renaissance-movie-lens_0
[2024-08-09T22:27:48.657Z] Running test renaissance-movie-lens_0 ...
[2024-08-09T22:27:48.657Z] ===============================================
[2024-08-09T22:27:48.657Z] renaissance-movie-lens_0 Start Time: Fri Aug 9 22:27:47 2024 Epoch Time (ms): 1723242467866
[2024-08-09T22:27:48.657Z] variation: NoOptions
[2024-08-09T22:27:48.657Z] JVM_OPTIONS:
[2024-08-09T22:27:48.657Z] { \
[2024-08-09T22:27:48.657Z] echo ""; echo "TEST SETUP:"; \
[2024-08-09T22:27:48.657Z] echo "Nothing to be done for setup."; \
[2024-08-09T22:27:48.657Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17232416127160/renaissance-movie-lens_0"; \
[2024-08-09T22:27:48.657Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17232416127160/renaissance-movie-lens_0"; \
[2024-08-09T22:27:48.657Z] echo ""; echo "TESTING:"; \
[2024-08-09T22:27:48.657Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17232416127160/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-09T22:27:48.657Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17232416127160/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-09T22:27:48.657Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-09T22:27:48.657Z] echo "Nothing to be done for teardown."; \
[2024-08-09T22:27:48.657Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17232416127160/TestTargetResult";
[2024-08-09T22:27:48.657Z]
[2024-08-09T22:27:48.657Z] TEST SETUP:
[2024-08-09T22:27:48.657Z] Nothing to be done for setup.
[2024-08-09T22:27:48.657Z]
[2024-08-09T22:27:48.657Z] TESTING:
[2024-08-09T22:27:51.637Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-09T22:27:53.570Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-08-09T22:27:55.510Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-09T22:27:56.450Z] Training: 60056, validation: 20285, test: 19854
[2024-08-09T22:27:56.450Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-09T22:27:56.450Z] GC before operation: completed in 71.392 ms, heap usage 57.092 MB -> 37.263 MB.
[2024-08-09T22:28:01.762Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T22:28:04.744Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T22:28:07.856Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T22:28:09.832Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T22:28:11.764Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T22:28:13.699Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T22:28:14.639Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T22:28:16.570Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T22:28:16.570Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-09T22:28:16.570Z] The best model improves the baseline by 14.52%.
[2024-08-09T22:28:16.570Z] Movies recommended for you:
[2024-08-09T22:28:16.570Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T22:28:16.570Z] There is no way to check that no silent failure occurred.
[2024-08-09T22:28:16.570Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (20678.761 ms) ======
[2024-08-09T22:28:16.570Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-09T22:28:17.522Z] GC before operation: completed in 78.308 ms, heap usage 178.134 MB -> 54.791 MB.
[2024-08-09T22:28:19.474Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T22:28:22.463Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T22:28:24.430Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T22:28:26.370Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T22:28:28.310Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T22:28:29.251Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T22:28:31.207Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T22:28:32.149Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T22:28:32.149Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-09T22:28:32.149Z] The best model improves the baseline by 14.52%.
[2024-08-09T22:28:33.091Z] Movies recommended for you:
[2024-08-09T22:28:33.091Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T22:28:33.091Z] There is no way to check that no silent failure occurred.
[2024-08-09T22:28:33.091Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (15663.292 ms) ======
[2024-08-09T22:28:33.091Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-09T22:28:33.091Z] GC before operation: completed in 69.619 ms, heap usage 343.259 MB -> 52.155 MB.
[2024-08-09T22:28:35.227Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T22:28:37.182Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T22:28:39.113Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T22:28:42.099Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T22:28:43.046Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T22:28:43.986Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T22:28:45.936Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T22:28:46.876Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T22:28:46.876Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-09T22:28:46.876Z] The best model improves the baseline by 14.52%.
[2024-08-09T22:28:46.876Z] Movies recommended for you:
[2024-08-09T22:28:46.876Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T22:28:46.876Z] There is no way to check that no silent failure occurred.
[2024-08-09T22:28:46.876Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (14408.392 ms) ======
[2024-08-09T22:28:46.876Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-09T22:28:46.876Z] GC before operation: completed in 62.846 ms, heap usage 316.325 MB -> 50.343 MB.
[2024-08-09T22:28:48.932Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T22:28:50.871Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T22:28:53.856Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T22:28:55.788Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T22:28:56.727Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T22:28:58.669Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T22:28:59.610Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T22:29:00.550Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T22:29:00.550Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-09T22:29:00.550Z] The best model improves the baseline by 14.52%.
[2024-08-09T22:29:01.498Z] Movies recommended for you:
[2024-08-09T22:29:01.498Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T22:29:01.498Z] There is no way to check that no silent failure occurred.
[2024-08-09T22:29:01.498Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (13797.940 ms) ======
[2024-08-09T22:29:01.498Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-09T22:29:01.498Z] GC before operation: completed in 66.058 ms, heap usage 99.488 MB -> 50.429 MB.
[2024-08-09T22:29:03.434Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T22:29:05.390Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T22:29:07.321Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T22:29:09.251Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T22:29:10.191Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T22:29:12.127Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T22:29:13.068Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T22:29:14.705Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T22:29:15.668Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-09T22:29:15.668Z] The best model improves the baseline by 14.52%.
[2024-08-09T22:29:15.668Z] Movies recommended for you:
[2024-08-09T22:29:15.668Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T22:29:15.668Z] There is no way to check that no silent failure occurred.
[2024-08-09T22:29:15.668Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (13620.591 ms) ======
[2024-08-09T22:29:15.668Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-09T22:29:15.668Z] GC before operation: completed in 77.534 ms, heap usage 85.805 MB -> 50.537 MB.
[2024-08-09T22:29:16.617Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T22:29:18.555Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T22:29:20.485Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T22:29:22.423Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T22:29:23.364Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T22:29:25.295Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T22:29:26.235Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T22:29:27.174Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T22:29:27.174Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-09T22:29:27.174Z] The best model improves the baseline by 14.52%.
[2024-08-09T22:29:28.116Z] Movies recommended for you:
[2024-08-09T22:29:28.116Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T22:29:28.116Z] There is no way to check that no silent failure occurred.
[2024-08-09T22:29:28.116Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (12873.770 ms) ======
[2024-08-09T22:29:28.116Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-09T22:29:28.116Z] GC before operation: completed in 70.128 ms, heap usage 87.099 MB -> 50.553 MB.
[2024-08-09T22:29:30.071Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T22:29:32.002Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T22:29:33.933Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T22:29:35.862Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T22:29:36.802Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T22:29:37.741Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T22:29:39.673Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T22:29:40.615Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T22:29:40.616Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-09T22:29:40.616Z] The best model improves the baseline by 14.52%.
[2024-08-09T22:29:40.616Z] Movies recommended for you:
[2024-08-09T22:29:40.616Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T22:29:40.616Z] There is no way to check that no silent failure occurred.
[2024-08-09T22:29:40.616Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (13218.515 ms) ======
[2024-08-09T22:29:40.616Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-09T22:29:41.555Z] GC before operation: completed in 98.295 ms, heap usage 259.471 MB -> 54.151 MB.
[2024-08-09T22:29:43.482Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T22:29:45.410Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T22:29:47.338Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T22:29:49.301Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T22:29:50.241Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T22:29:51.182Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T22:29:53.112Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T22:29:54.057Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T22:29:54.057Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-09T22:29:54.057Z] The best model improves the baseline by 14.52%.
[2024-08-09T22:29:54.057Z] Movies recommended for you:
[2024-08-09T22:29:54.057Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T22:29:54.057Z] There is no way to check that no silent failure occurred.
[2024-08-09T22:29:54.057Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (13337.776 ms) ======
[2024-08-09T22:29:54.057Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-09T22:29:54.057Z] GC before operation: completed in 79.970 ms, heap usage 479.138 MB -> 56.901 MB.
[2024-08-09T22:29:56.049Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T22:29:57.977Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T22:29:59.905Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T22:30:01.835Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T22:30:03.781Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T22:30:04.720Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T22:30:05.658Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T22:30:06.626Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T22:30:07.568Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-09T22:30:07.568Z] The best model improves the baseline by 14.52%.
[2024-08-09T22:30:07.568Z] Movies recommended for you:
[2024-08-09T22:30:07.569Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T22:30:07.569Z] There is no way to check that no silent failure occurred.
[2024-08-09T22:30:07.569Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (12778.380 ms) ======
[2024-08-09T22:30:07.569Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-09T22:30:07.569Z] GC before operation: completed in 71.827 ms, heap usage 413.315 MB -> 54.345 MB.
[2024-08-09T22:30:09.499Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T22:30:11.470Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T22:30:13.566Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T22:30:15.501Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T22:30:16.440Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T22:30:17.378Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T22:30:18.317Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T22:30:19.260Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T22:30:20.201Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-09T22:30:20.201Z] The best model improves the baseline by 14.52%.
[2024-08-09T22:30:20.201Z] Movies recommended for you:
[2024-08-09T22:30:20.201Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T22:30:20.201Z] There is no way to check that no silent failure occurred.
[2024-08-09T22:30:20.201Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (12724.213 ms) ======
[2024-08-09T22:30:20.201Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-09T22:30:20.201Z] GC before operation: completed in 69.539 ms, heap usage 195.204 MB -> 53.319 MB.
[2024-08-09T22:30:22.132Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T22:30:24.058Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T22:30:25.986Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T22:30:27.913Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T22:30:28.885Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T22:30:29.826Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T22:30:31.757Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T22:30:32.698Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T22:30:32.698Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-09T22:30:32.698Z] The best model improves the baseline by 14.52%.
[2024-08-09T22:30:32.698Z] Movies recommended for you:
[2024-08-09T22:30:32.698Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T22:30:32.698Z] There is no way to check that no silent failure occurred.
[2024-08-09T22:30:32.698Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (12606.388 ms) ======
[2024-08-09T22:30:32.698Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-09T22:30:32.698Z] GC before operation: completed in 61.990 ms, heap usage 292.564 MB -> 50.861 MB.
[2024-08-09T22:30:34.624Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T22:30:36.552Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T22:30:38.480Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T22:30:40.409Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T22:30:41.349Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T22:30:43.279Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T22:30:44.218Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T22:30:45.157Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T22:30:46.125Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-09T22:30:46.125Z] The best model improves the baseline by 14.52%.
[2024-08-09T22:30:46.125Z] Movies recommended for you:
[2024-08-09T22:30:46.125Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T22:30:46.125Z] There is no way to check that no silent failure occurred.
[2024-08-09T22:30:46.125Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (12999.493 ms) ======
[2024-08-09T22:30:46.125Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-09T22:30:46.125Z] GC before operation: completed in 68.124 ms, heap usage 174.949 MB -> 50.884 MB.
[2024-08-09T22:30:48.052Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T22:30:50.617Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T22:30:52.118Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T22:30:54.060Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T22:30:55.004Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T22:30:56.932Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T22:30:57.872Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T22:30:58.813Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T22:30:59.767Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-09T22:30:59.767Z] The best model improves the baseline by 14.52%.
[2024-08-09T22:30:59.767Z] Movies recommended for you:
[2024-08-09T22:30:59.767Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T22:30:59.767Z] There is no way to check that no silent failure occurred.
[2024-08-09T22:30:59.767Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (13559.266 ms) ======
[2024-08-09T22:30:59.767Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-09T22:30:59.767Z] GC before operation: completed in 70.863 ms, heap usage 227.568 MB -> 51.125 MB.
[2024-08-09T22:31:01.694Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T22:31:03.633Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T22:31:05.564Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T22:31:07.505Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T22:31:08.443Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T22:31:09.382Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T22:31:11.313Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T22:31:12.253Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T22:31:12.253Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-09T22:31:12.253Z] The best model improves the baseline by 14.52%.
[2024-08-09T22:31:12.253Z] Movies recommended for you:
[2024-08-09T22:31:12.253Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T22:31:12.253Z] There is no way to check that no silent failure occurred.
[2024-08-09T22:31:12.253Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (12905.162 ms) ======
[2024-08-09T22:31:12.253Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-09T22:31:12.253Z] GC before operation: completed in 74.771 ms, heap usage 281.620 MB -> 50.906 MB.
[2024-08-09T22:31:14.229Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T22:31:16.160Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T22:31:18.089Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T22:31:20.018Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T22:31:20.957Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T22:31:22.887Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T22:31:23.828Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T22:31:24.785Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T22:31:24.785Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-09T22:31:24.785Z] The best model improves the baseline by 14.52%.
[2024-08-09T22:31:24.785Z] Movies recommended for you:
[2024-08-09T22:31:24.785Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T22:31:24.785Z] There is no way to check that no silent failure occurred.
[2024-08-09T22:31:24.785Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (12736.371 ms) ======
[2024-08-09T22:31:24.785Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-09T22:31:25.727Z] GC before operation: completed in 74.636 ms, heap usage 337.598 MB -> 51.138 MB.
[2024-08-09T22:31:27.659Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T22:31:29.590Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T22:31:31.520Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T22:31:33.471Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T22:31:35.414Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T22:31:36.354Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T22:31:37.293Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T22:31:38.236Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T22:31:39.174Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-09T22:31:39.174Z] The best model improves the baseline by 14.52%.
[2024-08-09T22:31:39.174Z] Movies recommended for you:
[2024-08-09T22:31:39.174Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T22:31:39.174Z] There is no way to check that no silent failure occurred.
[2024-08-09T22:31:39.174Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (13708.733 ms) ======
[2024-08-09T22:31:39.174Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-09T22:31:39.174Z] GC before operation: completed in 71.675 ms, heap usage 231.140 MB -> 54.745 MB.
[2024-08-09T22:31:41.106Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T22:31:43.036Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T22:31:44.975Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T22:31:46.904Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T22:31:47.843Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T22:31:49.772Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T22:31:50.712Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T22:31:51.655Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T22:31:51.655Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-09T22:31:51.655Z] The best model improves the baseline by 14.52%.
[2024-08-09T22:31:51.655Z] Movies recommended for you:
[2024-08-09T22:31:51.655Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T22:31:51.655Z] There is no way to check that no silent failure occurred.
[2024-08-09T22:31:51.655Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (13006.927 ms) ======
[2024-08-09T22:31:51.655Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-09T22:31:52.594Z] GC before operation: completed in 75.451 ms, heap usage 649.736 MB -> 56.863 MB.
[2024-08-09T22:31:54.560Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T22:31:56.498Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T22:31:58.466Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T22:32:00.408Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T22:32:01.358Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T22:32:02.298Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T22:32:04.242Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T22:32:05.183Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T22:32:05.183Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-09T22:32:05.183Z] The best model improves the baseline by 14.52%.
[2024-08-09T22:32:05.183Z] Movies recommended for you:
[2024-08-09T22:32:05.183Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T22:32:05.183Z] There is no way to check that no silent failure occurred.
[2024-08-09T22:32:05.183Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (13114.906 ms) ======
[2024-08-09T22:32:05.183Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-09T22:32:05.183Z] GC before operation: completed in 90.327 ms, heap usage 208.485 MB -> 52.889 MB.
[2024-08-09T22:32:07.121Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T22:32:09.056Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T22:32:10.985Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T22:32:12.915Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T22:32:14.846Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T22:32:15.786Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T22:32:16.725Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T22:32:18.655Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T22:32:18.655Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-09T22:32:18.655Z] The best model improves the baseline by 14.52%.
[2024-08-09T22:32:18.655Z] Movies recommended for you:
[2024-08-09T22:32:18.655Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T22:32:18.655Z] There is no way to check that no silent failure occurred.
[2024-08-09T22:32:18.655Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (13262.855 ms) ======
[2024-08-09T22:32:18.655Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-09T22:32:18.655Z] GC before operation: completed in 90.815 ms, heap usage 159.285 MB -> 54.872 MB.
[2024-08-09T22:32:20.706Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-09T22:32:22.633Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-09T22:32:24.561Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-09T22:32:26.489Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-09T22:32:27.430Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-09T22:32:28.369Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-09T22:32:30.300Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-09T22:32:31.241Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-09T22:32:31.241Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-09T22:32:31.241Z] The best model improves the baseline by 14.52%.
[2024-08-09T22:32:31.241Z] Movies recommended for you:
[2024-08-09T22:32:31.241Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-09T22:32:31.241Z] There is no way to check that no silent failure occurred.
[2024-08-09T22:32:31.241Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (12901.777 ms) ======
[2024-08-09T22:32:32.179Z] -----------------------------------
[2024-08-09T22:32:32.179Z] renaissance-movie-lens_0_PASSED
[2024-08-09T22:32:32.179Z] -----------------------------------
[2024-08-09T22:32:32.179Z]
[2024-08-09T22:32:32.179Z] TEST TEARDOWN:
[2024-08-09T22:32:32.179Z] Nothing to be done for teardown.
[2024-08-09T22:32:32.179Z] renaissance-movie-lens_0 Finish Time: Fri Aug 9 22:32:31 2024 Epoch Time (ms): 1723242751713