[2024-08-17T07:16:36.501Z] Running test renaissance-movie-lens_0 ... [2024-08-17T07:16:36.812Z] =============================================== [2024-08-17T07:16:36.813Z] renaissance-movie-lens_0 Start Time: Sat Aug 17 07:16:36 2024 Epoch Time (ms): 1723878996695 [2024-08-17T07:16:37.121Z] variation: NoOptions [2024-08-17T07:16:37.444Z] JVM_OPTIONS: [2024-08-17T07:16:37.444Z] { \ [2024-08-17T07:16:37.444Z] echo ""; echo "TEST SETUP:"; \ [2024-08-17T07:16:37.444Z] echo "Nothing to be done for setup."; \ [2024-08-17T07:16:37.444Z] mkdir -p "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_1723877742735\\renaissance-movie-lens_0"; \ [2024-08-17T07:16:37.444Z] cd "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_1723877742735\\renaissance-movie-lens_0"; \ [2024-08-17T07:16:37.444Z] echo ""; echo "TESTING:"; \ [2024-08-17T07:16:37.444Z] "c:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows_testList_0/jdkbinary/j2sdk-image\\bin\\java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows_testList_0/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_1723877742735\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2024-08-17T07:16:37.444Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_1723877742735\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-17T07:16:37.444Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-17T07:16:37.444Z] echo "Nothing to be done for teardown."; \ [2024-08-17T07:16:37.444Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_1723877742735\\TestTargetResult"; [2024-08-17T07:16:37.444Z] [2024-08-17T07:16:37.444Z] TEST SETUP: [2024-08-17T07:16:37.444Z] Nothing to be done for setup. [2024-08-17T07:16:37.444Z] [2024-08-17T07:16:37.444Z] TESTING: [2024-08-17T07:16:48.045Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-17T07:16:49.646Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-08-17T07:16:52.563Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-17T07:16:52.963Z] Training: 60056, validation: 20285, test: 19854 [2024-08-17T07:16:52.963Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-17T07:16:53.291Z] GC before operation: completed in 70.235 ms, heap usage 56.818 MB -> 36.930 MB. [2024-08-17T07:17:06.328Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T07:17:13.441Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T07:17:22.222Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T07:17:28.003Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T07:17:32.612Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T07:17:36.303Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T07:17:40.944Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T07:17:44.642Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T07:17:45.017Z] 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. [2024-08-17T07:17:45.017Z] The best model improves the baseline by 14.52%. [2024-08-17T07:17:45.017Z] Movies recommended for you: [2024-08-17T07:17:45.017Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T07:17:45.017Z] There is no way to check that no silent failure occurred. [2024-08-17T07:17:45.017Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (51984.862 ms) ====== [2024-08-17T07:17:45.018Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-17T07:17:45.343Z] GC before operation: completed in 94.799 ms, heap usage 111.256 MB -> 47.259 MB. [2024-08-17T07:17:52.498Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T07:17:59.639Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T07:18:06.822Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T07:18:13.926Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T07:18:17.628Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T07:18:21.426Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T07:18:26.091Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T07:18:29.853Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T07:18:29.853Z] 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. [2024-08-17T07:18:29.853Z] The best model improves the baseline by 14.52%. [2024-08-17T07:18:29.853Z] Movies recommended for you: [2024-08-17T07:18:29.853Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T07:18:29.853Z] There is no way to check that no silent failure occurred. [2024-08-17T07:18:29.853Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (44637.212 ms) ====== [2024-08-17T07:18:29.853Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-17T07:18:30.177Z] GC before operation: completed in 81.780 ms, heap usage 73.220 MB -> 52.709 MB. [2024-08-17T07:18:37.332Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T07:18:44.479Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T07:18:51.594Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T07:18:57.367Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T07:19:01.997Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T07:19:05.694Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T07:19:09.425Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T07:19:13.106Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T07:19:13.106Z] 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. [2024-08-17T07:19:13.432Z] The best model improves the baseline by 14.52%. [2024-08-17T07:19:13.432Z] Movies recommended for you: [2024-08-17T07:19:13.432Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T07:19:13.432Z] There is no way to check that no silent failure occurred. [2024-08-17T07:19:13.432Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (43475.156 ms) ====== [2024-08-17T07:19:13.432Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-17T07:19:13.432Z] GC before operation: completed in 100.135 ms, heap usage 92.113 MB -> 52.876 MB. [2024-08-17T07:19:20.627Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T07:19:27.794Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T07:19:34.926Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T07:19:42.033Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T07:19:45.705Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T07:19:50.337Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T07:19:54.025Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T07:19:57.707Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T07:19:58.033Z] 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. [2024-08-17T07:19:58.033Z] The best model improves the baseline by 14.52%. [2024-08-17T07:19:58.033Z] Movies recommended for you: [2024-08-17T07:19:58.033Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T07:19:58.033Z] There is no way to check that no silent failure occurred. [2024-08-17T07:19:58.033Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (44566.075 ms) ====== [2024-08-17T07:19:58.033Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-17T07:19:58.033Z] GC before operation: completed in 89.672 ms, heap usage 105.639 MB -> 50.070 MB. [2024-08-17T07:20:05.175Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T07:20:12.329Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T07:20:19.446Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T07:20:25.211Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T07:20:29.872Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T07:20:33.541Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T07:20:37.229Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T07:20:41.877Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T07:20:41.877Z] 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. [2024-08-17T07:20:41.877Z] The best model improves the baseline by 14.52%. [2024-08-17T07:20:41.877Z] Movies recommended for you: [2024-08-17T07:20:41.877Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T07:20:41.878Z] There is no way to check that no silent failure occurred. [2024-08-17T07:20:41.878Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (43578.022 ms) ====== [2024-08-17T07:20:41.878Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-17T07:20:41.878Z] GC before operation: completed in 78.160 ms, heap usage 181.362 MB -> 50.350 MB. [2024-08-17T07:20:49.027Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T07:20:54.832Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T07:21:01.937Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T07:21:09.054Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T07:21:12.726Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T07:21:16.453Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T07:21:20.128Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T07:21:23.796Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T07:21:24.509Z] 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. [2024-08-17T07:21:24.509Z] The best model improves the baseline by 14.52%. [2024-08-17T07:21:24.509Z] Movies recommended for you: [2024-08-17T07:21:24.509Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T07:21:24.509Z] There is no way to check that no silent failure occurred. [2024-08-17T07:21:24.509Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (42760.120 ms) ====== [2024-08-17T07:21:24.509Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-17T07:21:24.830Z] GC before operation: completed in 84.363 ms, heap usage 183.049 MB -> 50.956 MB. [2024-08-17T07:21:31.990Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T07:21:39.103Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T07:21:46.208Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T07:21:52.006Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T07:21:55.678Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T07:21:59.358Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T07:22:03.997Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T07:22:07.667Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T07:22:07.667Z] 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. [2024-08-17T07:22:07.667Z] The best model improves the baseline by 14.52%. [2024-08-17T07:22:07.667Z] Movies recommended for you: [2024-08-17T07:22:07.667Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T07:22:07.667Z] There is no way to check that no silent failure occurred. [2024-08-17T07:22:07.667Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (43084.238 ms) ====== [2024-08-17T07:22:07.667Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-17T07:22:07.994Z] GC before operation: completed in 94.589 ms, heap usage 200.077 MB -> 50.447 MB. [2024-08-17T07:22:15.163Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T07:22:22.289Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T07:22:29.422Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T07:22:35.205Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T07:22:39.830Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T07:22:42.709Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T07:22:47.348Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T07:22:51.022Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T07:22:51.022Z] 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. [2024-08-17T07:22:51.022Z] The best model improves the baseline by 14.52%. [2024-08-17T07:22:51.348Z] Movies recommended for you: [2024-08-17T07:22:51.348Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T07:22:51.348Z] There is no way to check that no silent failure occurred. [2024-08-17T07:22:51.348Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (43440.410 ms) ====== [2024-08-17T07:22:51.348Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-17T07:22:51.348Z] GC before operation: completed in 85.197 ms, heap usage 117.562 MB -> 50.632 MB. [2024-08-17T07:22:58.476Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T07:23:05.590Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T07:23:12.731Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T07:23:18.509Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T07:23:22.221Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T07:23:25.933Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T07:23:29.615Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T07:23:33.303Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T07:23:33.645Z] 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. [2024-08-17T07:23:33.645Z] The best model improves the baseline by 14.52%. [2024-08-17T07:23:33.995Z] Movies recommended for you: [2024-08-17T07:23:33.995Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T07:23:33.995Z] There is no way to check that no silent failure occurred. [2024-08-17T07:23:33.995Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (42436.330 ms) ====== [2024-08-17T07:23:33.995Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-17T07:23:33.995Z] GC before operation: completed in 89.686 ms, heap usage 77.608 MB -> 53.703 MB. [2024-08-17T07:23:41.123Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T07:23:48.260Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T07:23:54.040Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T07:24:01.158Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T07:24:04.079Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T07:24:07.758Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T07:24:11.439Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T07:24:15.133Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T07:24:15.458Z] 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. [2024-08-17T07:24:15.458Z] The best model improves the baseline by 14.52%. [2024-08-17T07:24:15.458Z] Movies recommended for you: [2024-08-17T07:24:15.458Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T07:24:15.458Z] There is no way to check that no silent failure occurred. [2024-08-17T07:24:15.458Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (41642.199 ms) ====== [2024-08-17T07:24:15.458Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-17T07:24:15.810Z] GC before operation: completed in 91.855 ms, heap usage 193.572 MB -> 52.838 MB. [2024-08-17T07:24:22.944Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T07:24:30.064Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T07:24:35.829Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T07:24:42.993Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T07:24:46.670Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T07:24:50.356Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T07:24:54.030Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T07:24:57.741Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T07:24:57.741Z] 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. [2024-08-17T07:24:57.741Z] The best model improves the baseline by 14.52%. [2024-08-17T07:24:57.741Z] Movies recommended for you: [2024-08-17T07:24:57.741Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T07:24:57.741Z] There is no way to check that no silent failure occurred. [2024-08-17T07:24:57.741Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (42200.536 ms) ====== [2024-08-17T07:24:57.741Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-17T07:24:58.063Z] GC before operation: completed in 97.476 ms, heap usage 141.618 MB -> 53.561 MB. [2024-08-17T07:25:05.174Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T07:25:12.276Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T07:25:18.065Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T07:25:25.181Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T07:25:28.058Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T07:25:31.779Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T07:25:35.490Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T07:25:39.189Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T07:25:39.588Z] 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. [2024-08-17T07:25:39.588Z] The best model improves the baseline by 14.52%. [2024-08-17T07:25:39.588Z] Movies recommended for you: [2024-08-17T07:25:39.588Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T07:25:39.589Z] There is no way to check that no silent failure occurred. [2024-08-17T07:25:39.589Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (41605.569 ms) ====== [2024-08-17T07:25:39.589Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-17T07:25:39.589Z] GC before operation: completed in 90.506 ms, heap usage 222.364 MB -> 53.804 MB. [2024-08-17T07:25:46.703Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T07:25:53.828Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T07:26:00.941Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T07:26:06.691Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T07:26:10.357Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T07:26:14.980Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T07:26:18.668Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T07:26:22.345Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T07:26:22.345Z] 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. [2024-08-17T07:26:22.345Z] The best model improves the baseline by 14.52%. [2024-08-17T07:26:22.345Z] Movies recommended for you: [2024-08-17T07:26:22.345Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T07:26:22.345Z] There is no way to check that no silent failure occurred. [2024-08-17T07:26:22.345Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (42770.483 ms) ====== [2024-08-17T07:26:22.345Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-17T07:26:22.345Z] GC before operation: completed in 92.237 ms, heap usage 140.295 MB -> 50.655 MB. [2024-08-17T07:26:29.474Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T07:26:36.608Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T07:26:43.738Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T07:26:49.580Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T07:26:54.197Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T07:26:57.074Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T07:27:01.739Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T07:27:05.439Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T07:27:05.790Z] 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. [2024-08-17T07:27:05.790Z] The best model improves the baseline by 14.52%. [2024-08-17T07:27:05.790Z] Movies recommended for you: [2024-08-17T07:27:05.790Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T07:27:05.790Z] There is no way to check that no silent failure occurred. [2024-08-17T07:27:05.790Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (43303.183 ms) ====== [2024-08-17T07:27:05.790Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-17T07:27:05.790Z] GC before operation: completed in 85.540 ms, heap usage 223.825 MB -> 50.464 MB. [2024-08-17T07:27:12.891Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T07:27:19.995Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T07:27:27.187Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T07:27:34.294Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T07:27:37.980Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T07:27:41.658Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T07:27:45.361Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T07:27:49.038Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T07:27:49.374Z] 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. [2024-08-17T07:27:49.374Z] The best model improves the baseline by 14.52%. [2024-08-17T07:27:49.374Z] Movies recommended for you: [2024-08-17T07:27:49.374Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T07:27:49.374Z] There is no way to check that no silent failure occurred. [2024-08-17T07:27:49.374Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (43574.790 ms) ====== [2024-08-17T07:27:49.374Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-17T07:27:49.697Z] GC before operation: completed in 84.435 ms, heap usage 131.764 MB -> 50.577 MB. [2024-08-17T07:27:56.838Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T07:28:03.939Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T07:28:09.729Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T07:28:16.861Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T07:28:20.531Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T07:28:24.206Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T07:28:27.976Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T07:28:31.680Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T07:28:32.013Z] 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. [2024-08-17T07:28:32.352Z] The best model improves the baseline by 14.52%. [2024-08-17T07:28:32.352Z] Movies recommended for you: [2024-08-17T07:28:32.352Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T07:28:32.352Z] There is no way to check that no silent failure occurred. [2024-08-17T07:28:32.352Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (42758.802 ms) ====== [2024-08-17T07:28:32.352Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-17T07:28:32.352Z] GC before operation: completed in 92.930 ms, heap usage 138.192 MB -> 50.664 MB. [2024-08-17T07:28:39.501Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T07:28:46.597Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T07:28:53.718Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T07:28:59.507Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T07:29:03.198Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T07:29:06.934Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T07:29:10.630Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T07:29:14.305Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T07:29:14.645Z] 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. [2024-08-17T07:29:14.645Z] The best model improves the baseline by 14.52%. [2024-08-17T07:29:14.972Z] Movies recommended for you: [2024-08-17T07:29:14.972Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T07:29:14.972Z] There is no way to check that no silent failure occurred. [2024-08-17T07:29:14.972Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (42408.589 ms) ====== [2024-08-17T07:29:14.972Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-17T07:29:14.972Z] GC before operation: completed in 101.253 ms, heap usage 303.652 MB -> 50.679 MB. [2024-08-17T07:29:22.101Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T07:29:27.907Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T07:29:35.026Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T07:29:42.166Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T07:29:45.050Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T07:29:48.734Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T07:29:53.382Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T07:29:56.247Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T07:29:56.931Z] 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. [2024-08-17T07:29:56.931Z] The best model improves the baseline by 14.52%. [2024-08-17T07:29:56.931Z] Movies recommended for you: [2024-08-17T07:29:56.931Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T07:29:56.931Z] There is no way to check that no silent failure occurred. [2024-08-17T07:29:56.931Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (42074.380 ms) ====== [2024-08-17T07:29:56.931Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-17T07:29:56.931Z] GC before operation: completed in 84.754 ms, heap usage 178.273 MB -> 50.629 MB. [2024-08-17T07:30:04.047Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T07:30:09.801Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T07:30:16.932Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T07:30:24.036Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T07:30:27.720Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T07:30:30.603Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T07:30:35.246Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T07:30:38.943Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T07:30:38.943Z] 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. [2024-08-17T07:30:38.943Z] The best model improves the baseline by 14.52%. [2024-08-17T07:30:38.943Z] Movies recommended for you: [2024-08-17T07:30:38.943Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T07:30:38.943Z] There is no way to check that no silent failure occurred. [2024-08-17T07:30:38.943Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (41950.410 ms) ====== [2024-08-17T07:30:38.943Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-17T07:30:39.264Z] GC before operation: completed in 94.006 ms, heap usage 83.965 MB -> 50.669 MB. [2024-08-17T07:30:46.402Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T07:30:53.713Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T07:31:00.846Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T07:31:06.588Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T07:31:10.253Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T07:31:13.934Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T07:31:18.572Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T07:31:22.263Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T07:31:22.263Z] 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. [2024-08-17T07:31:22.263Z] The best model improves the baseline by 14.52%. [2024-08-17T07:31:22.583Z] Movies recommended for you: [2024-08-17T07:31:22.583Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T07:31:22.583Z] There is no way to check that no silent failure occurred. [2024-08-17T07:31:22.583Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (43305.579 ms) ====== [2024-08-17T07:31:22.906Z] ----------------------------------- [2024-08-17T07:31:22.906Z] renaissance-movie-lens_0_PASSED [2024-08-17T07:31:22.906Z] ----------------------------------- [2024-08-17T07:31:23.227Z] [2024-08-17T07:31:23.227Z] TEST TEARDOWN: [2024-08-17T07:31:23.227Z] Nothing to be done for teardown. [2024-08-17T07:31:23.538Z] renaissance-movie-lens_0 Finish Time: Sat Aug 17 07:31:23 2024 Epoch Time (ms): 1723879883316