissance-movie-lens_0 Start Time: Wed Aug 14 17:42:07 2024 Epoch Time (ms): 1723671727232
[2024-08-14T21:42:07.348Z] variation: NoOptions
[2024-08-14T21:42:07.348Z] JVM_OPTIONS:
[2024-08-14T21:42:07.348Z] { \
[2024-08-14T21:42:07.348Z] echo ""; echo "TEST SETUP:"; \
[2024-08-14T21:42:07.348Z] echo "Nothing to be done for setup."; \
[2024-08-14T21:42:07.348Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../TKG/output_17236713918350/renaissance-movie-lens_0"; \
[2024-08-14T21:42:07.348Z] cd "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../TKG/output_17236713918350/renaissance-movie-lens_0"; \
[2024-08-14T21:42:07.348Z] echo ""; echo "TESTING:"; \
[2024-08-14T21:42:07.348Z] "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac_testList_0/jdkbinary/j2sdk-image/Contents/Home/bin/..//bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../TKG/output_17236713918350/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-14T21:42:07.348Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../TKG/output_17236713918350/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-14T21:42:07.348Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-14T21:42:07.348Z] echo "Nothing to be done for teardown."; \
[2024-08-14T21:42:07.348Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../TKG/output_17236713918350/TestTargetResult";
[2024-08-14T21:42:07.348Z]
[2024-08-14T21:42:07.348Z] TEST SETUP:
[2024-08-14T21:42:07.348Z] Nothing to be done for setup.
[2024-08-14T21:42:07.348Z]
[2024-08-14T21:42:07.348Z] TESTING:
[2024-08-14T21:42:09.718Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-14T21:42:10.469Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2024-08-14T21:42:11.678Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-14T21:42:12.052Z] Training: 60056, validation: 20285, test: 19854
[2024-08-14T21:42:12.052Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-14T21:42:12.052Z] GC before operation: completed in 27.066 ms, heap usage 44.700 MB -> 36.570 MB.
[2024-08-14T21:42:15.187Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:42:16.974Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:42:18.205Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:42:19.460Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:42:20.714Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:42:21.466Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:42:22.228Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:42:22.983Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:42:22.983Z] 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.
[2024-08-14T21:42:22.983Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:42:22.983Z] Movies recommended for you:
[2024-08-14T21:42:22.983Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:42:22.983Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:42:22.983Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (11083.158 ms) ======
[2024-08-14T21:42:22.983Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-14T21:42:23.333Z] GC before operation: completed in 51.162 ms, heap usage 212.336 MB -> 49.267 MB.
[2024-08-14T21:42:24.573Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:42:25.800Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:42:27.571Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:42:28.806Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:42:29.573Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:42:30.331Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:42:31.101Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:42:31.894Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:42:31.894Z] 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.
[2024-08-14T21:42:31.894Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:42:32.244Z] Movies recommended for you:
[2024-08-14T21:42:32.244Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:42:32.244Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:42:32.244Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (8939.606 ms) ======
[2024-08-14T21:42:32.244Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-14T21:42:32.244Z] GC before operation: completed in 52.493 ms, heap usage 131.419 MB -> 48.837 MB.
[2024-08-14T21:42:33.485Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:42:35.257Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:42:36.488Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:42:37.739Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:42:38.511Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:42:39.272Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:42:40.045Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:42:40.802Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:42:41.154Z] 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.
[2024-08-14T21:42:41.154Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:42:41.154Z] Movies recommended for you:
[2024-08-14T21:42:41.154Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:42:41.154Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:42:41.154Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (8960.828 ms) ======
[2024-08-14T21:42:41.154Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-14T21:42:41.154Z] GC before operation: completed in 39.814 ms, heap usage 122.486 MB -> 49.084 MB.
[2024-08-14T21:42:42.392Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:42:43.621Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:42:44.879Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:42:46.639Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:42:46.994Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:42:47.746Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:42:48.501Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:42:49.264Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:42:49.264Z] 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.
[2024-08-14T21:42:49.264Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:42:49.264Z] Movies recommended for you:
[2024-08-14T21:42:49.264Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:42:49.264Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:42:49.264Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (8248.295 ms) ======
[2024-08-14T21:42:49.264Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-14T21:42:49.614Z] GC before operation: completed in 50.441 ms, heap usage 64.000 MB -> 49.592 MB.
[2024-08-14T21:42:50.853Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:42:52.069Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:42:53.299Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:42:54.521Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:42:55.741Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:42:56.093Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:42:56.842Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:42:57.639Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:42:57.992Z] 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.
[2024-08-14T21:42:57.992Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:42:57.992Z] Movies recommended for you:
[2024-08-14T21:42:57.992Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:42:57.992Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:42:57.992Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (8423.677 ms) ======
[2024-08-14T21:42:57.992Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-14T21:42:57.992Z] GC before operation: completed in 52.803 ms, heap usage 197.595 MB -> 49.784 MB.
[2024-08-14T21:42:59.253Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:43:00.475Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:43:01.243Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:43:02.486Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:43:03.268Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:43:04.041Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:43:04.812Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:43:05.199Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:43:05.548Z] 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.
[2024-08-14T21:43:05.548Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:43:05.548Z] Movies recommended for you:
[2024-08-14T21:43:05.548Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:43:05.548Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:43:05.548Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (7492.013 ms) ======
[2024-08-14T21:43:05.548Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-14T21:43:05.548Z] GC before operation: completed in 41.927 ms, heap usage 117.902 MB -> 49.617 MB.
[2024-08-14T21:43:07.339Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:43:08.116Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:43:09.346Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:43:10.571Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:43:11.326Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:43:12.087Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:43:12.859Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:43:13.622Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:43:13.977Z] 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.
[2024-08-14T21:43:13.977Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:43:13.977Z] Movies recommended for you:
[2024-08-14T21:43:13.977Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:43:13.977Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:43:13.977Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (8460.275 ms) ======
[2024-08-14T21:43:13.977Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-14T21:43:13.977Z] GC before operation: completed in 53.298 ms, heap usage 192.582 MB -> 49.840 MB.
[2024-08-14T21:43:15.199Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:43:16.442Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:43:17.696Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:43:18.937Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:43:19.712Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:43:20.474Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:43:21.721Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:43:22.494Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:43:22.494Z] 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.
[2024-08-14T21:43:22.494Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:43:22.494Z] Movies recommended for you:
[2024-08-14T21:43:22.494Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:43:22.495Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:43:22.495Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (8523.604 ms) ======
[2024-08-14T21:43:22.495Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-14T21:43:22.495Z] GC before operation: completed in 55.770 ms, heap usage 77.725 MB -> 53.366 MB.
[2024-08-14T21:43:24.317Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:43:25.542Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:43:26.804Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:43:28.630Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:43:28.991Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:43:30.219Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:43:30.970Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:43:31.750Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:43:31.750Z] 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.
[2024-08-14T21:43:31.750Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:43:31.750Z] Movies recommended for you:
[2024-08-14T21:43:31.750Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:43:31.750Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:43:31.750Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (9349.171 ms) ======
[2024-08-14T21:43:31.750Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-14T21:43:32.110Z] GC before operation: completed in 46.773 ms, heap usage 146.017 MB -> 49.885 MB.
[2024-08-14T21:43:33.340Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:43:34.577Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:43:36.318Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:43:38.088Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:43:38.954Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:43:39.714Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:43:40.474Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:43:41.229Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:43:41.579Z] 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.
[2024-08-14T21:43:41.579Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:43:41.579Z] Movies recommended for you:
[2024-08-14T21:43:41.579Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:43:41.579Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:43:41.579Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (9575.828 ms) ======
[2024-08-14T21:43:41.579Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-14T21:43:41.579Z] GC before operation: completed in 38.949 ms, heap usage 143.082 MB -> 49.979 MB.
[2024-08-14T21:43:42.833Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:43:44.603Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:43:45.851Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:43:47.075Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:43:47.831Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:43:48.589Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:43:49.353Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:43:50.128Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:43:50.128Z] 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.
[2024-08-14T21:43:50.128Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:43:50.128Z] Movies recommended for you:
[2024-08-14T21:43:50.128Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:43:50.128Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:43:50.128Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (8570.050 ms) ======
[2024-08-14T21:43:50.128Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-14T21:43:50.128Z] GC before operation: completed in 40.282 ms, heap usage 70.473 MB -> 49.928 MB.
[2024-08-14T21:43:51.911Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:43:53.145Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:43:54.379Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:43:56.160Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:43:56.518Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:43:57.277Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:43:58.034Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:43:58.790Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:43:58.790Z] 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.
[2024-08-14T21:43:58.790Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:43:58.790Z] Movies recommended for you:
[2024-08-14T21:43:58.791Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:43:58.791Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:43:58.791Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (8638.192 ms) ======
[2024-08-14T21:43:58.791Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-14T21:43:58.791Z] GC before operation: completed in 40.071 ms, heap usage 201.723 MB -> 50.031 MB.
[2024-08-14T21:44:00.010Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:44:01.244Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:44:02.477Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:44:03.736Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:44:04.499Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:44:05.274Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:44:06.056Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:44:06.412Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:44:06.774Z] 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.
[2024-08-14T21:44:06.774Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:44:06.774Z] Movies recommended for you:
[2024-08-14T21:44:06.774Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:44:06.774Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:44:06.774Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (7873.477 ms) ======
[2024-08-14T21:44:06.774Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-14T21:44:06.774Z] GC before operation: completed in 46.879 ms, heap usage 191.154 MB -> 50.174 MB.
[2024-08-14T21:44:08.004Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:44:09.245Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:44:10.474Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:44:11.690Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:44:12.451Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:44:13.679Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:44:14.062Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:44:15.279Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:44:15.279Z] 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.
[2024-08-14T21:44:15.279Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:44:15.279Z] Movies recommended for you:
[2024-08-14T21:44:15.279Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:44:15.279Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:44:15.279Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (8377.111 ms) ======
[2024-08-14T21:44:15.279Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-14T21:44:15.279Z] GC before operation: completed in 41.181 ms, heap usage 137.587 MB -> 49.846 MB.
[2024-08-14T21:44:16.525Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:44:18.955Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:44:20.186Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:44:21.423Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:44:22.185Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:44:23.416Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:44:24.195Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:44:24.952Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:44:24.952Z] 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.
[2024-08-14T21:44:24.952Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:44:25.307Z] Movies recommended for you:
[2024-08-14T21:44:25.307Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:44:25.307Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:44:25.307Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (9927.299 ms) ======
[2024-08-14T21:44:25.307Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-14T21:44:25.307Z] GC before operation: completed in 49.554 ms, heap usage 250.816 MB -> 50.130 MB.
[2024-08-14T21:44:27.065Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:44:28.282Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:44:29.525Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:44:31.293Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:44:32.055Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:44:32.822Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:44:34.064Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:44:34.843Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:44:34.843Z] 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.
[2024-08-14T21:44:34.843Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:44:34.843Z] Movies recommended for you:
[2024-08-14T21:44:34.843Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:44:34.843Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:44:34.843Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (9713.052 ms) ======
[2024-08-14T21:44:34.843Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-14T21:44:34.843Z] GC before operation: completed in 45.132 ms, heap usage 116.708 MB -> 50.069 MB.
[2024-08-14T21:44:36.612Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:44:38.374Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:44:40.141Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:44:41.384Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:44:42.156Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:44:43.419Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:44:44.186Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:44:44.947Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:44:45.327Z] 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.
[2024-08-14T21:44:45.327Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:44:45.327Z] Movies recommended for you:
[2024-08-14T21:44:45.327Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:44:45.327Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:44:45.327Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (10367.149 ms) ======
[2024-08-14T21:44:45.327Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-14T21:44:45.327Z] GC before operation: completed in 56.946 ms, heap usage 71.327 MB -> 49.843 MB.
[2024-08-14T21:44:47.109Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:44:48.908Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:44:50.133Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:44:51.898Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:44:52.673Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:44:53.457Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:44:54.704Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:44:55.477Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:44:55.477Z] 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.
[2024-08-14T21:44:55.477Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:44:55.830Z] Movies recommended for you:
[2024-08-14T21:44:55.830Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:44:55.830Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:44:55.830Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (10313.614 ms) ======
[2024-08-14T21:44:55.830Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-14T21:44:55.830Z] GC before operation: completed in 61.634 ms, heap usage 117.326 MB -> 49.983 MB.
[2024-08-14T21:44:57.603Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:44:58.846Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:45:00.646Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:45:01.893Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:45:02.677Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:45:03.942Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:45:04.708Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:45:05.510Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:45:05.868Z] 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.
[2024-08-14T21:45:05.868Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:45:05.868Z] Movies recommended for you:
[2024-08-14T21:45:05.868Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:45:05.868Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:45:05.868Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (10236.958 ms) ======
[2024-08-14T21:45:05.868Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-14T21:45:06.221Z] GC before operation: completed in 66.670 ms, heap usage 118.498 MB -> 50.159 MB.
[2024-08-14T21:45:07.446Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:45:09.231Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:45:11.015Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:45:12.812Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:45:13.599Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:45:14.382Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:45:15.613Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:45:16.380Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:45:16.736Z] 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.
[2024-08-14T21:45:16.736Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:45:16.736Z] Movies recommended for you:
[2024-08-14T21:45:16.736Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:45:16.736Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:45:16.736Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (10674.816 ms) ======
[2024-08-14T21:45:17.090Z] -----------------------------------
[2024-08-14T21:45:17.090Z] renaissance-movie-lens_0_PASSED
[2024-08-14T21:45:17.090Z] -----------------------------------
[2024-08-14T21:45:17.090Z]
[2024-08-14T21:45:17.090Z] TEST TEARDOWN:
[2024-08-14T21:45:17.090Z] Nothing to be done for teardown.
[2024-08-14T21:45:17.090Z] renaissance-movie-lens_0 Finish Time: Wed Aug 14 17:45:16 2024 Epoch Time (ms): 1723671916804