renaissance-movie-lens_0
[2024-11-07T23:20:55.488Z] Running test renaissance-movie-lens_0 ...
[2024-11-07T23:20:55.488Z] ===============================================
[2024-11-07T23:20:55.488Z] renaissance-movie-lens_0 Start Time: Thu Nov 7 23:20:55 2024 Epoch Time (ms): 1731021655150
[2024-11-07T23:20:55.488Z] variation: NoOptions
[2024-11-07T23:20:55.488Z] JVM_OPTIONS:
[2024-11-07T23:20:55.488Z] { \
[2024-11-07T23:20:55.488Z] echo ""; echo "TEST SETUP:"; \
[2024-11-07T23:20:55.488Z] echo "Nothing to be done for setup."; \
[2024-11-07T23:20:55.488Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17310206155553/renaissance-movie-lens_0"; \
[2024-11-07T23:20:55.488Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17310206155553/renaissance-movie-lens_0"; \
[2024-11-07T23:20:55.488Z] echo ""; echo "TESTING:"; \
[2024-11-07T23:20:55.488Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/jdkbinary/j2sdk-image/bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17310206155553/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-07T23:20:55.488Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17310206155553/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-07T23:20:55.488Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-07T23:20:55.488Z] echo "Nothing to be done for teardown."; \
[2024-11-07T23:20:55.488Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17310206155553/TestTargetResult";
[2024-11-07T23:20:55.488Z]
[2024-11-07T23:20:55.488Z] TEST SETUP:
[2024-11-07T23:20:55.488Z] Nothing to be done for setup.
[2024-11-07T23:20:55.488Z]
[2024-11-07T23:20:55.488Z] TESTING:
[2024-11-07T23:20:59.563Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-07T23:21:02.491Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-11-07T23:21:06.569Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-07T23:21:07.502Z] Training: 60056, validation: 20285, test: 19854
[2024-11-07T23:21:07.502Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-07T23:21:07.502Z] GC before operation: completed in 228.804 ms, heap usage 134.708 MB -> 25.876 MB.
[2024-11-07T23:21:14.141Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:21:17.115Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:21:21.199Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:21:23.117Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:21:25.041Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:21:26.997Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:21:28.914Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:21:30.833Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:21:30.833Z] 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.
[2024-11-07T23:21:30.833Z] The best model improves the baseline by 14.52%.
[2024-11-07T23:21:30.833Z] Movies recommended for you:
[2024-11-07T23:21:30.833Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:21:30.833Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:21:30.833Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (23568.030 ms) ======
[2024-11-07T23:21:30.833Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-07T23:21:31.775Z] GC before operation: completed in 327.401 ms, heap usage 181.851 MB -> 43.208 MB.
[2024-11-07T23:21:33.691Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:21:36.686Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:21:39.653Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:21:42.627Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:21:43.561Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:21:45.495Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:21:47.417Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:21:49.343Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:21:49.343Z] 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.
[2024-11-07T23:21:49.343Z] The best model improves the baseline by 14.52%.
[2024-11-07T23:21:49.343Z] Movies recommended for you:
[2024-11-07T23:21:49.343Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:21:49.343Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:21:49.343Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (18164.953 ms) ======
[2024-11-07T23:21:49.343Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-07T23:21:49.343Z] GC before operation: completed in 257.883 ms, heap usage 273.128 MB -> 41.150 MB.
[2024-11-07T23:21:52.311Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:21:55.296Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:21:57.232Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:22:00.198Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:22:01.131Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:22:03.051Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:22:03.985Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:22:06.599Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:22:06.599Z] 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.
[2024-11-07T23:22:06.599Z] The best model improves the baseline by 14.52%.
[2024-11-07T23:22:06.599Z] Movies recommended for you:
[2024-11-07T23:22:06.599Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:22:06.599Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:22:06.599Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16579.940 ms) ======
[2024-11-07T23:22:06.599Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-07T23:22:07.711Z] GC before operation: completed in 238.855 ms, heap usage 368.793 MB -> 41.596 MB.
[2024-11-07T23:22:08.646Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:22:11.618Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:22:13.540Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:22:16.504Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:22:17.446Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:22:19.365Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:22:21.286Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:22:22.220Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:22:23.162Z] 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.
[2024-11-07T23:22:23.162Z] The best model improves the baseline by 14.52%.
[2024-11-07T23:22:23.162Z] Movies recommended for you:
[2024-11-07T23:22:23.163Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:22:23.163Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:22:23.163Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16350.216 ms) ======
[2024-11-07T23:22:23.163Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-07T23:22:23.163Z] GC before operation: completed in 170.309 ms, heap usage 84.325 MB -> 41.361 MB.
[2024-11-07T23:22:25.085Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:22:28.068Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:22:29.988Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:22:32.952Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:22:33.892Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:22:35.813Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:22:37.739Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:22:38.675Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:22:38.675Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-07T23:22:38.675Z] The best model improves the baseline by 14.52%.
[2024-11-07T23:22:39.610Z] Movies recommended for you:
[2024-11-07T23:22:39.610Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:22:39.610Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:22:39.610Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16101.382 ms) ======
[2024-11-07T23:22:39.610Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-07T23:22:39.610Z] GC before operation: completed in 191.708 ms, heap usage 107.079 MB -> 43.405 MB.
[2024-11-07T23:22:41.537Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:22:44.504Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:22:46.422Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:22:48.357Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:22:50.272Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:22:52.196Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:22:53.131Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:22:55.050Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:22:55.050Z] 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.
[2024-11-07T23:22:55.050Z] The best model improves the baseline by 14.52%.
[2024-11-07T23:22:55.050Z] Movies recommended for you:
[2024-11-07T23:22:55.050Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:22:55.050Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:22:55.050Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15901.998 ms) ======
[2024-11-07T23:22:55.050Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-07T23:22:55.983Z] GC before operation: completed in 232.595 ms, heap usage 168.805 MB -> 42.015 MB.
[2024-11-07T23:22:57.907Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:22:59.840Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:23:02.809Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:23:04.736Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:23:05.680Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:23:07.599Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:23:08.535Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:23:10.333Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:23:10.333Z] 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.
[2024-11-07T23:23:10.333Z] The best model improves the baseline by 14.52%.
[2024-11-07T23:23:11.322Z] Movies recommended for you:
[2024-11-07T23:23:11.322Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:23:11.322Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:23:11.322Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15194.003 ms) ======
[2024-11-07T23:23:11.322Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-07T23:23:11.322Z] GC before operation: completed in 294.805 ms, heap usage 281.487 MB -> 70.483 MB.
[2024-11-07T23:23:13.246Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:23:15.501Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:23:18.511Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:23:20.428Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:23:22.351Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:23:23.290Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:23:25.212Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:23:26.146Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:23:26.146Z] 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.
[2024-11-07T23:23:26.146Z] The best model improves the baseline by 14.52%.
[2024-11-07T23:23:27.081Z] Movies recommended for you:
[2024-11-07T23:23:27.081Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:23:27.081Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:23:27.081Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15687.193 ms) ======
[2024-11-07T23:23:27.081Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-07T23:23:27.081Z] GC before operation: completed in 193.386 ms, heap usage 406.042 MB -> 60.043 MB.
[2024-11-07T23:23:29.003Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:23:31.975Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:23:33.893Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:23:35.812Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:23:37.902Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:23:38.836Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:23:40.757Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:23:41.691Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:23:42.625Z] 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.
[2024-11-07T23:23:42.625Z] The best model improves the baseline by 14.52%.
[2024-11-07T23:23:42.625Z] Movies recommended for you:
[2024-11-07T23:23:42.625Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:23:42.625Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:23:42.625Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15431.856 ms) ======
[2024-11-07T23:23:42.625Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-07T23:23:42.625Z] GC before operation: completed in 171.580 ms, heap usage 89.476 MB -> 41.969 MB.
[2024-11-07T23:23:44.547Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:23:46.465Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:23:49.441Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:23:51.370Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:23:53.294Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:23:54.229Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:23:56.165Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:23:57.109Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:23:57.109Z] 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.
[2024-11-07T23:23:57.110Z] The best model improves the baseline by 14.52%.
[2024-11-07T23:23:57.110Z] Movies recommended for you:
[2024-11-07T23:23:57.110Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:23:57.110Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:23:57.110Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15006.948 ms) ======
[2024-11-07T23:23:57.110Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-07T23:23:58.046Z] GC before operation: completed in 266.284 ms, heap usage 436.182 MB -> 71.196 MB.
[2024-11-07T23:23:59.964Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:24:01.890Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:24:04.852Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:24:06.771Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:24:07.706Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:24:09.625Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:24:10.672Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:24:12.594Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:24:12.594Z] 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.
[2024-11-07T23:24:12.594Z] The best model improves the baseline by 14.52%.
[2024-11-07T23:24:12.594Z] Movies recommended for you:
[2024-11-07T23:24:12.594Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:24:12.594Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:24:12.594Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15247.999 ms) ======
[2024-11-07T23:24:12.594Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-07T23:24:13.529Z] GC before operation: completed in 199.845 ms, heap usage 123.261 MB -> 41.748 MB.
[2024-11-07T23:24:15.453Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:24:17.376Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:24:20.342Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:24:22.263Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:24:23.198Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:24:25.117Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:24:26.059Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:24:27.981Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:24:27.981Z] 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.
[2024-11-07T23:24:27.981Z] The best model improves the baseline by 14.52%.
[2024-11-07T23:24:27.981Z] Movies recommended for you:
[2024-11-07T23:24:27.981Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:24:27.981Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:24:27.981Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14744.158 ms) ======
[2024-11-07T23:24:27.981Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-07T23:24:27.981Z] GC before operation: completed in 199.427 ms, heap usage 418.061 MB -> 70.825 MB.
[2024-11-07T23:24:30.951Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:24:32.872Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:24:34.796Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:24:36.715Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:24:38.639Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:24:39.574Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:24:41.499Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:24:42.435Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:24:42.435Z] 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.
[2024-11-07T23:24:42.435Z] The best model improves the baseline by 14.52%.
[2024-11-07T23:24:43.368Z] Movies recommended for you:
[2024-11-07T23:24:43.368Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:24:43.368Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:24:43.368Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (14780.291 ms) ======
[2024-11-07T23:24:43.369Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-07T23:24:43.369Z] GC before operation: completed in 199.778 ms, heap usage 430.199 MB -> 71.136 MB.
[2024-11-07T23:24:45.297Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:24:47.911Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:24:50.076Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:24:51.992Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:24:52.926Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:24:54.844Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:24:55.777Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:24:57.694Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:24:57.694Z] 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.
[2024-11-07T23:24:57.694Z] The best model improves the baseline by 14.52%.
[2024-11-07T23:24:57.694Z] Movies recommended for you:
[2024-11-07T23:24:57.694Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:24:57.694Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:24:57.694Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14567.860 ms) ======
[2024-11-07T23:24:57.694Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-07T23:24:57.694Z] GC before operation: completed in 226.583 ms, heap usage 155.983 MB -> 70.152 MB.
[2024-11-07T23:25:00.655Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:25:02.570Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:25:04.488Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:25:06.409Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:25:08.329Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:25:09.286Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:25:11.302Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:25:12.236Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:25:12.236Z] 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.
[2024-11-07T23:25:12.236Z] The best model improves the baseline by 14.52%.
[2024-11-07T23:25:12.236Z] Movies recommended for you:
[2024-11-07T23:25:12.237Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:25:12.237Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:25:12.237Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14554.827 ms) ======
[2024-11-07T23:25:12.237Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-07T23:25:13.170Z] GC before operation: completed in 199.090 ms, heap usage 162.773 MB -> 70.368 MB.
[2024-11-07T23:25:15.092Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:25:17.009Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:25:18.926Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:25:21.896Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:25:22.831Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:25:24.749Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:25:25.683Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:25:27.601Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:25:27.601Z] 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.
[2024-11-07T23:25:27.601Z] The best model improves the baseline by 14.52%.
[2024-11-07T23:25:27.601Z] Movies recommended for you:
[2024-11-07T23:25:27.601Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:25:27.601Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:25:27.601Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14827.808 ms) ======
[2024-11-07T23:25:27.601Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-07T23:25:27.601Z] GC before operation: completed in 198.311 ms, heap usage 171.293 MB -> 70.521 MB.
[2024-11-07T23:25:29.520Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:25:32.489Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:25:34.418Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:25:36.338Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:25:38.263Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:25:39.199Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:25:41.119Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:25:43.075Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:25:43.075Z] 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.
[2024-11-07T23:25:43.075Z] The best model improves the baseline by 14.52%.
[2024-11-07T23:25:43.075Z] Movies recommended for you:
[2024-11-07T23:25:43.075Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:25:43.075Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:25:43.075Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14856.862 ms) ======
[2024-11-07T23:25:43.075Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-07T23:25:43.075Z] GC before operation: completed in 235.655 ms, heap usage 161.753 MB -> 70.449 MB.
[2024-11-07T23:25:44.997Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:25:46.918Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:25:49.883Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:25:51.806Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:25:52.741Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:25:54.663Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:25:55.597Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:25:57.521Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:25:57.521Z] 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.
[2024-11-07T23:25:57.521Z] The best model improves the baseline by 14.52%.
[2024-11-07T23:25:57.521Z] Movies recommended for you:
[2024-11-07T23:25:57.521Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:25:57.521Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:25:57.521Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14734.732 ms) ======
[2024-11-07T23:25:57.521Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-07T23:25:57.521Z] GC before operation: completed in 216.540 ms, heap usage 164.506 MB -> 70.445 MB.
[2024-11-07T23:26:00.502Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:26:02.418Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:26:04.338Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:26:06.269Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:26:08.188Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:26:09.174Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:26:11.111Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:26:12.044Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:26:12.044Z] 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.
[2024-11-07T23:26:12.044Z] The best model improves the baseline by 14.52%.
[2024-11-07T23:26:12.986Z] Movies recommended for you:
[2024-11-07T23:26:12.986Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:26:12.986Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:26:12.986Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14718.221 ms) ======
[2024-11-07T23:26:12.986Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-07T23:26:12.986Z] GC before operation: completed in 208.376 ms, heap usage 190.889 MB -> 70.757 MB.
[2024-11-07T23:26:14.904Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-07T23:26:16.823Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-07T23:26:19.789Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-07T23:26:21.707Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-07T23:26:22.644Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-07T23:26:24.565Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-07T23:26:25.500Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-07T23:26:27.422Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-07T23:26:27.422Z] 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.
[2024-11-07T23:26:27.422Z] The best model improves the baseline by 14.52%.
[2024-11-07T23:26:27.422Z] Movies recommended for you:
[2024-11-07T23:26:27.422Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-07T23:26:27.422Z] There is no way to check that no silent failure occurred.
[2024-11-07T23:26:27.422Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14788.488 ms) ======
[2024-11-07T23:26:28.357Z] -----------------------------------
[2024-11-07T23:26:28.357Z] renaissance-movie-lens_0_PASSED
[2024-11-07T23:26:28.357Z] -----------------------------------
[2024-11-07T23:26:28.357Z]
[2024-11-07T23:26:28.357Z] TEST TEARDOWN:
[2024-11-07T23:26:28.357Z] Nothing to be done for teardown.
[2024-11-07T23:26:28.357Z] renaissance-movie-lens_0 Finish Time: Thu Nov 7 23:26:27 2024 Epoch Time (ms): 1731021987651