[2024-11-28T07:38:33.334Z] Running test renaissance-movie-lens_0 ... [2024-11-28T07:38:33.334Z] =============================================== [2024-11-28T07:38:33.650Z] renaissance-movie-lens_0 Start Time: Thu Nov 28 07:38:33 2024 Epoch Time (ms): 1732779513474 [2024-11-28T07:38:33.650Z] variation: NoOptions [2024-11-28T07:38:33.991Z] JVM_OPTIONS: [2024-11-28T07:38:33.991Z] { \ [2024-11-28T07:38:33.991Z] echo ""; echo "TEST SETUP:"; \ [2024-11-28T07:38:33.991Z] echo "Nothing to be done for setup."; \ [2024-11-28T07:38:33.991Z] mkdir -p "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17327785319577\\renaissance-movie-lens_0"; \ [2024-11-28T07:38:33.991Z] cd "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17327785319577\\renaissance-movie-lens_0"; \ [2024-11-28T07:38:33.991Z] echo ""; echo "TESTING:"; \ [2024-11-28T07:38:33.991Z] "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_17327785319577\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2024-11-28T07:38:33.991Z] 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_17327785319577\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-11-28T07:38:33.991Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-11-28T07:38:33.991Z] echo "Nothing to be done for teardown."; \ [2024-11-28T07:38:33.991Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17327785319577\\TestTargetResult"; [2024-11-28T07:38:33.991Z] [2024-11-28T07:38:33.991Z] TEST SETUP: [2024-11-28T07:38:33.991Z] Nothing to be done for setup. [2024-11-28T07:38:33.991Z] [2024-11-28T07:38:33.991Z] TESTING: [2024-11-28T07:38:44.714Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-11-28T07:38:46.948Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-11-28T07:38:50.010Z] Got 100004 ratings from 671 users on 9066 movies. [2024-11-28T07:38:50.010Z] Training: 60056, validation: 20285, test: 19854 [2024-11-28T07:38:50.010Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-11-28T07:38:50.010Z] GC before operation: completed in 51.031 ms, heap usage 116.733 MB -> 37.461 MB. [2024-11-28T07:39:03.153Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-28T07:39:10.362Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-28T07:39:19.192Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-28T07:39:25.032Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-28T07:39:29.750Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-28T07:39:34.453Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-28T07:39:38.216Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-28T07:39:42.902Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-28T07:39:42.902Z] 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. [2024-11-28T07:39:42.902Z] The best model improves the baseline by 14.52%. [2024-11-28T07:39:42.902Z] Movies recommended for you: [2024-11-28T07:39:42.902Z] WARNING: This benchmark provides no result that can be validated. [2024-11-28T07:39:42.902Z] There is no way to check that no silent failure occurred. [2024-11-28T07:39:42.902Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (52896.386 ms) ====== [2024-11-28T07:39:42.902Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-11-28T07:39:42.902Z] GC before operation: completed in 64.413 ms, heap usage 222.712 MB -> 58.497 MB. [2024-11-28T07:39:50.087Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-28T07:39:57.267Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-28T07:40:04.435Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-28T07:40:11.591Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-28T07:40:14.519Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-28T07:40:19.193Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-28T07:40:22.899Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-28T07:40:26.619Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-28T07:40:26.945Z] 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. [2024-11-28T07:40:26.945Z] The best model improves the baseline by 14.52%. [2024-11-28T07:40:27.283Z] Movies recommended for you: [2024-11-28T07:40:27.283Z] WARNING: This benchmark provides no result that can be validated. [2024-11-28T07:40:27.283Z] There is no way to check that no silent failure occurred. [2024-11-28T07:40:27.283Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (44122.002 ms) ====== [2024-11-28T07:40:27.283Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-11-28T07:40:27.283Z] GC before operation: completed in 57.190 ms, heap usage 174.601 MB -> 50.035 MB. [2024-11-28T07:40:34.458Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-28T07:40:41.620Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-28T07:40:48.762Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-28T07:40:54.556Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-28T07:40:58.281Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-28T07:41:02.006Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-28T07:41:06.690Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-28T07:41:09.596Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-28T07:41:10.298Z] 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. [2024-11-28T07:41:10.298Z] The best model improves the baseline by 14.52%. [2024-11-28T07:41:10.298Z] Movies recommended for you: [2024-11-28T07:41:10.298Z] WARNING: This benchmark provides no result that can be validated. [2024-11-28T07:41:10.298Z] There is no way to check that no silent failure occurred. [2024-11-28T07:41:10.298Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (43130.936 ms) ====== [2024-11-28T07:41:10.298Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-11-28T07:41:10.298Z] GC before operation: completed in 57.348 ms, heap usage 197.045 MB -> 50.463 MB. [2024-11-28T07:41:17.502Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-28T07:41:24.664Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-28T07:41:30.507Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-28T07:41:37.732Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-28T07:41:41.434Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-28T07:41:45.162Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-28T07:41:48.872Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-28T07:41:53.539Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-28T07:41:53.539Z] 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. [2024-11-28T07:41:53.539Z] The best model improves the baseline by 14.52%. [2024-11-28T07:41:53.539Z] Movies recommended for you: [2024-11-28T07:41:53.539Z] WARNING: This benchmark provides no result that can be validated. [2024-11-28T07:41:53.539Z] There is no way to check that no silent failure occurred. [2024-11-28T07:41:53.539Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (43044.700 ms) ====== [2024-11-28T07:41:53.539Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-11-28T07:41:53.539Z] GC before operation: completed in 58.784 ms, heap usage 141.735 MB -> 50.730 MB. [2024-11-28T07:42:00.705Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-28T07:42:06.529Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-28T07:42:13.730Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-28T07:42:20.895Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-28T07:42:24.600Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-28T07:42:28.386Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-28T07:42:32.094Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-28T07:42:35.800Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-28T07:42:36.133Z] 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. [2024-11-28T07:42:36.133Z] The best model improves the baseline by 14.52%. [2024-11-28T07:42:36.473Z] Movies recommended for you: [2024-11-28T07:42:36.473Z] WARNING: This benchmark provides no result that can be validated. [2024-11-28T07:42:36.473Z] There is no way to check that no silent failure occurred. [2024-11-28T07:42:36.473Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (42956.939 ms) ====== [2024-11-28T07:42:36.473Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-11-28T07:42:36.473Z] GC before operation: completed in 57.855 ms, heap usage 128.720 MB -> 50.909 MB. [2024-11-28T07:42:43.657Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-28T07:42:49.474Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-28T07:42:56.642Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-28T07:43:03.819Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-28T07:43:06.736Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-28T07:43:10.463Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-28T07:43:14.167Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-28T07:43:17.875Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-28T07:43:18.222Z] 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. [2024-11-28T07:43:18.222Z] The best model improves the baseline by 14.52%. [2024-11-28T07:43:18.555Z] Movies recommended for you: [2024-11-28T07:43:18.555Z] WARNING: This benchmark provides no result that can be validated. [2024-11-28T07:43:18.555Z] There is no way to check that no silent failure occurred. [2024-11-28T07:43:18.555Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (41950.295 ms) ====== [2024-11-28T07:43:18.555Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-11-28T07:43:18.555Z] GC before operation: completed in 75.875 ms, heap usage 102.097 MB -> 50.936 MB. [2024-11-28T07:43:25.741Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-28T07:43:31.564Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-28T07:43:38.723Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-28T07:43:45.901Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-28T07:43:49.638Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-28T07:43:53.444Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-28T07:43:57.166Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-28T07:44:00.903Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-28T07:44:01.230Z] 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. [2024-11-28T07:44:01.230Z] The best model improves the baseline by 14.52%. [2024-11-28T07:44:01.230Z] Movies recommended for you: [2024-11-28T07:44:01.230Z] WARNING: This benchmark provides no result that can be validated. [2024-11-28T07:44:01.230Z] There is no way to check that no silent failure occurred. [2024-11-28T07:44:01.230Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (42735.602 ms) ====== [2024-11-28T07:44:01.230Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-11-28T07:44:01.230Z] GC before operation: completed in 59.281 ms, heap usage 315.372 MB -> 51.225 MB. [2024-11-28T07:44:08.398Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-28T07:44:14.301Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-28T07:44:21.498Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-28T07:44:27.293Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-28T07:44:31.951Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-28T07:44:34.835Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-28T07:44:39.494Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-28T07:44:43.201Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-28T07:44:43.201Z] 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. [2024-11-28T07:44:43.201Z] The best model improves the baseline by 14.52%. [2024-11-28T07:44:43.201Z] Movies recommended for you: [2024-11-28T07:44:43.201Z] WARNING: This benchmark provides no result that can be validated. [2024-11-28T07:44:43.201Z] There is no way to check that no silent failure occurred. [2024-11-28T07:44:43.201Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (41862.060 ms) ====== [2024-11-28T07:44:43.201Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-11-28T07:44:43.201Z] GC before operation: completed in 60.448 ms, heap usage 185.258 MB -> 51.372 MB. [2024-11-28T07:44:50.352Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-28T07:44:56.165Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-28T07:45:04.942Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-28T07:45:10.740Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-28T07:45:14.473Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-28T07:45:18.174Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-28T07:45:21.894Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-28T07:45:25.619Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-28T07:45:25.619Z] 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. [2024-11-28T07:45:25.619Z] The best model improves the baseline by 14.52%. [2024-11-28T07:45:25.948Z] Movies recommended for you: [2024-11-28T07:45:25.948Z] WARNING: This benchmark provides no result that can be validated. [2024-11-28T07:45:25.948Z] There is no way to check that no silent failure occurred. [2024-11-28T07:45:25.948Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (42586.821 ms) ====== [2024-11-28T07:45:25.948Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-11-28T07:45:25.948Z] GC before operation: completed in 58.526 ms, heap usage 336.656 MB -> 51.342 MB. [2024-11-28T07:45:33.110Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-28T07:45:38.923Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-28T07:45:46.097Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-28T07:45:51.921Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-28T07:45:56.606Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-28T07:46:00.329Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-28T07:46:04.042Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-28T07:46:07.757Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-28T07:46:07.757Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-11-28T07:46:07.757Z] The best model improves the baseline by 14.52%. [2024-11-28T07:46:08.092Z] Movies recommended for you: [2024-11-28T07:46:08.092Z] WARNING: This benchmark provides no result that can be validated. [2024-11-28T07:46:08.092Z] There is no way to check that no silent failure occurred. [2024-11-28T07:46:08.092Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (42074.740 ms) ====== [2024-11-28T07:46:08.092Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-11-28T07:46:08.092Z] GC before operation: completed in 59.946 ms, heap usage 209.989 MB -> 51.275 MB. [2024-11-28T07:46:15.245Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-28T07:46:21.051Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-28T07:46:28.228Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-28T07:46:35.386Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-28T07:46:38.305Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-28T07:46:42.006Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-28T07:46:45.713Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-28T07:46:49.419Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-28T07:46:50.126Z] 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. [2024-11-28T07:46:50.126Z] The best model improves the baseline by 14.52%. [2024-11-28T07:46:50.126Z] Movies recommended for you: [2024-11-28T07:46:50.126Z] WARNING: This benchmark provides no result that can be validated. [2024-11-28T07:46:50.126Z] There is no way to check that no silent failure occurred. [2024-11-28T07:46:50.126Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (42053.839 ms) ====== [2024-11-28T07:46:50.126Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-11-28T07:46:50.126Z] GC before operation: completed in 58.716 ms, heap usage 203.211 MB -> 51.031 MB. [2024-11-28T07:46:57.277Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-28T07:47:03.110Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-28T07:47:10.292Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-28T07:47:16.178Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-28T07:47:19.914Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-28T07:47:23.639Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-28T07:47:28.406Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-28T07:47:31.363Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-28T07:47:31.698Z] 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. [2024-11-28T07:47:31.698Z] The best model improves the baseline by 14.52%. [2024-11-28T07:47:32.027Z] Movies recommended for you: [2024-11-28T07:47:32.027Z] WARNING: This benchmark provides no result that can be validated. [2024-11-28T07:47:32.027Z] There is no way to check that no silent failure occurred. [2024-11-28T07:47:32.027Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (41827.428 ms) ====== [2024-11-28T07:47:32.027Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-11-28T07:47:32.027Z] GC before operation: completed in 59.864 ms, heap usage 349.109 MB -> 51.368 MB. [2024-11-28T07:47:39.212Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-28T07:47:45.044Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-28T07:47:52.216Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-28T07:47:59.389Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-28T07:48:02.305Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-28T07:48:06.055Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-28T07:48:10.751Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-28T07:48:13.647Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-28T07:48:14.350Z] 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. [2024-11-28T07:48:14.350Z] The best model improves the baseline by 14.52%. [2024-11-28T07:48:14.350Z] Movies recommended for you: [2024-11-28T07:48:14.350Z] WARNING: This benchmark provides no result that can be validated. [2024-11-28T07:48:14.350Z] There is no way to check that no silent failure occurred. [2024-11-28T07:48:14.350Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (42290.032 ms) ====== [2024-11-28T07:48:14.350Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-11-28T07:48:14.350Z] GC before operation: completed in 60.548 ms, heap usage 212.950 MB -> 51.445 MB. [2024-11-28T07:48:21.505Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-28T07:48:27.329Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-28T07:48:34.495Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-28T07:48:41.669Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-28T07:48:44.622Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-28T07:48:48.375Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-28T07:48:52.099Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-28T07:48:55.797Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-28T07:48:56.156Z] 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. [2024-11-28T07:48:56.490Z] The best model improves the baseline by 14.52%. [2024-11-28T07:48:56.490Z] Movies recommended for you: [2024-11-28T07:48:56.490Z] WARNING: This benchmark provides no result that can be validated. [2024-11-28T07:48:56.490Z] There is no way to check that no silent failure occurred. [2024-11-28T07:48:56.490Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (42035.641 ms) ====== [2024-11-28T07:48:56.490Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-11-28T07:48:56.490Z] GC before operation: completed in 59.386 ms, heap usage 146.748 MB -> 51.168 MB. [2024-11-28T07:49:03.667Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-28T07:49:09.480Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-28T07:49:16.658Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-28T07:49:23.812Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-28T07:49:26.705Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-28T07:49:30.419Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-28T07:49:34.130Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-28T07:49:37.844Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-28T07:49:38.548Z] 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. [2024-11-28T07:49:38.548Z] The best model improves the baseline by 14.52%. [2024-11-28T07:49:38.548Z] Movies recommended for you: [2024-11-28T07:49:38.548Z] WARNING: This benchmark provides no result that can be validated. [2024-11-28T07:49:38.548Z] There is no way to check that no silent failure occurred. [2024-11-28T07:49:38.548Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (42043.960 ms) ====== [2024-11-28T07:49:38.548Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-11-28T07:49:38.548Z] GC before operation: completed in 60.973 ms, heap usage 201.661 MB -> 51.378 MB. [2024-11-28T07:49:45.712Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-28T07:49:51.555Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-28T07:49:58.757Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-28T07:50:04.567Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-28T07:50:08.307Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-28T07:50:12.007Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-28T07:50:16.696Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-28T07:50:19.575Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-28T07:50:19.903Z] 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. [2024-11-28T07:50:19.903Z] The best model improves the baseline by 14.52%. [2024-11-28T07:50:20.234Z] Movies recommended for you: [2024-11-28T07:50:20.234Z] WARNING: This benchmark provides no result that can be validated. [2024-11-28T07:50:20.234Z] There is no way to check that no silent failure occurred. [2024-11-28T07:50:20.234Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (41551.023 ms) ====== [2024-11-28T07:50:20.234Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-11-28T07:50:20.234Z] GC before operation: completed in 60.294 ms, heap usage 334.490 MB -> 51.533 MB. [2024-11-28T07:50:27.406Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-28T07:50:33.214Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-28T07:50:40.386Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-28T07:50:47.557Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-28T07:50:50.473Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-28T07:50:54.191Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-28T07:50:57.909Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-28T07:51:01.691Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-28T07:51:01.691Z] 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. [2024-11-28T07:51:01.691Z] The best model improves the baseline by 14.52%. [2024-11-28T07:51:02.018Z] Movies recommended for you: [2024-11-28T07:51:02.018Z] WARNING: This benchmark provides no result that can be validated. [2024-11-28T07:51:02.018Z] There is no way to check that no silent failure occurred. [2024-11-28T07:51:02.018Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (41597.619 ms) ====== [2024-11-28T07:51:02.018Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-11-28T07:51:02.018Z] GC before operation: completed in 59.402 ms, heap usage 197.000 MB -> 51.266 MB. [2024-11-28T07:51:07.824Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-28T07:51:15.140Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-28T07:51:20.971Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-28T07:51:28.149Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-28T07:51:31.040Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-28T07:51:34.761Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-28T07:51:38.510Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-28T07:51:42.229Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-28T07:51:42.565Z] 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. [2024-11-28T07:51:42.565Z] The best model improves the baseline by 14.52%. [2024-11-28T07:51:42.895Z] Movies recommended for you: [2024-11-28T07:51:42.895Z] WARNING: This benchmark provides no result that can be validated. [2024-11-28T07:51:42.895Z] There is no way to check that no silent failure occurred. [2024-11-28T07:51:42.895Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (40940.370 ms) ====== [2024-11-28T07:51:42.895Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-11-28T07:51:42.895Z] GC before operation: completed in 64.082 ms, heap usage 64.810 MB -> 51.187 MB. [2024-11-28T07:51:50.041Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-28T07:51:55.846Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-28T07:52:03.019Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-28T07:52:08.819Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-28T07:52:12.544Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-28T07:52:16.302Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-28T07:52:20.025Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-28T07:52:23.729Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-28T07:52:24.061Z] 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. [2024-11-28T07:52:24.061Z] The best model improves the baseline by 14.52%. [2024-11-28T07:52:24.397Z] Movies recommended for you: [2024-11-28T07:52:24.397Z] WARNING: This benchmark provides no result that can be validated. [2024-11-28T07:52:24.397Z] There is no way to check that no silent failure occurred. [2024-11-28T07:52:24.397Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (41446.060 ms) ====== [2024-11-28T07:52:24.397Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-11-28T07:52:24.397Z] GC before operation: completed in 62.693 ms, heap usage 99.563 MB -> 51.428 MB. [2024-11-28T07:52:31.569Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-28T07:52:37.399Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-28T07:52:44.654Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-28T07:52:50.476Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-28T07:52:54.229Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-28T07:52:57.944Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-28T07:53:01.681Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-28T07:53:04.611Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-28T07:53:05.327Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-11-28T07:53:05.327Z] The best model improves the baseline by 14.52%. [2024-11-28T07:53:05.327Z] Movies recommended for you: [2024-11-28T07:53:05.327Z] WARNING: This benchmark provides no result that can be validated. [2024-11-28T07:53:05.327Z] There is no way to check that no silent failure occurred. [2024-11-28T07:53:05.327Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (41045.490 ms) ====== [2024-11-28T07:53:06.022Z] ----------------------------------- [2024-11-28T07:53:06.022Z] renaissance-movie-lens_0_PASSED [2024-11-28T07:53:06.022Z] ----------------------------------- [2024-11-28T07:53:06.350Z] [2024-11-28T07:53:06.350Z] TEST TEARDOWN: [2024-11-28T07:53:06.350Z] Nothing to be done for teardown. [2024-11-28T07:53:06.350Z] renaissance-movie-lens_0 Finish Time: Thu Nov 28 07:53:06 2024 Epoch Time (ms): 1732780386316