renaissance-movie-lens_0
[2025-01-22T03:05:11.010Z] Running test renaissance-movie-lens_0 ...
[2025-01-22T03:05:11.010Z] ===============================================
[2025-01-22T03:05:11.010Z] renaissance-movie-lens_0 Start Time: Wed Jan 22 03:05:09 2025 Epoch Time (ms): 1737515109969
[2025-01-22T03:05:11.010Z] variation: NoOptions
[2025-01-22T03:05:11.010Z] JVM_OPTIONS:
[2025-01-22T03:05:11.010Z] { \
[2025-01-22T03:05:11.010Z] echo ""; echo "TEST SETUP:"; \
[2025-01-22T03:05:11.010Z] echo "Nothing to be done for setup."; \
[2025-01-22T03:05:11.010Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17375139154898/renaissance-movie-lens_0"; \
[2025-01-22T03:05:11.010Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17375139154898/renaissance-movie-lens_0"; \
[2025-01-22T03:05:11.010Z] echo ""; echo "TESTING:"; \
[2025-01-22T03:05:11.010Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/jdkbinary/j2sdk-image/bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17375139154898/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-01-22T03:05:11.010Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17375139154898/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-01-22T03:05:11.010Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-01-22T03:05:11.010Z] echo "Nothing to be done for teardown."; \
[2025-01-22T03:05:11.010Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17375139154898/TestTargetResult";
[2025-01-22T03:05:11.010Z]
[2025-01-22T03:05:11.010Z] TEST SETUP:
[2025-01-22T03:05:11.010Z] Nothing to be done for setup.
[2025-01-22T03:05:11.010Z]
[2025-01-22T03:05:11.010Z] TESTING:
[2025-01-22T03:05:14.290Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-01-22T03:05:17.610Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-01-22T03:05:22.899Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-01-22T03:05:22.899Z] Training: 60056, validation: 20285, test: 19854
[2025-01-22T03:05:22.900Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-01-22T03:05:22.900Z] GC before operation: completed in 225.932 ms, heap usage 135.793 MB -> 26.022 MB.
[2025-01-22T03:05:30.862Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T03:05:35.270Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T03:05:41.457Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T03:05:44.798Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T03:05:47.392Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T03:05:50.779Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T03:05:53.388Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T03:05:55.348Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T03:05:55.823Z] 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.
[2025-01-22T03:05:56.211Z] The best model improves the baseline by 14.52%.
[2025-01-22T03:05:56.211Z] Movies recommended for you:
[2025-01-22T03:05:56.211Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T03:05:56.211Z] There is no way to check that no silent failure occurred.
[2025-01-22T03:05:56.211Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (33473.975 ms) ======
[2025-01-22T03:05:56.211Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-01-22T03:05:56.605Z] GC before operation: completed in 355.833 ms, heap usage 620.028 MB -> 46.577 MB.
[2025-01-22T03:06:00.806Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T03:06:05.040Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T03:06:09.334Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T03:06:12.667Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T03:06:14.017Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T03:06:16.624Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T03:06:18.546Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T03:06:20.455Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T03:06:21.299Z] 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.
[2025-01-22T03:06:21.299Z] The best model improves the baseline by 14.52%.
[2025-01-22T03:06:21.299Z] Movies recommended for you:
[2025-01-22T03:06:21.299Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T03:06:21.299Z] There is no way to check that no silent failure occurred.
[2025-01-22T03:06:21.299Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (24666.044 ms) ======
[2025-01-22T03:06:21.299Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-01-22T03:06:21.687Z] GC before operation: completed in 270.143 ms, heap usage 122.713 MB -> 41.614 MB.
[2025-01-22T03:06:24.245Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T03:06:27.584Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T03:06:30.899Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T03:06:33.459Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T03:06:35.431Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T03:06:36.804Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T03:06:38.722Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T03:06:40.659Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T03:06:41.043Z] 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.
[2025-01-22T03:06:41.043Z] The best model improves the baseline by 14.52%.
[2025-01-22T03:06:41.043Z] Movies recommended for you:
[2025-01-22T03:06:41.043Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T03:06:41.043Z] There is no way to check that no silent failure occurred.
[2025-01-22T03:06:41.043Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (19502.049 ms) ======
[2025-01-22T03:06:41.043Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-01-22T03:06:41.428Z] GC before operation: completed in 250.753 ms, heap usage 447.503 MB -> 45.252 MB.
[2025-01-22T03:06:43.973Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T03:06:47.436Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T03:06:50.722Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T03:06:53.298Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T03:06:55.228Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T03:06:57.166Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T03:06:58.523Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T03:07:00.426Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T03:07:00.827Z] 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.
[2025-01-22T03:07:00.827Z] The best model improves the baseline by 14.52%.
[2025-01-22T03:07:00.827Z] Movies recommended for you:
[2025-01-22T03:07:00.827Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T03:07:00.827Z] There is no way to check that no silent failure occurred.
[2025-01-22T03:07:00.827Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (19583.641 ms) ======
[2025-01-22T03:07:00.827Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-01-22T03:07:01.209Z] GC before operation: completed in 212.070 ms, heap usage 454.333 MB -> 47.019 MB.
[2025-01-22T03:07:04.548Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T03:07:07.183Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T03:07:10.516Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T03:07:13.088Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T03:07:15.655Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T03:07:17.542Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T03:07:19.585Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T03:07:20.936Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T03:07:21.327Z] 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.
[2025-01-22T03:07:21.327Z] The best model improves the baseline by 14.52%.
[2025-01-22T03:07:21.327Z] Movies recommended for you:
[2025-01-22T03:07:21.327Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T03:07:21.327Z] There is no way to check that no silent failure occurred.
[2025-01-22T03:07:21.327Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (20361.833 ms) ======
[2025-01-22T03:07:21.327Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-01-22T03:07:21.713Z] GC before operation: completed in 206.757 ms, heap usage 519.180 MB -> 46.021 MB.
[2025-01-22T03:07:24.248Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T03:07:27.577Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T03:07:30.109Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T03:07:32.669Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T03:07:34.641Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T03:07:35.955Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T03:07:37.833Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T03:07:39.737Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T03:07:39.737Z] 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.
[2025-01-22T03:07:39.737Z] The best model improves the baseline by 14.52%.
[2025-01-22T03:07:39.737Z] Movies recommended for you:
[2025-01-22T03:07:39.737Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T03:07:39.737Z] There is no way to check that no silent failure occurred.
[2025-01-22T03:07:39.737Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (18185.811 ms) ======
[2025-01-22T03:07:39.737Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-01-22T03:07:40.127Z] GC before operation: completed in 210.580 ms, heap usage 417.493 MB -> 45.734 MB.
[2025-01-22T03:07:42.667Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T03:07:46.062Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T03:07:48.801Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T03:07:51.358Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T03:07:52.706Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T03:07:54.609Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T03:07:55.969Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T03:07:58.038Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T03:07:58.038Z] 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.
[2025-01-22T03:07:58.038Z] The best model improves the baseline by 14.52%.
[2025-01-22T03:07:58.038Z] Movies recommended for you:
[2025-01-22T03:07:58.038Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T03:07:58.038Z] There is no way to check that no silent failure occurred.
[2025-01-22T03:07:58.038Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (18139.147 ms) ======
[2025-01-22T03:07:58.038Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-01-22T03:07:58.426Z] GC before operation: completed in 193.879 ms, heap usage 435.517 MB -> 45.900 MB.
[2025-01-22T03:08:00.975Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T03:08:04.276Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T03:08:06.854Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T03:08:09.465Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T03:08:10.799Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T03:08:12.871Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T03:08:14.201Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T03:08:16.119Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T03:08:16.119Z] 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.
[2025-01-22T03:08:16.119Z] The best model improves the baseline by 14.52%.
[2025-01-22T03:08:16.507Z] Movies recommended for you:
[2025-01-22T03:08:16.507Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T03:08:16.507Z] There is no way to check that no silent failure occurred.
[2025-01-22T03:08:16.507Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (17943.475 ms) ======
[2025-01-22T03:08:16.507Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-01-22T03:08:16.507Z] GC before operation: completed in 186.537 ms, heap usage 441.016 MB -> 46.265 MB.
[2025-01-22T03:08:19.068Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T03:08:21.785Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T03:08:25.167Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T03:08:27.785Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T03:08:29.155Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T03:08:30.514Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T03:08:32.401Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T03:08:34.376Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T03:08:34.376Z] 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.
[2025-01-22T03:08:34.376Z] The best model improves the baseline by 14.52%.
[2025-01-22T03:08:34.376Z] Movies recommended for you:
[2025-01-22T03:08:34.376Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T03:08:34.376Z] There is no way to check that no silent failure occurred.
[2025-01-22T03:08:34.376Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (17946.142 ms) ======
[2025-01-22T03:08:34.376Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-01-22T03:08:34.767Z] GC before operation: completed in 186.700 ms, heap usage 410.712 MB -> 46.021 MB.
[2025-01-22T03:08:37.323Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T03:08:39.863Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T03:08:43.191Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T03:08:45.783Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T03:08:47.131Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T03:08:49.073Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T03:08:50.402Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T03:08:52.321Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T03:08:52.321Z] 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.
[2025-01-22T03:08:52.712Z] The best model improves the baseline by 14.52%.
[2025-01-22T03:08:52.712Z] Movies recommended for you:
[2025-01-22T03:08:52.712Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T03:08:52.712Z] There is no way to check that no silent failure occurred.
[2025-01-22T03:08:52.712Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (18024.330 ms) ======
[2025-01-22T03:08:52.712Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-01-22T03:08:52.712Z] GC before operation: completed in 214.815 ms, heap usage 426.992 MB -> 46.159 MB.
[2025-01-22T03:08:56.036Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T03:08:58.644Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T03:09:01.199Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T03:09:03.747Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T03:09:05.649Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T03:09:06.974Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T03:09:08.892Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T03:09:10.214Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T03:09:10.600Z] 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.
[2025-01-22T03:09:10.600Z] The best model improves the baseline by 14.52%.
[2025-01-22T03:09:10.989Z] Movies recommended for you:
[2025-01-22T03:09:10.989Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T03:09:10.989Z] There is no way to check that no silent failure occurred.
[2025-01-22T03:09:10.989Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (17952.870 ms) ======
[2025-01-22T03:09:10.989Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-01-22T03:09:10.989Z] GC before operation: completed in 158.380 ms, heap usage 409.216 MB -> 45.803 MB.
[2025-01-22T03:09:13.533Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T03:09:16.879Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T03:09:19.515Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T03:09:22.131Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T03:09:23.450Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T03:09:25.379Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T03:09:26.708Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T03:09:28.613Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T03:09:28.613Z] 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.
[2025-01-22T03:09:28.613Z] The best model improves the baseline by 14.52%.
[2025-01-22T03:09:29.000Z] Movies recommended for you:
[2025-01-22T03:09:29.000Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T03:09:29.000Z] There is no way to check that no silent failure occurred.
[2025-01-22T03:09:29.000Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (17928.430 ms) ======
[2025-01-22T03:09:29.000Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-01-22T03:09:29.000Z] GC before operation: completed in 173.808 ms, heap usage 413.410 MB -> 46.018 MB.
[2025-01-22T03:09:31.579Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T03:09:34.919Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T03:09:37.460Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T03:09:40.035Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T03:09:41.938Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T03:09:43.260Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T03:09:45.139Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T03:09:47.042Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T03:09:47.042Z] 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.
[2025-01-22T03:09:47.042Z] The best model improves the baseline by 14.52%.
[2025-01-22T03:09:47.042Z] Movies recommended for you:
[2025-01-22T03:09:47.042Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T03:09:47.042Z] There is no way to check that no silent failure occurred.
[2025-01-22T03:09:47.042Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (18069.039 ms) ======
[2025-01-22T03:09:47.042Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-01-22T03:09:47.423Z] GC before operation: completed in 161.898 ms, heap usage 414.351 MB -> 46.222 MB.
[2025-01-22T03:09:50.097Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T03:09:52.642Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T03:09:55.948Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T03:09:58.504Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T03:09:59.844Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T03:10:01.741Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T03:10:03.661Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T03:10:05.038Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T03:10:05.038Z] 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.
[2025-01-22T03:10:05.420Z] The best model improves the baseline by 14.52%.
[2025-01-22T03:10:05.420Z] Movies recommended for you:
[2025-01-22T03:10:05.420Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T03:10:05.420Z] There is no way to check that no silent failure occurred.
[2025-01-22T03:10:05.420Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (18047.977 ms) ======
[2025-01-22T03:10:05.420Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-01-22T03:10:05.420Z] GC before operation: completed in 162.495 ms, heap usage 430.406 MB -> 45.962 MB.
[2025-01-22T03:10:08.011Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T03:10:11.349Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T03:10:27.621Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T03:10:27.621Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T03:10:27.621Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T03:10:27.621Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T03:10:27.621Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T03:10:27.621Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T03:10:27.621Z] 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.
[2025-01-22T03:10:27.621Z] The best model improves the baseline by 14.52%.
[2025-01-22T03:10:27.621Z] Movies recommended for you:
[2025-01-22T03:10:27.621Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T03:10:27.621Z] There is no way to check that no silent failure occurred.
[2025-01-22T03:10:27.621Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (17826.637 ms) ======
[2025-01-22T03:10:27.621Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-01-22T03:10:27.621Z] GC before operation: completed in 149.343 ms, heap usage 408.347 MB -> 46.154 MB.
[2025-01-22T03:10:27.621Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T03:10:28.998Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T03:10:31.576Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T03:10:34.132Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T03:10:36.156Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T03:10:37.498Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T03:10:39.423Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T03:10:41.319Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T03:10:41.319Z] 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.
[2025-01-22T03:10:41.319Z] The best model improves the baseline by 14.52%.
[2025-01-22T03:10:41.703Z] Movies recommended for you:
[2025-01-22T03:10:41.703Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T03:10:41.703Z] There is no way to check that no silent failure occurred.
[2025-01-22T03:10:41.703Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (18010.845 ms) ======
[2025-01-22T03:10:41.703Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-01-22T03:10:41.703Z] GC before operation: completed in 154.455 ms, heap usage 431.773 MB -> 46.248 MB.
[2025-01-22T03:10:44.259Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T03:10:47.578Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T03:10:50.114Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T03:10:52.663Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T03:10:53.997Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T03:10:55.899Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T03:10:57.801Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T03:10:59.139Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T03:10:59.531Z] 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.
[2025-01-22T03:10:59.531Z] The best model improves the baseline by 14.52%.
[2025-01-22T03:10:59.531Z] Movies recommended for you:
[2025-01-22T03:10:59.531Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T03:10:59.531Z] There is no way to check that no silent failure occurred.
[2025-01-22T03:10:59.531Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (17855.102 ms) ======
[2025-01-22T03:10:59.531Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-01-22T03:10:59.531Z] GC before operation: completed in 167.015 ms, heap usage 425.627 MB -> 46.112 MB.
[2025-01-22T03:11:02.871Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T03:11:05.435Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T03:11:08.006Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T03:11:10.683Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T03:11:12.022Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T03:11:13.909Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T03:11:15.855Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T03:11:17.199Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T03:11:17.587Z] 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.
[2025-01-22T03:11:17.587Z] The best model improves the baseline by 14.52%.
[2025-01-22T03:11:17.587Z] Movies recommended for you:
[2025-01-22T03:11:17.587Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T03:11:17.587Z] There is no way to check that no silent failure occurred.
[2025-01-22T03:11:17.587Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (17882.940 ms) ======
[2025-01-22T03:11:17.587Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-01-22T03:11:17.587Z] GC before operation: completed in 150.853 ms, heap usage 439.700 MB -> 46.122 MB.
[2025-01-22T03:11:20.164Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T03:11:23.518Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T03:11:26.135Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T03:11:28.704Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T03:11:30.051Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T03:11:32.082Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T03:11:33.461Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T03:11:35.399Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T03:11:35.399Z] 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.
[2025-01-22T03:11:35.399Z] The best model improves the baseline by 14.52%.
[2025-01-22T03:11:35.399Z] Movies recommended for you:
[2025-01-22T03:11:35.399Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T03:11:35.399Z] There is no way to check that no silent failure occurred.
[2025-01-22T03:11:35.399Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (17719.303 ms) ======
[2025-01-22T03:11:35.399Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-01-22T03:11:35.780Z] GC before operation: completed in 148.262 ms, heap usage 420.741 MB -> 46.379 MB.
[2025-01-22T03:11:38.329Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-22T03:11:40.893Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-22T03:11:43.501Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-22T03:11:46.837Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-22T03:11:48.168Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-22T03:11:49.506Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-22T03:11:51.394Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-22T03:11:53.307Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-22T03:11:53.307Z] 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.
[2025-01-22T03:11:53.307Z] The best model improves the baseline by 14.52%.
[2025-01-22T03:11:53.692Z] Movies recommended for you:
[2025-01-22T03:11:53.692Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-22T03:11:53.692Z] There is no way to check that no silent failure occurred.
[2025-01-22T03:11:53.692Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (17925.649 ms) ======
[2025-01-22T03:11:54.072Z] -----------------------------------
[2025-01-22T03:11:54.072Z] renaissance-movie-lens_0_PASSED
[2025-01-22T03:11:54.072Z] -----------------------------------
[2025-01-22T03:11:54.072Z]
[2025-01-22T03:11:54.072Z] TEST TEARDOWN:
[2025-01-22T03:11:54.072Z] Nothing to be done for teardown.
[2025-01-22T03:11:54.072Z] renaissance-movie-lens_0 Finish Time: Wed Jan 22 03:11:54 2025 Epoch Time (ms): 1737515514042