renaissance-movie-lens_0
[2024-10-29T22:54:56.986Z] Running test renaissance-movie-lens_0 ...
[2024-10-29T22:54:56.986Z] ===============================================
[2024-10-29T22:54:56.986Z] renaissance-movie-lens_0 Start Time: Tue Oct 29 22:54:56 2024 Epoch Time (ms): 1730242496208
[2024-10-29T22:54:56.986Z] variation: NoOptions
[2024-10-29T22:54:56.986Z] JVM_OPTIONS:
[2024-10-29T22:54:56.986Z] { \
[2024-10-29T22:54:56.986Z] echo ""; echo "TEST SETUP:"; \
[2024-10-29T22:54:56.986Z] echo "Nothing to be done for setup."; \
[2024-10-29T22:54:56.986Z] mkdir -p "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/aqa-tests/TKG/../TKG/output_17302403458406/renaissance-movie-lens_0"; \
[2024-10-29T22:54:56.986Z] cd "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/aqa-tests/TKG/../TKG/output_17302403458406/renaissance-movie-lens_0"; \
[2024-10-29T22:54:56.986Z] echo ""; echo "TESTING:"; \
[2024-10-29T22:54:56.986Z] "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/jdkbinary/j2sdk-image/bin/java" -jar "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/aqa-tests/TKG/../TKG/output_17302403458406/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-10-29T22:54:56.986Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/aqa-tests/TKG/..; rm -f -r "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/aqa-tests/TKG/../TKG/output_17302403458406/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-10-29T22:54:56.986Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-10-29T22:54:56.986Z] echo "Nothing to be done for teardown."; \
[2024-10-29T22:54:56.986Z] } 2>&1 | tee -a "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/aqa-tests/TKG/../TKG/output_17302403458406/TestTargetResult";
[2024-10-29T22:54:56.986Z]
[2024-10-29T22:54:56.986Z] TEST SETUP:
[2024-10-29T22:54:56.986Z] Nothing to be done for setup.
[2024-10-29T22:54:56.986Z]
[2024-10-29T22:54:56.986Z] TESTING:
[2024-10-29T22:55:04.426Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-10-29T22:55:10.587Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 1 (out of 1) threads.
[2024-10-29T22:55:19.984Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-10-29T22:55:20.757Z] Training: 60056, validation: 20285, test: 19854
[2024-10-29T22:55:20.757Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-10-29T22:55:20.757Z] GC before operation: completed in 156.643 ms, heap usage 48.856 MB -> 26.282 MB.
[2024-10-29T22:55:36.125Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:55:43.679Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:55:50.293Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:55:57.560Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:56:00.495Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:56:04.337Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:56:08.176Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:56:12.013Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:56:12.752Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-10-29T22:56:12.752Z] The best model improves the baseline by 14.33%.
[2024-10-29T22:56:12.752Z] Movies recommended for you:
[2024-10-29T22:56:12.752Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:56:12.752Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:56:12.752Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (52148.844 ms) ======
[2024-10-29T22:56:12.752Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-10-29T22:56:13.379Z] GC before operation: completed in 325.453 ms, heap usage 106.674 MB -> 66.296 MB.
[2024-10-29T22:56:19.559Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:56:24.543Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:56:30.514Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:56:35.397Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:56:39.226Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:56:42.169Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:56:45.988Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:56:48.299Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:56:48.933Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-10-29T22:56:48.933Z] The best model improves the baseline by 14.33%.
[2024-10-29T22:56:49.599Z] Movies recommended for you:
[2024-10-29T22:56:49.599Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:56:49.599Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:56:49.599Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (36357.594 ms) ======
[2024-10-29T22:56:49.599Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-10-29T22:56:50.252Z] GC before operation: completed in 566.663 ms, heap usage 137.698 MB -> 70.748 MB.
[2024-10-29T22:56:54.735Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:56:59.538Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:57:04.385Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:57:09.452Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:57:14.319Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:57:17.228Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:57:20.202Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:57:22.290Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:57:22.932Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-10-29T22:57:22.932Z] The best model improves the baseline by 14.33%.
[2024-10-29T22:57:44.777Z] Movies recommended for you:
[2024-10-29T22:57:44.777Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:57:44.777Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:57:44.777Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (33336.549 ms) ======
[2024-10-29T22:57:44.777Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-10-29T22:57:45.446Z] GC before operation: completed in 22286.835 ms, heap usage 114.571 MB -> 75.988 MB.
[2024-10-29T22:57:49.722Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:57:54.533Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:57:58.392Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:58:03.257Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:58:05.420Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:58:08.387Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:58:11.247Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:58:13.337Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:58:14.008Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-10-29T22:58:14.008Z] The best model improves the baseline by 14.33%.
[2024-10-29T22:58:14.639Z] Movies recommended for you:
[2024-10-29T22:58:14.639Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:58:14.639Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:58:14.639Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (29008.299 ms) ======
[2024-10-29T22:58:14.639Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-10-29T22:58:14.639Z] GC before operation: completed in 297.281 ms, heap usage 149.756 MB -> 66.642 MB.
[2024-10-29T22:58:19.471Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:58:23.249Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:58:28.330Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:58:32.290Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:58:34.492Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:58:37.363Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:58:40.240Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:58:42.423Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:58:43.050Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-10-29T22:58:43.050Z] The best model improves the baseline by 14.33%.
[2024-10-29T22:58:43.050Z] Movies recommended for you:
[2024-10-29T22:58:43.050Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:58:43.050Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:58:43.050Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (28609.660 ms) ======
[2024-10-29T22:58:43.050Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-10-29T22:58:43.685Z] GC before operation: completed in 270.825 ms, heap usage 144.404 MB -> 72.460 MB.
[2024-10-29T22:58:48.091Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:58:51.995Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:58:56.799Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:59:00.684Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:59:03.700Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:59:06.614Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:59:09.506Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:59:12.425Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:59:13.216Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-10-29T22:59:13.216Z] The best model improves the baseline by 14.33%.
[2024-10-29T22:59:13.216Z] Movies recommended for you:
[2024-10-29T22:59:13.216Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:59:13.216Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:59:13.216Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (29971.129 ms) ======
[2024-10-29T22:59:13.216Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-10-29T22:59:13.881Z] GC before operation: completed in 245.536 ms, heap usage 157.437 MB -> 72.379 MB.
[2024-10-29T22:59:17.839Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:59:22.640Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:59:26.155Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:59:30.150Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:59:33.021Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:59:35.140Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:59:38.068Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:59:41.100Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:59:41.738Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-10-29T22:59:41.738Z] The best model improves the baseline by 14.33%.
[2024-10-29T22:59:41.738Z] Movies recommended for you:
[2024-10-29T22:59:41.738Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:59:41.738Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:59:41.738Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (28212.349 ms) ======
[2024-10-29T22:59:41.738Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-10-29T22:59:41.738Z] GC before operation: completed in 273.242 ms, heap usage 150.537 MB -> 72.766 MB.
[2024-10-29T22:59:46.650Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:59:50.569Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:59:55.359Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:59:59.222Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T23:00:02.118Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T23:00:05.110Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T23:00:08.030Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T23:00:10.142Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T23:00:10.766Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-10-29T23:00:10.766Z] The best model improves the baseline by 14.33%.
[2024-10-29T23:00:10.766Z] Movies recommended for you:
[2024-10-29T23:00:10.766Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T23:00:10.766Z] There is no way to check that no silent failure occurred.
[2024-10-29T23:00:10.766Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (28924.578 ms) ======
[2024-10-29T23:00:10.766Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-10-29T23:00:11.413Z] GC before operation: completed in 301.013 ms, heap usage 150.486 MB -> 67.796 MB.
[2024-10-29T23:00:15.213Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T23:00:19.525Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T23:00:24.359Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T23:00:28.226Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T23:00:30.271Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T23:00:33.161Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T23:00:36.080Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T23:00:38.194Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T23:00:38.819Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-10-29T23:00:38.819Z] The best model improves the baseline by 14.33%.
[2024-10-29T23:00:38.819Z] Movies recommended for you:
[2024-10-29T23:00:38.819Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T23:00:38.819Z] There is no way to check that no silent failure occurred.
[2024-10-29T23:00:38.819Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (27964.056 ms) ======
[2024-10-29T23:00:38.819Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-10-29T23:00:39.487Z] GC before operation: completed in 253.597 ms, heap usage 141.284 MB -> 73.021 MB.
[2024-10-29T23:00:43.383Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T23:00:47.284Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T23:00:52.094Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T23:00:56.218Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T23:00:59.692Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T23:01:00.996Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T23:01:03.887Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T23:01:06.843Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T23:01:06.843Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-10-29T23:01:06.844Z] The best model improves the baseline by 14.33%.
[2024-10-29T23:01:06.844Z] Movies recommended for you:
[2024-10-29T23:01:06.844Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T23:01:06.844Z] There is no way to check that no silent failure occurred.
[2024-10-29T23:01:06.844Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (27918.623 ms) ======
[2024-10-29T23:01:06.844Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-10-29T23:01:07.496Z] GC before operation: completed in 270.741 ms, heap usage 140.878 MB -> 73.106 MB.
[2024-10-29T23:01:11.291Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T23:01:16.136Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T23:01:19.895Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T23:01:23.851Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T23:01:26.808Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T23:01:28.864Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T23:01:33.682Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T23:01:35.874Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T23:01:36.499Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-10-29T23:01:36.499Z] The best model improves the baseline by 14.33%.
[2024-10-29T23:01:36.499Z] Movies recommended for you:
[2024-10-29T23:01:36.499Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T23:01:36.499Z] There is no way to check that no silent failure occurred.
[2024-10-29T23:01:36.499Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (29610.088 ms) ======
[2024-10-29T23:01:36.499Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-10-29T23:01:37.129Z] GC before operation: completed in 251.299 ms, heap usage 141.773 MB -> 72.384 MB.
[2024-10-29T23:01:40.891Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T23:01:44.963Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T23:01:50.026Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T23:01:53.531Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T23:01:56.422Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T23:01:58.496Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T23:02:01.395Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T23:02:04.348Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T23:02:04.348Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-10-29T23:02:04.348Z] The best model improves the baseline by 14.33%.
[2024-10-29T23:02:04.976Z] Movies recommended for you:
[2024-10-29T23:02:04.976Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T23:02:04.976Z] There is no way to check that no silent failure occurred.
[2024-10-29T23:02:04.976Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (27844.456 ms) ======
[2024-10-29T23:02:04.976Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-10-29T23:02:04.976Z] GC before operation: completed in 456.249 ms, heap usage 150.200 MB -> 70.478 MB.
[2024-10-29T23:02:08.832Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T23:02:13.773Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T23:02:18.612Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T23:02:22.537Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T23:02:25.488Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T23:02:27.557Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T23:02:30.455Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T23:02:32.988Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T23:02:33.629Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-10-29T23:02:33.629Z] The best model improves the baseline by 14.33%.
[2024-10-29T23:02:33.629Z] Movies recommended for you:
[2024-10-29T23:02:33.629Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T23:02:33.629Z] There is no way to check that no silent failure occurred.
[2024-10-29T23:02:33.629Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (28589.674 ms) ======
[2024-10-29T23:02:33.629Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-10-29T23:02:34.272Z] GC before operation: completed in 265.130 ms, heap usage 141.713 MB -> 73.293 MB.
[2024-10-29T23:02:39.127Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T23:02:43.049Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T23:02:47.908Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T23:02:51.732Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T23:02:53.837Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T23:02:56.960Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T23:02:59.072Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T23:03:02.037Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T23:03:02.037Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-10-29T23:03:02.709Z] The best model improves the baseline by 14.33%.
[2024-10-29T23:03:02.709Z] Movies recommended for you:
[2024-10-29T23:03:02.709Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T23:03:02.709Z] There is no way to check that no silent failure occurred.
[2024-10-29T23:03:02.709Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (28646.229 ms) ======
[2024-10-29T23:03:02.709Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-10-29T23:03:02.709Z] GC before operation: completed in 240.475 ms, heap usage 126.199 MB -> 71.746 MB.
[2024-10-29T23:03:07.571Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T23:03:11.566Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T23:03:15.386Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T23:03:19.525Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T23:03:21.646Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T23:03:24.390Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T23:03:27.369Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T23:03:30.507Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T23:03:31.165Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-10-29T23:03:31.165Z] The best model improves the baseline by 14.33%.
[2024-10-29T23:03:31.165Z] Movies recommended for you:
[2024-10-29T23:03:31.165Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T23:03:31.165Z] There is no way to check that no silent failure occurred.
[2024-10-29T23:03:31.165Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (28326.663 ms) ======
[2024-10-29T23:03:31.165Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-10-29T23:03:31.165Z] GC before operation: completed in 315.809 ms, heap usage 122.988 MB -> 73.474 MB.
[2024-10-29T23:03:35.110Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T23:03:39.931Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T23:03:43.922Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T23:03:48.731Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T23:03:50.262Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T23:03:53.223Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T23:03:56.115Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T23:03:58.175Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T23:03:58.816Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-10-29T23:03:58.816Z] The best model improves the baseline by 14.33%.
[2024-10-29T23:03:58.816Z] Movies recommended for you:
[2024-10-29T23:03:58.816Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T23:03:58.816Z] There is no way to check that no silent failure occurred.
[2024-10-29T23:03:58.816Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (27755.748 ms) ======
[2024-10-29T23:03:58.816Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-10-29T23:03:59.454Z] GC before operation: completed in 413.774 ms, heap usage 124.192 MB -> 68.649 MB.
[2024-10-29T23:04:03.418Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T23:04:07.313Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T23:04:12.890Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T23:04:17.904Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T23:04:20.203Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T23:04:22.571Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T23:04:25.867Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T23:04:27.953Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T23:04:28.600Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-10-29T23:04:28.600Z] The best model improves the baseline by 14.33%.
[2024-10-29T23:04:28.600Z] Movies recommended for you:
[2024-10-29T23:04:28.600Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T23:04:28.600Z] There is no way to check that no silent failure occurred.
[2024-10-29T23:04:28.600Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (29534.575 ms) ======
[2024-10-29T23:04:28.600Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-10-29T23:04:29.227Z] GC before operation: completed in 395.664 ms, heap usage 113.223 MB -> 75.647 MB.
[2024-10-29T23:04:32.996Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T23:04:37.872Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T23:04:41.644Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T23:04:45.437Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T23:04:48.350Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T23:04:50.410Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T23:04:53.251Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T23:04:55.577Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T23:04:56.203Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-10-29T23:04:56.203Z] The best model improves the baseline by 14.33%.
[2024-10-29T23:04:56.203Z] Movies recommended for you:
[2024-10-29T23:04:56.203Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T23:04:56.203Z] There is no way to check that no silent failure occurred.
[2024-10-29T23:04:56.203Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (27329.584 ms) ======
[2024-10-29T23:04:56.203Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-10-29T23:04:56.845Z] GC before operation: completed in 408.093 ms, heap usage 156.203 MB -> 77.494 MB.
[2024-10-29T23:05:01.272Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T23:05:05.359Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T23:05:09.242Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T23:05:13.034Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T23:05:15.155Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T23:05:17.277Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T23:05:20.293Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T23:05:22.356Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T23:05:23.155Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-10-29T23:05:23.155Z] The best model improves the baseline by 14.33%.
[2024-10-29T23:05:23.155Z] Movies recommended for you:
[2024-10-29T23:05:23.155Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T23:05:23.155Z] There is no way to check that no silent failure occurred.
[2024-10-29T23:05:23.155Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (26347.774 ms) ======
[2024-10-29T23:05:23.155Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-10-29T23:05:23.155Z] GC before operation: completed in 264.787 ms, heap usage 115.984 MB -> 72.730 MB.
[2024-10-29T23:05:26.974Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T23:05:32.035Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T23:05:35.932Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T23:05:39.729Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T23:05:41.994Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T23:05:44.871Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T23:05:47.003Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T23:05:49.866Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T23:05:50.518Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-10-29T23:05:50.518Z] The best model improves the baseline by 14.33%.
[2024-10-29T23:05:50.518Z] Movies recommended for you:
[2024-10-29T23:05:50.518Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T23:05:50.518Z] There is no way to check that no silent failure occurred.
[2024-10-29T23:05:50.518Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (27104.934 ms) ======
[2024-10-29T23:05:51.302Z] -----------------------------------
[2024-10-29T23:05:51.302Z] renaissance-movie-lens_0_PASSED
[2024-10-29T23:05:51.303Z] -----------------------------------
[2024-10-29T23:05:51.303Z]
[2024-10-29T23:05:51.303Z] TEST TEARDOWN:
[2024-10-29T23:05:51.303Z] Nothing to be done for teardown.
[2024-10-29T23:05:51.927Z] renaissance-movie-lens_0 Finish Time: Tue Oct 29 23:05:51 2024 Epoch Time (ms): 1730243151280