[2024-11-08T18:21:46.604Z] Running test renaissance-movie-lens_0 ... [2024-11-08T18:21:46.604Z] =============================================== [2024-11-08T18:21:46.604Z] renaissance-movie-lens_0 Start Time: Fri Nov 8 18:21:46 2024 Epoch Time (ms): 1731090106544 [2024-11-08T18:21:46.942Z] variation: NoOptions [2024-11-08T18:21:46.942Z] JVM_OPTIONS: [2024-11-08T18:21:46.942Z] { \ [2024-11-08T18:21:46.942Z] echo ""; echo "TEST SETUP:"; \ [2024-11-08T18:21:46.942Z] echo "Nothing to be done for setup."; \ [2024-11-08T18:21:46.942Z] mkdir -p "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17310891697444\\renaissance-movie-lens_0"; \ [2024-11-08T18:21:46.942Z] cd "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17310891697444\\renaissance-movie-lens_0"; \ [2024-11-08T18:21:46.942Z] echo ""; echo "TESTING:"; \ [2024-11-08T18:21:46.942Z] "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_17310891697444\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2024-11-08T18:21:46.942Z] 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_17310891697444\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-11-08T18:21:46.942Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-11-08T18:21:46.942Z] echo "Nothing to be done for teardown."; \ [2024-11-08T18:21:46.942Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17310891697444\\TestTargetResult"; [2024-11-08T18:21:46.942Z] [2024-11-08T18:21:46.942Z] TEST SETUP: [2024-11-08T18:21:46.942Z] Nothing to be done for setup. [2024-11-08T18:21:46.942Z] [2024-11-08T18:21:46.942Z] TESTING: [2024-11-08T18:21:57.546Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-11-08T18:21:58.257Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-11-08T18:22:01.408Z] Got 100004 ratings from 671 users on 9066 movies. [2024-11-08T18:22:01.750Z] Training: 60056, validation: 20285, test: 19854 [2024-11-08T18:22:01.750Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-11-08T18:22:01.750Z] GC before operation: completed in 53.600 ms, heap usage 83.564 MB -> 37.472 MB. [2024-11-08T18:22:12.461Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-08T18:22:19.601Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-08T18:22:28.334Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-08T18:22:34.101Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-08T18:22:37.801Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-08T18:22:41.503Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-08T18:22:45.188Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-08T18:22:48.913Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-08T18:22:49.238Z] 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. [2024-11-08T18:22:49.238Z] The best model improves the baseline by 14.52%. [2024-11-08T18:22:49.560Z] Movies recommended for you: [2024-11-08T18:22:49.560Z] WARNING: This benchmark provides no result that can be validated. [2024-11-08T18:22:49.560Z] There is no way to check that no silent failure occurred. [2024-11-08T18:22:49.560Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (47897.090 ms) ====== [2024-11-08T18:22:49.560Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-11-08T18:22:49.561Z] GC before operation: completed in 63.983 ms, heap usage 210.393 MB -> 60.195 MB. [2024-11-08T18:22:56.671Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-08T18:23:02.442Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-08T18:23:09.561Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-08T18:23:15.325Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-08T18:23:19.006Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-08T18:23:22.689Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-08T18:23:26.360Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-08T18:23:30.062Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-08T18:23:30.393Z] 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. [2024-11-08T18:23:30.393Z] The best model improves the baseline by 14.52%. [2024-11-08T18:23:30.393Z] Movies recommended for you: [2024-11-08T18:23:30.393Z] WARNING: This benchmark provides no result that can be validated. [2024-11-08T18:23:30.393Z] There is no way to check that no silent failure occurred. [2024-11-08T18:23:30.393Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (40939.092 ms) ====== [2024-11-08T18:23:30.393Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-11-08T18:23:30.393Z] GC before operation: completed in 62.269 ms, heap usage 106.559 MB -> 49.986 MB. [2024-11-08T18:23:37.512Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-08T18:23:43.277Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-08T18:23:50.408Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-08T18:23:56.174Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-08T18:23:59.037Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-08T18:24:02.725Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-08T18:24:06.400Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-08T18:24:10.071Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-08T18:24:10.071Z] 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. [2024-11-08T18:24:10.071Z] The best model improves the baseline by 14.52%. [2024-11-08T18:24:10.071Z] Movies recommended for you: [2024-11-08T18:24:10.071Z] WARNING: This benchmark provides no result that can be validated. [2024-11-08T18:24:10.072Z] There is no way to check that no silent failure occurred. [2024-11-08T18:24:10.072Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (39572.066 ms) ====== [2024-11-08T18:24:10.072Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-11-08T18:24:10.072Z] GC before operation: completed in 59.262 ms, heap usage 265.165 MB -> 50.298 MB. [2024-11-08T18:24:17.177Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-08T18:24:22.929Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-08T18:24:28.711Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-08T18:24:35.848Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-08T18:24:38.725Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-08T18:24:41.588Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-08T18:24:45.289Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-08T18:24:48.979Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-08T18:24:49.301Z] 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. [2024-11-08T18:24:49.301Z] The best model improves the baseline by 14.52%. [2024-11-08T18:24:49.301Z] Movies recommended for you: [2024-11-08T18:24:49.301Z] WARNING: This benchmark provides no result that can be validated. [2024-11-08T18:24:49.301Z] There is no way to check that no silent failure occurred. [2024-11-08T18:24:49.301Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (39124.534 ms) ====== [2024-11-08T18:24:49.301Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-11-08T18:24:49.301Z] GC before operation: completed in 59.467 ms, heap usage 189.843 MB -> 50.703 MB. [2024-11-08T18:24:55.075Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-08T18:25:02.185Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-08T18:25:07.939Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-08T18:25:13.703Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-08T18:25:17.373Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-08T18:25:21.068Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-08T18:25:24.760Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-08T18:25:28.439Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-08T18:25:28.439Z] 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. [2024-11-08T18:25:28.439Z] The best model improves the baseline by 14.52%. [2024-11-08T18:25:28.439Z] Movies recommended for you: [2024-11-08T18:25:28.439Z] WARNING: This benchmark provides no result that can be validated. [2024-11-08T18:25:28.439Z] There is no way to check that no silent failure occurred. [2024-11-08T18:25:28.439Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (39149.397 ms) ====== [2024-11-08T18:25:28.439Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-11-08T18:25:28.439Z] GC before operation: completed in 59.580 ms, heap usage 128.312 MB -> 50.738 MB. [2024-11-08T18:25:35.594Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-08T18:25:41.376Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-08T18:25:47.152Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-08T18:25:52.915Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-08T18:25:56.610Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-08T18:25:59.481Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-08T18:26:03.189Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-08T18:26:06.863Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-08T18:26:06.863Z] 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. [2024-11-08T18:26:06.863Z] The best model improves the baseline by 14.52%. [2024-11-08T18:26:07.185Z] Movies recommended for you: [2024-11-08T18:26:07.185Z] WARNING: This benchmark provides no result that can be validated. [2024-11-08T18:26:07.185Z] There is no way to check that no silent failure occurred. [2024-11-08T18:26:07.185Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (38544.736 ms) ====== [2024-11-08T18:26:07.185Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-11-08T18:26:07.185Z] GC before operation: completed in 58.865 ms, heap usage 103.145 MB -> 50.712 MB. [2024-11-08T18:26:12.979Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-08T18:26:20.104Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-08T18:26:25.892Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-08T18:26:31.662Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-08T18:26:35.339Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-08T18:26:38.288Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-08T18:26:41.977Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-08T18:26:45.681Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-08T18:26:45.681Z] 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. [2024-11-08T18:26:45.681Z] The best model improves the baseline by 14.52%. [2024-11-08T18:26:45.681Z] Movies recommended for you: [2024-11-08T18:26:45.681Z] WARNING: This benchmark provides no result that can be validated. [2024-11-08T18:26:45.681Z] There is no way to check that no silent failure occurred. [2024-11-08T18:26:45.681Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (38589.345 ms) ====== [2024-11-08T18:26:45.681Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-11-08T18:26:45.681Z] GC before operation: completed in 57.119 ms, heap usage 122.872 MB -> 50.843 MB. [2024-11-08T18:26:51.449Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-08T18:26:58.575Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-08T18:27:04.330Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-08T18:27:10.099Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-08T18:27:12.972Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-08T18:27:16.643Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-08T18:27:20.351Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-08T18:27:23.234Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-08T18:27:23.920Z] 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. [2024-11-08T18:27:23.920Z] The best model improves the baseline by 14.52%. [2024-11-08T18:27:23.920Z] Movies recommended for you: [2024-11-08T18:27:23.920Z] WARNING: This benchmark provides no result that can be validated. [2024-11-08T18:27:23.920Z] There is no way to check that no silent failure occurred. [2024-11-08T18:27:23.920Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (38140.308 ms) ====== [2024-11-08T18:27:23.920Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-11-08T18:27:23.921Z] GC before operation: completed in 58.924 ms, heap usage 335.464 MB -> 51.354 MB. [2024-11-08T18:27:31.051Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-08T18:27:36.812Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-08T18:27:42.569Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-08T18:27:48.366Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-08T18:27:51.237Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-08T18:27:54.972Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-08T18:27:58.677Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-08T18:28:01.640Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-08T18:28:01.963Z] 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. [2024-11-08T18:28:01.963Z] The best model improves the baseline by 14.52%. [2024-11-08T18:28:02.291Z] Movies recommended for you: [2024-11-08T18:28:02.291Z] WARNING: This benchmark provides no result that can be validated. [2024-11-08T18:28:02.291Z] There is no way to check that no silent failure occurred. [2024-11-08T18:28:02.291Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (38188.932 ms) ====== [2024-11-08T18:28:02.291Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-11-08T18:28:02.292Z] GC before operation: completed in 58.508 ms, heap usage 174.291 MB -> 51.078 MB. [2024-11-08T18:28:08.051Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-08T18:28:13.921Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-08T18:28:21.053Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-08T18:28:26.843Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-08T18:28:29.714Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-08T18:28:33.384Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-08T18:28:37.111Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-08T18:28:39.981Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-08T18:28:40.666Z] 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. [2024-11-08T18:28:40.666Z] The best model improves the baseline by 14.52%. [2024-11-08T18:28:40.666Z] Movies recommended for you: [2024-11-08T18:28:40.666Z] WARNING: This benchmark provides no result that can be validated. [2024-11-08T18:28:40.666Z] There is no way to check that no silent failure occurred. [2024-11-08T18:28:40.666Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (38340.867 ms) ====== [2024-11-08T18:28:40.666Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-11-08T18:28:40.666Z] GC before operation: completed in 58.365 ms, heap usage 253.982 MB -> 51.237 MB. [2024-11-08T18:28:46.436Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-08T18:28:53.559Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-08T18:28:59.315Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-08T18:29:05.083Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-08T18:29:07.961Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-08T18:29:11.666Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-08T18:29:15.349Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-08T18:29:18.227Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-08T18:29:18.557Z] 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. [2024-11-08T18:29:18.557Z] The best model improves the baseline by 14.52%. [2024-11-08T18:29:18.557Z] Movies recommended for you: [2024-11-08T18:29:18.557Z] WARNING: This benchmark provides no result that can be validated. [2024-11-08T18:29:18.557Z] There is no way to check that no silent failure occurred. [2024-11-08T18:29:18.557Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (37944.487 ms) ====== [2024-11-08T18:29:18.557Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-11-08T18:29:18.557Z] GC before operation: completed in 57.564 ms, heap usage 116.975 MB -> 50.907 MB. [2024-11-08T18:29:25.674Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-08T18:29:31.442Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-08T18:29:37.279Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-08T18:29:43.049Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-08T18:29:45.927Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-08T18:29:49.626Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-08T18:29:53.339Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-08T18:29:57.014Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-08T18:29:57.014Z] 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. [2024-11-08T18:29:57.014Z] The best model improves the baseline by 14.52%. [2024-11-08T18:29:57.014Z] Movies recommended for you: [2024-11-08T18:29:57.014Z] WARNING: This benchmark provides no result that can be validated. [2024-11-08T18:29:57.014Z] There is no way to check that no silent failure occurred. [2024-11-08T18:29:57.014Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (38352.804 ms) ====== [2024-11-08T18:29:57.014Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-11-08T18:29:57.014Z] GC before operation: completed in 58.983 ms, heap usage 339.669 MB -> 51.234 MB. [2024-11-08T18:30:02.786Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-08T18:30:09.909Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-08T18:30:15.687Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-08T18:30:21.476Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-08T18:30:24.346Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-08T18:30:28.022Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-08T18:30:31.732Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-08T18:30:35.434Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-08T18:30:35.434Z] 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. [2024-11-08T18:30:35.434Z] The best model improves the baseline by 14.52%. [2024-11-08T18:30:35.434Z] Movies recommended for you: [2024-11-08T18:30:35.434Z] WARNING: This benchmark provides no result that can be validated. [2024-11-08T18:30:35.434Z] There is no way to check that no silent failure occurred. [2024-11-08T18:30:35.434Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (38453.028 ms) ====== [2024-11-08T18:30:35.434Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-11-08T18:30:35.755Z] GC before operation: completed in 62.826 ms, heap usage 118.023 MB -> 51.227 MB. [2024-11-08T18:30:41.515Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-08T18:30:47.292Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-08T18:30:54.401Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-08T18:31:00.161Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-08T18:31:03.033Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-08T18:31:06.775Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-08T18:31:10.474Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-08T18:31:13.395Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-08T18:31:13.725Z] 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. [2024-11-08T18:31:13.725Z] The best model improves the baseline by 14.52%. [2024-11-08T18:31:14.052Z] Movies recommended for you: [2024-11-08T18:31:14.052Z] WARNING: This benchmark provides no result that can be validated. [2024-11-08T18:31:14.052Z] There is no way to check that no silent failure occurred. [2024-11-08T18:31:14.052Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (38369.752 ms) ====== [2024-11-08T18:31:14.052Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-11-08T18:31:14.052Z] GC before operation: completed in 61.731 ms, heap usage 248.829 MB -> 51.096 MB. [2024-11-08T18:31:19.816Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-08T18:31:26.949Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-08T18:31:32.720Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-08T18:31:38.614Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-08T18:31:41.508Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-08T18:31:45.213Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-08T18:31:48.918Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-08T18:31:51.810Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-08T18:31:52.139Z] 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. [2024-11-08T18:31:52.139Z] The best model improves the baseline by 14.52%. [2024-11-08T18:31:52.139Z] Movies recommended for you: [2024-11-08T18:31:52.139Z] WARNING: This benchmark provides no result that can be validated. [2024-11-08T18:31:52.139Z] There is no way to check that no silent failure occurred. [2024-11-08T18:31:52.139Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (38131.320 ms) ====== [2024-11-08T18:31:52.139Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-11-08T18:31:52.139Z] GC before operation: completed in 60.765 ms, heap usage 210.842 MB -> 51.179 MB. [2024-11-08T18:31:57.912Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-08T18:32:05.039Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-08T18:32:10.792Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-08T18:32:16.558Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-08T18:32:20.247Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-08T18:32:23.155Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-08T18:32:26.837Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-08T18:32:30.508Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-08T18:32:30.833Z] 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. [2024-11-08T18:32:30.833Z] The best model improves the baseline by 14.52%. [2024-11-08T18:32:31.156Z] Movies recommended for you: [2024-11-08T18:32:31.156Z] WARNING: This benchmark provides no result that can be validated. [2024-11-08T18:32:31.156Z] There is no way to check that no silent failure occurred. [2024-11-08T18:32:31.156Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (38854.735 ms) ====== [2024-11-08T18:32:31.156Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-11-08T18:32:31.156Z] GC before operation: completed in 59.881 ms, heap usage 61.839 MB -> 51.305 MB. [2024-11-08T18:32:36.924Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-08T18:32:44.058Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-08T18:32:49.831Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-08T18:32:55.583Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-08T18:32:58.461Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-08T18:33:02.196Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-08T18:33:05.874Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-08T18:33:08.738Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-08T18:33:09.421Z] 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. [2024-11-08T18:33:09.421Z] The best model improves the baseline by 14.52%. [2024-11-08T18:33:09.421Z] Movies recommended for you: [2024-11-08T18:33:09.421Z] WARNING: This benchmark provides no result that can be validated. [2024-11-08T18:33:09.421Z] There is no way to check that no silent failure occurred. [2024-11-08T18:33:09.421Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (38242.923 ms) ====== [2024-11-08T18:33:09.421Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-11-08T18:33:09.421Z] GC before operation: completed in 58.675 ms, heap usage 130.434 MB -> 51.040 MB. [2024-11-08T18:33:15.189Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-08T18:33:22.314Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-08T18:33:28.097Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-08T18:33:33.874Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-08T18:33:36.742Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-08T18:33:40.453Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-08T18:33:44.125Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-08T18:33:46.988Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-08T18:33:47.671Z] 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. [2024-11-08T18:33:47.672Z] The best model improves the baseline by 14.52%. [2024-11-08T18:33:47.672Z] Movies recommended for you: [2024-11-08T18:33:47.672Z] WARNING: This benchmark provides no result that can be validated. [2024-11-08T18:33:47.672Z] There is no way to check that no silent failure occurred. [2024-11-08T18:33:47.672Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (38188.696 ms) ====== [2024-11-08T18:33:47.672Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-11-08T18:33:47.672Z] GC before operation: completed in 59.534 ms, heap usage 295.084 MB -> 51.335 MB. [2024-11-08T18:33:53.438Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-08T18:34:00.548Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-08T18:34:06.337Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-08T18:34:12.097Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-08T18:34:15.765Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-08T18:34:18.648Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-08T18:34:22.324Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-08T18:34:26.012Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-08T18:34:26.012Z] 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. [2024-11-08T18:34:26.012Z] The best model improves the baseline by 14.52%. [2024-11-08T18:34:26.012Z] Movies recommended for you: [2024-11-08T18:34:26.012Z] WARNING: This benchmark provides no result that can be validated. [2024-11-08T18:34:26.012Z] There is no way to check that no silent failure occurred. [2024-11-08T18:34:26.012Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (38398.638 ms) ====== [2024-11-08T18:34:26.012Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-11-08T18:34:26.333Z] GC before operation: completed in 60.836 ms, heap usage 197.118 MB -> 51.424 MB. [2024-11-08T18:34:32.111Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-11-08T18:34:37.876Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-11-08T18:34:44.993Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-11-08T18:34:49.632Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-11-08T18:34:53.310Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-11-08T18:34:56.264Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-11-08T18:34:59.938Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-11-08T18:35:03.626Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-11-08T18:35:03.947Z] 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. [2024-11-08T18:35:03.947Z] The best model improves the baseline by 14.52%. [2024-11-08T18:35:03.947Z] Movies recommended for you: [2024-11-08T18:35:03.947Z] WARNING: This benchmark provides no result that can be validated. [2024-11-08T18:35:03.947Z] There is no way to check that no silent failure occurred. [2024-11-08T18:35:03.947Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (37802.436 ms) ====== [2024-11-08T18:35:04.629Z] ----------------------------------- [2024-11-08T18:35:04.629Z] renaissance-movie-lens_0_PASSED [2024-11-08T18:35:04.629Z] ----------------------------------- [2024-11-08T18:35:04.940Z] [2024-11-08T18:35:04.941Z] TEST TEARDOWN: [2024-11-08T18:35:04.941Z] Nothing to be done for teardown. [2024-11-08T18:35:05.262Z] renaissance-movie-lens_0 Finish Time: Fri Nov 8 18:35:04 2024 Epoch Time (ms): 1731090904927