renaissance-movie-lens_0
[2024-09-06T06:51:21.267Z] Running test renaissance-movie-lens_0 ...
[2024-09-06T06:51:21.267Z] ===============================================
[2024-09-06T06:51:21.267Z] renaissance-movie-lens_0 Start Time: Fri Sep 6 02:32:49 2024 Epoch Time (ms): 1725607969978
[2024-09-06T06:51:21.267Z] variation: NoOptions
[2024-09-06T06:51:21.881Z] JVM_OPTIONS:
[2024-09-06T06:51:21.881Z] { \
[2024-09-06T06:51:21.881Z] echo ""; echo "TEST SETUP:"; \
[2024-09-06T06:51:21.881Z] echo "Nothing to be done for setup."; \
[2024-09-06T06:51:21.881Z] mkdir -p "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris_rerun/aqa-tests/TKG/../TKG/output_17256079698271/renaissance-movie-lens_0"; \
[2024-09-06T06:51:21.881Z] cd "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris_rerun/aqa-tests/TKG/../TKG/output_17256079698271/renaissance-movie-lens_0"; \
[2024-09-06T06:51:21.881Z] echo ""; echo "TESTING:"; \
[2024-09-06T06:51:21.881Z] "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris_rerun/jdkbinary/j2sdk-image/bin/java" -jar "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris_rerun/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris_rerun/aqa-tests/TKG/../TKG/output_17256079698271/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-09-06T06:51:21.881Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris_rerun/aqa-tests/TKG/..; rm -f -r "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris_rerun/aqa-tests/TKG/../TKG/output_17256079698271/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-09-06T06:51:21.881Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-09-06T06:51:21.881Z] echo "Nothing to be done for teardown."; \
[2024-09-06T06:51:21.881Z] } 2>&1 | tee -a "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_sparcv9_solaris_rerun/aqa-tests/TKG/../TKG/output_17256079698271/TestTargetResult";
[2024-09-06T06:51:21.881Z]
[2024-09-06T06:51:21.881Z] TEST SETUP:
[2024-09-06T06:51:21.881Z] Nothing to be done for setup.
[2024-09-06T06:51:21.881Z]
[2024-09-06T06:51:21.881Z] TESTING:
[2024-09-06T06:51:30.351Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-09-06T06:51:35.019Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-09-06T06:51:49.983Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-09-06T06:51:49.983Z] Training: 60056, validation: 20285, test: 19854
[2024-09-06T06:51:49.983Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-09-06T06:51:49.983Z] GC before operation: completed in 557.486 ms, heap usage 79.524 MB -> 27.390 MB.
[2024-09-06T06:52:04.000Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T06:52:14.163Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T06:52:26.416Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T06:52:36.586Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T06:52:40.280Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T06:52:43.972Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T06:52:49.755Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T06:52:53.442Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T06:52:54.057Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-09-06T06:52:54.673Z] The best model improves the baseline by 14.52%.
[2024-09-06T06:52:55.287Z] Movies recommended for you:
[2024-09-06T06:52:55.287Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T06:52:55.287Z] There is no way to check that no silent failure occurred.
[2024-09-06T06:52:55.287Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (68319.871 ms) ======
[2024-09-06T06:52:55.287Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-09-06T06:52:55.901Z] GC before operation: completed in 636.065 ms, heap usage 333.134 MB -> 49.477 MB.
[2024-09-06T06:53:02.959Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T06:53:10.000Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T06:53:17.043Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T06:53:22.818Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T06:53:27.491Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T06:53:31.175Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T06:53:35.847Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T06:53:40.525Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T06:53:41.139Z] 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.
[2024-09-06T06:53:41.139Z] The best model improves the baseline by 14.52%.
[2024-09-06T06:53:41.139Z] Movies recommended for you:
[2024-09-06T06:53:41.139Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T06:53:41.139Z] There is no way to check that no silent failure occurred.
[2024-09-06T06:53:41.139Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (45557.298 ms) ======
[2024-09-06T06:53:41.139Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-09-06T06:53:41.750Z] GC before operation: completed in 526.394 ms, heap usage 194.346 MB -> 42.632 MB.
[2024-09-06T06:53:48.789Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T06:53:54.565Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T06:54:01.599Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T06:54:07.411Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T06:54:11.093Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T06:54:15.767Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T06:54:19.444Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T06:54:23.136Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T06:54:23.750Z] 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.
[2024-09-06T06:54:23.750Z] The best model improves the baseline by 14.52%.
[2024-09-06T06:54:23.750Z] Movies recommended for you:
[2024-09-06T06:54:23.750Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T06:54:23.750Z] There is no way to check that no silent failure occurred.
[2024-09-06T06:54:24.363Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (42252.660 ms) ======
[2024-09-06T06:54:24.363Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-09-06T06:54:24.363Z] GC before operation: completed in 496.794 ms, heap usage 108.971 MB -> 42.552 MB.
[2024-09-06T06:54:31.399Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T06:54:37.174Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T06:54:44.220Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T06:54:50.000Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T06:54:55.867Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T06:54:58.667Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T06:55:02.349Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T06:55:06.023Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T06:55:06.636Z] 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.
[2024-09-06T06:55:06.636Z] The best model improves the baseline by 14.52%.
[2024-09-06T06:55:07.248Z] Movies recommended for you:
[2024-09-06T06:55:07.248Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T06:55:07.248Z] There is no way to check that no silent failure occurred.
[2024-09-06T06:55:07.248Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (42397.694 ms) ======
[2024-09-06T06:55:07.248Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-09-06T06:55:07.248Z] GC before operation: completed in 457.687 ms, heap usage 67.465 MB -> 46.556 MB.
[2024-09-06T06:55:14.284Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T06:55:20.056Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T06:55:27.090Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T06:55:32.872Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T06:55:36.572Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T06:55:41.243Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T06:55:44.923Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T06:55:48.608Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T06:55:48.608Z] 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.
[2024-09-06T06:55:48.608Z] The best model improves the baseline by 14.52%.
[2024-09-06T06:55:49.229Z] Movies recommended for you:
[2024-09-06T06:55:49.229Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T06:55:49.229Z] There is no way to check that no silent failure occurred.
[2024-09-06T06:55:49.229Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (41835.944 ms) ======
[2024-09-06T06:55:49.229Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-09-06T06:55:49.843Z] GC before operation: completed in 460.501 ms, heap usage 89.886 MB -> 47.880 MB.
[2024-09-06T06:55:55.616Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T06:56:01.418Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T06:56:07.198Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T06:56:12.972Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T06:56:16.656Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T06:56:20.470Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T06:56:24.155Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T06:56:27.923Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T06:56:27.923Z] 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.
[2024-09-06T06:56:28.537Z] The best model improves the baseline by 14.52%.
[2024-09-06T06:56:28.537Z] Movies recommended for you:
[2024-09-06T06:56:28.537Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T06:56:28.537Z] There is no way to check that no silent failure occurred.
[2024-09-06T06:56:28.537Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (38789.563 ms) ======
[2024-09-06T06:56:28.537Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-09-06T06:56:29.150Z] GC before operation: completed in 438.495 ms, heap usage 157.503 MB -> 43.320 MB.
[2024-09-06T06:56:34.929Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T06:56:40.721Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T06:56:46.502Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T06:56:52.285Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T06:56:55.969Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T06:56:58.771Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T06:57:03.434Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T06:57:06.230Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T06:57:06.847Z] 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.
[2024-09-06T06:57:06.847Z] The best model improves the baseline by 14.52%.
[2024-09-06T06:57:07.459Z] Movies recommended for you:
[2024-09-06T06:57:07.459Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T06:57:07.459Z] There is no way to check that no silent failure occurred.
[2024-09-06T06:57:07.459Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (38394.836 ms) ======
[2024-09-06T06:57:07.459Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-09-06T06:57:07.459Z] GC before operation: completed in 371.147 ms, heap usage 116.799 MB -> 43.275 MB.
[2024-09-06T06:57:13.234Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T06:57:19.076Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T06:57:25.222Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T06:57:30.301Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T06:57:33.989Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T06:57:37.667Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T06:57:41.357Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T06:57:45.044Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T06:57:45.664Z] 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.
[2024-09-06T06:57:45.664Z] The best model improves the baseline by 14.52%.
[2024-09-06T06:57:46.276Z] Movies recommended for you:
[2024-09-06T06:57:46.276Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T06:57:46.276Z] There is no way to check that no silent failure occurred.
[2024-09-06T06:57:46.276Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (38262.813 ms) ======
[2024-09-06T06:57:46.276Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-09-06T06:57:46.276Z] GC before operation: completed in 367.296 ms, heap usage 100.435 MB -> 46.233 MB.
[2024-09-06T06:57:52.051Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T06:57:57.822Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T06:58:03.598Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T06:58:09.374Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T06:58:13.052Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T06:58:15.849Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T06:58:19.536Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T06:58:23.218Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T06:58:23.831Z] 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.
[2024-09-06T06:58:23.831Z] The best model improves the baseline by 14.52%.
[2024-09-06T06:58:23.831Z] Movies recommended for you:
[2024-09-06T06:58:23.831Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T06:58:23.831Z] There is no way to check that no silent failure occurred.
[2024-09-06T06:58:23.831Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (37608.954 ms) ======
[2024-09-06T06:58:23.831Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-09-06T06:58:24.444Z] GC before operation: completed in 357.983 ms, heap usage 110.680 MB -> 43.370 MB.
[2024-09-06T06:58:30.216Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T06:58:35.995Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T06:58:41.773Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T06:58:47.547Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T06:58:50.350Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T06:58:54.031Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T06:58:57.710Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T06:59:01.394Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T06:59:02.007Z] 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.
[2024-09-06T06:59:02.007Z] The best model improves the baseline by 14.52%.
[2024-09-06T06:59:02.635Z] Movies recommended for you:
[2024-09-06T06:59:02.635Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T06:59:02.635Z] There is no way to check that no silent failure occurred.
[2024-09-06T06:59:02.635Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (37999.146 ms) ======
[2024-09-06T06:59:02.635Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-09-06T06:59:02.635Z] GC before operation: completed in 529.264 ms, heap usage 89.982 MB -> 43.451 MB.
[2024-09-06T06:59:08.408Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T06:59:14.201Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T06:59:19.975Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T06:59:25.747Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T06:59:29.423Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T06:59:32.228Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T06:59:35.913Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T06:59:39.605Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T06:59:40.219Z] 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.
[2024-09-06T06:59:40.219Z] The best model improves the baseline by 14.52%.
[2024-09-06T06:59:40.219Z] Movies recommended for you:
[2024-09-06T06:59:40.219Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T06:59:40.219Z] There is no way to check that no silent failure occurred.
[2024-09-06T06:59:40.219Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (37523.962 ms) ======
[2024-09-06T06:59:40.219Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-09-06T06:59:40.878Z] GC before operation: completed in 412.364 ms, heap usage 700.281 MB -> 48.395 MB.
[2024-09-06T06:59:46.662Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T06:59:52.439Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T06:59:58.211Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T07:00:03.733Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T07:00:06.923Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T07:00:10.597Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T07:00:14.271Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T07:00:17.944Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T07:00:17.944Z] 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.
[2024-09-06T07:00:17.944Z] The best model improves the baseline by 14.52%.
[2024-09-06T07:00:18.560Z] Movies recommended for you:
[2024-09-06T07:00:18.560Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T07:00:18.561Z] There is no way to check that no silent failure occurred.
[2024-09-06T07:00:18.561Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (37681.013 ms) ======
[2024-09-06T07:00:18.561Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-09-06T07:00:18.561Z] GC before operation: completed in 362.011 ms, heap usage 704.685 MB -> 48.462 MB.
[2024-09-06T07:00:24.329Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T07:00:30.096Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T07:00:35.867Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T07:00:41.638Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T07:00:45.316Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T07:00:48.998Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T07:00:52.686Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T07:00:56.366Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T07:00:56.979Z] 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.
[2024-09-06T07:00:56.979Z] The best model improves the baseline by 14.52%.
[2024-09-06T07:00:56.979Z] Movies recommended for you:
[2024-09-06T07:00:56.979Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T07:00:56.979Z] There is no way to check that no silent failure occurred.
[2024-09-06T07:00:56.979Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (38230.432 ms) ======
[2024-09-06T07:00:56.979Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-09-06T07:00:57.593Z] GC before operation: completed in 391.216 ms, heap usage 704.925 MB -> 48.821 MB.
[2024-09-06T07:01:03.367Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T07:01:09.157Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T07:01:14.935Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T07:01:20.832Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T07:01:23.627Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T07:01:27.308Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T07:01:30.990Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T07:01:34.674Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T07:01:34.674Z] 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.
[2024-09-06T07:01:35.297Z] The best model improves the baseline by 14.52%.
[2024-09-06T07:01:35.297Z] Movies recommended for you:
[2024-09-06T07:01:35.297Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T07:01:35.297Z] There is no way to check that no silent failure occurred.
[2024-09-06T07:01:35.297Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (37810.508 ms) ======
[2024-09-06T07:01:35.297Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-09-06T07:01:35.915Z] GC before operation: completed in 355.745 ms, heap usage 714.284 MB -> 48.368 MB.
[2024-09-06T07:01:41.693Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T07:01:46.374Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T07:01:53.412Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T07:01:58.077Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T07:02:01.759Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T07:02:05.446Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T07:02:09.129Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T07:02:11.932Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T07:02:12.547Z] 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.
[2024-09-06T07:02:12.547Z] The best model improves the baseline by 14.52%.
[2024-09-06T07:02:13.164Z] Movies recommended for you:
[2024-09-06T07:02:13.164Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T07:02:13.164Z] There is no way to check that no silent failure occurred.
[2024-09-06T07:02:13.164Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (37387.468 ms) ======
[2024-09-06T07:02:13.164Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-09-06T07:02:13.164Z] GC before operation: completed in 351.113 ms, heap usage 83.320 MB -> 43.468 MB.
[2024-09-06T07:02:18.940Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T07:02:24.723Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T07:02:30.620Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T07:02:37.001Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T07:02:39.826Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T07:02:43.504Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T07:02:47.188Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T07:02:50.873Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T07:02:51.489Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-09-06T07:02:51.489Z] The best model improves the baseline by 14.52%.
[2024-09-06T07:02:51.489Z] Movies recommended for you:
[2024-09-06T07:02:51.489Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T07:02:51.489Z] There is no way to check that no silent failure occurred.
[2024-09-06T07:02:51.489Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (38344.559 ms) ======
[2024-09-06T07:02:51.489Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-09-06T07:02:52.103Z] GC before operation: completed in 408.579 ms, heap usage 703.470 MB -> 48.832 MB.
[2024-09-06T07:02:57.878Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T07:03:03.651Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T07:03:09.424Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T07:03:15.201Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T07:03:22.164Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T07:03:22.164Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T07:03:25.843Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T07:03:29.524Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T07:03:30.138Z] 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.
[2024-09-06T07:03:30.138Z] The best model improves the baseline by 14.52%.
[2024-09-06T07:03:30.138Z] Movies recommended for you:
[2024-09-06T07:03:30.138Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T07:03:30.138Z] There is no way to check that no silent failure occurred.
[2024-09-06T07:03:30.138Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (38242.684 ms) ======
[2024-09-06T07:03:30.138Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-09-06T07:03:30.753Z] GC before operation: completed in 375.152 ms, heap usage 705.701 MB -> 49.496 MB.
[2024-09-06T07:03:36.558Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T07:03:42.333Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T07:03:48.116Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T07:03:53.894Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T07:03:57.578Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T07:04:00.387Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T07:04:05.051Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T07:04:07.853Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T07:04:08.507Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-09-06T07:04:08.507Z] The best model improves the baseline by 14.52%.
[2024-09-06T07:04:08.507Z] Movies recommended for you:
[2024-09-06T07:04:08.507Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T07:04:08.507Z] There is no way to check that no silent failure occurred.
[2024-09-06T07:04:08.507Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (37955.133 ms) ======
[2024-09-06T07:04:08.507Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-09-06T07:04:09.121Z] GC before operation: completed in 410.360 ms, heap usage 138.996 MB -> 43.562 MB.
[2024-09-06T07:04:14.897Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T07:04:20.677Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T07:04:26.451Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T07:04:32.239Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T07:04:35.037Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T07:04:38.724Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T07:04:42.470Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T07:04:45.271Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T07:04:45.885Z] 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.
[2024-09-06T07:04:46.498Z] The best model improves the baseline by 14.52%.
[2024-09-06T07:04:46.498Z] Movies recommended for you:
[2024-09-06T07:04:46.498Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T07:04:46.498Z] There is no way to check that no silent failure occurred.
[2024-09-06T07:04:46.499Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (37406.379 ms) ======
[2024-09-06T07:04:46.499Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-09-06T07:04:47.118Z] GC before operation: completed in 357.427 ms, heap usage 102.011 MB -> 43.724 MB.
[2024-09-06T07:04:52.891Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T07:04:58.673Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T07:05:04.453Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T07:05:10.226Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T07:05:13.029Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T07:05:16.713Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T07:05:20.602Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T07:05:23.423Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T07:05:24.037Z] 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.
[2024-09-06T07:05:24.037Z] The best model improves the baseline by 14.52%.
[2024-09-06T07:05:24.650Z] Movies recommended for you:
[2024-09-06T07:05:24.650Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T07:05:24.650Z] There is no way to check that no silent failure occurred.
[2024-09-06T07:05:24.650Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (37551.750 ms) ======
[2024-09-06T07:05:25.261Z] -----------------------------------
[2024-09-06T07:05:25.261Z] renaissance-movie-lens_0_PASSED
[2024-09-06T07:05:25.261Z] -----------------------------------
[2024-09-06T07:05:25.261Z]
[2024-09-06T07:05:25.261Z] TEST TEARDOWN:
[2024-09-06T07:05:25.261Z] Nothing to be done for teardown.
[2024-09-06T07:05:25.261Z] renaissance-movie-lens_0 Finish Time: Fri Sep 6 02:46:53 2024 Epoch Time (ms): 1725608813761