renaissance-movie-lens_0
[2024-11-08T03:59:26.004Z] Running test renaissance-movie-lens_0 ...
[2024-11-08T03:59:26.004Z] ===============================================
[2024-11-08T03:59:26.004Z] renaissance-movie-lens_0 Start Time: Fri Nov 8 03:59:25 2024 Epoch Time (ms): 1731038365428
[2024-11-08T03:59:26.004Z] variation: NoOptions
[2024-11-08T03:59:26.004Z] JVM_OPTIONS:
[2024-11-08T03:59:26.004Z] { \
[2024-11-08T03:59:26.004Z] echo ""; echo "TEST SETUP:"; \
[2024-11-08T03:59:26.004Z] echo "Nothing to be done for setup."; \
[2024-11-08T03:59:26.004Z] mkdir -p "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/aqa-tests/TKG/../TKG/output_1731036378819/renaissance-movie-lens_0"; \
[2024-11-08T03:59:26.004Z] cd "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/aqa-tests/TKG/../TKG/output_1731036378819/renaissance-movie-lens_0"; \
[2024-11-08T03:59:26.004Z] echo ""; echo "TESTING:"; \
[2024-11-08T03:59:26.004Z] "/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_1731036378819/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-08T03:59:26.004Z] 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_1731036378819/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-08T03:59:26.004Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-08T03:59:26.004Z] echo "Nothing to be done for teardown."; \
[2024-11-08T03:59:26.004Z] } 2>&1 | tee -a "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/aqa-tests/TKG/../TKG/output_1731036378819/TestTargetResult";
[2024-11-08T03:59:26.004Z]
[2024-11-08T03:59:26.004Z] TEST SETUP:
[2024-11-08T03:59:26.005Z] Nothing to be done for setup.
[2024-11-08T03:59:26.005Z]
[2024-11-08T03:59:26.005Z] TESTING:
[2024-11-08T03:59:34.838Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-08T03:59:40.834Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 1 (out of 1) threads.
[2024-11-08T03:59:52.271Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-08T03:59:52.271Z] Training: 60056, validation: 20285, test: 19854
[2024-11-08T03:59:52.271Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-08T03:59:52.923Z] GC before operation: completed in 674.076 ms, heap usage 53.753 MB -> 26.307 MB.
[2024-11-08T04:00:08.339Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T04:00:16.016Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T04:00:23.433Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T04:00:29.506Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T04:00:34.539Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T04:00:37.536Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T04:00:42.428Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T04:00:45.338Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T04:00:45.976Z] 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.
[2024-11-08T04:00:46.646Z] The best model improves the baseline by 14.33%.
[2024-11-08T04:00:46.646Z] Movies recommended for you:
[2024-11-08T04:00:46.646Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T04:00:46.646Z] There is no way to check that no silent failure occurred.
[2024-11-08T04:00:46.646Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (54243.624 ms) ======
[2024-11-08T04:00:46.646Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-08T04:00:47.286Z] GC before operation: completed in 266.121 ms, heap usage 69.285 MB -> 49.773 MB.
[2024-11-08T04:00:53.554Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T04:00:59.796Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T04:01:05.843Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T04:01:10.917Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T04:01:14.843Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T04:01:18.710Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T04:01:21.730Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T04:01:24.839Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T04:01:25.571Z] 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.
[2024-11-08T04:01:25.571Z] The best model improves the baseline by 14.33%.
[2024-11-08T04:01:26.250Z] Movies recommended for you:
[2024-11-08T04:01:26.250Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T04:01:26.250Z] There is no way to check that no silent failure occurred.
[2024-11-08T04:01:26.250Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (38911.605 ms) ======
[2024-11-08T04:01:26.250Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-08T04:01:26.250Z] GC before operation: completed in 249.024 ms, heap usage 113.067 MB -> 71.124 MB.
[2024-11-08T04:01:30.800Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T04:01:36.877Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T04:01:40.821Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T04:01:45.777Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T04:01:48.727Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T04:01:50.843Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T04:01:53.803Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T04:01:56.868Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T04:01:57.532Z] 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.
[2024-11-08T04:01:58.193Z] The best model improves the baseline by 14.33%.
[2024-11-08T04:01:58.193Z] Movies recommended for you:
[2024-11-08T04:01:58.193Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T04:01:58.193Z] There is no way to check that no silent failure occurred.
[2024-11-08T04:01:58.193Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (31952.318 ms) ======
[2024-11-08T04:01:58.193Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-08T04:01:58.193Z] GC before operation: completed in 276.984 ms, heap usage 147.609 MB -> 63.574 MB.
[2024-11-08T04:02:04.338Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T04:02:08.516Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T04:02:13.020Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T04:02:16.891Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T04:02:19.855Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T04:02:22.523Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T04:02:25.473Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T04:02:28.403Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T04:02:28.403Z] 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.
[2024-11-08T04:02:29.125Z] The best model improves the baseline by 14.33%.
[2024-11-08T04:02:29.125Z] Movies recommended for you:
[2024-11-08T04:02:29.125Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T04:02:29.125Z] There is no way to check that no silent failure occurred.
[2024-11-08T04:02:29.125Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (30783.444 ms) ======
[2024-11-08T04:02:29.125Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-08T04:02:29.125Z] GC before operation: completed in 214.647 ms, heap usage 112.200 MB -> 71.599 MB.
[2024-11-08T04:02:34.093Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T04:02:37.971Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T04:02:42.930Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T04:02:46.750Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T04:02:49.676Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T04:02:51.777Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T04:02:54.746Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T04:02:56.921Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T04:02:57.601Z] 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.
[2024-11-08T04:02:57.601Z] The best model improves the baseline by 14.33%.
[2024-11-08T04:02:58.343Z] Movies recommended for you:
[2024-11-08T04:02:58.343Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T04:02:58.343Z] There is no way to check that no silent failure occurred.
[2024-11-08T04:02:58.343Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (28932.150 ms) ======
[2024-11-08T04:02:58.343Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-08T04:02:58.343Z] GC before operation: completed in 256.911 ms, heap usage 138.811 MB -> 74.172 MB.
[2024-11-08T04:03:02.288Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T04:03:07.324Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T04:03:11.847Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T04:03:15.704Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T04:03:18.750Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T04:03:21.700Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T04:03:46.762Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T04:03:49.734Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T04:03:49.734Z] 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.
[2024-11-08T04:03:50.370Z] The best model improves the baseline by 14.33%.
[2024-11-08T04:03:50.370Z] Movies recommended for you:
[2024-11-08T04:03:50.370Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T04:03:50.370Z] There is no way to check that no silent failure occurred.
[2024-11-08T04:03:50.370Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (52178.576 ms) ======
[2024-11-08T04:03:50.370Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-08T04:03:50.370Z] GC before operation: completed in 246.230 ms, heap usage 125.490 MB -> 72.215 MB.
[2024-11-08T04:03:55.386Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T04:03:59.286Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T04:04:04.211Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T04:04:09.217Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T04:04:11.383Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T04:04:13.496Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T04:04:16.553Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T04:04:20.055Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T04:04:20.055Z] 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.
[2024-11-08T04:04:20.055Z] The best model improves the baseline by 14.33%.
[2024-11-08T04:04:20.055Z] Movies recommended for you:
[2024-11-08T04:04:20.055Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T04:04:20.055Z] There is no way to check that no silent failure occurred.
[2024-11-08T04:04:20.055Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (29636.782 ms) ======
[2024-11-08T04:04:20.055Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-08T04:04:20.055Z] GC before operation: completed in 243.393 ms, heap usage 126.865 MB -> 66.948 MB.
[2024-11-08T04:04:25.047Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T04:04:51.295Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T04:04:56.192Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T04:05:00.013Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T04:05:02.173Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T04:05:05.183Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T04:05:07.381Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T04:05:10.342Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T04:05:10.979Z] 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.
[2024-11-08T04:05:10.979Z] The best model improves the baseline by 14.33%.
[2024-11-08T04:05:10.979Z] Movies recommended for you:
[2024-11-08T04:05:10.979Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T04:05:10.979Z] There is no way to check that no silent failure occurred.
[2024-11-08T04:05:10.979Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (50827.384 ms) ======
[2024-11-08T04:05:10.979Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-08T04:05:10.979Z] GC before operation: completed in 239.763 ms, heap usage 107.970 MB -> 71.359 MB.
[2024-11-08T04:05:15.874Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T04:05:19.741Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T04:05:24.731Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T04:05:28.740Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T04:05:31.364Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T04:05:34.298Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T04:05:36.385Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T04:05:39.474Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T04:05:39.474Z] 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.
[2024-11-08T04:05:39.474Z] The best model improves the baseline by 14.33%.
[2024-11-08T04:05:40.150Z] Movies recommended for you:
[2024-11-08T04:05:40.151Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T04:05:40.151Z] There is no way to check that no silent failure occurred.
[2024-11-08T04:05:40.151Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (28826.150 ms) ======
[2024-11-08T04:05:40.151Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-08T04:05:40.151Z] GC before operation: completed in 265.759 ms, heap usage 112.734 MB -> 71.393 MB.
[2024-11-08T04:05:44.072Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T04:05:49.086Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T04:05:52.928Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T04:05:56.770Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T04:05:59.689Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T04:06:01.860Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T04:06:04.855Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T04:06:07.022Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T04:06:07.661Z] 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.
[2024-11-08T04:06:07.661Z] The best model improves the baseline by 14.33%.
[2024-11-08T04:06:07.661Z] Movies recommended for you:
[2024-11-08T04:06:07.661Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T04:06:07.661Z] There is no way to check that no silent failure occurred.
[2024-11-08T04:06:07.661Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (27825.027 ms) ======
[2024-11-08T04:06:07.661Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-08T04:06:08.353Z] GC before operation: completed in 403.736 ms, heap usage 123.601 MB -> 76.227 MB.
[2024-11-08T04:06:12.575Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T04:06:16.521Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T04:06:20.951Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T04:06:24.984Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T04:06:27.939Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T04:06:30.144Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T04:06:33.075Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T04:06:35.162Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T04:06:35.800Z] 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.
[2024-11-08T04:06:35.800Z] The best model improves the baseline by 14.33%.
[2024-11-08T04:06:36.478Z] Movies recommended for you:
[2024-11-08T04:06:36.478Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T04:06:36.478Z] There is no way to check that no silent failure occurred.
[2024-11-08T04:06:36.478Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (27955.470 ms) ======
[2024-11-08T04:06:36.478Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-08T04:06:36.478Z] GC before operation: completed in 263.355 ms, heap usage 134.496 MB -> 66.131 MB.
[2024-11-08T04:06:40.335Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T04:06:44.323Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T04:06:49.213Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T04:06:52.139Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T04:06:55.079Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T04:06:57.289Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T04:07:00.213Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T04:07:03.155Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T04:07:03.155Z] 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.
[2024-11-08T04:07:03.155Z] The best model improves the baseline by 14.33%.
[2024-11-08T04:07:03.792Z] Movies recommended for you:
[2024-11-08T04:07:03.792Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T04:07:03.792Z] There is no way to check that no silent failure occurred.
[2024-11-08T04:07:03.792Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (27185.748 ms) ======
[2024-11-08T04:07:03.792Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-08T04:07:03.792Z] GC before operation: completed in 375.541 ms, heap usage 130.157 MB -> 75.460 MB.
[2024-11-08T04:07:08.140Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T04:07:12.187Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T04:07:17.176Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T04:07:21.038Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T04:07:27.084Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T04:07:31.042Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T04:07:56.390Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T04:07:59.355Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T04:08:00.079Z] 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.
[2024-11-08T04:08:00.079Z] The best model improves the baseline by 14.33%.
[2024-11-08T04:08:00.079Z] Movies recommended for you:
[2024-11-08T04:08:00.079Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T04:08:00.079Z] There is no way to check that no silent failure occurred.
[2024-11-08T04:08:00.079Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (56444.423 ms) ======
[2024-11-08T04:08:00.079Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-08T04:08:00.079Z] GC before operation: completed in 228.095 ms, heap usage 133.837 MB -> 71.482 MB.
[2024-11-08T04:08:05.139Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T04:08:09.062Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T04:08:13.906Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T04:08:17.133Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T04:08:20.292Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T04:08:22.405Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T04:08:25.375Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T04:08:27.494Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T04:08:28.204Z] 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.
[2024-11-08T04:08:28.204Z] The best model improves the baseline by 14.33%.
[2024-11-08T04:08:28.204Z] Movies recommended for you:
[2024-11-08T04:08:28.204Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T04:08:28.204Z] There is no way to check that no silent failure occurred.
[2024-11-08T04:08:28.204Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (27905.942 ms) ======
[2024-11-08T04:08:28.204Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-08T04:08:28.204Z] GC before operation: completed in 248.568 ms, heap usage 133.018 MB -> 70.404 MB.
[2024-11-08T04:08:32.143Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T04:08:37.020Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T04:08:41.011Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T04:08:44.914Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T04:08:47.958Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T04:08:50.047Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T04:08:53.027Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T04:08:56.149Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T04:08:56.149Z] 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.
[2024-11-08T04:08:56.149Z] The best model improves the baseline by 14.33%.
[2024-11-08T04:08:56.794Z] Movies recommended for you:
[2024-11-08T04:08:56.794Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T04:08:56.794Z] There is no way to check that no silent failure occurred.
[2024-11-08T04:08:56.794Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (28159.839 ms) ======
[2024-11-08T04:08:56.794Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-08T04:08:56.794Z] GC before operation: completed in 401.584 ms, heap usage 132.697 MB -> 70.286 MB.
[2024-11-08T04:09:00.712Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T04:09:04.865Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T04:09:09.782Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T04:09:13.628Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T04:09:17.518Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T04:09:19.628Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T04:09:23.147Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T04:09:25.234Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T04:09:25.234Z] 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.
[2024-11-08T04:09:25.234Z] The best model improves the baseline by 14.33%.
[2024-11-08T04:09:25.897Z] Movies recommended for you:
[2024-11-08T04:09:25.897Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T04:09:25.897Z] There is no way to check that no silent failure occurred.
[2024-11-08T04:09:25.897Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (28878.851 ms) ======
[2024-11-08T04:09:25.897Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-08T04:09:25.897Z] GC before operation: completed in 426.772 ms, heap usage 128.750 MB -> 75.232 MB.
[2024-11-08T04:09:29.778Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T04:09:33.741Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T04:09:38.832Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T04:09:43.715Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T04:09:46.724Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T04:09:54.399Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T04:09:54.399Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T04:09:55.053Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T04:09:55.700Z] 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.
[2024-11-08T04:09:55.700Z] The best model improves the baseline by 14.33%.
[2024-11-08T04:09:55.700Z] Movies recommended for you:
[2024-11-08T04:09:55.700Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T04:09:55.700Z] There is no way to check that no silent failure occurred.
[2024-11-08T04:09:55.700Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (29964.491 ms) ======
[2024-11-08T04:09:55.700Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-08T04:09:56.361Z] GC before operation: completed in 332.582 ms, heap usage 134.239 MB -> 72.197 MB.
[2024-11-08T04:10:00.273Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T04:10:05.199Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T04:10:09.181Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T04:10:13.129Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T04:10:16.159Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T04:10:18.276Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T04:10:20.349Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T04:10:23.270Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T04:10:23.270Z] 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.
[2024-11-08T04:10:23.270Z] The best model improves the baseline by 14.33%.
[2024-11-08T04:10:23.906Z] Movies recommended for you:
[2024-11-08T04:10:23.906Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T04:10:23.906Z] There is no way to check that no silent failure occurred.
[2024-11-08T04:10:23.906Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (27514.541 ms) ======
[2024-11-08T04:10:23.906Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-08T04:10:23.906Z] GC before operation: completed in 338.708 ms, heap usage 132.415 MB -> 73.347 MB.
[2024-11-08T04:10:31.196Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T04:10:34.211Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T04:10:39.155Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T04:10:44.549Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T04:10:46.645Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T04:10:48.822Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T04:10:51.755Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T04:10:53.856Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T04:10:53.856Z] 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.
[2024-11-08T04:10:53.856Z] The best model improves the baseline by 14.33%.
[2024-11-08T04:10:54.509Z] Movies recommended for you:
[2024-11-08T04:10:54.509Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T04:10:54.509Z] There is no way to check that no silent failure occurred.
[2024-11-08T04:10:54.510Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (30322.378 ms) ======
[2024-11-08T04:10:54.510Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-08T04:10:54.510Z] GC before operation: completed in 435.224 ms, heap usage 130.458 MB -> 70.062 MB.
[2024-11-08T04:10:58.438Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-08T04:11:03.387Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-08T04:11:29.330Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-08T04:11:33.299Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-08T04:11:35.498Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-08T04:11:38.527Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-08T04:11:40.604Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-08T04:11:42.737Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-08T04:11:43.374Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-11-08T04:11:43.374Z] The best model improves the baseline by 14.33%.
[2024-11-08T04:11:44.318Z] Movies recommended for you:
[2024-11-08T04:11:44.318Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-08T04:11:44.318Z] There is no way to check that no silent failure occurred.
[2024-11-08T04:11:44.318Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (49169.855 ms) ======
[2024-11-08T04:11:44.962Z] -----------------------------------
[2024-11-08T04:11:44.962Z] renaissance-movie-lens_0_PASSED
[2024-11-08T04:11:44.962Z] -----------------------------------
[2024-11-08T04:11:44.962Z]
[2024-11-08T04:11:44.962Z] TEST TEARDOWN:
[2024-11-08T04:11:44.962Z] Nothing to be done for teardown.
[2024-11-08T04:11:44.962Z] renaissance-movie-lens_0 Finish Time: Fri Nov 8 04:11:44 2024 Epoch Time (ms): 1731039104432