renaissance-movie-lens_0
[2024-09-02T10:28:35.158Z] Running test renaissance-movie-lens_0 ...
[2024-09-02T10:28:35.158Z] ===============================================
[2024-09-02T10:28:35.158Z] renaissance-movie-lens_0 Start Time: Mon Sep 2 11:28:34 2024 Epoch Time (ms): 1725272914451
[2024-09-02T10:28:35.158Z] variation: NoOptions
[2024-09-02T10:28:35.158Z] JVM_OPTIONS:
[2024-09-02T10:28:35.158Z] { \
[2024-09-02T10:28:35.158Z] echo ""; echo "TEST SETUP:"; \
[2024-09-02T10:28:35.158Z] echo "Nothing to be done for setup."; \
[2024-09-02T10:28:35.158Z] mkdir -p "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/aqa-tests/TKG/../TKG/output_17252715867334/renaissance-movie-lens_0"; \
[2024-09-02T10:28:35.158Z] cd "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/aqa-tests/TKG/../TKG/output_17252715867334/renaissance-movie-lens_0"; \
[2024-09-02T10:28:35.158Z] echo ""; echo "TESTING:"; \
[2024-09-02T10:28:35.158Z] "/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_17252715867334/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-09-02T10:28:35.158Z] 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_17252715867334/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-09-02T10:28:35.158Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-09-02T10:28:35.158Z] echo "Nothing to be done for teardown."; \
[2024-09-02T10:28:35.158Z] } 2>&1 | tee -a "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/aqa-tests/TKG/../TKG/output_17252715867334/TestTargetResult";
[2024-09-02T10:28:35.158Z]
[2024-09-02T10:28:35.158Z] TEST SETUP:
[2024-09-02T10:28:35.158Z] Nothing to be done for setup.
[2024-09-02T10:28:35.158Z]
[2024-09-02T10:28:35.158Z] TESTING:
[2024-09-02T10:28:40.958Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-09-02T10:28:44.863Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 1 (out of 1) threads.
[2024-09-02T10:28:52.960Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-09-02T10:28:52.960Z] Training: 60056, validation: 20285, test: 19854
[2024-09-02T10:28:52.960Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-09-02T10:28:52.960Z] GC before operation: completed in 94.133 ms, heap usage 52.996 MB -> 26.253 MB.
[2024-09-02T10:29:02.027Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T10:29:06.840Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T10:29:11.685Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T10:29:15.417Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T10:29:17.482Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T10:29:19.491Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T10:29:21.565Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T10:29:24.702Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T10:29:24.702Z] 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.
[2024-09-02T10:29:25.344Z] The best model improves the baseline by 14.33%.
[2024-09-02T10:29:25.344Z] Movies recommended for you:
[2024-09-02T10:29:25.344Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T10:29:25.344Z] There is no way to check that no silent failure occurred.
[2024-09-02T10:29:25.344Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (32813.545 ms) ======
[2024-09-02T10:29:25.344Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-09-02T10:29:25.344Z] GC before operation: completed in 164.698 ms, heap usage 97.495 MB -> 63.531 MB.
[2024-09-02T10:29:29.100Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T10:29:33.934Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T10:29:37.726Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T10:29:40.726Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T10:29:43.131Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T10:29:45.194Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T10:29:47.387Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T10:29:49.430Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T10:29:50.062Z] 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.
[2024-09-02T10:29:50.062Z] The best model improves the baseline by 14.33%.
[2024-09-02T10:29:50.062Z] Movies recommended for you:
[2024-09-02T10:29:50.062Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T10:29:50.062Z] There is no way to check that no silent failure occurred.
[2024-09-02T10:29:50.062Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (24544.892 ms) ======
[2024-09-02T10:29:50.062Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-09-02T10:29:50.062Z] GC before operation: completed in 121.111 ms, heap usage 86.709 MB -> 48.522 MB.
[2024-09-02T10:29:53.068Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T10:29:56.045Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T10:29:59.982Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T10:30:02.835Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T10:30:04.142Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T10:30:06.201Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T10:30:08.228Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T10:30:11.182Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T10:30:11.182Z] 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.
[2024-09-02T10:30:11.182Z] The best model improves the baseline by 14.33%.
[2024-09-02T10:30:11.182Z] Movies recommended for you:
[2024-09-02T10:30:11.182Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T10:30:11.182Z] There is no way to check that no silent failure occurred.
[2024-09-02T10:30:11.182Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (21095.746 ms) ======
[2024-09-02T10:30:11.182Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-09-02T10:30:11.182Z] GC before operation: completed in 160.224 ms, heap usage 134.694 MB -> 64.948 MB.
[2024-09-02T10:30:14.917Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T10:30:18.661Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T10:30:21.409Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T10:30:24.263Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T10:30:26.294Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T10:30:27.625Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T10:30:29.707Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T10:30:31.000Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T10:30:31.640Z] 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.
[2024-09-02T10:30:31.640Z] The best model improves the baseline by 14.33%.
[2024-09-02T10:30:31.640Z] Movies recommended for you:
[2024-09-02T10:30:31.640Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T10:30:31.640Z] There is no way to check that no silent failure occurred.
[2024-09-02T10:30:31.640Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (20235.252 ms) ======
[2024-09-02T10:30:31.640Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-09-02T10:30:31.640Z] GC before operation: completed in 143.708 ms, heap usage 119.384 MB -> 69.832 MB.
[2024-09-02T10:30:34.495Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T10:30:37.807Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T10:30:40.652Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T10:30:44.425Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T10:30:46.559Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T10:30:47.956Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T10:30:50.102Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T10:30:51.416Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T10:30:52.039Z] 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.
[2024-09-02T10:30:52.039Z] The best model improves the baseline by 14.33%.
[2024-09-02T10:30:52.039Z] Movies recommended for you:
[2024-09-02T10:30:52.039Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T10:30:52.039Z] There is no way to check that no silent failure occurred.
[2024-09-02T10:30:52.039Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (20121.277 ms) ======
[2024-09-02T10:30:52.039Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-09-02T10:30:52.039Z] GC before operation: completed in 314.412 ms, heap usage 138.801 MB -> 74.622 MB.
[2024-09-02T10:30:54.899Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T10:30:57.746Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T10:31:00.730Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T10:31:02.755Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T10:31:04.823Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T10:31:06.187Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T10:31:08.195Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T10:31:10.258Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T10:31:10.258Z] 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.
[2024-09-02T10:31:10.258Z] The best model improves the baseline by 14.33%.
[2024-09-02T10:31:11.010Z] Movies recommended for you:
[2024-09-02T10:31:11.010Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T10:31:11.010Z] There is no way to check that no silent failure occurred.
[2024-09-02T10:31:11.010Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (18416.466 ms) ======
[2024-09-02T10:31:11.010Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-09-02T10:31:11.010Z] GC before operation: completed in 132.832 ms, heap usage 144.616 MB -> 68.807 MB.
[2024-09-02T10:31:13.037Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T10:31:15.883Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T10:31:19.638Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T10:31:22.523Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T10:31:24.568Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T10:31:25.907Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T10:31:28.209Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T10:31:29.489Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T10:31:29.489Z] 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.
[2024-09-02T10:31:29.489Z] The best model improves the baseline by 14.33%.
[2024-09-02T10:31:30.105Z] Movies recommended for you:
[2024-09-02T10:31:30.105Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T10:31:30.105Z] There is no way to check that no silent failure occurred.
[2024-09-02T10:31:30.105Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (19205.694 ms) ======
[2024-09-02T10:31:30.105Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-09-02T10:31:30.105Z] GC before operation: completed in 240.626 ms, heap usage 135.605 MB -> 65.345 MB.
[2024-09-02T10:31:33.415Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T10:31:35.476Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T10:31:38.454Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T10:31:40.497Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T10:31:42.551Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T10:31:43.925Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T10:31:46.199Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T10:31:47.503Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T10:31:47.503Z] 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.
[2024-09-02T10:31:48.225Z] The best model improves the baseline by 14.33%.
[2024-09-02T10:31:48.225Z] Movies recommended for you:
[2024-09-02T10:31:48.225Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T10:31:48.225Z] There is no way to check that no silent failure occurred.
[2024-09-02T10:31:48.225Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (17760.991 ms) ======
[2024-09-02T10:31:48.225Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-09-02T10:31:48.225Z] GC before operation: completed in 283.866 ms, heap usage 143.940 MB -> 74.375 MB.
[2024-09-02T10:31:50.564Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T10:31:53.402Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T10:31:56.435Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T10:31:58.507Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T10:32:00.637Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T10:32:01.920Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T10:32:03.985Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T10:32:05.286Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T10:32:05.286Z] 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.
[2024-09-02T10:32:05.286Z] The best model improves the baseline by 14.33%.
[2024-09-02T10:32:05.286Z] Movies recommended for you:
[2024-09-02T10:32:05.286Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T10:32:05.286Z] There is no way to check that no silent failure occurred.
[2024-09-02T10:32:05.286Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (17363.527 ms) ======
[2024-09-02T10:32:05.286Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-09-02T10:32:05.911Z] GC before operation: completed in 254.570 ms, heap usage 137.377 MB -> 70.930 MB.
[2024-09-02T10:32:08.106Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T10:32:10.908Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T10:32:13.763Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T10:32:16.817Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T10:32:17.551Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T10:32:19.559Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T10:32:20.874Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T10:32:22.940Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T10:32:22.940Z] 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.
[2024-09-02T10:32:22.940Z] The best model improves the baseline by 14.33%.
[2024-09-02T10:32:23.558Z] Movies recommended for you:
[2024-09-02T10:32:23.558Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T10:32:23.558Z] There is no way to check that no silent failure occurred.
[2024-09-02T10:32:23.558Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (17419.031 ms) ======
[2024-09-02T10:32:23.558Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-09-02T10:32:23.558Z] GC before operation: completed in 183.297 ms, heap usage 134.172 MB -> 71.272 MB.
[2024-09-02T10:32:26.458Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T10:32:28.484Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T10:32:32.267Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T10:32:34.318Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T10:32:36.363Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T10:32:37.659Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T10:32:39.953Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T10:32:41.335Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T10:32:41.335Z] 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.
[2024-09-02T10:32:41.335Z] The best model improves the baseline by 14.33%.
[2024-09-02T10:32:41.954Z] Movies recommended for you:
[2024-09-02T10:32:41.954Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T10:32:41.954Z] There is no way to check that no silent failure occurred.
[2024-09-02T10:32:41.954Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (18295.083 ms) ======
[2024-09-02T10:32:41.954Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-09-02T10:32:41.954Z] GC before operation: completed in 154.971 ms, heap usage 120.031 MB -> 66.942 MB.
[2024-09-02T10:32:44.991Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T10:32:47.094Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T10:32:49.959Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T10:32:52.969Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T10:32:54.266Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T10:32:55.668Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T10:32:57.834Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T10:32:59.211Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T10:32:59.887Z] 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.
[2024-09-02T10:32:59.887Z] The best model improves the baseline by 14.33%.
[2024-09-02T10:32:59.887Z] Movies recommended for you:
[2024-09-02T10:32:59.887Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T10:32:59.887Z] There is no way to check that no silent failure occurred.
[2024-09-02T10:32:59.887Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (17983.107 ms) ======
[2024-09-02T10:32:59.887Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-09-02T10:32:59.887Z] GC before operation: completed in 169.324 ms, heap usage 121.845 MB -> 71.673 MB.
[2024-09-02T10:33:02.736Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T10:33:05.718Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T10:33:08.557Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T10:33:12.702Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T10:33:13.383Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T10:33:15.395Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T10:33:17.416Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T10:33:18.700Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T10:33:19.317Z] 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.
[2024-09-02T10:33:19.317Z] The best model improves the baseline by 14.33%.
[2024-09-02T10:33:19.317Z] Movies recommended for you:
[2024-09-02T10:33:19.317Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T10:33:19.317Z] There is no way to check that no silent failure occurred.
[2024-09-02T10:33:19.317Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (19087.690 ms) ======
[2024-09-02T10:33:19.317Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-09-02T10:33:19.317Z] GC before operation: completed in 327.815 ms, heap usage 149.326 MB -> 76.356 MB.
[2024-09-02T10:33:22.156Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T10:33:25.003Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T10:33:27.845Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T10:33:30.807Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T10:33:32.241Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T10:33:33.529Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T10:33:35.574Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T10:33:36.855Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T10:33:37.507Z] 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.
[2024-09-02T10:33:37.507Z] The best model improves the baseline by 14.33%.
[2024-09-02T10:33:37.507Z] Movies recommended for you:
[2024-09-02T10:33:37.507Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T10:33:37.507Z] There is no way to check that no silent failure occurred.
[2024-09-02T10:33:37.507Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (17902.996 ms) ======
[2024-09-02T10:33:37.507Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-09-02T10:33:37.507Z] GC before operation: completed in 160.991 ms, heap usage 152.541 MB -> 72.494 MB.
[2024-09-02T10:33:40.466Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T10:33:42.583Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T10:33:45.434Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T10:33:49.157Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T10:33:50.486Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T10:33:51.810Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T10:33:53.945Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T10:33:55.231Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T10:33:55.852Z] 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.
[2024-09-02T10:33:55.852Z] The best model improves the baseline by 14.33%.
[2024-09-02T10:33:55.852Z] Movies recommended for you:
[2024-09-02T10:33:55.852Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T10:33:55.852Z] There is no way to check that no silent failure occurred.
[2024-09-02T10:33:55.852Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (18496.458 ms) ======
[2024-09-02T10:33:55.852Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-09-02T10:33:56.469Z] GC before operation: completed in 156.667 ms, heap usage 142.051 MB -> 65.432 MB.
[2024-09-02T10:33:59.295Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T10:34:01.368Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T10:34:04.255Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T10:34:07.108Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T10:34:08.449Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T10:34:10.581Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T10:34:11.879Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T10:34:13.920Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T10:34:13.920Z] 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.
[2024-09-02T10:34:13.920Z] The best model improves the baseline by 14.33%.
[2024-09-02T10:34:14.539Z] Movies recommended for you:
[2024-09-02T10:34:14.539Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T10:34:14.539Z] There is no way to check that no silent failure occurred.
[2024-09-02T10:34:14.539Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (18065.022 ms) ======
[2024-09-02T10:34:14.539Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-09-02T10:34:14.539Z] GC before operation: completed in 156.990 ms, heap usage 138.003 MB -> 72.056 MB.
[2024-09-02T10:34:17.564Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T10:34:20.391Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T10:34:23.300Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T10:34:26.129Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T10:34:28.143Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T10:34:30.221Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T10:34:31.502Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T10:34:33.550Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T10:34:33.550Z] 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.
[2024-09-02T10:34:34.172Z] The best model improves the baseline by 14.33%.
[2024-09-02T10:34:34.172Z] Movies recommended for you:
[2024-09-02T10:34:34.172Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T10:34:34.172Z] There is no way to check that no silent failure occurred.
[2024-09-02T10:34:34.173Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (19611.140 ms) ======
[2024-09-02T10:34:34.173Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-09-02T10:34:34.173Z] GC before operation: completed in 140.385 ms, heap usage 126.840 MB -> 72.653 MB.
[2024-09-02T10:34:36.729Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T10:34:39.678Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T10:34:42.512Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T10:34:44.556Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T10:34:46.594Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T10:34:47.905Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T10:34:49.977Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T10:34:51.423Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T10:34:52.072Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-09-02T10:34:52.072Z] The best model improves the baseline by 14.33%.
[2024-09-02T10:34:52.072Z] Movies recommended for you:
[2024-09-02T10:34:52.072Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T10:34:52.072Z] There is no way to check that no silent failure occurred.
[2024-09-02T10:34:52.072Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (17799.090 ms) ======
[2024-09-02T10:34:52.072Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-09-02T10:34:52.072Z] GC before operation: completed in 138.116 ms, heap usage 152.542 MB -> 72.641 MB.
[2024-09-02T10:34:59.850Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T10:34:59.850Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T10:35:00.559Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T10:35:02.784Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T10:35:04.185Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T10:35:05.595Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T10:35:07.786Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T10:35:09.266Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T10:35:09.266Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-09-02T10:35:09.266Z] The best model improves the baseline by 14.33%.
[2024-09-02T10:35:09.937Z] Movies recommended for you:
[2024-09-02T10:35:09.937Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T10:35:09.937Z] There is no way to check that no silent failure occurred.
[2024-09-02T10:35:09.937Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (17500.648 ms) ======
[2024-09-02T10:35:09.937Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-09-02T10:35:09.937Z] GC before operation: completed in 172.275 ms, heap usage 154.746 MB -> 66.828 MB.
[2024-09-02T10:35:12.155Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-02T10:35:16.685Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-02T10:35:18.083Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-02T10:35:21.163Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-02T10:35:22.713Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-02T10:35:24.094Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-02T10:35:25.506Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-02T10:35:26.993Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-02T10:35:27.669Z] 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.
[2024-09-02T10:35:27.669Z] The best model improves the baseline by 14.33%.
[2024-09-02T10:35:27.669Z] Movies recommended for you:
[2024-09-02T10:35:27.669Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-02T10:35:27.669Z] There is no way to check that no silent failure occurred.
[2024-09-02T10:35:27.669Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (17986.243 ms) ======
[2024-09-02T10:35:28.374Z] -----------------------------------
[2024-09-02T10:35:28.374Z] renaissance-movie-lens_0_PASSED
[2024-09-02T10:35:28.374Z] -----------------------------------
[2024-09-02T10:35:28.374Z]
[2024-09-02T10:35:28.374Z] TEST TEARDOWN:
[2024-09-02T10:35:28.374Z] Nothing to be done for teardown.
[2024-09-02T10:35:28.374Z] renaissance-movie-lens_0 Finish Time: Mon Sep 2 11:35:28 2024 Epoch Time (ms): 1725273328070