renaissance-movie-lens_0
[2024-08-01T21:58:11.199Z] Running test renaissance-movie-lens_0 ...
[2024-08-01T21:58:11.199Z] ===============================================
[2024-08-01T21:58:11.199Z] renaissance-movie-lens_0 Start Time: Thu Aug 1 21:58:10 2024 Epoch Time (ms): 1722549490366
[2024-08-01T21:58:11.199Z] variation: NoOptions
[2024-08-01T21:58:11.199Z] JVM_OPTIONS:
[2024-08-01T21:58:11.199Z] { \
[2024-08-01T21:58:11.199Z] echo ""; echo "TEST SETUP:"; \
[2024-08-01T21:58:11.199Z] echo "Nothing to be done for setup."; \
[2024-08-01T21:58:11.199Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17225485449689/renaissance-movie-lens_0"; \
[2024-08-01T21:58:11.199Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17225485449689/renaissance-movie-lens_0"; \
[2024-08-01T21:58:11.199Z] echo ""; echo "TESTING:"; \
[2024-08-01T21:58:11.199Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux_testList_0/jdkbinary/j2sdk-image/bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17225485449689/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-01T21:58:11.199Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17225485449689/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-01T21:58:11.199Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-01T21:58:11.199Z] echo "Nothing to be done for teardown."; \
[2024-08-01T21:58:11.199Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17225485449689/TestTargetResult";
[2024-08-01T21:58:11.199Z]
[2024-08-01T21:58:11.199Z] TEST SETUP:
[2024-08-01T21:58:11.199Z] Nothing to be done for setup.
[2024-08-01T21:58:11.199Z]
[2024-08-01T21:58:11.199Z] TESTING:
[2024-08-01T21:58:14.148Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-01T21:58:17.652Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-08-01T21:58:21.737Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-01T21:58:22.665Z] Training: 60056, validation: 20285, test: 19854
[2024-08-01T21:58:22.665Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-01T21:58:22.666Z] GC before operation: completed in 217.620 ms, heap usage 54.045 MB -> 25.751 MB.
[2024-08-01T21:58:29.229Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T21:58:33.289Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T21:58:36.245Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T21:58:39.944Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T21:58:41.492Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T21:58:42.421Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T21:58:44.332Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T21:58:46.239Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T21:58:46.239Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-01T21:58:46.239Z] The best model improves the baseline by 14.52%.
[2024-08-01T21:58:47.167Z] Movies recommended for you:
[2024-08-01T21:58:47.167Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T21:58:47.167Z] There is no way to check that no silent failure occurred.
[2024-08-01T21:58:47.167Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (23971.054 ms) ======
[2024-08-01T21:58:47.167Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-01T21:58:47.167Z] GC before operation: completed in 338.053 ms, heap usage 329.611 MB -> 46.940 MB.
[2024-08-01T21:58:50.149Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T21:58:52.067Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T21:58:55.015Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T21:58:57.962Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T21:58:59.877Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T21:59:00.809Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T21:59:02.721Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T21:59:04.647Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T21:59:04.647Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-01T21:59:04.647Z] The best model improves the baseline by 14.52%.
[2024-08-01T21:59:04.647Z] Movies recommended for you:
[2024-08-01T21:59:04.647Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T21:59:04.647Z] There is no way to check that no silent failure occurred.
[2024-08-01T21:59:04.647Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17820.654 ms) ======
[2024-08-01T21:59:04.647Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-01T21:59:05.579Z] GC before operation: completed in 211.961 ms, heap usage 166.565 MB -> 43.891 MB.
[2024-08-01T21:59:07.488Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T21:59:10.456Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T21:59:13.405Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T21:59:15.313Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T21:59:17.231Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T21:59:18.160Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T21:59:20.073Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T21:59:21.981Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T21:59:21.981Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-01T21:59:21.981Z] The best model improves the baseline by 14.52%.
[2024-08-01T21:59:21.981Z] Movies recommended for you:
[2024-08-01T21:59:21.981Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T21:59:21.981Z] There is no way to check that no silent failure occurred.
[2024-08-01T21:59:21.981Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16906.819 ms) ======
[2024-08-01T21:59:21.981Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-01T21:59:21.981Z] GC before operation: completed in 228.324 ms, heap usage 296.548 MB -> 41.580 MB.
[2024-08-01T21:59:24.929Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T21:59:26.842Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T21:59:29.792Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T21:59:32.746Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T21:59:33.676Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T21:59:35.593Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T21:59:36.537Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T21:59:38.448Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T21:59:38.448Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-01T21:59:38.448Z] The best model improves the baseline by 14.52%.
[2024-08-01T21:59:38.448Z] Movies recommended for you:
[2024-08-01T21:59:38.448Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T21:59:38.448Z] There is no way to check that no silent failure occurred.
[2024-08-01T21:59:38.448Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16548.146 ms) ======
[2024-08-01T21:59:38.448Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-01T21:59:39.379Z] GC before operation: completed in 206.299 ms, heap usage 336.301 MB -> 42.145 MB.
[2024-08-01T21:59:41.289Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T21:59:44.262Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T21:59:46.172Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T21:59:48.151Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T21:59:50.020Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T21:59:51.937Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T21:59:52.868Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T21:59:54.782Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T21:59:54.782Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-01T21:59:54.782Z] The best model improves the baseline by 14.52%.
[2024-08-01T21:59:54.782Z] Movies recommended for you:
[2024-08-01T21:59:54.782Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T21:59:54.782Z] There is no way to check that no silent failure occurred.
[2024-08-01T21:59:54.782Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15985.357 ms) ======
[2024-08-01T21:59:54.782Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-01T21:59:54.782Z] GC before operation: completed in 221.196 ms, heap usage 335.645 MB -> 45.554 MB.
[2024-08-01T21:59:57.733Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T21:59:59.657Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T22:00:02.678Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T22:00:04.596Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T22:00:05.526Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T22:00:07.486Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T22:00:08.420Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T22:00:10.391Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T22:00:10.391Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-01T22:00:10.391Z] The best model improves the baseline by 14.52%.
[2024-08-01T22:00:10.391Z] Movies recommended for you:
[2024-08-01T22:00:10.391Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T22:00:10.391Z] There is no way to check that no silent failure occurred.
[2024-08-01T22:00:10.391Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15510.761 ms) ======
[2024-08-01T22:00:10.391Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-01T22:00:11.321Z] GC before operation: completed in 207.714 ms, heap usage 133.155 MB -> 44.921 MB.
[2024-08-01T22:00:13.233Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T22:00:15.163Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T22:00:18.152Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T22:00:20.063Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T22:00:20.994Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T22:00:22.903Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T22:00:23.833Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T22:00:25.743Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T22:00:25.743Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-01T22:00:25.743Z] The best model improves the baseline by 14.52%.
[2024-08-01T22:00:25.743Z] Movies recommended for you:
[2024-08-01T22:00:25.743Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T22:00:25.743Z] There is no way to check that no silent failure occurred.
[2024-08-01T22:00:25.743Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15098.299 ms) ======
[2024-08-01T22:00:25.743Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-01T22:00:26.676Z] GC before operation: completed in 233.861 ms, heap usage 142.529 MB -> 70.204 MB.
[2024-08-01T22:00:28.585Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T22:00:30.495Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T22:00:33.446Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T22:00:35.355Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T22:00:36.285Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T22:00:38.198Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T22:00:39.126Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T22:00:41.034Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T22:00:41.034Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-01T22:00:41.034Z] The best model improves the baseline by 14.52%.
[2024-08-01T22:00:41.034Z] Movies recommended for you:
[2024-08-01T22:00:41.034Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T22:00:41.035Z] There is no way to check that no silent failure occurred.
[2024-08-01T22:00:41.035Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (14845.973 ms) ======
[2024-08-01T22:00:41.035Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-01T22:00:41.035Z] GC before operation: completed in 212.374 ms, heap usage 164.893 MB -> 70.512 MB.
[2024-08-01T22:00:44.001Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T22:00:45.913Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T22:00:47.820Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T22:00:50.807Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T22:00:51.735Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T22:00:52.664Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T22:00:55.757Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T22:00:56.688Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T22:00:56.688Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-01T22:00:56.688Z] The best model improves the baseline by 14.52%.
[2024-08-01T22:00:56.688Z] Movies recommended for you:
[2024-08-01T22:00:56.688Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T22:00:56.688Z] There is no way to check that no silent failure occurred.
[2024-08-01T22:00:56.688Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15544.785 ms) ======
[2024-08-01T22:00:56.688Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-01T22:00:56.688Z] GC before operation: completed in 168.233 ms, heap usage 121.327 MB -> 45.218 MB.
[2024-08-01T22:00:59.637Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T22:01:01.548Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T22:01:03.512Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T22:01:06.461Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T22:01:07.392Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T22:01:08.322Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T22:01:10.231Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T22:01:11.326Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T22:01:12.257Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-01T22:01:12.257Z] The best model improves the baseline by 14.52%.
[2024-08-01T22:01:12.257Z] Movies recommended for you:
[2024-08-01T22:01:12.257Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T22:01:12.257Z] There is no way to check that no silent failure occurred.
[2024-08-01T22:01:12.257Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14958.425 ms) ======
[2024-08-01T22:01:12.257Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-01T22:01:12.257Z] GC before operation: completed in 278.276 ms, heap usage 139.598 MB -> 70.531 MB.
[2024-08-01T22:01:14.302Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T22:01:16.253Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T22:01:19.296Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T22:01:21.208Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T22:01:22.140Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T22:01:24.058Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T22:01:24.991Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T22:01:27.026Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T22:01:27.026Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-01T22:01:27.026Z] The best model improves the baseline by 14.52%.
[2024-08-01T22:01:27.026Z] Movies recommended for you:
[2024-08-01T22:01:27.026Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T22:01:27.026Z] There is no way to check that no silent failure occurred.
[2024-08-01T22:01:27.026Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14620.182 ms) ======
[2024-08-01T22:01:27.026Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-01T22:01:27.026Z] GC before operation: completed in 205.193 ms, heap usage 158.695 MB -> 70.143 MB.
[2024-08-01T22:01:28.941Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T22:01:31.915Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T22:01:33.824Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T22:01:35.736Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T22:01:37.668Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T22:01:38.599Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T22:01:39.527Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T22:01:41.467Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T22:01:41.467Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-01T22:01:41.467Z] The best model improves the baseline by 14.52%.
[2024-08-01T22:01:41.467Z] Movies recommended for you:
[2024-08-01T22:01:41.467Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T22:01:41.467Z] There is no way to check that no silent failure occurred.
[2024-08-01T22:01:41.467Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14459.516 ms) ======
[2024-08-01T22:01:41.467Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-01T22:01:41.467Z] GC before operation: completed in 236.138 ms, heap usage 167.318 MB -> 70.389 MB.
[2024-08-01T22:01:44.435Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T22:01:47.253Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T22:01:48.224Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T22:01:50.134Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T22:01:52.046Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T22:01:52.979Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T22:01:54.894Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T22:01:55.826Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T22:01:55.826Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-01T22:01:55.826Z] The best model improves the baseline by 14.52%.
[2024-08-01T22:01:55.826Z] Movies recommended for you:
[2024-08-01T22:01:55.826Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T22:01:55.826Z] There is no way to check that no silent failure occurred.
[2024-08-01T22:01:55.826Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (14311.478 ms) ======
[2024-08-01T22:01:55.826Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-01T22:01:56.755Z] GC before operation: completed in 216.178 ms, heap usage 168.906 MB -> 70.568 MB.
[2024-08-01T22:01:58.747Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T22:02:00.663Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T22:02:02.671Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T22:02:04.733Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T22:02:06.641Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T22:02:07.579Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T22:02:08.509Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T22:02:10.420Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T22:02:10.420Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-01T22:02:10.420Z] The best model improves the baseline by 14.52%.
[2024-08-01T22:02:10.420Z] Movies recommended for you:
[2024-08-01T22:02:10.420Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T22:02:10.420Z] There is no way to check that no silent failure occurred.
[2024-08-01T22:02:10.420Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14287.866 ms) ======
[2024-08-01T22:02:10.420Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-01T22:02:10.420Z] GC before operation: completed in 217.439 ms, heap usage 161.434 MB -> 70.338 MB.
[2024-08-01T22:02:13.393Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T22:02:15.301Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T22:02:17.209Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T22:02:19.177Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T22:02:21.087Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T22:02:22.016Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T22:02:23.925Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T22:02:24.855Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T22:02:24.855Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-01T22:02:24.855Z] The best model improves the baseline by 14.52%.
[2024-08-01T22:02:24.855Z] Movies recommended for you:
[2024-08-01T22:02:24.855Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T22:02:24.855Z] There is no way to check that no silent failure occurred.
[2024-08-01T22:02:24.855Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14392.585 ms) ======
[2024-08-01T22:02:24.855Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-01T22:02:25.813Z] GC before operation: completed in 222.919 ms, heap usage 162.933 MB -> 70.464 MB.
[2024-08-01T22:02:27.722Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T22:02:29.801Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T22:02:31.710Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T22:02:34.660Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T22:02:35.588Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T22:02:36.518Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T22:02:38.472Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T22:02:39.403Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T22:02:39.403Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-01T22:02:39.403Z] The best model improves the baseline by 14.52%.
[2024-08-01T22:02:40.331Z] Movies recommended for you:
[2024-08-01T22:02:40.331Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T22:02:40.331Z] There is no way to check that no silent failure occurred.
[2024-08-01T22:02:40.331Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14439.555 ms) ======
[2024-08-01T22:02:40.331Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-01T22:02:40.331Z] GC before operation: completed in 209.187 ms, heap usage 165.546 MB -> 70.610 MB.
[2024-08-01T22:02:42.267Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T22:02:44.176Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T22:02:48.168Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T22:02:49.106Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T22:02:50.037Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T22:02:50.968Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T22:02:52.880Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T22:02:53.810Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T22:02:54.741Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-01T22:02:54.741Z] The best model improves the baseline by 14.52%.
[2024-08-01T22:02:54.741Z] Movies recommended for you:
[2024-08-01T22:02:54.741Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T22:02:54.741Z] There is no way to check that no silent failure occurred.
[2024-08-01T22:02:54.741Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14362.212 ms) ======
[2024-08-01T22:02:54.741Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-01T22:02:54.741Z] GC before operation: completed in 246.123 ms, heap usage 194.898 MB -> 70.578 MB.
[2024-08-01T22:02:56.652Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T22:02:58.562Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T22:03:01.510Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T22:03:03.419Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T22:03:04.348Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T22:03:06.256Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T22:03:07.186Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T22:03:08.115Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T22:03:09.045Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-01T22:03:09.045Z] The best model improves the baseline by 14.52%.
[2024-08-01T22:03:09.045Z] Movies recommended for you:
[2024-08-01T22:03:09.045Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T22:03:09.045Z] There is no way to check that no silent failure occurred.
[2024-08-01T22:03:09.045Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14148.940 ms) ======
[2024-08-01T22:03:09.045Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-01T22:03:09.045Z] GC before operation: completed in 233.855 ms, heap usage 165.610 MB -> 70.489 MB.
[2024-08-01T22:03:10.957Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T22:03:13.907Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T22:03:15.817Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T22:03:17.862Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T22:03:18.792Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T22:03:19.722Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T22:03:21.631Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T22:03:22.564Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T22:03:22.564Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-01T22:03:22.564Z] The best model improves the baseline by 14.52%.
[2024-08-01T22:03:22.564Z] Movies recommended for you:
[2024-08-01T22:03:22.564Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T22:03:22.564Z] There is no way to check that no silent failure occurred.
[2024-08-01T22:03:22.564Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (13876.712 ms) ======
[2024-08-01T22:03:22.564Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-01T22:03:23.494Z] GC before operation: completed in 190.236 ms, heap usage 185.666 MB -> 70.807 MB.
[2024-08-01T22:03:25.403Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T22:03:27.310Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T22:03:29.218Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T22:03:31.127Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T22:03:33.035Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T22:03:33.965Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T22:03:34.895Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T22:03:36.804Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T22:03:36.804Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-08-01T22:03:36.804Z] The best model improves the baseline by 14.52%.
[2024-08-01T22:03:36.804Z] Movies recommended for you:
[2024-08-01T22:03:36.804Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T22:03:36.804Z] There is no way to check that no silent failure occurred.
[2024-08-01T22:03:36.804Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (13706.189 ms) ======
[2024-08-01T22:03:37.735Z] -----------------------------------
[2024-08-01T22:03:37.735Z] renaissance-movie-lens_0_PASSED
[2024-08-01T22:03:37.735Z] -----------------------------------
[2024-08-01T22:03:37.735Z]
[2024-08-01T22:03:37.735Z] TEST TEARDOWN:
[2024-08-01T22:03:37.735Z] Nothing to be done for teardown.
[2024-08-01T22:03:37.735Z] renaissance-movie-lens_0 Finish Time: Thu Aug 1 22:03:36 2024 Epoch Time (ms): 1722549816974