[2024-09-25T22:39:36.363Z] Running test renaissance-movie-lens_0 ... [2024-09-25T22:39:36.363Z] =============================================== [2024-09-25T22:39:36.363Z] renaissance-movie-lens_0 Start Time: Wed Sep 25 22:39:36 2024 Epoch Time (ms): 1727303976312 [2024-09-25T22:39:36.667Z] variation: NoOptions [2024-09-25T22:39:36.667Z] JVM_OPTIONS: [2024-09-25T22:39:36.667Z] { \ [2024-09-25T22:39:36.667Z] echo ""; echo "TEST SETUP:"; \ [2024-09-25T22:39:36.667Z] echo "Nothing to be done for setup."; \ [2024-09-25T22:39:36.667Z] mkdir -p "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17273026372534\\renaissance-movie-lens_0"; \ [2024-09-25T22:39:36.667Z] cd "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17273026372534\\renaissance-movie-lens_0"; \ [2024-09-25T22:39:36.667Z] echo ""; echo "TESTING:"; \ [2024-09-25T22:39:36.667Z] "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_17273026372534\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2024-09-25T22:39:36.667Z] 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_17273026372534\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-09-25T22:39:36.667Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-09-25T22:39:36.667Z] echo "Nothing to be done for teardown."; \ [2024-09-25T22:39:36.667Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17273026372534\\TestTargetResult"; [2024-09-25T22:39:36.984Z] [2024-09-25T22:39:36.984Z] TEST SETUP: [2024-09-25T22:39:36.984Z] Nothing to be done for setup. [2024-09-25T22:39:36.984Z] [2024-09-25T22:39:36.984Z] TESTING: [2024-09-25T22:39:47.516Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-09-25T22:39:49.097Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-09-25T22:39:51.979Z] Got 100004 ratings from 671 users on 9066 movies. [2024-09-25T22:39:52.321Z] Training: 60056, validation: 20285, test: 19854 [2024-09-25T22:39:52.321Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-09-25T22:39:52.321Z] GC before operation: completed in 64.308 ms, heap usage 75.558 MB -> 36.929 MB. [2024-09-25T22:40:05.197Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-25T22:40:13.849Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-25T22:40:20.880Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-25T22:40:27.967Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-25T22:40:32.554Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-25T22:40:36.246Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-25T22:40:40.847Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-25T22:40:44.453Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-25T22:40:44.797Z] 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. [2024-09-25T22:40:45.136Z] The best model improves the baseline by 14.52%. [2024-09-25T22:40:45.512Z] Movies recommended for you: [2024-09-25T22:40:45.512Z] WARNING: This benchmark provides no result that can be validated. [2024-09-25T22:40:45.512Z] There is no way to check that no silent failure occurred. [2024-09-25T22:40:45.512Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (52938.112 ms) ====== [2024-09-25T22:40:45.512Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-09-25T22:40:45.512Z] GC before operation: completed in 97.971 ms, heap usage 160.283 MB -> 49.804 MB. [2024-09-25T22:40:52.548Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-25T22:40:59.644Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-25T22:41:08.269Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-25T22:41:15.334Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-25T22:41:18.209Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-25T22:41:22.779Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-25T22:41:26.381Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-25T22:41:30.027Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-25T22:41:30.397Z] 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. [2024-09-25T22:41:30.397Z] The best model improves the baseline by 14.52%. [2024-09-25T22:41:30.397Z] Movies recommended for you: [2024-09-25T22:41:30.397Z] WARNING: This benchmark provides no result that can be validated. [2024-09-25T22:41:30.397Z] There is no way to check that no silent failure occurred. [2024-09-25T22:41:30.397Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (45081.879 ms) ====== [2024-09-25T22:41:30.397Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-09-25T22:41:30.731Z] GC before operation: completed in 97.457 ms, heap usage 216.071 MB -> 52.702 MB. [2024-09-25T22:41:37.781Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-25T22:41:44.882Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-25T22:41:51.931Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-25T22:41:58.980Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-25T22:42:02.602Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-25T22:42:07.170Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-25T22:42:10.799Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-25T22:42:14.516Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-25T22:42:14.516Z] 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. [2024-09-25T22:42:14.841Z] The best model improves the baseline by 14.52%. [2024-09-25T22:42:14.841Z] Movies recommended for you: [2024-09-25T22:42:14.841Z] WARNING: This benchmark provides no result that can be validated. [2024-09-25T22:42:14.841Z] There is no way to check that no silent failure occurred. [2024-09-25T22:42:14.841Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (44246.956 ms) ====== [2024-09-25T22:42:14.841Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-09-25T22:42:14.841Z] GC before operation: completed in 85.599 ms, heap usage 159.766 MB -> 52.935 MB. [2024-09-25T22:42:21.895Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-25T22:42:28.950Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-25T22:42:36.010Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-25T22:42:43.044Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-25T22:42:45.874Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-25T22:42:49.548Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-25T22:42:54.143Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-25T22:42:56.978Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-25T22:42:57.656Z] 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. [2024-09-25T22:42:57.656Z] The best model improves the baseline by 14.52%. [2024-09-25T22:42:57.656Z] Movies recommended for you: [2024-09-25T22:42:57.656Z] WARNING: This benchmark provides no result that can be validated. [2024-09-25T22:42:57.656Z] There is no way to check that no silent failure occurred. [2024-09-25T22:42:57.656Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (42814.853 ms) ====== [2024-09-25T22:42:57.656Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-09-25T22:42:57.973Z] GC before operation: completed in 91.523 ms, heap usage 197.888 MB -> 53.387 MB. [2024-09-25T22:43:05.021Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-25T22:43:12.130Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-25T22:43:19.199Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-25T22:43:26.244Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-25T22:43:29.898Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-25T22:43:33.547Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-25T22:43:37.219Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-25T22:43:40.905Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-25T22:43:41.699Z] 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. [2024-09-25T22:43:41.699Z] The best model improves the baseline by 14.52%. [2024-09-25T22:43:41.699Z] Movies recommended for you: [2024-09-25T22:43:41.699Z] WARNING: This benchmark provides no result that can be validated. [2024-09-25T22:43:41.699Z] There is no way to check that no silent failure occurred. [2024-09-25T22:43:41.699Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (43807.521 ms) ====== [2024-09-25T22:43:41.699Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-09-25T22:43:42.050Z] GC before operation: completed in 92.526 ms, heap usage 210.616 MB -> 53.554 MB. [2024-09-25T22:43:49.090Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-25T22:43:56.122Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-25T22:44:03.148Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-25T22:44:08.837Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-25T22:44:13.425Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-25T22:44:17.039Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-25T22:44:20.774Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-25T22:44:24.437Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-25T22:44:24.437Z] 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. [2024-09-25T22:44:24.437Z] The best model improves the baseline by 14.52%. [2024-09-25T22:44:24.761Z] Movies recommended for you: [2024-09-25T22:44:24.761Z] WARNING: This benchmark provides no result that can be validated. [2024-09-25T22:44:24.761Z] There is no way to check that no silent failure occurred. [2024-09-25T22:44:24.761Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (42960.641 ms) ====== [2024-09-25T22:44:24.761Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-09-25T22:44:24.761Z] GC before operation: completed in 95.392 ms, heap usage 107.197 MB -> 53.349 MB. [2024-09-25T22:44:31.825Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-25T22:44:38.881Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-25T22:44:45.908Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-25T22:44:52.937Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-25T22:44:55.782Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-25T22:44:59.409Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-25T22:45:04.005Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-25T22:45:07.627Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-25T22:45:07.627Z] 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. [2024-09-25T22:45:07.627Z] The best model improves the baseline by 14.52%. [2024-09-25T22:45:07.980Z] Movies recommended for you: [2024-09-25T22:45:07.980Z] WARNING: This benchmark provides no result that can be validated. [2024-09-25T22:45:07.980Z] There is no way to check that no silent failure occurred. [2024-09-25T22:45:07.980Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (43096.182 ms) ====== [2024-09-25T22:45:07.980Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-09-25T22:45:07.980Z] GC before operation: completed in 101.288 ms, heap usage 293.623 MB -> 53.728 MB. [2024-09-25T22:45:15.038Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-25T22:45:22.200Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-25T22:45:29.246Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-25T22:45:34.936Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-25T22:45:39.494Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-25T22:45:42.313Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-25T22:45:46.978Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-25T22:45:49.823Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-25T22:45:50.138Z] 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. [2024-09-25T22:45:50.138Z] The best model improves the baseline by 14.52%. [2024-09-25T22:45:50.452Z] Movies recommended for you: [2024-09-25T22:45:50.452Z] WARNING: This benchmark provides no result that can be validated. [2024-09-25T22:45:50.452Z] There is no way to check that no silent failure occurred. [2024-09-25T22:45:50.452Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (42432.384 ms) ====== [2024-09-25T22:45:50.452Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-09-25T22:45:50.452Z] GC before operation: completed in 89.580 ms, heap usage 82.206 MB -> 53.759 MB. [2024-09-25T22:45:57.490Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-25T22:46:04.551Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-25T22:46:11.570Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-25T22:46:18.620Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-25T22:46:21.447Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-25T22:46:26.021Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-25T22:46:29.695Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-25T22:46:33.300Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-25T22:46:33.632Z] 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. [2024-09-25T22:46:33.632Z] The best model improves the baseline by 14.52%. [2024-09-25T22:46:33.947Z] Movies recommended for you: [2024-09-25T22:46:33.947Z] WARNING: This benchmark provides no result that can be validated. [2024-09-25T22:46:33.947Z] There is no way to check that no silent failure occurred. [2024-09-25T22:46:33.947Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (43371.806 ms) ====== [2024-09-25T22:46:33.947Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-09-25T22:46:33.947Z] GC before operation: completed in 86.671 ms, heap usage 150.679 MB -> 50.486 MB. [2024-09-25T22:46:40.971Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-25T22:46:48.027Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-25T22:46:55.053Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-25T22:47:02.097Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-25T22:47:04.925Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-25T22:47:08.567Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-25T22:47:13.238Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-25T22:47:16.869Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-25T22:47:17.202Z] 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. [2024-09-25T22:47:17.203Z] The best model improves the baseline by 14.52%. [2024-09-25T22:47:17.203Z] Movies recommended for you: [2024-09-25T22:47:17.203Z] WARNING: This benchmark provides no result that can be validated. [2024-09-25T22:47:17.203Z] There is no way to check that no silent failure occurred. [2024-09-25T22:47:17.203Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (43252.316 ms) ====== [2024-09-25T22:47:17.203Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-09-25T22:47:17.203Z] GC before operation: completed in 81.074 ms, heap usage 142.857 MB -> 52.744 MB. [2024-09-25T22:47:24.303Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-25T22:47:31.349Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-25T22:47:38.400Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-25T22:47:44.166Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-25T22:47:48.736Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-25T22:47:52.397Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-25T22:47:56.018Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-25T22:48:00.612Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-25T22:48:00.612Z] 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. [2024-09-25T22:48:00.612Z] The best model improves the baseline by 14.52%. [2024-09-25T22:48:00.612Z] Movies recommended for you: [2024-09-25T22:48:00.612Z] WARNING: This benchmark provides no result that can be validated. [2024-09-25T22:48:00.612Z] There is no way to check that no silent failure occurred. [2024-09-25T22:48:00.612Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (43209.138 ms) ====== [2024-09-25T22:48:00.612Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-09-25T22:48:00.612Z] GC before operation: completed in 83.638 ms, heap usage 206.702 MB -> 50.355 MB. [2024-09-25T22:48:07.653Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-25T22:48:14.666Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-25T22:48:21.698Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-25T22:48:27.419Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-25T22:48:31.976Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-25T22:48:35.629Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-25T22:48:39.262Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-25T22:48:42.888Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-25T22:48:43.237Z] 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. [2024-09-25T22:48:43.237Z] The best model improves the baseline by 14.52%. [2024-09-25T22:48:43.237Z] Movies recommended for you: [2024-09-25T22:48:43.237Z] WARNING: This benchmark provides no result that can be validated. [2024-09-25T22:48:43.237Z] There is no way to check that no silent failure occurred. [2024-09-25T22:48:43.237Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (42736.611 ms) ====== [2024-09-25T22:48:43.237Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-09-25T22:48:43.553Z] GC before operation: completed in 86.755 ms, heap usage 245.569 MB -> 53.781 MB. [2024-09-25T22:48:50.606Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-25T22:48:57.643Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-25T22:49:04.691Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-25T22:49:10.416Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-25T22:49:14.128Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-25T22:49:17.743Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-25T22:49:22.310Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-25T22:49:25.145Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-25T22:49:25.821Z] 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. [2024-09-25T22:49:25.821Z] The best model improves the baseline by 14.52%. [2024-09-25T22:49:25.821Z] Movies recommended for you: [2024-09-25T22:49:25.821Z] WARNING: This benchmark provides no result that can be validated. [2024-09-25T22:49:25.821Z] There is no way to check that no silent failure occurred. [2024-09-25T22:49:25.821Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (42352.702 ms) ====== [2024-09-25T22:49:25.821Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-09-25T22:49:25.821Z] GC before operation: completed in 94.021 ms, heap usage 109.112 MB -> 53.849 MB. [2024-09-25T22:49:32.893Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-25T22:49:39.979Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-25T22:49:47.017Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-25T22:49:52.709Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-25T22:49:56.319Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-25T22:49:59.986Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-25T22:50:04.659Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-25T22:50:08.319Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-25T22:50:08.320Z] 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. [2024-09-25T22:50:08.320Z] The best model improves the baseline by 14.52%. [2024-09-25T22:50:08.320Z] Movies recommended for you: [2024-09-25T22:50:08.320Z] WARNING: This benchmark provides no result that can be validated. [2024-09-25T22:50:08.320Z] There is no way to check that no silent failure occurred. [2024-09-25T22:50:08.320Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (42423.761 ms) ====== [2024-09-25T22:50:08.320Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-09-25T22:50:08.320Z] GC before operation: completed in 87.245 ms, heap usage 247.041 MB -> 53.740 MB. [2024-09-25T22:50:15.370Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-25T22:50:22.406Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-25T22:50:29.448Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-25T22:50:35.157Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-25T22:50:38.784Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-25T22:50:42.548Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-25T22:50:46.180Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-25T22:50:49.805Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-25T22:50:50.130Z] 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. [2024-09-25T22:50:50.446Z] The best model improves the baseline by 14.52%. [2024-09-25T22:50:50.446Z] Movies recommended for you: [2024-09-25T22:50:50.446Z] WARNING: This benchmark provides no result that can be validated. [2024-09-25T22:50:50.446Z] There is no way to check that no silent failure occurred. [2024-09-25T22:50:50.446Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (42027.291 ms) ====== [2024-09-25T22:50:50.446Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-09-25T22:50:50.446Z] GC before operation: completed in 89.707 ms, heap usage 147.594 MB -> 53.792 MB. [2024-09-25T22:50:57.480Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-25T22:51:04.542Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-25T22:51:11.609Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-25T22:51:17.317Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-25T22:51:21.882Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-25T22:51:25.533Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-25T22:51:29.156Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-25T22:51:32.805Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-25T22:51:33.122Z] 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. [2024-09-25T22:51:33.122Z] The best model improves the baseline by 14.52%. [2024-09-25T22:51:33.455Z] Movies recommended for you: [2024-09-25T22:51:33.455Z] WARNING: This benchmark provides no result that can be validated. [2024-09-25T22:51:33.455Z] There is no way to check that no silent failure occurred. [2024-09-25T22:51:33.456Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (42828.435 ms) ====== [2024-09-25T22:51:33.456Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-09-25T22:51:33.456Z] GC before operation: completed in 99.931 ms, heap usage 127.489 MB -> 50.628 MB. [2024-09-25T22:51:40.511Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-25T22:51:47.552Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-25T22:51:54.578Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-25T22:52:00.281Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-25T22:52:04.867Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-25T22:52:08.525Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-25T22:52:13.100Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-25T22:52:15.911Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-25T22:52:16.612Z] 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. [2024-09-25T22:52:16.612Z] The best model improves the baseline by 14.52%. [2024-09-25T22:52:16.612Z] Movies recommended for you: [2024-09-25T22:52:16.612Z] WARNING: This benchmark provides no result that can be validated. [2024-09-25T22:52:16.612Z] There is no way to check that no silent failure occurred. [2024-09-25T22:52:16.612Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (43194.132 ms) ====== [2024-09-25T22:52:16.612Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-09-25T22:52:16.612Z] GC before operation: completed in 82.423 ms, heap usage 160.297 MB -> 50.531 MB. [2024-09-25T22:52:23.663Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-25T22:52:30.708Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-25T22:52:37.748Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-25T22:52:44.815Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-25T22:52:47.744Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-25T22:52:52.326Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-25T22:52:55.957Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-25T22:52:59.593Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-25T22:52:59.910Z] 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. [2024-09-25T22:52:59.910Z] The best model improves the baseline by 14.52%. [2024-09-25T22:53:00.233Z] Movies recommended for you: [2024-09-25T22:53:00.233Z] WARNING: This benchmark provides no result that can be validated. [2024-09-25T22:53:00.233Z] There is no way to check that no silent failure occurred. [2024-09-25T22:53:00.233Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (43422.672 ms) ====== [2024-09-25T22:53:00.233Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-09-25T22:53:00.233Z] GC before operation: completed in 99.865 ms, heap usage 97.919 MB -> 50.518 MB. [2024-09-25T22:53:07.285Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-25T22:53:14.328Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-25T22:53:21.414Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-25T22:53:27.112Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-25T22:53:30.751Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-25T22:53:35.356Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-25T22:53:38.970Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-25T22:53:42.594Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-25T22:53:42.971Z] 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. [2024-09-25T22:53:42.971Z] The best model improves the baseline by 14.52%. [2024-09-25T22:53:42.971Z] Movies recommended for you: [2024-09-25T22:53:42.971Z] WARNING: This benchmark provides no result that can be validated. [2024-09-25T22:53:42.971Z] There is no way to check that no silent failure occurred. [2024-09-25T22:53:42.971Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (42707.613 ms) ====== [2024-09-25T22:53:42.971Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-09-25T22:53:42.971Z] GC before operation: completed in 88.653 ms, heap usage 189.758 MB -> 53.974 MB. [2024-09-25T22:53:50.026Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-25T22:53:57.072Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-25T22:54:04.132Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-25T22:54:11.177Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-25T22:54:14.855Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-25T22:54:18.479Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-25T22:54:22.144Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-25T22:54:25.808Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-25T22:54:26.479Z] 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. [2024-09-25T22:54:26.479Z] The best model improves the baseline by 14.52%. [2024-09-25T22:54:26.479Z] Movies recommended for you: [2024-09-25T22:54:26.479Z] WARNING: This benchmark provides no result that can be validated. [2024-09-25T22:54:26.479Z] There is no way to check that no silent failure occurred. [2024-09-25T22:54:26.479Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (43482.602 ms) ====== [2024-09-25T22:54:27.146Z] ----------------------------------- [2024-09-25T22:54:27.146Z] renaissance-movie-lens_0_PASSED [2024-09-25T22:54:27.146Z] ----------------------------------- [2024-09-25T22:54:27.447Z] [2024-09-25T22:54:27.447Z] TEST TEARDOWN: [2024-09-25T22:54:27.447Z] Nothing to be done for teardown. [2024-09-25T22:54:27.447Z] renaissance-movie-lens_0 Finish Time: Wed Sep 25 22:54:27 2024 Epoch Time (ms): 1727304867322