renaissance-movie-lens_0
[2024-08-14T21:04:53.888Z] Running test renaissance-movie-lens_0 ...
[2024-08-14T21:04:53.888Z] ===============================================
[2024-08-14T21:04:53.888Z] renaissance-movie-lens_0 Start Time: Wed Aug 14 17:04:53 2024 Epoch Time (ms): 1723669493371
[2024-08-14T21:04:53.888Z] variation: NoOptions
[2024-08-14T21:04:53.888Z] JVM_OPTIONS:
[2024-08-14T21:04:53.888Z] { \
[2024-08-14T21:04:53.888Z] echo ""; echo "TEST SETUP:"; \
[2024-08-14T21:04:53.888Z] echo "Nothing to be done for setup."; \
[2024-08-14T21:04:53.888Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../TKG/output_17236692022236/renaissance-movie-lens_0"; \
[2024-08-14T21:04:53.888Z] cd "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../TKG/output_17236692022236/renaissance-movie-lens_0"; \
[2024-08-14T21:04:53.888Z] echo ""; echo "TESTING:"; \
[2024-08-14T21:04:53.888Z] "/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_17236692022236/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-14T21:04:53.888Z] 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_17236692022236/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-14T21:04:53.888Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-14T21:04:53.888Z] echo "Nothing to be done for teardown."; \
[2024-08-14T21:04:53.888Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac_testList_0/aqa-tests/TKG/../TKG/output_17236692022236/TestTargetResult";
[2024-08-14T21:04:53.888Z]
[2024-08-14T21:04:53.888Z] TEST SETUP:
[2024-08-14T21:04:53.888Z] Nothing to be done for setup.
[2024-08-14T21:04:53.888Z]
[2024-08-14T21:04:53.888Z] TESTING:
[2024-08-14T21:04:55.646Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-14T21:04:55.997Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2024-08-14T21:04:57.766Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-14T21:04:57.766Z] Training: 60056, validation: 20285, test: 19854
[2024-08-14T21:04:57.766Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-14T21:04:57.766Z] GC before operation: completed in 22.253 ms, heap usage 66.573 MB -> 36.956 MB.
[2024-08-14T21:05:00.167Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:05:01.976Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:05:03.246Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:05:05.046Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:05:05.523Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:05:06.300Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:05:07.054Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:05:07.810Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:05:07.810Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-14T21:05:07.810Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:05:08.159Z] Movies recommended for you:
[2024-08-14T21:05:08.159Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:05:08.159Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:05:08.159Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (10356.927 ms) ======
[2024-08-14T21:05:08.159Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-14T21:05:08.159Z] GC before operation: completed in 29.532 ms, heap usage 232.612 MB -> 52.462 MB.
[2024-08-14T21:05:09.374Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:05:10.137Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:05:11.345Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:05:12.123Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:05:12.872Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:05:13.642Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:05:13.994Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:05:14.757Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:05:14.757Z] 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.
[2024-08-14T21:05:14.757Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:05:14.757Z] Movies recommended for you:
[2024-08-14T21:05:14.757Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:05:14.757Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:05:14.757Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (6854.457 ms) ======
[2024-08-14T21:05:14.757Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-14T21:05:14.757Z] GC before operation: completed in 26.723 ms, heap usage 66.120 MB -> 49.105 MB.
[2024-08-14T21:05:15.990Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:05:16.754Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:05:17.979Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:05:18.752Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:05:19.517Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:05:20.282Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:05:20.649Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:05:21.418Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:05:21.418Z] 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.
[2024-08-14T21:05:21.418Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:05:21.418Z] Movies recommended for you:
[2024-08-14T21:05:21.419Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:05:21.419Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:05:21.419Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (6633.012 ms) ======
[2024-08-14T21:05:21.419Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-14T21:05:21.419Z] GC before operation: completed in 29.461 ms, heap usage 296.827 MB -> 49.814 MB.
[2024-08-14T21:05:22.639Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:05:23.398Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:05:24.639Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:05:25.859Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:05:26.208Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:05:26.973Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:05:27.324Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:05:28.097Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:05:28.097Z] 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.
[2024-08-14T21:05:28.097Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:05:28.447Z] Movies recommended for you:
[2024-08-14T21:05:28.447Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:05:28.447Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:05:28.447Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (6736.538 ms) ======
[2024-08-14T21:05:28.447Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-14T21:05:28.447Z] GC before operation: completed in 27.921 ms, heap usage 148.162 MB -> 49.968 MB.
[2024-08-14T21:05:29.208Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:05:30.429Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:05:31.670Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:05:32.426Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:05:33.195Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:05:33.545Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:05:34.304Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:05:34.663Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:05:35.011Z] 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.
[2024-08-14T21:05:35.011Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:05:35.011Z] Movies recommended for you:
[2024-08-14T21:05:35.011Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:05:35.011Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:05:35.011Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (6606.713 ms) ======
[2024-08-14T21:05:35.011Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-14T21:05:35.011Z] GC before operation: completed in 28.798 ms, heap usage 102.595 MB -> 52.289 MB.
[2024-08-14T21:05:36.231Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:05:36.983Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:05:38.204Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:05:38.954Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:05:39.309Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:05:40.057Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:05:40.811Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:05:41.184Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:05:41.184Z] 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.
[2024-08-14T21:05:41.184Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:05:41.649Z] Movies recommended for you:
[2024-08-14T21:05:41.649Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:05:41.649Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:05:41.649Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (6417.163 ms) ======
[2024-08-14T21:05:41.649Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-14T21:05:41.649Z] GC before operation: completed in 31.183 ms, heap usage 342.149 MB -> 50.357 MB.
[2024-08-14T21:05:42.401Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:05:43.613Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:05:44.362Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:05:45.593Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:05:45.948Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:05:46.696Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:05:47.458Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:05:47.813Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:05:47.813Z] 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.
[2024-08-14T21:05:47.813Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:05:47.813Z] Movies recommended for you:
[2024-08-14T21:05:47.813Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:05:47.813Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:05:47.813Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (6563.116 ms) ======
[2024-08-14T21:05:47.813Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-14T21:05:48.169Z] GC before operation: completed in 33.733 ms, heap usage 181.797 MB -> 50.435 MB.
[2024-08-14T21:05:48.924Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:05:50.140Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:05:51.361Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:05:52.585Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:05:52.935Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:05:53.689Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:05:54.442Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:05:55.197Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:05:55.197Z] 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.
[2024-08-14T21:05:55.197Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:05:55.197Z] Movies recommended for you:
[2024-08-14T21:05:55.197Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:05:55.197Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:05:55.197Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (7149.569 ms) ======
[2024-08-14T21:05:55.197Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-14T21:05:55.197Z] GC before operation: completed in 29.449 ms, heap usage 261.549 MB -> 50.645 MB.
[2024-08-14T21:05:56.416Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:05:57.675Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:05:58.437Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:05:59.188Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:05:59.940Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:06:00.712Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:06:01.069Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:06:01.833Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:06:01.833Z] 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.
[2024-08-14T21:06:01.833Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:06:01.833Z] Movies recommended for you:
[2024-08-14T21:06:01.833Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:06:01.833Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:06:01.833Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (6667.430 ms) ======
[2024-08-14T21:06:01.833Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-14T21:06:01.833Z] GC before operation: completed in 28.671 ms, heap usage 126.406 MB -> 50.520 MB.
[2024-08-14T21:06:03.061Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:06:03.826Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:06:04.600Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:06:05.826Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:06:06.173Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:06:06.927Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:06:07.693Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:06:08.059Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:06:08.059Z] 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.
[2024-08-14T21:06:08.059Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:06:08.059Z] Movies recommended for you:
[2024-08-14T21:06:08.059Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:06:08.059Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:06:08.059Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (6350.355 ms) ======
[2024-08-14T21:06:08.059Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-14T21:06:08.545Z] GC before operation: completed in 30.801 ms, heap usage 276.697 MB -> 50.621 MB.
[2024-08-14T21:06:09.297Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:06:10.523Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:06:11.275Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:06:12.508Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:06:12.874Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:06:13.629Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:06:13.985Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:06:14.753Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:06:14.753Z] 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.
[2024-08-14T21:06:14.753Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:06:14.753Z] Movies recommended for you:
[2024-08-14T21:06:14.753Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:06:14.754Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:06:14.754Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (6642.585 ms) ======
[2024-08-14T21:06:14.754Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-14T21:06:15.106Z] GC before operation: completed in 29.102 ms, heap usage 146.909 MB -> 50.244 MB.
[2024-08-14T21:06:15.865Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:06:16.610Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:06:17.835Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:06:18.601Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:06:18.948Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:06:19.705Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:06:20.057Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:06:20.412Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:06:20.767Z] 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.
[2024-08-14T21:06:20.767Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:06:20.767Z] Movies recommended for you:
[2024-08-14T21:06:20.767Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:06:20.767Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:06:20.767Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (5734.627 ms) ======
[2024-08-14T21:06:20.767Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-14T21:06:20.767Z] GC before operation: completed in 29.562 ms, heap usage 411.900 MB -> 53.992 MB.
[2024-08-14T21:06:21.521Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:06:22.284Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:06:23.516Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:06:24.277Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:06:24.634Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:06:25.398Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:06:25.746Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:06:26.512Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:06:26.512Z] 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.
[2024-08-14T21:06:26.512Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:06:26.512Z] Movies recommended for you:
[2024-08-14T21:06:26.512Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:06:26.512Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:06:26.512Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (5795.031 ms) ======
[2024-08-14T21:06:26.512Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-14T21:06:26.512Z] GC before operation: completed in 29.496 ms, heap usage 66.289 MB -> 50.489 MB.
[2024-08-14T21:06:27.258Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:06:28.482Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:06:29.248Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:06:30.019Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:06:30.769Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:06:31.522Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:06:31.878Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:06:32.633Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:06:32.633Z] 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.
[2024-08-14T21:06:32.633Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:06:32.633Z] Movies recommended for you:
[2024-08-14T21:06:32.633Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:06:32.633Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:06:32.633Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (6018.155 ms) ======
[2024-08-14T21:06:32.633Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-14T21:06:32.633Z] GC before operation: completed in 29.863 ms, heap usage 163.605 MB -> 50.326 MB.
[2024-08-14T21:06:33.389Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:06:34.615Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:06:35.843Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:06:36.597Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:06:37.352Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:06:37.721Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:06:38.477Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:06:38.866Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:06:38.866Z] 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.
[2024-08-14T21:06:38.866Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:06:38.866Z] Movies recommended for you:
[2024-08-14T21:06:38.866Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:06:38.866Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:06:38.866Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (6449.525 ms) ======
[2024-08-14T21:06:38.866Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-14T21:06:39.216Z] GC before operation: completed in 30.028 ms, heap usage 303.504 MB -> 50.746 MB.
[2024-08-14T21:06:39.974Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:06:41.185Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:06:41.938Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:06:43.168Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:06:43.524Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:06:44.285Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:06:44.636Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:06:44.991Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:06:45.348Z] 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.
[2024-08-14T21:06:45.348Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:06:45.348Z] Movies recommended for you:
[2024-08-14T21:06:45.348Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:06:45.348Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:06:45.348Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (6194.998 ms) ======
[2024-08-14T21:06:45.348Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-14T21:06:45.348Z] GC before operation: completed in 29.326 ms, heap usage 240.577 MB -> 50.712 MB.
[2024-08-14T21:06:46.565Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:06:47.321Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:06:48.576Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:06:49.324Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:06:50.077Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:06:50.839Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:06:51.190Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:06:51.954Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:06:51.954Z] 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.
[2024-08-14T21:06:51.954Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:06:51.954Z] Movies recommended for you:
[2024-08-14T21:06:51.954Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:06:51.954Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:06:51.954Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (6611.977 ms) ======
[2024-08-14T21:06:51.954Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-14T21:06:51.954Z] GC before operation: completed in 30.742 ms, heap usage 304.169 MB -> 50.742 MB.
[2024-08-14T21:06:53.162Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:06:53.913Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:06:55.137Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:06:55.890Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:06:56.642Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:06:56.998Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:06:57.745Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:06:58.504Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:06:58.504Z] 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.
[2024-08-14T21:06:58.504Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:06:58.504Z] Movies recommended for you:
[2024-08-14T21:06:58.504Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:06:58.504Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:06:58.504Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (6666.488 ms) ======
[2024-08-14T21:06:58.504Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-14T21:06:58.504Z] GC before operation: completed in 32.300 ms, heap usage 146.828 MB -> 50.599 MB.
[2024-08-14T21:06:59.722Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:07:00.498Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:07:01.751Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:07:03.001Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:07:03.351Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:07:03.705Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:07:04.475Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:07:05.252Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:07:05.252Z] 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.
[2024-08-14T21:07:05.252Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:07:05.252Z] Movies recommended for you:
[2024-08-14T21:07:05.252Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:07:05.252Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:07:05.252Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (6600.844 ms) ======
[2024-08-14T21:07:05.252Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-14T21:07:05.252Z] GC before operation: completed in 29.939 ms, heap usage 241.453 MB -> 50.793 MB.
[2024-08-14T21:07:06.000Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-14T21:07:07.367Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-14T21:07:08.131Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-14T21:07:09.352Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-14T21:07:09.706Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-14T21:07:10.462Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-14T21:07:10.819Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-14T21:07:11.566Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-14T21:07:11.566Z] 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.
[2024-08-14T21:07:11.566Z] The best model improves the baseline by 14.52%.
[2024-08-14T21:07:11.566Z] Movies recommended for you:
[2024-08-14T21:07:11.566Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-14T21:07:11.566Z] There is no way to check that no silent failure occurred.
[2024-08-14T21:07:11.566Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (6387.139 ms) ======
[2024-08-14T21:07:11.920Z] -----------------------------------
[2024-08-14T21:07:11.920Z] renaissance-movie-lens_0_PASSED
[2024-08-14T21:07:11.920Z] -----------------------------------
[2024-08-14T21:07:11.920Z]
[2024-08-14T21:07:11.920Z] TEST TEARDOWN:
[2024-08-14T21:07:11.920Z] Nothing to be done for teardown.
[2024-08-14T21:07:11.920Z] renaissance-movie-lens_0 Finish Time: Wed Aug 14 17:07:11 2024 Epoch Time (ms): 1723669631615