renaissance-movie-lens_0
[2024-08-17T02:08:11.176Z] Running test renaissance-movie-lens_0 ...
[2024-08-17T02:08:11.176Z] ===============================================
[2024-08-17T02:08:11.176Z] renaissance-movie-lens_0 Start Time: Sat Aug 17 02:08:10 2024 Epoch Time (ms): 1723860490797
[2024-08-17T02:08:11.176Z] variation: NoOptions
[2024-08-17T02:08:11.176Z] JVM_OPTIONS:
[2024-08-17T02:08:11.176Z] { \
[2024-08-17T02:08:11.176Z] echo ""; echo "TEST SETUP:"; \
[2024-08-17T02:08:11.176Z] echo "Nothing to be done for setup."; \
[2024-08-17T02:08:11.177Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17238570491189/renaissance-movie-lens_0"; \
[2024-08-17T02:08:11.177Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17238570491189/renaissance-movie-lens_0"; \
[2024-08-17T02:08:11.177Z] echo ""; echo "TESTING:"; \
[2024-08-17T02:08:11.177Z] "/home/jenkins/workspace/Test_openjdk11_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_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17238570491189/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-17T02:08:11.177Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17238570491189/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-17T02:08:11.177Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-17T02:08:11.177Z] echo "Nothing to be done for teardown."; \
[2024-08-17T02:08:11.177Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17238570491189/TestTargetResult";
[2024-08-17T02:08:11.177Z]
[2024-08-17T02:08:11.177Z] TEST SETUP:
[2024-08-17T02:08:11.177Z] Nothing to be done for setup.
[2024-08-17T02:08:11.177Z]
[2024-08-17T02:08:11.177Z] TESTING:
[2024-08-17T02:08:18.319Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-17T02:08:24.764Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-08-17T02:08:35.384Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-17T02:08:37.068Z] Training: 60056, validation: 20285, test: 19854
[2024-08-17T02:08:37.068Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-17T02:08:37.068Z] GC before operation: completed in 296.753 ms, heap usage 115.604 MB -> 36.485 MB.
[2024-08-17T02:09:03.698Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T02:09:18.020Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T02:09:32.291Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T02:09:47.229Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T02:09:54.417Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T02:10:00.321Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T02:10:07.600Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T02:10:12.311Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T02:10:13.136Z] 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.
[2024-08-17T02:10:13.136Z] The best model improves the baseline by 14.52%.
[2024-08-17T02:10:13.999Z] Movies recommended for you:
[2024-08-17T02:10:13.999Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T02:10:13.999Z] There is no way to check that no silent failure occurred.
[2024-08-17T02:10:13.999Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (96472.051 ms) ======
[2024-08-17T02:10:13.999Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-17T02:10:13.999Z] GC before operation: completed in 568.369 ms, heap usage 173.383 MB -> 49.004 MB.
[2024-08-17T02:10:24.428Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T02:10:34.772Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T02:10:45.100Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T02:10:54.327Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T02:11:00.217Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T02:11:06.228Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T02:11:12.124Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T02:11:17.998Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T02:11:17.998Z] 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.
[2024-08-17T02:11:17.998Z] The best model improves the baseline by 14.52%.
[2024-08-17T02:11:18.824Z] Movies recommended for you:
[2024-08-17T02:11:18.824Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T02:11:18.824Z] There is no way to check that no silent failure occurred.
[2024-08-17T02:11:18.824Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (64417.378 ms) ======
[2024-08-17T02:11:18.824Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-17T02:11:18.824Z] GC before operation: completed in 338.599 ms, heap usage 115.295 MB -> 48.953 MB.
[2024-08-17T02:11:29.119Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T02:11:37.981Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T02:11:48.228Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T02:11:57.444Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T02:12:02.146Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T02:12:08.001Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T02:12:13.847Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T02:12:19.750Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T02:12:20.563Z] 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.
[2024-08-17T02:12:20.563Z] The best model improves the baseline by 14.52%.
[2024-08-17T02:12:20.563Z] Movies recommended for you:
[2024-08-17T02:12:20.563Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T02:12:20.563Z] There is no way to check that no silent failure occurred.
[2024-08-17T02:12:20.563Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (61575.121 ms) ======
[2024-08-17T02:12:20.563Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-17T02:12:21.376Z] GC before operation: completed in 355.505 ms, heap usage 130.983 MB -> 49.243 MB.
[2024-08-17T02:12:31.652Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T02:12:42.071Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T02:12:50.707Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T02:12:59.339Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T02:13:05.671Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T02:13:11.576Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T02:13:16.257Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T02:13:22.188Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T02:13:22.188Z] 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.
[2024-08-17T02:13:22.188Z] The best model improves the baseline by 14.52%.
[2024-08-17T02:13:22.996Z] Movies recommended for you:
[2024-08-17T02:13:22.996Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T02:13:22.996Z] There is no way to check that no silent failure occurred.
[2024-08-17T02:13:22.996Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (61731.051 ms) ======
[2024-08-17T02:13:22.996Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-17T02:13:22.996Z] GC before operation: completed in 281.555 ms, heap usage 121.122 MB -> 49.584 MB.
[2024-08-17T02:13:31.704Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T02:13:40.404Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T02:13:49.134Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T02:13:57.748Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T02:14:02.419Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T02:14:07.697Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T02:14:13.526Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T02:14:19.387Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T02:14:20.212Z] 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.
[2024-08-17T02:14:20.212Z] The best model improves the baseline by 14.52%.
[2024-08-17T02:14:21.054Z] Movies recommended for you:
[2024-08-17T02:14:21.054Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T02:14:21.054Z] There is no way to check that no silent failure occurred.
[2024-08-17T02:14:21.054Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (57717.594 ms) ======
[2024-08-17T02:14:21.054Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-17T02:14:21.054Z] GC before operation: completed in 433.062 ms, heap usage 211.731 MB -> 49.834 MB.
[2024-08-17T02:14:31.308Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T02:14:40.033Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T02:14:50.282Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T02:14:57.422Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T02:15:02.004Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T02:15:05.522Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T02:15:10.651Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T02:15:15.285Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T02:15:16.091Z] 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.
[2024-08-17T02:15:16.091Z] The best model improves the baseline by 14.52%.
[2024-08-17T02:15:16.091Z] Movies recommended for you:
[2024-08-17T02:15:16.091Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T02:15:16.091Z] There is no way to check that no silent failure occurred.
[2024-08-17T02:15:16.091Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (54914.587 ms) ======
[2024-08-17T02:15:16.091Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-17T02:15:16.091Z] GC before operation: completed in 352.773 ms, heap usage 269.866 MB -> 49.879 MB.
[2024-08-17T02:15:26.318Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T02:15:33.440Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T02:15:42.171Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T02:15:50.675Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T02:15:54.268Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T02:15:58.886Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T02:16:02.534Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T02:16:07.165Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T02:16:07.165Z] 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.
[2024-08-17T02:16:08.519Z] The best model improves the baseline by 14.52%.
[2024-08-17T02:16:08.519Z] Movies recommended for you:
[2024-08-17T02:16:08.519Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T02:16:08.519Z] There is no way to check that no silent failure occurred.
[2024-08-17T02:16:08.519Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (51316.420 ms) ======
[2024-08-17T02:16:08.519Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-17T02:16:08.519Z] GC before operation: completed in 269.757 ms, heap usage 324.495 MB -> 50.075 MB.
[2024-08-17T02:16:15.661Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T02:16:24.248Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T02:16:31.351Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T02:16:37.220Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T02:16:40.748Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T02:16:44.295Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T02:16:47.827Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T02:16:52.432Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T02:16:52.432Z] 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.
[2024-08-17T02:16:52.432Z] The best model improves the baseline by 14.52%.
[2024-08-17T02:16:52.432Z] Movies recommended for you:
[2024-08-17T02:16:52.432Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T02:16:52.432Z] There is no way to check that no silent failure occurred.
[2024-08-17T02:16:52.432Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (44673.810 ms) ======
[2024-08-17T02:16:52.432Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-17T02:16:53.224Z] GC before operation: completed in 233.475 ms, heap usage 296.309 MB -> 50.290 MB.
[2024-08-17T02:16:59.039Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T02:17:06.156Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T02:17:12.460Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T02:17:18.264Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T02:17:22.882Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T02:17:26.424Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T02:17:29.959Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T02:17:33.503Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T02:17:34.367Z] 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.
[2024-08-17T02:17:34.367Z] The best model improves the baseline by 14.52%.
[2024-08-17T02:17:34.367Z] Movies recommended for you:
[2024-08-17T02:17:34.367Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T02:17:34.367Z] There is no way to check that no silent failure occurred.
[2024-08-17T02:17:34.367Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (41714.413 ms) ======
[2024-08-17T02:17:34.367Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-17T02:17:35.167Z] GC before operation: completed in 233.658 ms, heap usage 332.378 MB -> 50.163 MB.
[2024-08-17T02:17:42.358Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T02:17:48.107Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T02:17:55.138Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T02:18:00.891Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T02:18:04.416Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T02:18:07.523Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T02:18:11.064Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T02:18:15.657Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T02:18:15.657Z] 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.
[2024-08-17T02:18:15.657Z] The best model improves the baseline by 14.52%.
[2024-08-17T02:18:16.463Z] Movies recommended for you:
[2024-08-17T02:18:16.463Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T02:18:16.463Z] There is no way to check that no silent failure occurred.
[2024-08-17T02:18:16.463Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (41325.380 ms) ======
[2024-08-17T02:18:16.463Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-17T02:18:16.463Z] GC before operation: completed in 272.969 ms, heap usage 181.820 MB -> 50.140 MB.
[2024-08-17T02:18:22.240Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T02:18:28.024Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T02:18:35.130Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T02:18:40.896Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T02:18:44.455Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T02:18:47.998Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T02:18:51.552Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T02:18:55.266Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T02:18:55.266Z] 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.
[2024-08-17T02:18:55.266Z] The best model improves the baseline by 14.52%.
[2024-08-17T02:18:56.067Z] Movies recommended for you:
[2024-08-17T02:18:56.067Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T02:18:56.067Z] There is no way to check that no silent failure occurred.
[2024-08-17T02:18:56.067Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (39394.167 ms) ======
[2024-08-17T02:18:56.067Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-17T02:18:56.067Z] GC before operation: completed in 285.845 ms, heap usage 312.449 MB -> 49.995 MB.
[2024-08-17T02:19:03.155Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T02:19:09.251Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T02:19:16.566Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T02:19:22.329Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T02:19:25.880Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T02:19:29.435Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T02:19:32.996Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T02:19:36.557Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T02:19:37.356Z] 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.
[2024-08-17T02:19:37.356Z] The best model improves the baseline by 14.52%.
[2024-08-17T02:19:37.356Z] Movies recommended for you:
[2024-08-17T02:19:37.356Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T02:19:37.356Z] There is no way to check that no silent failure occurred.
[2024-08-17T02:19:37.356Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (41155.382 ms) ======
[2024-08-17T02:19:37.356Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-17T02:19:37.356Z] GC before operation: completed in 192.903 ms, heap usage 116.422 MB -> 49.975 MB.
[2024-08-17T02:19:44.388Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T02:19:50.168Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T02:19:57.251Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T02:20:03.557Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T02:20:08.196Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T02:20:12.812Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T02:20:17.405Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T02:20:19.959Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T02:20:20.788Z] 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.
[2024-08-17T02:20:20.788Z] The best model improves the baseline by 14.52%.
[2024-08-17T02:20:21.621Z] Movies recommended for you:
[2024-08-17T02:20:21.621Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T02:20:21.621Z] There is no way to check that no silent failure occurred.
[2024-08-17T02:20:21.621Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (43651.245 ms) ======
[2024-08-17T02:20:21.621Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-17T02:20:21.621Z] GC before operation: completed in 238.846 ms, heap usage 300.025 MB -> 50.295 MB.
[2024-08-17T02:20:28.692Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T02:20:35.828Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T02:20:42.906Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T02:20:49.968Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T02:20:53.611Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T02:20:57.152Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T02:21:02.478Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T02:21:05.056Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T02:21:05.860Z] 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.
[2024-08-17T02:21:05.860Z] The best model improves the baseline by 14.52%.
[2024-08-17T02:21:06.654Z] Movies recommended for you:
[2024-08-17T02:21:06.654Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T02:21:06.654Z] There is no way to check that no silent failure occurred.
[2024-08-17T02:21:06.654Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (44980.686 ms) ======
[2024-08-17T02:21:06.654Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-17T02:21:06.654Z] GC before operation: completed in 291.099 ms, heap usage 325.372 MB -> 50.092 MB.
[2024-08-17T02:21:13.755Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T02:21:20.814Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T02:21:27.884Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T02:21:33.753Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T02:21:38.360Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T02:21:41.892Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T02:21:46.464Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T02:21:50.031Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T02:21:50.832Z] 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.
[2024-08-17T02:21:50.832Z] The best model improves the baseline by 14.52%.
[2024-08-17T02:21:50.832Z] Movies recommended for you:
[2024-08-17T02:21:50.832Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T02:21:50.832Z] There is no way to check that no silent failure occurred.
[2024-08-17T02:21:50.832Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (44438.266 ms) ======
[2024-08-17T02:21:50.832Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-17T02:21:51.632Z] GC before operation: completed in 320.011 ms, heap usage 280.084 MB -> 50.213 MB.
[2024-08-17T02:22:00.286Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T02:22:06.436Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T02:22:15.108Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T02:22:23.610Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T02:22:26.163Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T02:22:29.683Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T02:22:34.323Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T02:22:38.944Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T02:22:38.944Z] 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.
[2024-08-17T02:22:38.944Z] The best model improves the baseline by 14.52%.
[2024-08-17T02:22:39.738Z] Movies recommended for you:
[2024-08-17T02:22:39.738Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T02:22:39.738Z] There is no way to check that no silent failure occurred.
[2024-08-17T02:22:39.738Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (47984.050 ms) ======
[2024-08-17T02:22:39.738Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-17T02:22:39.738Z] GC before operation: completed in 249.040 ms, heap usage 171.179 MB -> 50.231 MB.
[2024-08-17T02:22:46.813Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T02:22:52.569Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T02:22:59.638Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T02:23:05.986Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T02:23:09.508Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T02:23:13.039Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T02:23:16.553Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T02:23:20.093Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T02:23:20.882Z] 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.
[2024-08-17T02:23:20.882Z] The best model improves the baseline by 14.52%.
[2024-08-17T02:23:20.882Z] Movies recommended for you:
[2024-08-17T02:23:20.882Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T02:23:20.882Z] There is no way to check that no silent failure occurred.
[2024-08-17T02:23:20.882Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (41355.656 ms) ======
[2024-08-17T02:23:20.882Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-17T02:23:20.882Z] GC before operation: completed in 234.630 ms, heap usage 282.765 MB -> 50.145 MB.
[2024-08-17T02:23:27.946Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T02:23:33.738Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T02:23:40.782Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T02:23:46.568Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T02:23:50.112Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T02:23:53.653Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T02:23:57.224Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T02:24:01.076Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T02:24:01.885Z] 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.
[2024-08-17T02:24:01.885Z] The best model improves the baseline by 14.52%.
[2024-08-17T02:24:02.681Z] Movies recommended for you:
[2024-08-17T02:24:02.682Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T02:24:02.682Z] There is no way to check that no silent failure occurred.
[2024-08-17T02:24:02.682Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (41063.619 ms) ======
[2024-08-17T02:24:02.682Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-17T02:24:02.682Z] GC before operation: completed in 273.751 ms, heap usage 207.657 MB -> 50.147 MB.
[2024-08-17T02:24:09.817Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T02:24:15.733Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T02:24:21.649Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T02:24:27.562Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T02:24:31.189Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T02:24:34.950Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T02:24:38.577Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T02:24:42.210Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T02:24:43.022Z] 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.
[2024-08-17T02:24:43.022Z] The best model improves the baseline by 14.52%.
[2024-08-17T02:24:43.861Z] Movies recommended for you:
[2024-08-17T02:24:43.861Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T02:24:43.861Z] There is no way to check that no silent failure occurred.
[2024-08-17T02:24:43.861Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (40926.855 ms) ======
[2024-08-17T02:24:43.861Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-17T02:24:43.861Z] GC before operation: completed in 210.548 ms, heap usage 337.698 MB -> 50.454 MB.
[2024-08-17T02:24:51.058Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-17T02:24:56.945Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-17T02:25:04.214Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-17T02:25:08.925Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-17T02:25:12.559Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-17T02:25:16.178Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-17T02:25:19.801Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-17T02:25:23.429Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-17T02:25:24.261Z] 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.
[2024-08-17T02:25:24.261Z] The best model improves the baseline by 14.52%.
[2024-08-17T02:25:25.093Z] Movies recommended for you:
[2024-08-17T02:25:25.093Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-17T02:25:25.093Z] There is no way to check that no silent failure occurred.
[2024-08-17T02:25:25.093Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (41181.170 ms) ======
[2024-08-17T02:25:25.938Z] -----------------------------------
[2024-08-17T02:25:25.938Z] renaissance-movie-lens_0_PASSED
[2024-08-17T02:25:25.938Z] -----------------------------------
[2024-08-17T02:25:25.938Z]
[2024-08-17T02:25:25.938Z] TEST TEARDOWN:
[2024-08-17T02:25:25.938Z] Nothing to be done for teardown.
[2024-08-17T02:25:25.938Z] renaissance-movie-lens_0 Finish Time: Sat Aug 17 02:25:25 2024 Epoch Time (ms): 1723861525487