[2024-08-01T08:38:23.618Z] Running test renaissance-movie-lens_0 ... [2024-08-01T08:38:23.618Z] =============================================== [2024-08-01T08:38:23.937Z] renaissance-movie-lens_0 Start Time: Thu Aug 1 08:38:23 2024 Epoch Time (ms): 1722501503645 [2024-08-01T08:38:23.937Z] variation: NoOptions [2024-08-01T08:38:23.937Z] JVM_OPTIONS: [2024-08-01T08:38:23.937Z] { \ [2024-08-01T08:38:23.937Z] echo ""; echo "TEST SETUP:"; \ [2024-08-01T08:38:23.937Z] echo "Nothing to be done for setup."; \ [2024-08-01T08:38:23.937Z] mkdir -p "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17225001842933\\renaissance-movie-lens_0"; \ [2024-08-01T08:38:23.937Z] cd "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17225001842933\\renaissance-movie-lens_0"; \ [2024-08-01T08:38:23.937Z] echo ""; echo "TESTING:"; \ [2024-08-01T08:38:23.937Z] "c:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows_testList_0/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_testList_0/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17225001842933\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2024-08-01T08:38:23.937Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17225001842933\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-01T08:38:23.937Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-01T08:38:23.937Z] echo "Nothing to be done for teardown."; \ [2024-08-01T08:38:23.938Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17225001842933\\TestTargetResult"; [2024-08-01T08:38:24.265Z] [2024-08-01T08:38:24.265Z] TEST SETUP: [2024-08-01T08:38:24.265Z] Nothing to be done for setup. [2024-08-01T08:38:24.265Z] [2024-08-01T08:38:24.265Z] TESTING: [2024-08-01T08:38:37.161Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-01T08:38:37.161Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-08-01T08:38:41.006Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-01T08:38:41.006Z] Training: 60056, validation: 20285, test: 19854 [2024-08-01T08:38:41.006Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-01T08:38:41.006Z] GC before operation: completed in 68.058 ms, heap usage 108.032 MB -> 36.953 MB. [2024-08-01T08:38:54.122Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T08:39:02.843Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T08:39:11.564Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T08:39:18.690Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T08:39:22.377Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T08:39:27.001Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T08:39:31.679Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T08:39:35.358Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T08:39:35.701Z] 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. [2024-08-01T08:39:36.023Z] The best model improves the baseline by 14.52%. [2024-08-01T08:39:36.023Z] Movies recommended for you: [2024-08-01T08:39:36.023Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T08:39:36.023Z] There is no way to check that no silent failure occurred. [2024-08-01T08:39:36.023Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (55256.841 ms) ====== [2024-08-01T08:39:36.023Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-01T08:39:36.023Z] GC before operation: completed in 92.345 ms, heap usage 132.795 MB -> 47.304 MB. [2024-08-01T08:39:44.742Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T08:39:51.871Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T08:39:59.005Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T08:40:06.182Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T08:40:10.798Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T08:40:14.495Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T08:40:19.124Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T08:40:23.849Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T08:40:23.849Z] 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. [2024-08-01T08:40:23.849Z] The best model improves the baseline by 14.52%. [2024-08-01T08:40:23.849Z] Movies recommended for you: [2024-08-01T08:40:23.849Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T08:40:23.849Z] There is no way to check that no silent failure occurred. [2024-08-01T08:40:23.849Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (47780.738 ms) ====== [2024-08-01T08:40:23.849Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-01T08:40:24.174Z] GC before operation: completed in 86.270 ms, heap usage 181.839 MB -> 49.572 MB. [2024-08-01T08:40:31.367Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T08:40:40.081Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T08:40:47.210Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T08:40:52.974Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T08:40:57.606Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T08:41:01.279Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T08:41:05.954Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T08:41:09.639Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T08:41:10.335Z] 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. [2024-08-01T08:41:10.335Z] The best model improves the baseline by 14.52%. [2024-08-01T08:41:10.335Z] Movies recommended for you: [2024-08-01T08:41:10.335Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T08:41:10.335Z] There is no way to check that no silent failure occurred. [2024-08-01T08:41:10.335Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (46303.154 ms) ====== [2024-08-01T08:41:10.335Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-01T08:41:10.335Z] GC before operation: completed in 82.519 ms, heap usage 150.273 MB -> 49.803 MB. [2024-08-01T08:41:17.447Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T08:41:26.159Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T08:41:33.324Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T08:41:40.455Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T08:41:44.129Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T08:41:47.808Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T08:41:52.441Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T08:41:56.113Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T08:41:56.541Z] 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. [2024-08-01T08:41:56.541Z] The best model improves the baseline by 14.52%. [2024-08-01T08:41:56.541Z] Movies recommended for you: [2024-08-01T08:41:56.541Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T08:41:56.541Z] There is no way to check that no silent failure occurred. [2024-08-01T08:41:56.541Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (46077.413 ms) ====== [2024-08-01T08:41:56.541Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-01T08:41:56.541Z] GC before operation: completed in 86.382 ms, heap usage 227.591 MB -> 53.422 MB. [2024-08-01T08:42:05.255Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T08:42:12.392Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T08:42:19.529Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T08:42:26.625Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T08:42:30.324Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T08:42:33.987Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T08:42:38.622Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T08:42:42.288Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T08:42:42.685Z] 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. [2024-08-01T08:42:42.685Z] The best model improves the baseline by 14.52%. [2024-08-01T08:42:42.685Z] Movies recommended for you: [2024-08-01T08:42:42.685Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T08:42:42.685Z] There is no way to check that no silent failure occurred. [2024-08-01T08:42:42.685Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (46082.750 ms) ====== [2024-08-01T08:42:42.685Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-01T08:42:42.685Z] GC before operation: completed in 89.497 ms, heap usage 220.291 MB -> 53.587 MB. [2024-08-01T08:42:49.861Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T08:42:57.008Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T08:43:04.145Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T08:43:11.279Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T08:43:15.929Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T08:43:19.599Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T08:43:23.281Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T08:43:27.908Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T08:43:27.908Z] 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. [2024-08-01T08:43:27.908Z] The best model improves the baseline by 14.52%. [2024-08-01T08:43:27.908Z] Movies recommended for you: [2024-08-01T08:43:27.908Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T08:43:27.908Z] There is no way to check that no silent failure occurred. [2024-08-01T08:43:27.908Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (45041.779 ms) ====== [2024-08-01T08:43:27.908Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-01T08:43:27.908Z] GC before operation: completed in 93.877 ms, heap usage 215.169 MB -> 53.547 MB. [2024-08-01T08:43:35.037Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T08:43:42.155Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T08:43:49.270Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T08:43:56.377Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T08:44:00.058Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T08:44:03.718Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T08:44:07.377Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T08:44:12.089Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T08:44:12.089Z] 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. [2024-08-01T08:44:12.089Z] The best model improves the baseline by 14.52%. [2024-08-01T08:44:12.089Z] Movies recommended for you: [2024-08-01T08:44:12.089Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T08:44:12.090Z] There is no way to check that no silent failure occurred. [2024-08-01T08:44:12.090Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (44169.121 ms) ====== [2024-08-01T08:44:12.090Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-01T08:44:12.090Z] GC before operation: completed in 88.603 ms, heap usage 213.074 MB -> 53.663 MB. [2024-08-01T08:44:19.280Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T08:44:26.377Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T08:44:33.489Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T08:44:40.584Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T08:44:44.260Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T08:44:47.912Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T08:44:51.593Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T08:44:55.268Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T08:44:55.595Z] 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. [2024-08-01T08:44:55.915Z] The best model improves the baseline by 14.52%. [2024-08-01T08:44:55.915Z] Movies recommended for you: [2024-08-01T08:44:55.915Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T08:44:55.915Z] There is no way to check that no silent failure occurred. [2024-08-01T08:44:55.915Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (43730.959 ms) ====== [2024-08-01T08:44:55.915Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-01T08:44:55.915Z] GC before operation: completed in 87.275 ms, heap usage 261.570 MB -> 54.030 MB. [2024-08-01T08:45:03.017Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T08:45:10.134Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T08:45:17.242Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T08:45:24.322Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T08:45:27.999Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T08:45:31.662Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T08:45:36.300Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T08:45:40.011Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T08:45:40.011Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-01T08:45:40.011Z] The best model improves the baseline by 14.52%. [2024-08-01T08:45:40.011Z] Movies recommended for you: [2024-08-01T08:45:40.011Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T08:45:40.011Z] There is no way to check that no silent failure occurred. [2024-08-01T08:45:40.011Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (44138.697 ms) ====== [2024-08-01T08:45:40.011Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-01T08:45:40.330Z] GC before operation: completed in 90.278 ms, heap usage 228.372 MB -> 53.816 MB. [2024-08-01T08:45:47.429Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T08:45:54.555Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T08:46:01.638Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T08:46:08.759Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T08:46:11.629Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T08:46:15.321Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T08:46:19.953Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T08:46:23.628Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T08:46:23.628Z] 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. [2024-08-01T08:46:23.628Z] The best model improves the baseline by 14.52%. [2024-08-01T08:46:23.954Z] Movies recommended for you: [2024-08-01T08:46:23.954Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T08:46:23.954Z] There is no way to check that no silent failure occurred. [2024-08-01T08:46:23.954Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (43667.668 ms) ====== [2024-08-01T08:46:23.954Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-01T08:46:23.954Z] GC before operation: completed in 93.405 ms, heap usage 259.916 MB -> 53.963 MB. [2024-08-01T08:46:31.083Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T08:46:38.194Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T08:46:45.311Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T08:46:52.399Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T08:46:56.078Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T08:46:59.767Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T08:47:03.439Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T08:47:07.102Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T08:47:07.789Z] 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. [2024-08-01T08:47:07.789Z] The best model improves the baseline by 14.52%. [2024-08-01T08:47:07.789Z] Movies recommended for you: [2024-08-01T08:47:07.789Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T08:47:07.789Z] There is no way to check that no silent failure occurred. [2024-08-01T08:47:07.789Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (43802.757 ms) ====== [2024-08-01T08:47:07.789Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-01T08:47:07.789Z] GC before operation: completed in 98.452 ms, heap usage 229.967 MB -> 53.656 MB. [2024-08-01T08:47:14.910Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T08:47:22.025Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T08:47:29.126Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T08:47:36.264Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T08:47:39.981Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T08:47:43.649Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T08:47:48.288Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T08:47:51.959Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T08:47:51.959Z] 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. [2024-08-01T08:47:51.959Z] The best model improves the baseline by 14.52%. [2024-08-01T08:47:52.283Z] Movies recommended for you: [2024-08-01T08:47:52.283Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T08:47:52.283Z] There is no way to check that no silent failure occurred. [2024-08-01T08:47:52.283Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (44410.050 ms) ====== [2024-08-01T08:47:52.283Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-01T08:47:52.283Z] GC before operation: completed in 88.187 ms, heap usage 109.055 MB -> 56.032 MB. [2024-08-01T08:47:59.407Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T08:48:06.532Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T08:48:13.674Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T08:48:20.778Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T08:48:24.439Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T08:48:29.053Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T08:48:32.716Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T08:48:37.377Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T08:48:37.377Z] 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. [2024-08-01T08:48:37.377Z] The best model improves the baseline by 14.52%. [2024-08-01T08:48:37.377Z] Movies recommended for you: [2024-08-01T08:48:37.377Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T08:48:37.377Z] There is no way to check that no silent failure occurred. [2024-08-01T08:48:37.377Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (44870.857 ms) ====== [2024-08-01T08:48:37.377Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-01T08:48:37.377Z] GC before operation: completed in 85.399 ms, heap usage 128.771 MB -> 50.674 MB. [2024-08-01T08:48:44.485Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T08:48:51.576Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T08:48:58.726Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T08:49:04.581Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T08:49:09.219Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T08:49:12.905Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T08:49:17.518Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T08:49:21.193Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T08:49:21.193Z] 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. [2024-08-01T08:49:21.193Z] The best model improves the baseline by 14.52%. [2024-08-01T08:49:21.193Z] Movies recommended for you: [2024-08-01T08:49:21.193Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T08:49:21.193Z] There is no way to check that no silent failure occurred. [2024-08-01T08:49:21.193Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (43930.094 ms) ====== [2024-08-01T08:49:21.193Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-01T08:49:21.193Z] GC before operation: completed in 81.336 ms, heap usage 104.842 MB -> 50.429 MB. [2024-08-01T08:49:28.304Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T08:49:35.471Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T08:49:44.202Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T08:49:49.972Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T08:49:53.694Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T08:49:57.374Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T08:50:02.038Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T08:50:05.716Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T08:50:06.036Z] 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. [2024-08-01T08:50:06.036Z] The best model improves the baseline by 14.52%. [2024-08-01T08:50:06.372Z] Movies recommended for you: [2024-08-01T08:50:06.372Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T08:50:06.372Z] There is no way to check that no silent failure occurred. [2024-08-01T08:50:06.372Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (44957.330 ms) ====== [2024-08-01T08:50:06.372Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-01T08:50:06.372Z] GC before operation: completed in 82.464 ms, heap usage 98.200 MB -> 52.763 MB. [2024-08-01T08:50:13.505Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T08:50:20.620Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T08:50:27.748Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T08:50:34.857Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T08:50:38.530Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T08:50:42.221Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T08:50:46.828Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T08:50:50.520Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T08:50:50.520Z] 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. [2024-08-01T08:50:50.520Z] The best model improves the baseline by 14.52%. [2024-08-01T08:50:50.520Z] Movies recommended for you: [2024-08-01T08:50:50.520Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T08:50:50.520Z] There is no way to check that no silent failure occurred. [2024-08-01T08:50:50.520Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (44216.562 ms) ====== [2024-08-01T08:50:50.520Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-01T08:50:50.868Z] GC before operation: completed in 99.000 ms, heap usage 241.538 MB -> 54.012 MB. [2024-08-01T08:50:57.971Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T08:51:05.094Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T08:51:12.199Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T08:51:17.958Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T08:51:21.637Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T08:51:25.298Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T08:51:29.930Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T08:51:33.616Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T08:51:33.941Z] 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. [2024-08-01T08:51:33.941Z] The best model improves the baseline by 14.52%. [2024-08-01T08:51:33.941Z] Movies recommended for you: [2024-08-01T08:51:33.941Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T08:51:33.941Z] There is no way to check that no silent failure occurred. [2024-08-01T08:51:33.941Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (43326.333 ms) ====== [2024-08-01T08:51:33.941Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-01T08:51:34.262Z] GC before operation: completed in 93.511 ms, heap usage 85.516 MB -> 53.709 MB. [2024-08-01T08:51:41.351Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T08:51:48.455Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T08:51:55.577Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T08:52:01.324Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T08:52:05.942Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T08:52:09.639Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T08:52:13.338Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T08:52:17.005Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T08:52:17.738Z] 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. [2024-08-01T08:52:17.738Z] The best model improves the baseline by 14.52%. [2024-08-01T08:52:17.738Z] Movies recommended for you: [2024-08-01T08:52:17.738Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T08:52:17.738Z] There is no way to check that no silent failure occurred. [2024-08-01T08:52:17.738Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (43610.256 ms) ====== [2024-08-01T08:52:17.738Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-01T08:52:17.738Z] GC before operation: completed in 91.564 ms, heap usage 213.468 MB -> 53.913 MB. [2024-08-01T08:52:24.836Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T08:52:31.948Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T08:52:39.068Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T08:52:46.177Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T08:52:49.852Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T08:52:53.541Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T08:52:57.251Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T08:53:00.965Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T08:53:01.346Z] 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. [2024-08-01T08:53:01.346Z] The best model improves the baseline by 14.52%. [2024-08-01T08:53:01.667Z] Movies recommended for you: [2024-08-01T08:53:01.667Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T08:53:01.667Z] There is no way to check that no silent failure occurred. [2024-08-01T08:53:01.667Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (43628.787 ms) ====== [2024-08-01T08:53:01.667Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-01T08:53:01.667Z] GC before operation: completed in 89.197 ms, heap usage 188.177 MB -> 54.057 MB. [2024-08-01T08:53:08.761Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T08:53:15.870Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T08:53:24.596Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T08:53:30.416Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T08:53:34.118Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T08:53:37.792Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T08:53:42.432Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T08:53:46.124Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T08:53:46.803Z] 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. [2024-08-01T08:53:46.803Z] The best model improves the baseline by 14.52%. [2024-08-01T08:53:46.803Z] Movies recommended for you: [2024-08-01T08:53:46.803Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T08:53:46.803Z] There is no way to check that no silent failure occurred. [2024-08-01T08:53:46.803Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (45351.414 ms) ====== [2024-08-01T08:53:47.487Z] ----------------------------------- [2024-08-01T08:53:47.487Z] renaissance-movie-lens_0_PASSED [2024-08-01T08:53:47.487Z] ----------------------------------- [2024-08-01T08:53:47.807Z] [2024-08-01T08:53:47.807Z] TEST TEARDOWN: [2024-08-01T08:53:47.807Z] Nothing to be done for teardown. [2024-08-01T08:53:48.129Z] renaissance-movie-lens_0 Finish Time: Thu Aug 1 08:53:47 2024 Epoch Time (ms): 1722502427882