[2025-02-06T05:54:17.505Z] Running test renaissance-movie-lens_0 ... [2025-02-06T05:54:17.505Z] =============================================== [2025-02-06T05:54:17.821Z] renaissance-movie-lens_0 Start Time: Thu Feb 6 05:54:17 2025 Epoch Time (ms): 1738821257548 [2025-02-06T05:54:17.821Z] variation: NoOptions [2025-02-06T05:54:18.155Z] JVM_OPTIONS: [2025-02-06T05:54:18.155Z] { \ [2025-02-06T05:54:18.155Z] echo ""; echo "TEST SETUP:"; \ [2025-02-06T05:54:18.155Z] echo "Nothing to be done for setup."; \ [2025-02-06T05:54:18.155Z] mkdir -p "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17388201555792\\renaissance-movie-lens_0"; \ [2025-02-06T05:54:18.155Z] cd "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17388201555792\\renaissance-movie-lens_0"; \ [2025-02-06T05:54:18.155Z] echo ""; echo "TESTING:"; \ [2025-02-06T05:54:18.155Z] "c:/jenkins/workspace/Test_openjdk17_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_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17388201555792\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2025-02-06T05:54:18.155Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17388201555792\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-02-06T05:54:18.155Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-02-06T05:54:18.155Z] echo "Nothing to be done for teardown."; \ [2025-02-06T05:54:18.155Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17388201555792\\TestTargetResult"; [2025-02-06T05:54:18.155Z] [2025-02-06T05:54:18.155Z] TEST SETUP: [2025-02-06T05:54:18.156Z] Nothing to be done for setup. [2025-02-06T05:54:18.156Z] [2025-02-06T05:54:18.156Z] TESTING: [2025-02-06T05:54:33.755Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2025-02-06T05:54:34.090Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-02-06T05:54:37.881Z] Got 100004 ratings from 671 users on 9066 movies. [2025-02-06T05:54:38.206Z] Training: 60056, validation: 20285, test: 19854 [2025-02-06T05:54:38.206Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-02-06T05:54:38.206Z] GC before operation: completed in 68.652 ms, heap usage 60.358 MB -> 37.537 MB. [2025-02-06T05:54:51.188Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-06T05:54:59.964Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-06T05:55:10.646Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-06T05:55:17.768Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-06T05:55:22.397Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-06T05:55:28.155Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-06T05:55:32.780Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-06T05:55:37.467Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-06T05:55:37.809Z] 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. [2025-02-06T05:55:37.809Z] The best model improves the baseline by 14.52%. [2025-02-06T05:55:38.167Z] Movies recommended for you: [2025-02-06T05:55:38.167Z] WARNING: This benchmark provides no result that can be validated. [2025-02-06T05:55:38.167Z] There is no way to check that no silent failure occurred. [2025-02-06T05:55:38.167Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (59937.687 ms) ====== [2025-02-06T05:55:38.167Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-02-06T05:55:38.167Z] GC before operation: completed in 77.079 ms, heap usage 165.888 MB -> 57.798 MB. [2025-02-06T05:55:46.885Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-06T05:55:55.677Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-06T05:56:02.807Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-06T05:56:11.534Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-06T05:56:15.210Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-06T05:56:19.867Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-06T05:56:24.492Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-06T05:56:29.133Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-06T05:56:29.133Z] 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. [2025-02-06T05:56:29.133Z] The best model improves the baseline by 14.52%. [2025-02-06T05:56:29.133Z] Movies recommended for you: [2025-02-06T05:56:29.133Z] WARNING: This benchmark provides no result that can be validated. [2025-02-06T05:56:29.133Z] There is no way to check that no silent failure occurred. [2025-02-06T05:56:29.133Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (51161.953 ms) ====== [2025-02-06T05:56:29.133Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-02-06T05:56:29.458Z] GC before operation: completed in 71.018 ms, heap usage 219.474 MB -> 49.980 MB. [2025-02-06T05:56:38.155Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-06T05:56:45.266Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-06T05:56:53.967Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-06T05:57:01.073Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-06T05:57:04.734Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-06T05:57:09.399Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-06T05:57:14.021Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-06T05:57:18.648Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-06T05:57:18.648Z] 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. [2025-02-06T05:57:18.648Z] The best model improves the baseline by 14.52%. [2025-02-06T05:57:18.971Z] Movies recommended for you: [2025-02-06T05:57:18.971Z] WARNING: This benchmark provides no result that can be validated. [2025-02-06T05:57:18.971Z] There is no way to check that no silent failure occurred. [2025-02-06T05:57:18.971Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (49627.913 ms) ====== [2025-02-06T05:57:18.971Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-02-06T05:57:18.971Z] GC before operation: completed in 65.400 ms, heap usage 225.086 MB -> 50.276 MB. [2025-02-06T05:57:27.673Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-06T05:57:34.792Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-06T05:57:43.491Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-06T05:57:50.601Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-06T05:57:55.224Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-06T05:57:58.902Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-06T05:58:03.542Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-06T05:58:08.175Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-06T05:58:08.498Z] 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. [2025-02-06T05:58:08.498Z] The best model improves the baseline by 14.52%. [2025-02-06T05:58:08.498Z] Movies recommended for you: [2025-02-06T05:58:08.498Z] WARNING: This benchmark provides no result that can be validated. [2025-02-06T05:58:08.498Z] There is no way to check that no silent failure occurred. [2025-02-06T05:58:08.498Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (49578.070 ms) ====== [2025-02-06T05:58:08.498Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-02-06T05:58:08.498Z] GC before operation: completed in 66.067 ms, heap usage 93.746 MB -> 50.540 MB. [2025-02-06T05:58:17.201Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-06T05:58:24.327Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-06T05:58:33.062Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-06T05:58:40.188Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-06T05:58:44.799Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-06T05:58:49.440Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-06T05:58:54.058Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-06T05:58:58.693Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-06T05:58:58.693Z] 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. [2025-02-06T05:58:58.693Z] The best model improves the baseline by 14.52%. [2025-02-06T05:58:59.015Z] Movies recommended for you: [2025-02-06T05:58:59.015Z] WARNING: This benchmark provides no result that can be validated. [2025-02-06T05:58:59.015Z] There is no way to check that no silent failure occurred. [2025-02-06T05:58:59.015Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (50357.875 ms) ====== [2025-02-06T05:58:59.015Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-02-06T05:58:59.015Z] GC before operation: completed in 67.515 ms, heap usage 206.664 MB -> 50.829 MB. [2025-02-06T05:59:07.702Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-06T05:59:14.853Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-06T05:59:23.568Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-06T05:59:30.730Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-06T05:59:35.379Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-06T05:59:40.030Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-06T05:59:45.825Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-06T05:59:49.502Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-06T05:59:49.827Z] 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. [2025-02-06T05:59:49.827Z] The best model improves the baseline by 14.52%. [2025-02-06T05:59:49.827Z] Movies recommended for you: [2025-02-06T05:59:49.827Z] WARNING: This benchmark provides no result that can be validated. [2025-02-06T05:59:49.827Z] There is no way to check that no silent failure occurred. [2025-02-06T05:59:49.827Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (50791.554 ms) ====== [2025-02-06T05:59:49.827Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-02-06T05:59:49.827Z] GC before operation: completed in 69.347 ms, heap usage 59.123 MB -> 50.696 MB. [2025-02-06T05:59:58.545Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-06T06:00:05.670Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-06T06:00:14.439Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-06T06:00:21.552Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-06T06:00:26.206Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-06T06:00:30.833Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-06T06:00:35.468Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-06T06:00:39.133Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-06T06:00:39.848Z] 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. [2025-02-06T06:00:39.848Z] The best model improves the baseline by 14.52%. [2025-02-06T06:00:40.188Z] Movies recommended for you: [2025-02-06T06:00:40.188Z] WARNING: This benchmark provides no result that can be validated. [2025-02-06T06:00:40.188Z] There is no way to check that no silent failure occurred. [2025-02-06T06:00:40.188Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (50082.517 ms) ====== [2025-02-06T06:00:40.188Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-02-06T06:00:40.188Z] GC before operation: completed in 69.698 ms, heap usage 193.412 MB -> 50.958 MB. [2025-02-06T06:00:48.927Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-06T06:00:56.011Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-06T06:01:04.754Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-06T06:01:11.833Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-06T06:01:15.503Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-06T06:01:20.129Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-06T06:01:24.760Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-06T06:01:29.391Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-06T06:01:29.391Z] 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. [2025-02-06T06:01:29.391Z] The best model improves the baseline by 14.52%. [2025-02-06T06:01:29.391Z] Movies recommended for you: [2025-02-06T06:01:29.391Z] WARNING: This benchmark provides no result that can be validated. [2025-02-06T06:01:29.391Z] There is no way to check that no silent failure occurred. [2025-02-06T06:01:29.391Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (49376.963 ms) ====== [2025-02-06T06:01:29.391Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-02-06T06:01:29.391Z] GC before operation: completed in 65.078 ms, heap usage 272.574 MB -> 51.325 MB. [2025-02-06T06:01:38.110Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-06T06:01:45.217Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-06T06:01:53.917Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-06T06:01:59.676Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-06T06:02:04.316Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-06T06:02:08.977Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-06T06:02:12.665Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-06T06:02:17.302Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-06T06:02:17.302Z] 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. [2025-02-06T06:02:17.639Z] The best model improves the baseline by 14.52%. [2025-02-06T06:02:17.639Z] Movies recommended for you: [2025-02-06T06:02:17.639Z] WARNING: This benchmark provides no result that can be validated. [2025-02-06T06:02:17.639Z] There is no way to check that no silent failure occurred. [2025-02-06T06:02:17.639Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (48086.874 ms) ====== [2025-02-06T06:02:17.639Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-02-06T06:02:17.639Z] GC before operation: completed in 71.045 ms, heap usage 390.307 MB -> 51.283 MB. [2025-02-06T06:02:26.347Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-06T06:02:33.474Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-06T06:02:42.192Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-06T06:02:49.296Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-06T06:02:52.960Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-06T06:02:57.589Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-06T06:03:02.305Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-06T06:03:05.958Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-06T06:03:06.680Z] 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. [2025-02-06T06:03:06.680Z] The best model improves the baseline by 14.52%. [2025-02-06T06:03:06.680Z] Movies recommended for you: [2025-02-06T06:03:06.680Z] WARNING: This benchmark provides no result that can be validated. [2025-02-06T06:03:06.680Z] There is no way to check that no silent failure occurred. [2025-02-06T06:03:06.680Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (49090.944 ms) ====== [2025-02-06T06:03:06.680Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-02-06T06:03:06.999Z] GC before operation: completed in 66.973 ms, heap usage 261.942 MB -> 51.325 MB. [2025-02-06T06:03:15.710Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-06T06:03:22.817Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-06T06:03:29.932Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-06T06:03:38.653Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-06T06:03:42.326Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-06T06:03:46.946Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-06T06:03:51.575Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-06T06:03:55.240Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-06T06:03:55.933Z] 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. [2025-02-06T06:03:55.933Z] The best model improves the baseline by 14.52%. [2025-02-06T06:03:55.933Z] Movies recommended for you: [2025-02-06T06:03:55.933Z] WARNING: This benchmark provides no result that can be validated. [2025-02-06T06:03:55.933Z] There is no way to check that no silent failure occurred. [2025-02-06T06:03:55.933Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (49117.382 ms) ====== [2025-02-06T06:03:55.933Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-02-06T06:03:55.933Z] GC before operation: completed in 65.823 ms, heap usage 221.180 MB -> 51.014 MB. [2025-02-06T06:04:04.688Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-06T06:04:11.792Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-06T06:04:20.502Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-06T06:04:27.646Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-06T06:04:31.336Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-06T06:04:35.955Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-06T06:04:40.576Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-06T06:04:44.240Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-06T06:04:44.926Z] 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. [2025-02-06T06:04:44.926Z] The best model improves the baseline by 14.52%. [2025-02-06T06:04:44.926Z] Movies recommended for you: [2025-02-06T06:04:44.926Z] WARNING: This benchmark provides no result that can be validated. [2025-02-06T06:04:44.926Z] There is no way to check that no silent failure occurred. [2025-02-06T06:04:44.926Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (48869.334 ms) ====== [2025-02-06T06:04:44.926Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-02-06T06:04:44.926Z] GC before operation: completed in 66.366 ms, heap usage 103.267 MB -> 51.126 MB. [2025-02-06T06:04:53.650Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-06T06:05:00.750Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-06T06:05:07.857Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-06T06:05:16.555Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-06T06:05:20.236Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-06T06:05:23.907Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-06T06:05:28.519Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-06T06:05:33.148Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-06T06:05:33.853Z] 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. [2025-02-06T06:05:33.853Z] The best model improves the baseline by 14.52%. [2025-02-06T06:05:33.853Z] Movies recommended for you: [2025-02-06T06:05:33.853Z] WARNING: This benchmark provides no result that can be validated. [2025-02-06T06:05:33.853Z] There is no way to check that no silent failure occurred. [2025-02-06T06:05:33.853Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (48844.721 ms) ====== [2025-02-06T06:05:33.853Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-02-06T06:05:33.853Z] GC before operation: completed in 67.963 ms, heap usage 220.299 MB -> 51.378 MB. [2025-02-06T06:05:42.564Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-06T06:05:49.681Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-06T06:05:58.405Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-06T06:06:05.552Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-06T06:06:09.229Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-06T06:06:13.845Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-06T06:06:18.470Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-06T06:06:23.145Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-06T06:06:23.145Z] 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. [2025-02-06T06:06:23.145Z] The best model improves the baseline by 14.52%. [2025-02-06T06:06:23.145Z] Movies recommended for you: [2025-02-06T06:06:23.145Z] WARNING: This benchmark provides no result that can be validated. [2025-02-06T06:06:23.145Z] There is no way to check that no silent failure occurred. [2025-02-06T06:06:23.145Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (49244.999 ms) ====== [2025-02-06T06:06:23.145Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-02-06T06:06:23.145Z] GC before operation: completed in 70.783 ms, heap usage 189.447 MB -> 51.094 MB. [2025-02-06T06:06:31.852Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-06T06:06:38.976Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-06T06:06:46.114Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-06T06:06:54.816Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-06T06:06:58.507Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-06T06:07:02.168Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-06T06:07:06.805Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-06T06:07:10.505Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-06T06:07:11.199Z] 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. [2025-02-06T06:07:11.199Z] The best model improves the baseline by 14.52%. [2025-02-06T06:07:11.535Z] Movies recommended for you: [2025-02-06T06:07:11.535Z] WARNING: This benchmark provides no result that can be validated. [2025-02-06T06:07:11.535Z] There is no way to check that no silent failure occurred. [2025-02-06T06:07:11.535Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (48211.479 ms) ====== [2025-02-06T06:07:11.535Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-02-06T06:07:11.535Z] GC before operation: completed in 85.390 ms, heap usage 278.832 MB -> 51.387 MB. [2025-02-06T06:07:18.647Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-06T06:07:27.359Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-06T06:07:34.515Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-06T06:07:43.224Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-06T06:07:46.099Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-06T06:07:50.739Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-06T06:07:55.413Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-06T06:07:59.079Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-06T06:07:59.778Z] 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. [2025-02-06T06:07:59.778Z] The best model improves the baseline by 14.52%. [2025-02-06T06:07:59.778Z] Movies recommended for you: [2025-02-06T06:07:59.778Z] WARNING: This benchmark provides no result that can be validated. [2025-02-06T06:07:59.778Z] There is no way to check that no silent failure occurred. [2025-02-06T06:07:59.778Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (48363.942 ms) ====== [2025-02-06T06:07:59.778Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-02-06T06:08:00.100Z] GC before operation: completed in 70.595 ms, heap usage 134.987 MB -> 51.356 MB. [2025-02-06T06:08:08.824Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-06T06:08:15.953Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-06T06:08:24.699Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-06T06:08:30.451Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-06T06:08:35.067Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-06T06:08:39.683Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-06T06:08:44.324Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-06T06:08:48.014Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-06T06:08:48.333Z] 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. [2025-02-06T06:08:48.333Z] The best model improves the baseline by 14.52%. [2025-02-06T06:08:48.664Z] Movies recommended for you: [2025-02-06T06:08:48.664Z] WARNING: This benchmark provides no result that can be validated. [2025-02-06T06:08:48.664Z] There is no way to check that no silent failure occurred. [2025-02-06T06:08:48.664Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (48622.023 ms) ====== [2025-02-06T06:08:48.664Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-02-06T06:08:48.664Z] GC before operation: completed in 69.637 ms, heap usage 229.904 MB -> 51.329 MB. [2025-02-06T06:08:57.372Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-06T06:09:04.494Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-06T06:09:11.596Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-06T06:09:20.311Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-06T06:09:23.984Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-06T06:09:27.682Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-06T06:09:33.448Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-06T06:09:37.126Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-06T06:09:37.465Z] 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. [2025-02-06T06:09:37.465Z] The best model improves the baseline by 14.52%. [2025-02-06T06:09:37.465Z] Movies recommended for you: [2025-02-06T06:09:37.465Z] WARNING: This benchmark provides no result that can be validated. [2025-02-06T06:09:37.465Z] There is no way to check that no silent failure occurred. [2025-02-06T06:09:37.465Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (48920.658 ms) ====== [2025-02-06T06:09:37.465Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-02-06T06:09:37.787Z] GC before operation: completed in 73.655 ms, heap usage 210.271 MB -> 51.352 MB. [2025-02-06T06:09:46.518Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-06T06:09:53.597Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-06T06:10:00.739Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-06T06:10:07.926Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-06T06:10:12.569Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-06T06:10:17.230Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-06T06:10:21.846Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-06T06:10:25.543Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-06T06:10:26.277Z] 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. [2025-02-06T06:10:26.277Z] The best model improves the baseline by 14.52%. [2025-02-06T06:10:26.600Z] Movies recommended for you: [2025-02-06T06:10:26.600Z] WARNING: This benchmark provides no result that can be validated. [2025-02-06T06:10:26.600Z] There is no way to check that no silent failure occurred. [2025-02-06T06:10:26.600Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (48744.895 ms) ====== [2025-02-06T06:10:26.600Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-02-06T06:10:26.600Z] GC before operation: completed in 66.851 ms, heap usage 334.775 MB -> 51.603 MB. [2025-02-06T06:10:33.705Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-06T06:10:42.434Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-06T06:10:49.532Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-06T06:10:58.237Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-06T06:11:01.975Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-06T06:11:05.647Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-06T06:11:10.287Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-06T06:11:14.904Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-06T06:11:15.229Z] 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. [2025-02-06T06:11:15.229Z] The best model improves the baseline by 14.52%. [2025-02-06T06:11:15.229Z] Movies recommended for you: [2025-02-06T06:11:15.229Z] WARNING: This benchmark provides no result that can be validated. [2025-02-06T06:11:15.229Z] There is no way to check that no silent failure occurred. [2025-02-06T06:11:15.229Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (48883.208 ms) ====== [2025-02-06T06:11:15.915Z] ----------------------------------- [2025-02-06T06:11:15.915Z] renaissance-movie-lens_0_PASSED [2025-02-06T06:11:15.915Z] ----------------------------------- [2025-02-06T06:11:16.597Z] [2025-02-06T06:11:16.597Z] TEST TEARDOWN: [2025-02-06T06:11:16.597Z] Nothing to be done for teardown. [2025-02-06T06:11:16.597Z] renaissance-movie-lens_0 Finish Time: Thu Feb 6 06:11:16 2025 Epoch Time (ms): 1738822276466