[2024-07-31T23:58:07.006Z] Running test renaissance-movie-lens_0 ... [2024-07-31T23:58:07.006Z] =============================================== [2024-07-31T23:58:07.006Z] renaissance-movie-lens_0 Start Time: Wed Jul 31 23:58:06 2024 Epoch Time (ms): 1722470286632 [2024-07-31T23:58:07.006Z] variation: NoOptions [2024-07-31T23:58:07.006Z] JVM_OPTIONS: [2024-07-31T23:58:07.006Z] { \ [2024-07-31T23:58:07.006Z] echo ""; echo "TEST SETUP:"; \ [2024-07-31T23:58:07.006Z] echo "Nothing to be done for setup."; \ [2024-07-31T23:58:07.006Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17224694024745/renaissance-movie-lens_0"; \ [2024-07-31T23:58:07.006Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17224694024745/renaissance-movie-lens_0"; \ [2024-07-31T23:58:07.006Z] echo ""; echo "TESTING:"; \ [2024-07-31T23:58:07.006Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_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 "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17224694024745/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-07-31T23:58:07.006Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17224694024745/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-07-31T23:58:07.006Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-07-31T23:58:07.006Z] echo "Nothing to be done for teardown."; \ [2024-07-31T23:58:07.006Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17224694024745/TestTargetResult"; [2024-07-31T23:58:07.006Z] [2024-07-31T23:58:07.006Z] TEST SETUP: [2024-07-31T23:58:07.006Z] Nothing to be done for setup. [2024-07-31T23:58:07.006Z] [2024-07-31T23:58:07.006Z] TESTING: [2024-07-31T23:58:11.035Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-07-31T23:58:12.924Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-07-31T23:58:15.842Z] Got 100004 ratings from 671 users on 9066 movies. [2024-07-31T23:58:16.761Z] Training: 60056, validation: 20285, test: 19854 [2024-07-31T23:58:16.761Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-07-31T23:58:16.761Z] GC before operation: completed in 74.216 ms, heap usage 76.745 MB -> 36.430 MB. [2024-07-31T23:58:21.980Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-07-31T23:58:26.162Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-07-31T23:58:29.079Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-07-31T23:58:30.966Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-07-31T23:58:32.857Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-07-31T23:58:34.751Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-07-31T23:58:35.669Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-07-31T23:58:37.557Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-07-31T23:58:37.557Z] 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. [2024-07-31T23:58:38.475Z] The best model improves the baseline by 14.52%. [2024-07-31T23:58:38.475Z] Movies recommended for you: [2024-07-31T23:58:38.475Z] WARNING: This benchmark provides no result that can be validated. [2024-07-31T23:58:38.475Z] There is no way to check that no silent failure occurred. [2024-07-31T23:58:38.475Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (21754.033 ms) ====== [2024-07-31T23:58:38.475Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-07-31T23:58:38.475Z] GC before operation: completed in 87.994 ms, heap usage 275.832 MB -> 48.259 MB. [2024-07-31T23:58:41.390Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-07-31T23:58:43.279Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-07-31T23:58:46.195Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-07-31T23:58:48.084Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-07-31T23:58:49.975Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-07-31T23:58:51.940Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-07-31T23:58:52.859Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-07-31T23:58:54.753Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-07-31T23:58:54.753Z] 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. [2024-07-31T23:58:54.753Z] The best model improves the baseline by 14.52%. [2024-07-31T23:58:56.389Z] Movies recommended for you: [2024-07-31T23:58:56.389Z] WARNING: This benchmark provides no result that can be validated. [2024-07-31T23:58:56.389Z] There is no way to check that no silent failure occurred. [2024-07-31T23:58:56.389Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17075.712 ms) ====== [2024-07-31T23:58:56.389Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-07-31T23:58:56.389Z] GC before operation: completed in 101.162 ms, heap usage 217.437 MB -> 49.086 MB. [2024-07-31T23:58:58.411Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-07-31T23:59:00.298Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-07-31T23:59:03.214Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-07-31T23:59:05.102Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-07-31T23:59:06.992Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-07-31T23:59:08.880Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-07-31T23:59:09.799Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-07-31T23:59:11.692Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-07-31T23:59:11.692Z] 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. [2024-07-31T23:59:11.692Z] The best model improves the baseline by 14.52%. [2024-07-31T23:59:11.692Z] Movies recommended for you: [2024-07-31T23:59:11.692Z] WARNING: This benchmark provides no result that can be validated. [2024-07-31T23:59:11.692Z] There is no way to check that no silent failure occurred. [2024-07-31T23:59:11.692Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16516.669 ms) ====== [2024-07-31T23:59:11.692Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-07-31T23:59:11.692Z] GC before operation: completed in 106.214 ms, heap usage 182.516 MB -> 49.412 MB. [2024-07-31T23:59:14.629Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-07-31T23:59:17.550Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-07-31T23:59:19.439Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-07-31T23:59:22.395Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-07-31T23:59:23.317Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-07-31T23:59:25.207Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-07-31T23:59:27.099Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-07-31T23:59:28.019Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-07-31T23:59:28.019Z] 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. [2024-07-31T23:59:28.019Z] The best model improves the baseline by 14.52%. [2024-07-31T23:59:28.939Z] Movies recommended for you: [2024-07-31T23:59:28.939Z] WARNING: This benchmark provides no result that can be validated. [2024-07-31T23:59:28.939Z] There is no way to check that no silent failure occurred. [2024-07-31T23:59:28.939Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16439.564 ms) ====== [2024-07-31T23:59:28.939Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-07-31T23:59:28.939Z] GC before operation: completed in 106.406 ms, heap usage 226.196 MB -> 49.717 MB. [2024-07-31T23:59:30.830Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-07-31T23:59:33.754Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-07-31T23:59:36.674Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-07-31T23:59:38.564Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-07-31T23:59:40.453Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-07-31T23:59:41.373Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-07-31T23:59:44.064Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-07-31T23:59:44.064Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-07-31T23:59:44.986Z] 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. [2024-07-31T23:59:44.986Z] The best model improves the baseline by 14.52%. [2024-07-31T23:59:44.986Z] Movies recommended for you: [2024-07-31T23:59:44.986Z] WARNING: This benchmark provides no result that can be validated. [2024-07-31T23:59:44.986Z] There is no way to check that no silent failure occurred. [2024-07-31T23:59:44.986Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16317.367 ms) ====== [2024-07-31T23:59:44.986Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-07-31T23:59:44.986Z] GC before operation: completed in 96.154 ms, heap usage 189.065 MB -> 49.872 MB. [2024-07-31T23:59:47.906Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-07-31T23:59:49.794Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-07-31T23:59:51.690Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-07-31T23:59:54.634Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-07-31T23:59:55.553Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-07-31T23:59:57.443Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-07-31T23:59:58.364Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T00:00:00.258Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T00:00:00.258Z] 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. [2024-08-01T00:00:00.258Z] The best model improves the baseline by 14.52%. [2024-08-01T00:00:00.258Z] Movies recommended for you: [2024-08-01T00:00:00.258Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T00:00:00.258Z] There is no way to check that no silent failure occurred. [2024-08-01T00:00:00.258Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15544.949 ms) ====== [2024-08-01T00:00:00.258Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-01T00:00:00.258Z] GC before operation: completed in 106.054 ms, heap usage 69.623 MB -> 49.688 MB. [2024-08-01T00:00:03.183Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T00:00:05.071Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T00:00:07.998Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T00:00:09.887Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T00:00:11.790Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T00:00:17.639Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T00:00:17.639Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T00:00:17.639Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T00:00:17.639Z] 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. [2024-08-01T00:00:17.639Z] The best model improves the baseline by 14.52%. [2024-08-01T00:00:17.639Z] Movies recommended for you: [2024-08-01T00:00:17.639Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T00:00:17.639Z] There is no way to check that no silent failure occurred. [2024-08-01T00:00:17.639Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15372.389 ms) ====== [2024-08-01T00:00:17.639Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-01T00:00:17.639Z] GC before operation: completed in 95.226 ms, heap usage 323.415 MB -> 50.092 MB. [2024-08-01T00:00:18.559Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T00:00:21.479Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T00:00:23.376Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T00:00:25.267Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T00:00:27.164Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T00:00:28.087Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T00:00:29.990Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T00:00:30.913Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T00:00:31.835Z] 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. [2024-08-01T00:00:31.835Z] The best model improves the baseline by 14.52%. [2024-08-01T00:00:31.835Z] Movies recommended for you: [2024-08-01T00:00:31.835Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T00:00:31.835Z] There is no way to check that no silent failure occurred. [2024-08-01T00:00:31.835Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15410.858 ms) ====== [2024-08-01T00:00:31.835Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-01T00:00:31.835Z] GC before operation: completed in 95.854 ms, heap usage 243.416 MB -> 50.340 MB. [2024-08-01T00:00:34.757Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T00:00:36.648Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T00:00:38.536Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T00:00:41.457Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T00:00:42.377Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T00:00:43.297Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T00:00:45.190Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T00:00:46.110Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T00:00:47.031Z] 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. [2024-08-01T00:00:47.031Z] The best model improves the baseline by 14.52%. [2024-08-01T00:00:47.031Z] Movies recommended for you: [2024-08-01T00:00:47.031Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T00:00:47.031Z] There is no way to check that no silent failure occurred. [2024-08-01T00:00:47.031Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15129.390 ms) ====== [2024-08-01T00:00:47.031Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-01T00:00:47.031Z] GC before operation: completed in 97.054 ms, heap usage 223.069 MB -> 50.076 MB. [2024-08-01T00:00:49.953Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T00:00:52.663Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T00:00:53.587Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T00:00:56.513Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T00:00:57.433Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T00:00:59.320Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T00:01:00.241Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T00:01:01.194Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T00:01:02.115Z] 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. [2024-08-01T00:01:02.115Z] The best model improves the baseline by 14.52%. [2024-08-01T00:01:02.115Z] Movies recommended for you: [2024-08-01T00:01:02.115Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T00:01:02.115Z] There is no way to check that no silent failure occurred. [2024-08-01T00:01:02.115Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15191.985 ms) ====== [2024-08-01T00:01:02.115Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-01T00:01:02.115Z] GC before operation: completed in 92.572 ms, heap usage 275.070 MB -> 50.284 MB. [2024-08-01T00:01:05.043Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T00:01:06.939Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T00:01:08.837Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T00:01:11.768Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T00:01:12.686Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T00:01:13.607Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T00:01:15.495Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T00:01:16.415Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T00:01:17.335Z] 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. [2024-08-01T00:01:17.335Z] The best model improves the baseline by 14.52%. [2024-08-01T00:01:17.335Z] Movies recommended for you: [2024-08-01T00:01:17.335Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T00:01:17.335Z] There is no way to check that no silent failure occurred. [2024-08-01T00:01:17.335Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14989.443 ms) ====== [2024-08-01T00:01:17.335Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-01T00:01:17.335Z] GC before operation: completed in 99.575 ms, heap usage 190.248 MB -> 49.920 MB. [2024-08-01T00:01:20.262Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T00:01:22.151Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T00:01:24.041Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T00:01:26.962Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T00:01:27.881Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T00:01:29.769Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T00:01:30.687Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T00:01:32.575Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T00:01:32.575Z] 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. [2024-08-01T00:01:32.575Z] The best model improves the baseline by 14.52%. [2024-08-01T00:01:32.575Z] Movies recommended for you: [2024-08-01T00:01:32.575Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T00:01:32.575Z] There is no way to check that no silent failure occurred. [2024-08-01T00:01:32.575Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15260.472 ms) ====== [2024-08-01T00:01:32.575Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-01T00:01:32.575Z] GC before operation: completed in 99.557 ms, heap usage 221.484 MB -> 50.142 MB. [2024-08-01T00:01:34.464Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T00:01:37.401Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T00:01:39.292Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T00:01:41.190Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T00:01:43.086Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T00:01:44.009Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T00:01:45.900Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T00:01:46.821Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T00:01:47.747Z] 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. [2024-08-01T00:01:47.747Z] The best model improves the baseline by 14.52%. [2024-08-01T00:01:47.747Z] Movies recommended for you: [2024-08-01T00:01:47.747Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T00:01:47.747Z] There is no way to check that no silent failure occurred. [2024-08-01T00:01:47.747Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15067.152 ms) ====== [2024-08-01T00:01:47.747Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-01T00:01:47.747Z] GC before operation: completed in 100.686 ms, heap usage 204.167 MB -> 50.263 MB. [2024-08-01T00:01:50.682Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T00:01:52.192Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T00:01:55.172Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T00:01:57.060Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T00:01:57.978Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T00:01:59.865Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T00:02:00.805Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T00:02:02.693Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T00:02:02.694Z] 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. [2024-08-01T00:02:02.694Z] The best model improves the baseline by 14.52%. [2024-08-01T00:02:02.694Z] Movies recommended for you: [2024-08-01T00:02:02.694Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T00:02:02.694Z] There is no way to check that no silent failure occurred. [2024-08-01T00:02:02.694Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15021.911 ms) ====== [2024-08-01T00:02:02.694Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-01T00:02:02.694Z] GC before operation: completed in 88.685 ms, heap usage 71.759 MB -> 49.904 MB. [2024-08-01T00:02:05.776Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T00:02:07.664Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T00:02:09.557Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T00:02:11.463Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T00:02:13.357Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T00:02:14.275Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T00:02:15.195Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T00:02:17.082Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T00:02:17.082Z] 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. [2024-08-01T00:02:17.082Z] The best model improves the baseline by 14.52%. [2024-08-01T00:02:17.082Z] Movies recommended for you: [2024-08-01T00:02:17.082Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T00:02:17.082Z] There is no way to check that no silent failure occurred. [2024-08-01T00:02:17.082Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14477.484 ms) ====== [2024-08-01T00:02:17.082Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-01T00:02:17.082Z] GC before operation: completed in 108.304 ms, heap usage 174.160 MB -> 50.184 MB. [2024-08-01T00:02:19.997Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T00:02:21.898Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T00:02:24.814Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T00:02:26.702Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T00:02:27.621Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T00:02:29.509Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T00:02:30.428Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T00:02:32.319Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T00:02:32.319Z] 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. [2024-08-01T00:02:32.319Z] The best model improves the baseline by 14.52%. [2024-08-01T00:02:32.319Z] Movies recommended for you: [2024-08-01T00:02:32.319Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T00:02:32.319Z] There is no way to check that no silent failure occurred. [2024-08-01T00:02:32.319Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14841.553 ms) ====== [2024-08-01T00:02:32.319Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-01T00:02:32.319Z] GC before operation: completed in 85.086 ms, heap usage 58.913 MB -> 50.288 MB. [2024-08-01T00:02:34.210Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T00:02:37.126Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T00:02:39.015Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T00:02:40.909Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T00:02:41.828Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T00:02:43.717Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T00:02:44.639Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T00:02:46.528Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T00:02:46.528Z] 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. [2024-08-01T00:02:46.528Z] The best model improves the baseline by 14.52%. [2024-08-01T00:02:46.528Z] Movies recommended for you: [2024-08-01T00:02:46.528Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T00:02:46.528Z] There is no way to check that no silent failure occurred. [2024-08-01T00:02:46.528Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14116.130 ms) ====== [2024-08-01T00:02:46.528Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-01T00:02:46.528Z] GC before operation: completed in 106.311 ms, heap usage 281.702 MB -> 50.161 MB. [2024-08-01T00:02:49.457Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T00:02:51.108Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T00:02:54.051Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T00:02:55.960Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T00:02:56.883Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T00:02:58.772Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T00:02:59.693Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T00:03:01.583Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T00:03:01.583Z] 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. [2024-08-01T00:03:01.583Z] The best model improves the baseline by 14.52%. [2024-08-01T00:03:01.583Z] Movies recommended for you: [2024-08-01T00:03:01.583Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T00:03:01.583Z] There is no way to check that no silent failure occurred. [2024-08-01T00:03:01.583Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (15090.106 ms) ====== [2024-08-01T00:03:01.583Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-01T00:03:01.583Z] GC before operation: completed in 96.934 ms, heap usage 260.800 MB -> 50.264 MB. [2024-08-01T00:03:04.566Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T00:03:06.458Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T00:03:08.349Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T00:03:10.238Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T00:03:12.126Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T00:03:13.045Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T00:03:14.931Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T00:03:15.849Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T00:03:15.849Z] 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. [2024-08-01T00:03:15.849Z] The best model improves the baseline by 14.52%. [2024-08-01T00:03:15.849Z] Movies recommended for you: [2024-08-01T00:03:15.849Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T00:03:15.849Z] There is no way to check that no silent failure occurred. [2024-08-01T00:03:15.849Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14418.728 ms) ====== [2024-08-01T00:03:15.849Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-01T00:03:16.768Z] GC before operation: completed in 88.293 ms, heap usage 174.656 MB -> 50.341 MB. [2024-08-01T00:03:18.659Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T00:03:20.555Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T00:03:22.488Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T00:03:25.584Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T00:03:26.504Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T00:03:27.426Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T00:03:29.318Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T00:03:30.244Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T00:03:31.167Z] 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. [2024-08-01T00:03:31.167Z] The best model improves the baseline by 14.52%. [2024-08-01T00:03:31.167Z] Movies recommended for you: [2024-08-01T00:03:31.167Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T00:03:31.167Z] There is no way to check that no silent failure occurred. [2024-08-01T00:03:31.167Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14687.743 ms) ====== [2024-08-01T00:03:31.167Z] ----------------------------------- [2024-08-01T00:03:31.167Z] renaissance-movie-lens_0_PASSED [2024-08-01T00:03:31.167Z] ----------------------------------- [2024-08-01T00:03:32.087Z] [2024-08-01T00:03:32.087Z] TEST TEARDOWN: [2024-08-01T00:03:32.087Z] Nothing to be done for teardown. [2024-08-01T00:03:32.087Z] renaissance-movie-lens_0 Finish Time: Thu Aug 1 00:03:31 2024 Epoch Time (ms): 1722470611114