[2024-08-17T11:45:22.004Z] Running test renaissance-movie-lens_0 ... [2024-08-17T11:45:22.004Z] =============================================== [2024-08-17T11:45:22.004Z] renaissance-movie-lens_0 Start Time: Sat Aug 17 11:45:21 2024 Epoch Time (ms): 1723895121532 [2024-08-17T11:45:22.004Z] variation: NoOptions [2024-08-17T11:45:22.004Z] JVM_OPTIONS: [2024-08-17T11:45:22.004Z] { \ [2024-08-17T11:45:22.004Z] echo ""; echo "TEST SETUP:"; \ [2024-08-17T11:45:22.004Z] echo "Nothing to be done for setup."; \ [2024-08-17T11:45:22.004Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17238936138096/renaissance-movie-lens_0"; \ [2024-08-17T11:45:22.004Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17238936138096/renaissance-movie-lens_0"; \ [2024-08-17T11:45:22.004Z] echo ""; echo "TESTING:"; \ [2024-08-17T11:45:22.004Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-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_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17238936138096/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-08-17T11:45:22.004Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17238936138096/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-17T11:45:22.004Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-17T11:45:22.004Z] echo "Nothing to be done for teardown."; \ [2024-08-17T11:45:22.004Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17238936138096/TestTargetResult"; [2024-08-17T11:45:22.004Z] [2024-08-17T11:45:22.004Z] TEST SETUP: [2024-08-17T11:45:22.004Z] Nothing to be done for setup. [2024-08-17T11:45:22.004Z] [2024-08-17T11:45:22.004Z] TESTING: [2024-08-17T11:45:26.582Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-17T11:45:31.200Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-08-17T11:45:38.247Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-17T11:45:39.051Z] Training: 60056, validation: 20285, test: 19854 [2024-08-17T11:45:39.051Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-17T11:45:39.854Z] GC before operation: completed in 126.458 ms, heap usage 97.666 MB -> 37.088 MB. [2024-08-17T11:45:56.380Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T11:46:05.207Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T11:46:15.371Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T11:46:23.968Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T11:46:27.556Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T11:46:31.084Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T11:46:35.719Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T11:46:39.270Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T11:46:40.072Z] 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. [2024-08-17T11:46:40.072Z] The best model improves the baseline by 14.52%. [2024-08-17T11:46:40.865Z] Movies recommended for you: [2024-08-17T11:46:40.865Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T11:46:40.865Z] There is no way to check that no silent failure occurred. [2024-08-17T11:46:40.865Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (60930.799 ms) ====== [2024-08-17T11:46:40.865Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-17T11:46:40.865Z] GC before operation: completed in 229.491 ms, heap usage 216.491 MB -> 53.209 MB. [2024-08-17T11:46:47.919Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T11:46:53.735Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T11:47:00.227Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T11:47:05.986Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T11:47:09.503Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T11:47:12.179Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T11:47:15.928Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T11:47:19.617Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T11:47:20.455Z] 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. [2024-08-17T11:47:20.456Z] The best model improves the baseline by 14.52%. [2024-08-17T11:47:20.456Z] Movies recommended for you: [2024-08-17T11:47:20.456Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T11:47:20.456Z] There is no way to check that no silent failure occurred. [2024-08-17T11:47:20.456Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (39649.288 ms) ====== [2024-08-17T11:47:20.456Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-17T11:47:20.456Z] GC before operation: completed in 204.182 ms, heap usage 346.263 MB -> 49.817 MB. [2024-08-17T11:47:26.519Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T11:47:32.553Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T11:47:37.374Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T11:47:42.199Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T11:47:45.935Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T11:47:49.636Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T11:47:53.343Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T11:47:55.071Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T11:47:55.911Z] 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. [2024-08-17T11:47:55.911Z] The best model improves the baseline by 14.52%. [2024-08-17T11:47:55.911Z] Movies recommended for you: [2024-08-17T11:47:55.911Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T11:47:55.911Z] There is no way to check that no silent failure occurred. [2024-08-17T11:47:55.911Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (35664.087 ms) ====== [2024-08-17T11:47:55.911Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-17T11:47:56.759Z] GC before operation: completed in 142.361 ms, heap usage 190.173 MB -> 49.955 MB. [2024-08-17T11:48:01.575Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T11:48:06.373Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T11:48:11.968Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T11:48:16.901Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T11:48:20.633Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T11:48:23.316Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T11:48:25.984Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T11:48:29.694Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T11:48:29.694Z] 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. [2024-08-17T11:48:29.694Z] The best model improves the baseline by 14.52%. [2024-08-17T11:48:30.536Z] Movies recommended for you: [2024-08-17T11:48:30.536Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T11:48:30.536Z] There is no way to check that no silent failure occurred. [2024-08-17T11:48:30.536Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (33755.925 ms) ====== [2024-08-17T11:48:30.536Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-17T11:48:30.536Z] GC before operation: completed in 145.677 ms, heap usage 166.582 MB -> 50.215 MB. [2024-08-17T11:48:35.355Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T11:48:41.362Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T11:48:46.172Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T11:48:50.971Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T11:48:54.683Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T11:48:58.399Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T11:49:02.107Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T11:49:04.788Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T11:49:04.788Z] 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. [2024-08-17T11:49:04.788Z] The best model improves the baseline by 14.52%. [2024-08-17T11:49:05.622Z] Movies recommended for you: [2024-08-17T11:49:05.622Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T11:49:05.622Z] There is no way to check that no silent failure occurred. [2024-08-17T11:49:05.622Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (34979.679 ms) ====== [2024-08-17T11:49:05.622Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-17T11:49:05.622Z] GC before operation: completed in 173.734 ms, heap usage 89.984 MB -> 51.284 MB. [2024-08-17T11:49:10.420Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T11:49:16.733Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T11:49:21.556Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T11:49:26.373Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T11:49:30.091Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T11:49:32.810Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T11:49:35.656Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T11:49:39.556Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T11:49:39.556Z] 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. [2024-08-17T11:49:39.556Z] The best model improves the baseline by 14.52%. [2024-08-17T11:49:40.452Z] Movies recommended for you: [2024-08-17T11:49:40.453Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T11:49:40.453Z] There is no way to check that no silent failure occurred. [2024-08-17T11:49:40.453Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (34580.355 ms) ====== [2024-08-17T11:49:40.453Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-17T11:49:40.453Z] GC before operation: completed in 139.257 ms, heap usage 179.313 MB -> 50.464 MB. [2024-08-17T11:49:46.752Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T11:49:50.678Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T11:49:56.950Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T11:49:59.759Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T11:50:02.581Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T11:50:05.389Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T11:50:08.242Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T11:50:12.127Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T11:50:12.127Z] 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. [2024-08-17T11:50:12.127Z] The best model improves the baseline by 14.52%. [2024-08-17T11:50:13.020Z] Movies recommended for you: [2024-08-17T11:50:13.020Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T11:50:13.020Z] There is no way to check that no silent failure occurred. [2024-08-17T11:50:13.020Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (32415.395 ms) ====== [2024-08-17T11:50:13.020Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-17T11:50:13.020Z] GC before operation: completed in 157.201 ms, heap usage 77.841 MB -> 52.810 MB. [2024-08-17T11:50:18.379Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T11:50:23.436Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T11:50:27.322Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T11:50:32.398Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T11:50:36.285Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T11:50:39.114Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T11:50:41.936Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T11:50:45.822Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T11:50:45.822Z] 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. [2024-08-17T11:50:45.822Z] The best model improves the baseline by 14.52%. [2024-08-17T11:50:45.822Z] Movies recommended for you: [2024-08-17T11:50:45.822Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T11:50:45.822Z] There is no way to check that no silent failure occurred. [2024-08-17T11:50:45.822Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (33332.711 ms) ====== [2024-08-17T11:50:45.822Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-17T11:50:46.701Z] GC before operation: completed in 153.322 ms, heap usage 284.415 MB -> 50.955 MB. [2024-08-17T11:50:50.583Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T11:50:56.902Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T11:51:01.946Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T11:51:06.977Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T11:51:09.784Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T11:51:12.615Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T11:51:15.446Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T11:51:18.318Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T11:51:18.318Z] 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. [2024-08-17T11:51:18.318Z] The best model improves the baseline by 14.52%. [2024-08-17T11:51:18.318Z] Movies recommended for you: [2024-08-17T11:51:18.318Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T11:51:18.318Z] There is no way to check that no silent failure occurred. [2024-08-17T11:51:18.318Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (32340.759 ms) ====== [2024-08-17T11:51:18.318Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-17T11:51:18.318Z] GC before operation: completed in 136.528 ms, heap usage 244.625 MB -> 50.827 MB. [2024-08-17T11:51:23.369Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T11:51:28.075Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T11:51:34.385Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T11:51:39.459Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T11:51:43.360Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T11:51:46.203Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T11:51:50.114Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T11:51:52.970Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T11:51:53.859Z] 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. [2024-08-17T11:51:53.859Z] The best model improves the baseline by 14.52%. [2024-08-17T11:51:53.859Z] Movies recommended for you: [2024-08-17T11:51:53.859Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T11:51:53.859Z] There is no way to check that no silent failure occurred. [2024-08-17T11:51:53.859Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (35030.610 ms) ====== [2024-08-17T11:51:53.859Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-17T11:51:53.859Z] GC before operation: completed in 181.071 ms, heap usage 148.961 MB -> 50.771 MB. [2024-08-17T11:51:58.935Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T11:52:05.243Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T11:52:10.293Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T11:52:15.350Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T11:52:18.265Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T11:52:21.111Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T11:52:24.999Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T11:52:27.831Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T11:52:28.718Z] 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. [2024-08-17T11:52:28.718Z] The best model improves the baseline by 14.52%. [2024-08-17T11:52:28.718Z] Movies recommended for you: [2024-08-17T11:52:28.718Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T11:52:28.718Z] There is no way to check that no silent failure occurred. [2024-08-17T11:52:28.718Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (34798.519 ms) ====== [2024-08-17T11:52:28.718Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-17T11:52:28.718Z] GC before operation: completed in 136.109 ms, heap usage 178.556 MB -> 50.612 MB. [2024-08-17T11:52:33.746Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T11:52:38.286Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T11:52:43.331Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T11:52:48.349Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T11:52:51.164Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T11:52:53.990Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T11:52:56.816Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T11:52:59.630Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T11:52:59.631Z] 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. [2024-08-17T11:52:59.631Z] The best model improves the baseline by 14.52%. [2024-08-17T11:52:59.631Z] Movies recommended for you: [2024-08-17T11:52:59.631Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T11:52:59.631Z] There is no way to check that no silent failure occurred. [2024-08-17T11:52:59.631Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (30877.067 ms) ====== [2024-08-17T11:52:59.631Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-17T11:52:59.631Z] GC before operation: completed in 171.654 ms, heap usage 147.517 MB -> 50.724 MB. [2024-08-17T11:53:04.677Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T11:53:09.718Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T11:53:13.598Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T11:53:18.646Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T11:53:21.471Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T11:53:24.274Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T11:53:27.101Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T11:53:29.931Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T11:53:29.931Z] 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. [2024-08-17T11:53:29.931Z] The best model improves the baseline by 14.52%. [2024-08-17T11:53:29.931Z] Movies recommended for you: [2024-08-17T11:53:29.931Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T11:53:29.931Z] There is no way to check that no silent failure occurred. [2024-08-17T11:53:29.931Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (30172.921 ms) ====== [2024-08-17T11:53:29.931Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-17T11:53:29.931Z] GC before operation: completed in 130.951 ms, heap usage 232.179 MB -> 50.929 MB. [2024-08-17T11:53:34.968Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T11:53:39.987Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T11:53:44.551Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T11:53:49.586Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T11:53:51.397Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T11:53:54.213Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T11:53:57.027Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T11:53:59.838Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T11:54:00.728Z] 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. [2024-08-17T11:54:00.728Z] The best model improves the baseline by 14.52%. [2024-08-17T11:54:00.728Z] Movies recommended for you: [2024-08-17T11:54:00.728Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T11:54:00.728Z] There is no way to check that no silent failure occurred. [2024-08-17T11:54:00.728Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (30515.178 ms) ====== [2024-08-17T11:54:00.728Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-17T11:54:00.728Z] GC before operation: completed in 168.372 ms, heap usage 234.300 MB -> 50.691 MB. [2024-08-17T11:54:05.765Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T11:54:09.644Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T11:54:14.673Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T11:54:19.711Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T11:54:22.531Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T11:54:25.346Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T11:54:28.147Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T11:54:30.966Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T11:54:30.966Z] 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. [2024-08-17T11:54:30.966Z] The best model improves the baseline by 14.52%. [2024-08-17T11:54:30.966Z] Movies recommended for you: [2024-08-17T11:54:30.966Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T11:54:30.966Z] There is no way to check that no silent failure occurred. [2024-08-17T11:54:30.967Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (30400.109 ms) ====== [2024-08-17T11:54:30.967Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-17T11:54:31.849Z] GC before operation: completed in 177.605 ms, heap usage 348.642 MB -> 51.055 MB. [2024-08-17T11:54:35.731Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T11:54:40.742Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T11:54:45.763Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T11:54:50.912Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T11:54:52.792Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T11:54:56.669Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T11:54:59.488Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T11:55:02.310Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T11:55:02.310Z] 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. [2024-08-17T11:55:02.310Z] The best model improves the baseline by 14.52%. [2024-08-17T11:55:02.310Z] Movies recommended for you: [2024-08-17T11:55:02.310Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T11:55:02.310Z] There is no way to check that no silent failure occurred. [2024-08-17T11:55:02.310Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (31202.489 ms) ====== [2024-08-17T11:55:02.310Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-17T11:55:03.195Z] GC before operation: completed in 136.330 ms, heap usage 169.562 MB -> 50.848 MB. [2024-08-17T11:55:07.077Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T11:55:12.105Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T11:55:16.007Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T11:55:20.234Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T11:55:23.054Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T11:55:25.863Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T11:55:28.698Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T11:55:31.512Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T11:55:32.394Z] 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. [2024-08-17T11:55:32.394Z] The best model improves the baseline by 14.52%. [2024-08-17T11:55:32.394Z] Movies recommended for you: [2024-08-17T11:55:32.394Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T11:55:32.394Z] There is no way to check that no silent failure occurred. [2024-08-17T11:55:32.394Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (29367.435 ms) ====== [2024-08-17T11:55:32.394Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-17T11:55:32.394Z] GC before operation: completed in 141.300 ms, heap usage 268.140 MB -> 50.832 MB. [2024-08-17T11:55:37.427Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T11:55:41.316Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T11:55:46.384Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T11:55:50.274Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T11:55:53.086Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T11:55:54.938Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T11:55:58.392Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T11:56:01.199Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T11:56:01.199Z] 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. [2024-08-17T11:56:01.199Z] The best model improves the baseline by 14.52%. [2024-08-17T11:56:01.199Z] Movies recommended for you: [2024-08-17T11:56:01.199Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T11:56:01.199Z] There is no way to check that no silent failure occurred. [2024-08-17T11:56:01.199Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (28955.709 ms) ====== [2024-08-17T11:56:01.199Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-17T11:56:01.199Z] GC before operation: completed in 121.445 ms, heap usage 146.533 MB -> 50.750 MB. [2024-08-17T11:56:06.237Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T11:56:10.107Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T11:56:15.141Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T11:56:19.186Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T11:56:22.007Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T11:56:24.815Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T11:56:27.633Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T11:56:30.464Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T11:56:30.464Z] 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. [2024-08-17T11:56:30.464Z] The best model improves the baseline by 14.52%. [2024-08-17T11:56:31.355Z] Movies recommended for you: [2024-08-17T11:56:31.355Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T11:56:31.355Z] There is no way to check that no silent failure occurred. [2024-08-17T11:56:31.355Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (29565.972 ms) ====== [2024-08-17T11:56:31.355Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-17T11:56:31.355Z] GC before operation: completed in 149.751 ms, heap usage 256.907 MB -> 51.076 MB. [2024-08-17T11:56:36.395Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-17T11:56:40.304Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-17T11:56:45.337Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-17T11:56:50.426Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-17T11:56:51.306Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-17T11:56:54.131Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-17T11:56:56.958Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-17T11:56:58.791Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-17T11:56:59.686Z] 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. [2024-08-17T11:56:59.686Z] The best model improves the baseline by 14.52%. [2024-08-17T11:56:59.686Z] Movies recommended for you: [2024-08-17T11:56:59.686Z] WARNING: This benchmark provides no result that can be validated. [2024-08-17T11:56:59.686Z] There is no way to check that no silent failure occurred. [2024-08-17T11:56:59.686Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (28718.179 ms) ====== [2024-08-17T11:57:00.574Z] ----------------------------------- [2024-08-17T11:57:00.574Z] renaissance-movie-lens_0_PASSED [2024-08-17T11:57:00.574Z] ----------------------------------- [2024-08-17T11:57:00.574Z] [2024-08-17T11:57:00.574Z] TEST TEARDOWN: [2024-08-17T11:57:00.574Z] Nothing to be done for teardown. [2024-08-17T11:57:00.574Z] renaissance-movie-lens_0 Finish Time: Sat Aug 17 11:57:00 2024 Epoch Time (ms): 1723895820029