renaissance-movie-lens_0
[2024-11-21T12:02:25.580Z] Running test renaissance-movie-lens_0 ...
[2024-11-21T12:02:25.580Z] ===============================================
[2024-11-21T12:02:25.580Z] renaissance-movie-lens_0 Start Time: Thu Nov 21 12:02:23 2024 Epoch Time (ms): 1732190543977
[2024-11-21T12:02:25.580Z] variation: NoOptions
[2024-11-21T12:02:25.580Z] JVM_OPTIONS:
[2024-11-21T12:02:25.580Z] { \
[2024-11-21T12:02:25.580Z] echo ""; echo "TEST SETUP:"; \
[2024-11-21T12:02:25.580Z] echo "Nothing to be done for setup."; \
[2024-11-21T12:02:25.580Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17321875451188/renaissance-movie-lens_0"; \
[2024-11-21T12:02:25.580Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17321875451188/renaissance-movie-lens_0"; \
[2024-11-21T12:02:25.580Z] echo ""; echo "TESTING:"; \
[2024-11-21T12:02:25.580Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17321875451188/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-21T12:02:25.580Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17321875451188/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-21T12:02:25.580Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-21T12:02:25.580Z] echo "Nothing to be done for teardown."; \
[2024-11-21T12:02:25.580Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17321875451188/TestTargetResult";
[2024-11-21T12:02:25.580Z]
[2024-11-21T12:02:25.580Z] TEST SETUP:
[2024-11-21T12:02:25.580Z] Nothing to be done for setup.
[2024-11-21T12:02:25.580Z]
[2024-11-21T12:02:25.580Z] TESTING:
[2024-11-21T12:02:36.518Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-21T12:02:39.786Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads.
[2024-11-21T12:02:53.390Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-21T12:02:54.363Z] Training: 60056, validation: 20285, test: 19854
[2024-11-21T12:02:54.363Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-21T12:02:54.363Z] GC before operation: completed in 589.698 ms, heap usage 109.288 MB -> 37.117 MB.
[2024-11-21T12:03:17.075Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T12:03:31.554Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T12:03:50.750Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T12:04:02.520Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T12:04:09.228Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T12:04:17.226Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T12:04:22.516Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T12:04:28.175Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T12:04:28.175Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T12:04:28.887Z] The best model improves the baseline by 14.34%.
[2024-11-21T12:04:30.615Z] Movies recommended for you:
[2024-11-21T12:04:30.615Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T12:04:30.615Z] There is no way to check that no silent failure occurred.
[2024-11-21T12:04:30.615Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (96112.763 ms) ======
[2024-11-21T12:04:30.615Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-21T12:04:31.496Z] GC before operation: completed in 621.655 ms, heap usage 150.982 MB -> 51.044 MB.
[2024-11-21T12:04:39.617Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T12:04:51.024Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T12:05:00.530Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T12:05:08.655Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T12:05:16.214Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T12:05:21.786Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T12:05:27.003Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T12:05:34.128Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T12:05:34.914Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T12:05:34.914Z] The best model improves the baseline by 14.34%.
[2024-11-21T12:05:35.737Z] Movies recommended for you:
[2024-11-21T12:05:35.737Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T12:05:35.737Z] There is no way to check that no silent failure occurred.
[2024-11-21T12:05:35.737Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (64248.181 ms) ======
[2024-11-21T12:05:35.737Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-21T12:05:35.737Z] GC before operation: completed in 312.920 ms, heap usage 387.089 MB -> 52.375 MB.
[2024-11-21T12:05:43.687Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T12:05:53.046Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T12:06:01.298Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T12:06:11.474Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T12:06:17.226Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T12:06:20.429Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T12:06:28.502Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T12:06:31.645Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T12:06:32.356Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T12:06:32.356Z] The best model improves the baseline by 14.34%.
[2024-11-21T12:06:32.356Z] Movies recommended for you:
[2024-11-21T12:06:32.356Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T12:06:32.356Z] There is no way to check that no silent failure occurred.
[2024-11-21T12:06:32.356Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (56696.334 ms) ======
[2024-11-21T12:06:32.356Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-21T12:06:33.166Z] GC before operation: completed in 292.633 ms, heap usage 273.572 MB -> 49.489 MB.
[2024-11-21T12:06:42.452Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T12:06:50.422Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T12:07:00.425Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T12:07:07.013Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T12:07:12.826Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T12:07:15.981Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T12:07:20.073Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T12:07:28.373Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T12:07:28.373Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T12:07:28.373Z] The best model improves the baseline by 14.34%.
[2024-11-21T12:07:29.079Z] Movies recommended for you:
[2024-11-21T12:07:29.079Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T12:07:29.079Z] There is no way to check that no silent failure occurred.
[2024-11-21T12:07:29.079Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (56153.465 ms) ======
[2024-11-21T12:07:29.079Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-21T12:07:29.079Z] GC before operation: completed in 397.853 ms, heap usage 155.955 MB -> 49.614 MB.
[2024-11-21T12:07:41.155Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T12:07:52.895Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T12:08:02.744Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T12:08:10.860Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T12:08:18.055Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T12:08:22.582Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T12:08:28.013Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T12:08:32.295Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T12:08:33.003Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T12:08:33.750Z] The best model improves the baseline by 14.34%.
[2024-11-21T12:08:33.751Z] Movies recommended for you:
[2024-11-21T12:08:33.751Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T12:08:33.751Z] There is no way to check that no silent failure occurred.
[2024-11-21T12:08:33.751Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (64446.535 ms) ======
[2024-11-21T12:08:33.751Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-21T12:08:33.751Z] GC before operation: completed in 332.569 ms, heap usage 249.859 MB -> 49.882 MB.
[2024-11-21T12:08:43.695Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T12:08:50.047Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T12:08:59.801Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T12:09:08.905Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T12:09:15.588Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T12:09:22.617Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T12:09:26.749Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T12:09:33.556Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T12:09:36.491Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T12:09:36.491Z] The best model improves the baseline by 14.34%.
[2024-11-21T12:09:36.491Z] Movies recommended for you:
[2024-11-21T12:09:36.491Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T12:09:36.491Z] There is no way to check that no silent failure occurred.
[2024-11-21T12:09:36.491Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (62403.799 ms) ======
[2024-11-21T12:09:36.491Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-21T12:09:36.491Z] GC before operation: completed in 145.657 ms, heap usage 257.094 MB -> 49.820 MB.
[2024-11-21T12:09:50.833Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T12:10:00.609Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T12:10:09.508Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T12:10:19.426Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T12:10:23.639Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T12:10:28.329Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T12:10:35.477Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T12:10:39.721Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T12:10:42.183Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T12:10:42.183Z] The best model improves the baseline by 14.34%.
[2024-11-21T12:10:42.183Z] Movies recommended for you:
[2024-11-21T12:10:42.183Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T12:10:42.183Z] There is no way to check that no silent failure occurred.
[2024-11-21T12:10:42.183Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (65364.900 ms) ======
[2024-11-21T12:10:42.183Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-21T12:10:42.183Z] GC before operation: completed in 261.082 ms, heap usage 314.469 MB -> 50.114 MB.
[2024-11-21T12:10:48.897Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T12:11:01.078Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T12:11:10.444Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T12:11:17.085Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T12:11:22.383Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T12:11:25.435Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T12:11:32.044Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T12:11:36.345Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T12:11:37.015Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T12:11:37.015Z] The best model improves the baseline by 14.34%.
[2024-11-21T12:11:37.015Z] Movies recommended for you:
[2024-11-21T12:11:37.015Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T12:11:37.015Z] There is no way to check that no silent failure occurred.
[2024-11-21T12:11:37.015Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (55009.858 ms) ======
[2024-11-21T12:11:37.015Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-21T12:11:37.849Z] GC before operation: completed in 846.957 ms, heap usage 276.603 MB -> 50.342 MB.
[2024-11-21T12:11:47.864Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T12:12:01.747Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T12:12:09.884Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T12:12:18.865Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T12:12:23.246Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T12:12:30.390Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T12:12:35.992Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T12:12:41.477Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T12:12:43.817Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T12:12:44.553Z] The best model improves the baseline by 14.34%.
[2024-11-21T12:12:44.553Z] Movies recommended for you:
[2024-11-21T12:12:44.553Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T12:12:44.553Z] There is no way to check that no silent failure occurred.
[2024-11-21T12:12:44.553Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (66754.784 ms) ======
[2024-11-21T12:12:44.553Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-21T12:12:45.294Z] GC before operation: completed in 346.730 ms, heap usage 244.577 MB -> 50.155 MB.
[2024-11-21T12:12:53.431Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T12:13:01.937Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T12:13:08.434Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T12:13:18.183Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T12:13:20.381Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T12:13:26.276Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T12:13:29.708Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T12:13:36.429Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T12:13:36.429Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T12:13:36.429Z] The best model improves the baseline by 14.34%.
[2024-11-21T12:13:36.429Z] Movies recommended for you:
[2024-11-21T12:13:36.429Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T12:13:36.429Z] There is no way to check that no silent failure occurred.
[2024-11-21T12:13:36.429Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (51418.112 ms) ======
[2024-11-21T12:13:36.429Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-21T12:13:37.131Z] GC before operation: completed in 310.125 ms, heap usage 126.507 MB -> 52.173 MB.
[2024-11-21T12:13:44.939Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T12:13:52.267Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T12:14:00.428Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T12:14:07.110Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T12:14:12.325Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T12:14:16.436Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T12:14:22.225Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T12:14:27.787Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T12:14:27.787Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T12:14:28.554Z] The best model improves the baseline by 14.34%.
[2024-11-21T12:14:28.554Z] Movies recommended for you:
[2024-11-21T12:14:28.554Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T12:14:28.554Z] There is no way to check that no silent failure occurred.
[2024-11-21T12:14:28.554Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (51491.404 ms) ======
[2024-11-21T12:14:28.554Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-21T12:14:29.246Z] GC before operation: completed in 502.606 ms, heap usage 329.180 MB -> 50.172 MB.
[2024-11-21T12:14:37.597Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T12:14:48.249Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T12:14:56.812Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T12:15:05.041Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T12:15:10.217Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T12:15:13.517Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T12:15:19.039Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T12:15:21.230Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T12:15:21.990Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T12:15:21.990Z] The best model improves the baseline by 14.34%.
[2024-11-21T12:15:22.648Z] Movies recommended for you:
[2024-11-21T12:15:22.648Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T12:15:22.648Z] There is no way to check that no silent failure occurred.
[2024-11-21T12:15:22.648Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (53792.816 ms) ======
[2024-11-21T12:15:22.648Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-21T12:15:22.648Z] GC before operation: completed in 108.871 ms, heap usage 109.176 MB -> 52.931 MB.
[2024-11-21T12:15:30.786Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T12:15:38.206Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T12:15:47.850Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T12:15:54.586Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T12:15:57.732Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T12:16:02.950Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T12:16:07.340Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T12:16:12.879Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T12:16:13.604Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T12:16:13.604Z] The best model improves the baseline by 14.34%.
[2024-11-21T12:16:14.322Z] Movies recommended for you:
[2024-11-21T12:16:14.322Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T12:16:14.322Z] There is no way to check that no silent failure occurred.
[2024-11-21T12:16:14.322Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (51164.779 ms) ======
[2024-11-21T12:16:14.322Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-21T12:16:14.322Z] GC before operation: completed in 536.255 ms, heap usage 341.362 MB -> 53.652 MB.
[2024-11-21T12:16:23.821Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T12:16:29.717Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T12:16:36.534Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T12:16:44.337Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T12:16:48.478Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T12:16:52.822Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T12:16:58.175Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T12:17:02.694Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T12:17:03.380Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T12:17:03.380Z] The best model improves the baseline by 14.34%.
[2024-11-21T12:17:04.215Z] Movies recommended for you:
[2024-11-21T12:17:04.215Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T12:17:04.215Z] There is no way to check that no silent failure occurred.
[2024-11-21T12:17:04.215Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (49515.871 ms) ======
[2024-11-21T12:17:04.215Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-21T12:17:04.975Z] GC before operation: completed in 684.327 ms, heap usage 122.577 MB -> 50.293 MB.
[2024-11-21T12:17:14.346Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T12:17:21.169Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T12:17:28.470Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T12:17:35.239Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T12:17:39.595Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T12:17:42.697Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T12:17:46.916Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T12:17:51.364Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T12:17:51.364Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T12:17:51.364Z] The best model improves the baseline by 14.34%.
[2024-11-21T12:17:52.263Z] Movies recommended for you:
[2024-11-21T12:17:52.263Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T12:17:52.263Z] There is no way to check that no silent failure occurred.
[2024-11-21T12:17:52.263Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (47152.567 ms) ======
[2024-11-21T12:17:52.263Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-21T12:17:53.122Z] GC before operation: completed in 815.093 ms, heap usage 275.223 MB -> 50.309 MB.
[2024-11-21T12:18:01.656Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T12:18:08.091Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T12:18:17.338Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T12:18:24.054Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T12:18:28.352Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T12:18:32.447Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T12:18:36.907Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T12:18:43.368Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T12:18:43.368Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T12:18:43.368Z] The best model improves the baseline by 14.34%.
[2024-11-21T12:18:43.368Z] Movies recommended for you:
[2024-11-21T12:18:43.368Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T12:18:43.368Z] There is no way to check that no silent failure occurred.
[2024-11-21T12:18:43.368Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (50754.303 ms) ======
[2024-11-21T12:18:43.368Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-21T12:18:44.087Z] GC before operation: completed in 357.244 ms, heap usage 224.921 MB -> 47.962 MB.
[2024-11-21T12:18:50.439Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T12:18:57.428Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T12:19:03.866Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T12:19:10.083Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T12:19:15.417Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T12:19:18.565Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T12:19:22.789Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T12:19:25.879Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T12:19:27.362Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T12:19:27.362Z] The best model improves the baseline by 14.34%.
[2024-11-21T12:19:27.362Z] Movies recommended for you:
[2024-11-21T12:19:27.362Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T12:19:27.362Z] There is no way to check that no silent failure occurred.
[2024-11-21T12:19:27.362Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (43437.152 ms) ======
[2024-11-21T12:19:27.362Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-21T12:19:28.063Z] GC before operation: completed in 527.439 ms, heap usage 232.569 MB -> 48.349 MB.
[2024-11-21T12:19:34.796Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T12:19:43.286Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T12:19:51.087Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T12:19:56.570Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T12:20:01.964Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T12:20:07.534Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T12:20:10.698Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T12:20:15.109Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T12:20:15.820Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T12:20:15.820Z] The best model improves the baseline by 14.34%.
[2024-11-21T12:20:16.615Z] Movies recommended for you:
[2024-11-21T12:20:16.615Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T12:20:16.615Z] There is no way to check that no silent failure occurred.
[2024-11-21T12:20:16.615Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (48572.574 ms) ======
[2024-11-21T12:20:16.615Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-21T12:20:17.350Z] GC before operation: completed in 952.902 ms, heap usage 300.292 MB -> 48.496 MB.
[2024-11-21T12:20:25.316Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T12:20:33.794Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T12:20:44.586Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T12:20:51.280Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T12:20:55.398Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T12:20:59.575Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T12:21:08.123Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T12:21:15.084Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T12:21:16.662Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T12:21:16.662Z] The best model improves the baseline by 14.34%.
[2024-11-21T12:21:16.662Z] Movies recommended for you:
[2024-11-21T12:21:16.662Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T12:21:16.662Z] There is no way to check that no silent failure occurred.
[2024-11-21T12:21:16.662Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (59508.386 ms) ======
[2024-11-21T12:21:16.662Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-21T12:21:17.395Z] GC before operation: completed in 402.050 ms, heap usage 247.259 MB -> 47.966 MB.
[2024-11-21T12:21:24.506Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T12:21:30.976Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T12:21:37.439Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T12:21:42.734Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T12:21:48.574Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T12:21:51.246Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T12:21:56.536Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T12:22:00.065Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T12:22:01.753Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T12:22:02.514Z] The best model improves the baseline by 14.34%.
[2024-11-21T12:22:02.514Z] Movies recommended for you:
[2024-11-21T12:22:02.514Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T12:22:02.514Z] There is no way to check that no silent failure occurred.
[2024-11-21T12:22:02.514Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (45518.785 ms) ======
[2024-11-21T12:22:04.032Z] -----------------------------------
[2024-11-21T12:22:04.032Z] renaissance-movie-lens_0_PASSED
[2024-11-21T12:22:04.032Z] -----------------------------------
[2024-11-21T12:22:04.032Z]
[2024-11-21T12:22:04.032Z] TEST TEARDOWN:
[2024-11-21T12:22:04.032Z] Nothing to be done for teardown.
[2024-11-21T12:22:04.032Z] renaissance-movie-lens_0 Finish Time: Thu Nov 21 12:22:03 2024 Epoch Time (ms): 1732191723711