renaissance-movie-lens_0
[2024-11-15T06:18:18.392Z] Running test renaissance-movie-lens_0 ...
[2024-11-15T06:18:18.392Z] ===============================================
[2024-11-15T06:18:18.392Z] renaissance-movie-lens_0 Start Time: Fri Nov 15 06:18:17 2024 Epoch Time (ms): 1731651497641
[2024-11-15T06:18:18.392Z] variation: NoOptions
[2024-11-15T06:18:18.392Z] JVM_OPTIONS:
[2024-11-15T06:18:18.392Z] { \
[2024-11-15T06:18:18.392Z] echo ""; echo "TEST SETUP:"; \
[2024-11-15T06:18:18.392Z] echo "Nothing to be done for setup."; \
[2024-11-15T06:18:18.392Z] mkdir -p "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/aqa-tests/TKG/../TKG/output_17316492184916/renaissance-movie-lens_0"; \
[2024-11-15T06:18:18.392Z] cd "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/aqa-tests/TKG/../TKG/output_17316492184916/renaissance-movie-lens_0"; \
[2024-11-15T06:18:18.392Z] echo ""; echo "TESTING:"; \
[2024-11-15T06:18:18.392Z] "/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_17316492184916/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-15T06:18:18.392Z] 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_17316492184916/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-15T06:18:18.392Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-15T06:18:18.392Z] echo "Nothing to be done for teardown."; \
[2024-11-15T06:18:18.392Z] } 2>&1 | tee -a "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/aqa-tests/TKG/../TKG/output_17316492184916/TestTargetResult";
[2024-11-15T06:18:18.392Z]
[2024-11-15T06:18:18.392Z] TEST SETUP:
[2024-11-15T06:18:18.392Z] Nothing to be done for setup.
[2024-11-15T06:18:18.392Z]
[2024-11-15T06:18:18.392Z] TESTING:
[2024-11-15T06:18:29.409Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-15T06:18:35.663Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 1 (out of 1) threads.
[2024-11-15T06:18:45.055Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-15T06:18:45.055Z] Training: 60056, validation: 20285, test: 19854
[2024-11-15T06:18:45.055Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-15T06:18:45.056Z] GC before operation: completed in 155.060 ms, heap usage 55.277 MB -> 26.259 MB.
[2024-11-15T06:18:58.319Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T06:19:07.214Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T06:19:13.405Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T06:19:19.933Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T06:19:24.322Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T06:19:28.189Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T06:19:31.167Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T06:19:36.041Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T06:19:36.675Z] 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.
[2024-11-15T06:19:36.675Z] The best model improves the baseline by 14.33%.
[2024-11-15T06:19:37.330Z] Movies recommended for you:
[2024-11-15T06:19:37.330Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T06:19:37.330Z] There is no way to check that no silent failure occurred.
[2024-11-15T06:19:37.330Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (52423.607 ms) ======
[2024-11-15T06:19:37.330Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-15T06:19:37.330Z] GC before operation: completed in 308.946 ms, heap usage 87.559 MB -> 65.759 MB.
[2024-11-15T06:19:44.660Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T06:19:52.081Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T06:19:57.029Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T06:20:02.064Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T06:20:05.097Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T06:20:08.079Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T06:20:11.001Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T06:20:13.333Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T06:20:13.973Z] 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.
[2024-11-15T06:20:13.973Z] The best model improves the baseline by 14.33%.
[2024-11-15T06:20:13.973Z] Movies recommended for you:
[2024-11-15T06:20:13.973Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T06:20:13.973Z] There is no way to check that no silent failure occurred.
[2024-11-15T06:20:13.973Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (36751.953 ms) ======
[2024-11-15T06:20:13.973Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-15T06:20:14.608Z] GC before operation: completed in 205.647 ms, heap usage 113.943 MB -> 68.495 MB.
[2024-11-15T06:20:20.737Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T06:20:25.930Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T06:20:45.802Z] Cannot contact test-azure-solaris10-x64-1: java.lang.InterruptedException
[2024-11-15T06:20:52.451Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T06:20:57.536Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T06:21:02.409Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T06:21:05.341Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T06:21:08.396Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T06:21:11.348Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T06:21:12.020Z] 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.
[2024-11-15T06:21:12.020Z] The best model improves the baseline by 14.33%.
[2024-11-15T06:21:12.020Z] Movies recommended for you:
[2024-11-15T06:21:12.020Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T06:21:12.020Z] There is no way to check that no silent failure occurred.
[2024-11-15T06:21:12.020Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (57717.568 ms) ======
[2024-11-15T06:21:12.020Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-15T06:21:12.665Z] GC before operation: completed in 274.696 ms, heap usage 154.494 MB -> 71.229 MB.
[2024-11-15T06:21:17.655Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T06:21:21.634Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T06:21:26.800Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T06:21:30.684Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T06:21:33.695Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T06:21:36.617Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T06:21:39.558Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T06:21:41.657Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T06:21:42.396Z] 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.
[2024-11-15T06:21:42.396Z] The best model improves the baseline by 14.33%.
[2024-11-15T06:21:43.073Z] Movies recommended for you:
[2024-11-15T06:21:43.073Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T06:21:43.073Z] There is no way to check that no silent failure occurred.
[2024-11-15T06:21:43.073Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (30411.393 ms) ======
[2024-11-15T06:21:43.073Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-15T06:21:43.073Z] GC before operation: completed in 222.540 ms, heap usage 138.443 MB -> 64.556 MB.
[2024-11-15T06:21:47.932Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T06:21:52.789Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T06:21:57.678Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T06:22:01.626Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T06:22:04.000Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T06:22:06.955Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T06:22:09.868Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T06:22:12.622Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T06:22:13.273Z] 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.
[2024-11-15T06:22:13.273Z] The best model improves the baseline by 14.33%.
[2024-11-15T06:22:13.273Z] Movies recommended for you:
[2024-11-15T06:22:13.273Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T06:22:13.273Z] There is no way to check that no silent failure occurred.
[2024-11-15T06:22:13.273Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (30392.119 ms) ======
[2024-11-15T06:22:13.273Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-15T06:22:13.273Z] GC before operation: completed in 233.106 ms, heap usage 111.961 MB -> 71.464 MB.
[2024-11-15T06:22:18.152Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T06:22:23.047Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T06:22:28.111Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T06:22:31.940Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T06:22:34.850Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T06:22:38.018Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T06:22:41.101Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T06:22:43.194Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T06:22:43.855Z] 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.
[2024-11-15T06:22:43.855Z] The best model improves the baseline by 14.33%.
[2024-11-15T06:22:44.570Z] Movies recommended for you:
[2024-11-15T06:22:44.570Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T06:22:44.570Z] There is no way to check that no silent failure occurred.
[2024-11-15T06:22:44.570Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (30757.355 ms) ======
[2024-11-15T06:22:44.570Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-15T06:22:44.570Z] GC before operation: completed in 236.601 ms, heap usage 124.345 MB -> 67.910 MB.
[2024-11-15T06:22:49.459Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T06:22:54.389Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T06:22:59.884Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T06:23:04.805Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T06:23:06.879Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T06:23:09.852Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T06:23:12.011Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T06:23:14.984Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T06:23:15.646Z] 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.
[2024-11-15T06:23:15.646Z] The best model improves the baseline by 14.33%.
[2024-11-15T06:23:15.646Z] Movies recommended for you:
[2024-11-15T06:23:15.646Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T06:23:15.646Z] There is no way to check that no silent failure occurred.
[2024-11-15T06:23:15.646Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (31104.971 ms) ======
[2024-11-15T06:23:15.646Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-15T06:23:15.646Z] GC before operation: completed in 227.227 ms, heap usage 119.734 MB -> 66.792 MB.
[2024-11-15T06:23:20.625Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T06:23:25.557Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T06:23:30.662Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T06:23:34.623Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T06:23:37.528Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T06:23:40.435Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T06:23:43.445Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T06:23:46.626Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T06:23:46.626Z] 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.
[2024-11-15T06:23:46.626Z] The best model improves the baseline by 14.33%.
[2024-11-15T06:23:46.626Z] Movies recommended for you:
[2024-11-15T06:23:46.626Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T06:23:46.626Z] There is no way to check that no silent failure occurred.
[2024-11-15T06:23:46.626Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (30906.463 ms) ======
[2024-11-15T06:23:46.626Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-15T06:23:46.626Z] GC before operation: completed in 208.407 ms, heap usage 120.244 MB -> 62.836 MB.
[2024-11-15T06:23:52.098Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T06:23:57.045Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T06:24:00.872Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T06:24:05.933Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T06:24:08.146Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T06:24:10.270Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T06:24:13.571Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T06:24:15.668Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T06:24:16.393Z] 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.
[2024-11-15T06:24:16.393Z] The best model improves the baseline by 14.33%.
[2024-11-15T06:24:16.393Z] Movies recommended for you:
[2024-11-15T06:24:16.393Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T06:24:16.393Z] There is no way to check that no silent failure occurred.
[2024-11-15T06:24:16.393Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (29643.784 ms) ======
[2024-11-15T06:24:16.393Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-15T06:24:16.393Z] GC before operation: completed in 206.126 ms, heap usage 128.217 MB -> 68.983 MB.
[2024-11-15T06:24:21.319Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T06:24:26.209Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T06:24:31.423Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T06:24:35.264Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T06:24:38.031Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T06:24:41.162Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T06:24:44.127Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T06:24:46.204Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T06:24:46.880Z] 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.
[2024-11-15T06:24:46.880Z] The best model improves the baseline by 14.33%.
[2024-11-15T06:24:46.880Z] Movies recommended for you:
[2024-11-15T06:24:46.880Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T06:24:46.880Z] There is no way to check that no silent failure occurred.
[2024-11-15T06:24:46.880Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (30199.629 ms) ======
[2024-11-15T06:24:46.880Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-15T06:24:46.880Z] GC before operation: completed in 216.716 ms, heap usage 130.363 MB -> 67.148 MB.
[2024-11-15T06:25:14.348Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T06:25:19.232Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T06:25:24.113Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T06:25:28.088Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T06:25:30.169Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T06:25:33.213Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T06:25:35.312Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T06:25:38.294Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T06:25:38.294Z] 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.
[2024-11-15T06:25:38.294Z] The best model improves the baseline by 14.33%.
[2024-11-15T06:25:38.988Z] Movies recommended for you:
[2024-11-15T06:25:38.988Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T06:25:38.988Z] There is no way to check that no silent failure occurred.
[2024-11-15T06:25:38.988Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (51764.242 ms) ======
[2024-11-15T06:25:38.988Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-15T06:25:38.988Z] GC before operation: completed in 216.120 ms, heap usage 131.102 MB -> 66.648 MB.
[2024-11-15T06:25:43.896Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T06:25:48.423Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T06:25:53.719Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T06:25:57.619Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T06:26:00.593Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T06:26:02.741Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T06:26:05.742Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T06:26:08.732Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T06:26:09.384Z] 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.
[2024-11-15T06:26:09.385Z] The best model improves the baseline by 14.33%.
[2024-11-15T06:26:09.385Z] Movies recommended for you:
[2024-11-15T06:26:09.385Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T06:26:09.385Z] There is no way to check that no silent failure occurred.
[2024-11-15T06:26:09.385Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (30340.335 ms) ======
[2024-11-15T06:26:09.385Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-15T06:26:09.385Z] GC before operation: completed in 395.005 ms, heap usage 120.645 MB -> 66.713 MB.
[2024-11-15T06:26:14.350Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T06:26:20.440Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T06:26:25.319Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T06:26:29.223Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T06:26:32.297Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T06:26:35.595Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T06:26:37.700Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T06:26:40.593Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T06:26:41.244Z] 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.
[2024-11-15T06:26:41.988Z] The best model improves the baseline by 14.33%.
[2024-11-15T06:26:41.988Z] Movies recommended for you:
[2024-11-15T06:26:41.988Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T06:26:41.988Z] There is no way to check that no silent failure occurred.
[2024-11-15T06:26:41.988Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (32119.443 ms) ======
[2024-11-15T06:26:41.988Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-15T06:26:41.988Z] GC before operation: completed in 207.279 ms, heap usage 126.806 MB -> 68.605 MB.
[2024-11-15T06:26:48.077Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T06:26:51.976Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T06:26:56.809Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T06:27:00.871Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T06:27:03.774Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T06:27:06.737Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T06:27:08.986Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T06:27:11.256Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T06:27:11.893Z] 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.
[2024-11-15T06:27:11.893Z] The best model improves the baseline by 14.33%.
[2024-11-15T06:27:12.534Z] Movies recommended for you:
[2024-11-15T06:27:12.534Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T06:27:12.534Z] There is no way to check that no silent failure occurred.
[2024-11-15T06:27:12.534Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (30390.863 ms) ======
[2024-11-15T06:27:12.534Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-15T06:27:12.534Z] GC before operation: completed in 203.375 ms, heap usage 121.611 MB -> 67.712 MB.
[2024-11-15T06:27:17.404Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T06:27:21.738Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T06:27:26.605Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T06:27:31.654Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T06:27:34.575Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T06:27:37.165Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T06:27:40.113Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T06:27:42.225Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T06:27:42.877Z] 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.
[2024-11-15T06:27:42.877Z] The best model improves the baseline by 14.33%.
[2024-11-15T06:27:42.877Z] Movies recommended for you:
[2024-11-15T06:27:42.877Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T06:27:42.877Z] There is no way to check that no silent failure occurred.
[2024-11-15T06:27:42.877Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (30407.780 ms) ======
[2024-11-15T06:27:42.877Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-15T06:27:42.877Z] GC before operation: completed in 200.703 ms, heap usage 121.761 MB -> 66.799 MB.
[2024-11-15T06:27:47.764Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T06:27:52.620Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T06:27:56.564Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T06:28:01.462Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T06:28:03.600Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T06:28:06.569Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T06:28:08.668Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T06:28:11.910Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T06:28:11.910Z] 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.
[2024-11-15T06:28:11.910Z] The best model improves the baseline by 14.33%.
[2024-11-15T06:28:12.545Z] Movies recommended for you:
[2024-11-15T06:28:12.545Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T06:28:12.545Z] There is no way to check that no silent failure occurred.
[2024-11-15T06:28:12.545Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (29310.773 ms) ======
[2024-11-15T06:28:12.545Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-15T06:28:12.545Z] GC before operation: completed in 200.902 ms, heap usage 118.542 MB -> 62.242 MB.
[2024-11-15T06:28:17.406Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T06:28:22.433Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T06:28:27.434Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T06:28:31.255Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T06:28:34.274Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T06:28:37.359Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T06:28:39.458Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T06:28:43.283Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T06:28:43.283Z] 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.
[2024-11-15T06:28:43.283Z] The best model improves the baseline by 14.33%.
[2024-11-15T06:28:43.918Z] Movies recommended for you:
[2024-11-15T06:28:43.919Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T06:28:43.919Z] There is no way to check that no silent failure occurred.
[2024-11-15T06:28:43.919Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (31244.335 ms) ======
[2024-11-15T06:28:43.919Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-15T06:28:43.919Z] GC before operation: completed in 247.950 ms, heap usage 113.624 MB -> 67.461 MB.
[2024-11-15T06:28:48.809Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T06:28:53.709Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T06:28:58.333Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T06:29:02.175Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T06:29:05.148Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T06:29:08.137Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T06:29:10.229Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T06:29:13.217Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T06:29:13.217Z] 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.
[2024-11-15T06:29:13.217Z] The best model improves the baseline by 14.33%.
[2024-11-15T06:29:13.859Z] Movies recommended for you:
[2024-11-15T06:29:13.859Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T06:29:13.859Z] There is no way to check that no silent failure occurred.
[2024-11-15T06:29:13.859Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (29618.983 ms) ======
[2024-11-15T06:29:13.859Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-15T06:29:13.859Z] GC before operation: completed in 203.358 ms, heap usage 121.096 MB -> 67.888 MB.
[2024-11-15T06:29:18.826Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T06:29:23.725Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T06:29:28.639Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T06:29:32.484Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T06:29:35.423Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T06:29:37.554Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T06:29:40.517Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T06:29:43.515Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T06:29:43.516Z] 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.
[2024-11-15T06:29:43.516Z] The best model improves the baseline by 14.33%.
[2024-11-15T06:29:44.452Z] Movies recommended for you:
[2024-11-15T06:29:44.453Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T06:29:44.453Z] There is no way to check that no silent failure occurred.
[2024-11-15T06:29:44.453Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (30138.666 ms) ======
[2024-11-15T06:29:44.453Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-15T06:29:44.453Z] GC before operation: completed in 376.071 ms, heap usage 119.211 MB -> 70.266 MB.
[2024-11-15T06:29:49.398Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-15T06:29:54.424Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-15T06:29:59.468Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-15T06:30:03.337Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-15T06:30:06.266Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-15T06:30:09.190Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-15T06:30:11.297Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-15T06:30:13.790Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-15T06:30:14.425Z] 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.
[2024-11-15T06:30:14.425Z] The best model improves the baseline by 14.33%.
[2024-11-15T06:30:14.425Z] Movies recommended for you:
[2024-11-15T06:30:14.425Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-15T06:30:14.425Z] There is no way to check that no silent failure occurred.
[2024-11-15T06:30:14.425Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (30222.130 ms) ======
[2024-11-15T06:30:15.978Z] -----------------------------------
[2024-11-15T06:30:15.978Z] renaissance-movie-lens_0_PASSED
[2024-11-15T06:30:15.978Z] -----------------------------------
[2024-11-15T06:30:15.978Z]
[2024-11-15T06:30:15.978Z] TEST TEARDOWN:
[2024-11-15T06:30:15.978Z] Nothing to be done for teardown.
[2024-11-15T06:30:15.978Z] renaissance-movie-lens_0 Finish Time: Fri Nov 15 06:30:15 2024 Epoch Time (ms): 1731652215388