[2025-01-22T15:17:15.968Z] Running test renaissance-movie-lens_0 ... [2025-01-22T15:17:15.968Z] =============================================== [2025-01-22T15:17:16.279Z] renaissance-movie-lens_0 Start Time: Wed Jan 22 15:17:16 2025 Epoch Time (ms): 1737559036079 [2025-01-22T15:17:16.279Z] variation: NoOptions [2025-01-22T15:17:16.624Z] JVM_OPTIONS: [2025-01-22T15:17:16.624Z] { \ [2025-01-22T15:17:16.624Z] echo ""; echo "TEST SETUP:"; \ [2025-01-22T15:17:16.624Z] echo "Nothing to be done for setup."; \ [2025-01-22T15:17:16.624Z] mkdir -p "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17375575473055\\renaissance-movie-lens_0"; \ [2025-01-22T15:17:16.624Z] cd "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17375575473055\\renaissance-movie-lens_0"; \ [2025-01-22T15:17:16.624Z] echo ""; echo "TESTING:"; \ [2025-01-22T15:17:16.624Z] "c:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/jdkbinary/j2sdk-image\\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 "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17375575473055\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2025-01-22T15:17:16.624Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17375575473055\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-01-22T15:17:16.624Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-01-22T15:17:16.624Z] echo "Nothing to be done for teardown."; \ [2025-01-22T15:17:16.624Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17375575473055\\TestTargetResult"; [2025-01-22T15:17:16.624Z] [2025-01-22T15:17:16.624Z] TEST SETUP: [2025-01-22T15:17:16.624Z] Nothing to be done for setup. [2025-01-22T15:17:16.624Z] [2025-01-22T15:17:16.624Z] TESTING: [2025-01-22T15:17:32.258Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2025-01-22T15:17:33.476Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-01-22T15:17:37.278Z] Got 100004 ratings from 671 users on 9066 movies. [2025-01-22T15:17:37.278Z] Training: 60056, validation: 20285, test: 19854 [2025-01-22T15:17:37.278Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-01-22T15:17:37.278Z] GC before operation: completed in 73.438 ms, heap usage 71.388 MB -> 36.925 MB. [2025-01-22T15:17:53.104Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-22T15:18:01.898Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-22T15:18:12.628Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-22T15:18:19.744Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-22T15:18:25.590Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-22T15:18:30.276Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-22T15:18:36.065Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-22T15:18:40.720Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-22T15:18:40.720Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-22T15:18:41.063Z] The best model improves the baseline by 14.52%. [2025-01-22T15:18:41.063Z] Movies recommended for you: [2025-01-22T15:18:41.063Z] WARNING: This benchmark provides no result that can be validated. [2025-01-22T15:18:41.063Z] There is no way to check that no silent failure occurred. [2025-01-22T15:18:41.063Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (63822.224 ms) ====== [2025-01-22T15:18:41.063Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-01-22T15:18:41.396Z] GC before operation: completed in 105.518 ms, heap usage 140.320 MB -> 50.865 MB. [2025-01-22T15:18:50.101Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-22T15:18:58.836Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-22T15:19:09.468Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-22T15:19:16.589Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-22T15:19:21.239Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-22T15:19:25.891Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-22T15:19:30.543Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-22T15:19:36.327Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-22T15:19:36.327Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-22T15:19:36.327Z] The best model improves the baseline by 14.52%. [2025-01-22T15:19:36.327Z] Movies recommended for you: [2025-01-22T15:19:36.327Z] WARNING: This benchmark provides no result that can be validated. [2025-01-22T15:19:36.327Z] There is no way to check that no silent failure occurred. [2025-01-22T15:19:36.327Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (54910.855 ms) ====== [2025-01-22T15:19:36.327Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-01-22T15:19:36.327Z] GC before operation: completed in 99.365 ms, heap usage 242.150 MB -> 52.806 MB. [2025-01-22T15:19:45.055Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-22T15:19:53.782Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-22T15:20:02.516Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-22T15:20:11.239Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-22T15:20:14.911Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-22T15:20:19.575Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-22T15:20:25.347Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-22T15:20:29.960Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-22T15:20:29.960Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-22T15:20:29.960Z] The best model improves the baseline by 14.52%. [2025-01-22T15:20:30.285Z] Movies recommended for you: [2025-01-22T15:20:30.285Z] WARNING: This benchmark provides no result that can be validated. [2025-01-22T15:20:30.285Z] There is no way to check that no silent failure occurred. [2025-01-22T15:20:30.285Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (53994.240 ms) ====== [2025-01-22T15:20:30.285Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-01-22T15:20:30.285Z] GC before operation: completed in 104.877 ms, heap usage 187.575 MB -> 49.848 MB. [2025-01-22T15:20:39.012Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-22T15:20:49.694Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-22T15:20:56.932Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-22T15:21:05.679Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-22T15:21:11.437Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-22T15:21:16.085Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-22T15:21:20.723Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-22T15:21:25.401Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-22T15:21:26.145Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-22T15:21:26.145Z] The best model improves the baseline by 14.52%. [2025-01-22T15:21:26.548Z] Movies recommended for you: [2025-01-22T15:21:26.548Z] WARNING: This benchmark provides no result that can be validated. [2025-01-22T15:21:26.548Z] There is no way to check that no silent failure occurred. [2025-01-22T15:21:26.548Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (55939.038 ms) ====== [2025-01-22T15:21:26.548Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-01-22T15:21:26.548Z] GC before operation: completed in 112.835 ms, heap usage 162.523 MB -> 50.133 MB. [2025-01-22T15:21:35.382Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-22T15:21:44.145Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-22T15:21:52.875Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-22T15:21:59.994Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-22T15:22:04.640Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-22T15:22:09.279Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-22T15:22:13.917Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-22T15:22:18.578Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-22T15:22:18.978Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-22T15:22:18.978Z] The best model improves the baseline by 14.52%. [2025-01-22T15:22:18.978Z] Movies recommended for you: [2025-01-22T15:22:18.978Z] WARNING: This benchmark provides no result that can be validated. [2025-01-22T15:22:18.978Z] There is no way to check that no silent failure occurred. [2025-01-22T15:22:18.978Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (52586.750 ms) ====== [2025-01-22T15:22:18.978Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-01-22T15:22:19.308Z] GC before operation: completed in 103.979 ms, heap usage 237.994 MB -> 53.619 MB. [2025-01-22T15:22:28.107Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-22T15:22:35.285Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-22T15:22:44.008Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-22T15:22:52.955Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-22T15:22:56.634Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-22T15:23:01.272Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-22T15:23:05.926Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-22T15:23:10.580Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-22T15:23:10.952Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-22T15:23:10.952Z] The best model improves the baseline by 14.52%. [2025-01-22T15:23:10.952Z] Movies recommended for you: [2025-01-22T15:23:10.952Z] WARNING: This benchmark provides no result that can be validated. [2025-01-22T15:23:10.952Z] There is no way to check that no silent failure occurred. [2025-01-22T15:23:10.952Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (51946.442 ms) ====== [2025-01-22T15:23:10.952Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-01-22T15:23:11.286Z] GC before operation: completed in 98.394 ms, heap usage 213.780 MB -> 53.476 MB. [2025-01-22T15:23:20.066Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-22T15:23:28.766Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-22T15:23:37.543Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-22T15:23:44.709Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-22T15:23:49.373Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-22T15:23:54.113Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-22T15:23:59.873Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-22T15:24:04.587Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-22T15:24:04.587Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-22T15:24:04.587Z] The best model improves the baseline by 14.52%. [2025-01-22T15:24:04.587Z] Movies recommended for you: [2025-01-22T15:24:04.587Z] WARNING: This benchmark provides no result that can be validated. [2025-01-22T15:24:04.587Z] There is no way to check that no silent failure occurred. [2025-01-22T15:24:04.587Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (53562.001 ms) ====== [2025-01-22T15:24:04.587Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-01-22T15:24:04.936Z] GC before operation: completed in 101.054 ms, heap usage 96.246 MB -> 50.362 MB. [2025-01-22T15:24:13.661Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-22T15:24:22.379Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-22T15:24:31.080Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-22T15:24:39.795Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-22T15:24:43.463Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-22T15:24:48.097Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-22T15:24:53.916Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-22T15:24:58.546Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-22T15:24:58.546Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-22T15:24:58.546Z] The best model improves the baseline by 14.52%. [2025-01-22T15:24:58.875Z] Movies recommended for you: [2025-01-22T15:24:58.875Z] WARNING: This benchmark provides no result that can be validated. [2025-01-22T15:24:58.875Z] There is no way to check that no silent failure occurred. [2025-01-22T15:24:58.875Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (54002.660 ms) ====== [2025-01-22T15:24:58.875Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-01-22T15:24:58.876Z] GC before operation: completed in 117.365 ms, heap usage 62.335 MB -> 50.646 MB. [2025-01-22T15:25:07.610Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-22T15:25:16.343Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-22T15:25:25.076Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-22T15:25:33.784Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-22T15:25:38.429Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-22T15:25:42.124Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-22T15:25:47.916Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-22T15:25:52.551Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-22T15:25:52.901Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-22T15:25:52.901Z] The best model improves the baseline by 14.52%. [2025-01-22T15:25:52.901Z] Movies recommended for you: [2025-01-22T15:25:52.901Z] WARNING: This benchmark provides no result that can be validated. [2025-01-22T15:25:52.901Z] There is no way to check that no silent failure occurred. [2025-01-22T15:25:52.901Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (54027.153 ms) ====== [2025-01-22T15:25:52.901Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-01-22T15:25:53.239Z] GC before operation: completed in 101.160 ms, heap usage 241.508 MB -> 50.549 MB. [2025-01-22T15:26:01.948Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-22T15:26:10.675Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-22T15:26:19.436Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-22T15:26:28.183Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-22T15:26:31.951Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-22T15:26:36.592Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-22T15:26:42.368Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-22T15:26:46.070Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-22T15:26:46.772Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-22T15:26:46.772Z] The best model improves the baseline by 14.52%. [2025-01-22T15:26:46.772Z] Movies recommended for you: [2025-01-22T15:26:46.772Z] WARNING: This benchmark provides no result that can be validated. [2025-01-22T15:26:46.772Z] There is no way to check that no silent failure occurred. [2025-01-22T15:26:46.772Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (53774.974 ms) ====== [2025-01-22T15:26:46.772Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-01-22T15:26:46.772Z] GC before operation: completed in 99.889 ms, heap usage 127.535 MB -> 50.571 MB. [2025-01-22T15:26:55.509Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-22T15:27:04.257Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-22T15:27:12.957Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-22T15:27:21.670Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-22T15:27:25.357Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-22T15:27:29.999Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-22T15:27:35.818Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-22T15:27:40.452Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-22T15:27:40.452Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-22T15:27:40.452Z] The best model improves the baseline by 14.52%. [2025-01-22T15:27:40.797Z] Movies recommended for you: [2025-01-22T15:27:40.797Z] WARNING: This benchmark provides no result that can be validated. [2025-01-22T15:27:40.797Z] There is no way to check that no silent failure occurred. [2025-01-22T15:27:40.797Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (53797.343 ms) ====== [2025-01-22T15:27:40.797Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-01-22T15:27:40.797Z] GC before operation: completed in 109.503 ms, heap usage 164.544 MB -> 50.366 MB. [2025-01-22T15:27:49.499Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-22T15:27:58.214Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-22T15:28:06.922Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-22T15:28:15.676Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-22T15:28:19.365Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-22T15:28:24.033Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-22T15:28:29.815Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-22T15:28:33.549Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-22T15:28:34.278Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-22T15:28:34.278Z] The best model improves the baseline by 14.52%. [2025-01-22T15:28:34.278Z] Movies recommended for you: [2025-01-22T15:28:34.278Z] WARNING: This benchmark provides no result that can be validated. [2025-01-22T15:28:34.278Z] There is no way to check that no silent failure occurred. [2025-01-22T15:28:34.278Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (53395.625 ms) ====== [2025-01-22T15:28:34.278Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-01-22T15:28:34.278Z] GC before operation: completed in 103.390 ms, heap usage 240.323 MB -> 53.804 MB. [2025-01-22T15:28:43.011Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-22T15:28:51.818Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-22T15:29:00.565Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-22T15:29:09.281Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-22T15:29:13.911Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-22T15:29:18.557Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-22T15:29:23.203Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-22T15:29:27.846Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-22T15:29:28.183Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-22T15:29:28.516Z] The best model improves the baseline by 14.52%. [2025-01-22T15:29:28.516Z] Movies recommended for you: [2025-01-22T15:29:28.516Z] WARNING: This benchmark provides no result that can be validated. [2025-01-22T15:29:28.516Z] There is no way to check that no silent failure occurred. [2025-01-22T15:29:28.516Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (54193.267 ms) ====== [2025-01-22T15:29:28.516Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-01-22T15:29:28.516Z] GC before operation: completed in 108.738 ms, heap usage 84.238 MB -> 50.601 MB. [2025-01-22T15:29:37.265Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-22T15:29:46.019Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-22T15:29:54.760Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-22T15:30:03.513Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-22T15:30:08.180Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-22T15:30:12.807Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-22T15:30:18.601Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-22T15:30:22.303Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-22T15:30:23.005Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-22T15:30:23.005Z] The best model improves the baseline by 14.52%. [2025-01-22T15:30:23.005Z] Movies recommended for you: [2025-01-22T15:30:23.005Z] WARNING: This benchmark provides no result that can be validated. [2025-01-22T15:30:23.005Z] There is no way to check that no silent failure occurred. [2025-01-22T15:30:23.005Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (54353.071 ms) ====== [2025-01-22T15:30:23.005Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-01-22T15:30:23.005Z] GC before operation: completed in 103.211 ms, heap usage 211.989 MB -> 50.482 MB. [2025-01-22T15:30:31.777Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-22T15:30:40.501Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-22T15:30:49.279Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-22T15:30:57.983Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-22T15:31:02.634Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-22T15:31:07.270Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-22T15:31:12.075Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-22T15:31:16.711Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-22T15:31:16.711Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-22T15:31:17.043Z] The best model improves the baseline by 14.52%. [2025-01-22T15:31:17.043Z] Movies recommended for you: [2025-01-22T15:31:17.043Z] WARNING: This benchmark provides no result that can be validated. [2025-01-22T15:31:17.043Z] There is no way to check that no silent failure occurred. [2025-01-22T15:31:17.043Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (54006.315 ms) ====== [2025-01-22T15:31:17.043Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-01-22T15:31:17.043Z] GC before operation: completed in 94.592 ms, heap usage 117.610 MB -> 50.576 MB. [2025-01-22T15:31:25.807Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-22T15:31:34.567Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-22T15:31:43.328Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-22T15:31:52.066Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-22T15:31:56.697Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-22T15:32:01.322Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-22T15:32:07.102Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-22T15:32:10.812Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-22T15:32:11.536Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-22T15:32:11.536Z] The best model improves the baseline by 14.52%. [2025-01-22T15:32:11.536Z] Movies recommended for you: [2025-01-22T15:32:11.536Z] WARNING: This benchmark provides no result that can be validated. [2025-01-22T15:32:11.536Z] There is no way to check that no silent failure occurred. [2025-01-22T15:32:11.536Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (54387.404 ms) ====== [2025-01-22T15:32:11.536Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-01-22T15:32:11.880Z] GC before operation: completed in 133.748 ms, heap usage 117.738 MB -> 50.703 MB. [2025-01-22T15:32:22.484Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-22T15:32:29.604Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-22T15:32:38.373Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-22T15:32:47.092Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-22T15:32:51.735Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-22T15:32:56.376Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-22T15:33:01.040Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-22T15:33:06.828Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-22T15:33:06.828Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-22T15:33:06.828Z] The best model improves the baseline by 14.52%. [2025-01-22T15:33:06.828Z] Movies recommended for you: [2025-01-22T15:33:06.828Z] WARNING: This benchmark provides no result that can be validated. [2025-01-22T15:33:06.828Z] There is no way to check that no silent failure occurred. [2025-01-22T15:33:06.828Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (55019.587 ms) ====== [2025-01-22T15:33:06.828Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-01-22T15:33:06.828Z] GC before operation: completed in 108.974 ms, heap usage 67.592 MB -> 50.434 MB. [2025-01-22T15:33:15.543Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-22T15:33:24.250Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-22T15:33:33.011Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-22T15:33:41.747Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-22T15:33:45.424Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-22T15:33:50.132Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-22T15:33:55.919Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-22T15:34:00.537Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-22T15:34:00.537Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-22T15:34:00.537Z] The best model improves the baseline by 14.52%. [2025-01-22T15:34:00.879Z] Movies recommended for you: [2025-01-22T15:34:00.879Z] WARNING: This benchmark provides no result that can be validated. [2025-01-22T15:34:00.879Z] There is no way to check that no silent failure occurred. [2025-01-22T15:34:00.879Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (53917.782 ms) ====== [2025-01-22T15:34:00.879Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-01-22T15:34:00.879Z] GC before operation: completed in 100.669 ms, heap usage 136.638 MB -> 52.354 MB. [2025-01-22T15:34:09.658Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-22T15:34:18.428Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-22T15:34:27.128Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-22T15:34:34.234Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-22T15:34:40.000Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-22T15:34:44.650Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-22T15:34:49.307Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-22T15:34:53.943Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-22T15:34:54.285Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-22T15:34:54.285Z] The best model improves the baseline by 14.52%. [2025-01-22T15:34:54.646Z] Movies recommended for you: [2025-01-22T15:34:54.646Z] WARNING: This benchmark provides no result that can be validated. [2025-01-22T15:34:54.646Z] There is no way to check that no silent failure occurred. [2025-01-22T15:34:54.646Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (53742.482 ms) ====== [2025-01-22T15:34:54.646Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-01-22T15:34:54.646Z] GC before operation: completed in 99.264 ms, heap usage 92.497 MB -> 50.729 MB. [2025-01-22T15:35:03.399Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-22T15:35:12.125Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-22T15:35:20.863Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-22T15:35:27.980Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-22T15:35:33.749Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-22T15:35:37.421Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-22T15:35:42.068Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-22T15:35:46.719Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-22T15:35:47.427Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-22T15:35:47.427Z] The best model improves the baseline by 14.52%. [2025-01-22T15:35:47.427Z] Movies recommended for you: [2025-01-22T15:35:47.427Z] WARNING: This benchmark provides no result that can be validated. [2025-01-22T15:35:47.427Z] There is no way to check that no silent failure occurred. [2025-01-22T15:35:47.427Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (52772.612 ms) ====== [2025-01-22T15:35:48.122Z] ----------------------------------- [2025-01-22T15:35:48.122Z] renaissance-movie-lens_0_PASSED [2025-01-22T15:35:48.122Z] ----------------------------------- [2025-01-22T15:35:48.809Z] [2025-01-22T15:35:48.809Z] TEST TEARDOWN: [2025-01-22T15:35:48.809Z] Nothing to be done for teardown. [2025-01-22T15:35:48.809Z] renaissance-movie-lens_0 Finish Time: Wed Jan 22 15:35:48 2025 Epoch Time (ms): 1737560148682