renaissance-movie-lens_0
[2024-09-05T21:37:13.772Z] Running test renaissance-movie-lens_0 ...
[2024-09-05T21:37:13.772Z] ===============================================
[2024-09-05T21:37:13.772Z] renaissance-movie-lens_0 Start Time: Thu Sep 5 22:37:12 2024 Epoch Time (ms): 1725572232887
[2024-09-05T21:37:13.772Z] variation: NoOptions
[2024-09-05T21:37:13.772Z] JVM_OPTIONS:
[2024-09-05T21:37:13.772Z] { \
[2024-09-05T21:37:13.772Z] echo ""; echo "TEST SETUP:"; \
[2024-09-05T21:37:13.772Z] echo "Nothing to be done for setup."; \
[2024-09-05T21:37:13.772Z] mkdir -p "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/aqa-tests/TKG/../TKG/output_17255707848343/renaissance-movie-lens_0"; \
[2024-09-05T21:37:13.772Z] cd "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/aqa-tests/TKG/../TKG/output_17255707848343/renaissance-movie-lens_0"; \
[2024-09-05T21:37:13.772Z] echo ""; echo "TESTING:"; \
[2024-09-05T21:37:13.772Z] "/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_17255707848343/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-09-05T21:37:13.772Z] 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_17255707848343/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-09-05T21:37:13.772Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-09-05T21:37:13.772Z] echo "Nothing to be done for teardown."; \
[2024-09-05T21:37:13.772Z] } 2>&1 | tee -a "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/aqa-tests/TKG/../TKG/output_17255707848343/TestTargetResult";
[2024-09-05T21:37:13.772Z]
[2024-09-05T21:37:13.772Z] TEST SETUP:
[2024-09-05T21:37:13.772Z] Nothing to be done for setup.
[2024-09-05T21:37:13.772Z]
[2024-09-05T21:37:13.772Z] TESTING:
[2024-09-05T21:37:19.788Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-09-05T21:37:24.200Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 1 (out of 1) threads.
[2024-09-05T21:37:31.976Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-09-05T21:37:31.976Z] Training: 60056, validation: 20285, test: 19854
[2024-09-05T21:37:31.976Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-09-05T21:37:31.976Z] GC before operation: completed in 95.781 ms, heap usage 48.877 MB -> 26.043 MB.
[2024-09-05T21:37:43.127Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:37:47.135Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:37:52.197Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:37:57.179Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:38:00.135Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:38:02.242Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:38:05.234Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:38:08.339Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:38:08.974Z] 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.
[2024-09-05T21:38:08.974Z] The best model improves the baseline by 14.33%.
[2024-09-05T21:38:08.974Z] Movies recommended for you:
[2024-09-05T21:38:08.974Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:38:08.974Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:38:08.974Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (37210.241 ms) ======
[2024-09-05T21:38:08.974Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-09-05T21:38:08.974Z] GC before operation: completed in 214.191 ms, heap usage 90.595 MB -> 51.131 MB.
[2024-09-05T21:38:12.796Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:38:16.320Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:38:20.158Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:38:24.159Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:38:26.408Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:38:29.349Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:38:31.555Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:38:34.490Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:38:34.490Z] 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.
[2024-09-05T21:38:34.490Z] The best model improves the baseline by 14.33%.
[2024-09-05T21:38:34.490Z] Movies recommended for you:
[2024-09-05T21:38:34.490Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:38:34.490Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:38:34.490Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (25351.560 ms) ======
[2024-09-05T21:38:34.490Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-09-05T21:38:35.126Z] GC before operation: completed in 317.899 ms, heap usage 100.407 MB -> 76.110 MB.
[2024-09-05T21:38:39.111Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:38:41.997Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:38:45.825Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:38:48.803Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:38:50.873Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:38:52.230Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:38:54.364Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:38:56.498Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:38:56.498Z] 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.
[2024-09-05T21:38:56.498Z] The best model improves the baseline by 14.33%.
[2024-09-05T21:38:57.147Z] Movies recommended for you:
[2024-09-05T21:38:57.147Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:38:57.147Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:38:57.147Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (21901.119 ms) ======
[2024-09-05T21:38:57.147Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-09-05T21:38:57.147Z] GC before operation: completed in 213.062 ms, heap usage 139.858 MB -> 65.652 MB.
[2024-09-05T21:39:00.590Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:39:03.173Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:39:07.061Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:39:09.990Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:39:11.399Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:39:13.497Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:39:15.606Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:39:17.001Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:39:17.645Z] 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.
[2024-09-05T21:39:17.645Z] The best model improves the baseline by 14.33%.
[2024-09-05T21:39:17.645Z] Movies recommended for you:
[2024-09-05T21:39:17.645Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:39:17.645Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:39:17.645Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (20630.273 ms) ======
[2024-09-05T21:39:17.645Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-09-05T21:39:17.645Z] GC before operation: completed in 147.490 ms, heap usage 127.761 MB -> 71.854 MB.
[2024-09-05T21:39:21.447Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:39:24.417Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:39:27.324Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:39:30.389Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:39:31.745Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:39:33.906Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:39:36.013Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:39:37.329Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:39:37.964Z] 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.
[2024-09-05T21:39:37.964Z] The best model improves the baseline by 14.33%.
[2024-09-05T21:39:37.964Z] Movies recommended for you:
[2024-09-05T21:39:37.964Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:39:37.964Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:39:37.964Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (20293.366 ms) ======
[2024-09-05T21:39:37.964Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-09-05T21:39:37.964Z] GC before operation: completed in 147.942 ms, heap usage 139.627 MB -> 68.815 MB.
[2024-09-05T21:39:41.752Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:39:44.738Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:39:47.979Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:39:50.943Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:39:52.319Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:39:54.551Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:39:55.966Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:39:58.241Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:39:58.241Z] 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.
[2024-09-05T21:39:58.241Z] The best model improves the baseline by 14.33%.
[2024-09-05T21:39:58.878Z] Movies recommended for you:
[2024-09-05T21:39:58.878Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:39:58.879Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:39:58.879Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (20332.205 ms) ======
[2024-09-05T21:39:58.879Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-09-05T21:39:58.879Z] GC before operation: completed in 152.780 ms, heap usage 139.796 MB -> 72.704 MB.
[2024-09-05T21:40:01.780Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:40:05.648Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:40:08.551Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:40:11.488Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:40:13.600Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:40:14.936Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:40:17.022Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:40:19.143Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:40:19.779Z] 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.
[2024-09-05T21:40:19.779Z] The best model improves the baseline by 14.33%.
[2024-09-05T21:40:19.779Z] Movies recommended for you:
[2024-09-05T21:40:19.779Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:40:19.779Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:40:19.779Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (20928.244 ms) ======
[2024-09-05T21:40:19.779Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-09-05T21:40:19.779Z] GC before operation: completed in 296.475 ms, heap usage 140.083 MB -> 69.302 MB.
[2024-09-05T21:40:22.731Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:40:25.714Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:40:28.694Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:40:31.744Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:40:34.037Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:40:35.360Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:40:37.448Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:40:38.785Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:40:38.785Z] 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.
[2024-09-05T21:40:39.425Z] The best model improves the baseline by 14.33%.
[2024-09-05T21:40:39.425Z] Movies recommended for you:
[2024-09-05T21:40:39.425Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:40:39.425Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:40:39.425Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (19279.670 ms) ======
[2024-09-05T21:40:39.425Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-09-05T21:40:39.425Z] GC before operation: completed in 145.097 ms, heap usage 122.388 MB -> 71.419 MB.
[2024-09-05T21:40:42.378Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:40:45.398Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:40:48.328Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:40:51.420Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:40:52.774Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:40:54.872Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:40:56.219Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:40:58.357Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:40:58.357Z] 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.
[2024-09-05T21:40:58.357Z] The best model improves the baseline by 14.33%.
[2024-09-05T21:40:58.357Z] Movies recommended for you:
[2024-09-05T21:40:58.357Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:40:58.357Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:40:58.357Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (19113.047 ms) ======
[2024-09-05T21:40:58.357Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-09-05T21:40:59.068Z] GC before operation: completed in 179.601 ms, heap usage 140.787 MB -> 71.784 MB.
[2024-09-05T21:41:02.034Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:41:05.003Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:41:07.942Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:41:10.877Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:41:12.994Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:41:14.376Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:41:16.164Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:41:17.590Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:41:18.226Z] 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.
[2024-09-05T21:41:18.226Z] The best model improves the baseline by 14.33%.
[2024-09-05T21:41:18.226Z] Movies recommended for you:
[2024-09-05T21:41:18.226Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:41:18.226Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:41:18.226Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (19718.913 ms) ======
[2024-09-05T21:41:18.226Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-09-05T21:41:18.877Z] GC before operation: completed in 153.360 ms, heap usage 142.460 MB -> 72.336 MB.
[2024-09-05T21:41:20.999Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:41:24.042Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:41:28.043Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:41:30.940Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:41:33.116Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:41:34.480Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:41:36.645Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:41:37.985Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:41:38.628Z] 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.
[2024-09-05T21:41:38.628Z] The best model improves the baseline by 14.33%.
[2024-09-05T21:41:38.628Z] Movies recommended for you:
[2024-09-05T21:41:38.628Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:41:38.628Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:41:38.628Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (20111.487 ms) ======
[2024-09-05T21:41:38.628Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-09-05T21:41:38.628Z] GC before operation: completed in 178.906 ms, heap usage 130.107 MB -> 65.946 MB.
[2024-09-05T21:41:41.576Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:41:44.499Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:41:47.399Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:41:50.313Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:41:52.454Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:41:53.936Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:41:56.081Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:41:57.455Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:41:58.096Z] 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.
[2024-09-05T21:41:58.096Z] The best model improves the baseline by 14.33%.
[2024-09-05T21:41:58.096Z] Movies recommended for you:
[2024-09-05T21:41:58.096Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:41:58.096Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:41:58.096Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (19196.205 ms) ======
[2024-09-05T21:41:58.096Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-09-05T21:41:58.096Z] GC before operation: completed in 149.458 ms, heap usage 133.173 MB -> 71.417 MB.
[2024-09-05T21:42:01.199Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:42:04.447Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:42:08.329Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:42:11.284Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:42:12.634Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:42:14.844Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:42:16.936Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:42:18.285Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:42:18.931Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-09-05T21:42:18.931Z] The best model improves the baseline by 14.33%.
[2024-09-05T21:42:18.931Z] Movies recommended for you:
[2024-09-05T21:42:18.931Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:42:18.931Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:42:18.931Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (20668.843 ms) ======
[2024-09-05T21:42:18.931Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-09-05T21:42:18.931Z] GC before operation: completed in 165.196 ms, heap usage 131.806 MB -> 73.222 MB.
[2024-09-05T21:42:21.851Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:42:24.755Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:42:27.932Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:42:30.881Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:42:32.865Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:42:35.135Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:42:36.461Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:42:38.571Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:42:38.571Z] 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.
[2024-09-05T21:42:38.571Z] The best model improves the baseline by 14.33%.
[2024-09-05T21:42:38.571Z] Movies recommended for you:
[2024-09-05T21:42:38.571Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:42:38.571Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:42:38.571Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (19701.852 ms) ======
[2024-09-05T21:42:38.571Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-09-05T21:42:39.231Z] GC before operation: completed in 254.721 ms, heap usage 132.940 MB -> 75.437 MB.
[2024-09-05T21:42:42.175Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:42:45.206Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:42:48.324Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:42:51.323Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:42:52.690Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:42:54.807Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:42:56.147Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:42:58.227Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:42:58.227Z] 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.
[2024-09-05T21:42:58.227Z] The best model improves the baseline by 14.33%.
[2024-09-05T21:42:58.227Z] Movies recommended for you:
[2024-09-05T21:42:58.227Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:42:58.227Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:42:58.227Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (19557.370 ms) ======
[2024-09-05T21:42:58.227Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-09-05T21:42:58.866Z] GC before operation: completed in 281.019 ms, heap usage 140.487 MB -> 70.210 MB.
[2024-09-05T21:43:02.021Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:43:05.129Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:43:08.133Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:43:10.415Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:43:12.611Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:43:13.957Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:43:16.226Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:43:17.552Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:43:18.190Z] 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.
[2024-09-05T21:43:18.190Z] The best model improves the baseline by 14.33%.
[2024-09-05T21:43:18.190Z] Movies recommended for you:
[2024-09-05T21:43:18.190Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:43:18.190Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:43:18.190Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (19436.322 ms) ======
[2024-09-05T21:43:18.190Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-09-05T21:43:18.190Z] GC before operation: completed in 148.388 ms, heap usage 124.180 MB -> 72.710 MB.
[2024-09-05T21:43:21.144Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:43:24.074Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:43:27.889Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:43:32.167Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:43:32.802Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:43:34.447Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:43:36.634Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:43:38.885Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:43:39.525Z] 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.
[2024-09-05T21:43:39.525Z] The best model improves the baseline by 14.33%.
[2024-09-05T21:43:39.525Z] Movies recommended for you:
[2024-09-05T21:43:39.525Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:43:39.525Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:43:39.525Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (21082.986 ms) ======
[2024-09-05T21:43:39.525Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-09-05T21:43:39.525Z] GC before operation: completed in 251.298 ms, heap usage 131.979 MB -> 74.895 MB.
[2024-09-05T21:43:42.465Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:43:46.375Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:43:49.442Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:43:52.408Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:43:53.771Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:43:55.946Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:43:58.056Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:43:59.415Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:43:59.415Z] 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.
[2024-09-05T21:43:59.415Z] The best model improves the baseline by 14.33%.
[2024-09-05T21:43:59.415Z] Movies recommended for you:
[2024-09-05T21:43:59.415Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:43:59.415Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:43:59.415Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (19939.703 ms) ======
[2024-09-05T21:43:59.415Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-09-05T21:44:00.053Z] GC before operation: completed in 175.897 ms, heap usage 138.228 MB -> 71.708 MB.
[2024-09-05T21:44:03.074Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:44:06.507Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:44:09.482Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:44:11.558Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:44:13.759Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:44:15.088Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:44:17.391Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:44:18.761Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:44:19.400Z] 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.
[2024-09-05T21:44:19.400Z] The best model improves the baseline by 14.33%.
[2024-09-05T21:44:19.400Z] Movies recommended for you:
[2024-09-05T21:44:19.400Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:44:19.400Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:44:19.400Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (19556.854 ms) ======
[2024-09-05T21:44:19.400Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-09-05T21:44:19.400Z] GC before operation: completed in 246.181 ms, heap usage 124.795 MB -> 69.408 MB.
[2024-09-05T21:44:22.329Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-05T21:44:25.268Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-05T21:44:29.143Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-05T21:44:31.232Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-05T21:44:33.338Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-05T21:44:34.698Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-05T21:44:36.794Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-05T21:44:38.903Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-05T21:44:38.903Z] 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.
[2024-09-05T21:44:38.903Z] The best model improves the baseline by 14.33%.
[2024-09-05T21:44:38.903Z] Movies recommended for you:
[2024-09-05T21:44:38.903Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-05T21:44:38.903Z] There is no way to check that no silent failure occurred.
[2024-09-05T21:44:38.903Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (19508.524 ms) ======
[2024-09-05T21:44:39.562Z] -----------------------------------
[2024-09-05T21:44:39.562Z] renaissance-movie-lens_0_PASSED
[2024-09-05T21:44:39.562Z] -----------------------------------
[2024-09-05T21:44:39.562Z]
[2024-09-05T21:44:39.562Z] TEST TEARDOWN:
[2024-09-05T21:44:39.562Z] Nothing to be done for teardown.
[2024-09-05T21:44:39.562Z] renaissance-movie-lens_0 Finish Time: Thu Sep 5 22:44:39 2024 Epoch Time (ms): 1725572679432