renaissance-movie-lens_0
[2024-08-28T21:25:28.007Z] Running test renaissance-movie-lens_0 ...
[2024-08-28T21:25:28.007Z] ===============================================
[2024-08-28T21:25:28.007Z] renaissance-movie-lens_0 Start Time: Wed Aug 28 21:25:27 2024 Epoch Time (ms): 1724880327565
[2024-08-28T21:25:28.007Z] variation: NoOptions
[2024-08-28T21:25:28.007Z] JVM_OPTIONS:
[2024-08-28T21:25:28.007Z] { \
[2024-08-28T21:25:28.007Z] echo ""; echo "TEST SETUP:"; \
[2024-08-28T21:25:28.007Z] echo "Nothing to be done for setup."; \
[2024-08-28T21:25:28.007Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17248791343223/renaissance-movie-lens_0"; \
[2024-08-28T21:25:28.007Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17248791343223/renaissance-movie-lens_0"; \
[2024-08-28T21:25:28.007Z] echo ""; echo "TESTING:"; \
[2024-08-28T21:25:28.007Z] "/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_17248791343223/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-28T21:25:28.007Z] 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_17248791343223/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-28T21:25:28.007Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-28T21:25:28.007Z] echo "Nothing to be done for teardown."; \
[2024-08-28T21:25:28.007Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17248791343223/TestTargetResult";
[2024-08-28T21:25:28.007Z]
[2024-08-28T21:25:28.007Z] TEST SETUP:
[2024-08-28T21:25:28.007Z] Nothing to be done for setup.
[2024-08-28T21:25:28.007Z]
[2024-08-28T21:25:28.007Z] TESTING:
[2024-08-28T21:25:31.809Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-28T21:25:33.879Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads.
[2024-08-28T21:25:37.723Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-28T21:25:37.723Z] Training: 60056, validation: 20285, test: 19854
[2024-08-28T21:25:37.723Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-28T21:25:37.723Z] GC before operation: completed in 66.290 ms, heap usage 78.691 MB -> 37.002 MB.
[2024-08-28T21:25:43.527Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:25:48.180Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:25:51.894Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:25:55.597Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:25:57.982Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:26:00.797Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:26:03.648Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:26:05.686Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:26:06.320Z] 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.
[2024-08-28T21:26:06.320Z] The best model improves the baseline by 14.34%.
[2024-08-28T21:26:06.320Z] Movies recommended for you:
[2024-08-28T21:26:06.320Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:26:06.320Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:26:06.320Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (28735.769 ms) ======
[2024-08-28T21:26:06.320Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-28T21:26:06.948Z] GC before operation: completed in 222.123 ms, heap usage 163.047 MB -> 57.761 MB.
[2024-08-28T21:26:10.711Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:26:14.394Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:26:19.277Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:26:22.140Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:26:25.067Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:26:27.127Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:26:29.183Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:26:31.269Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:26:31.900Z] 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.
[2024-08-28T21:26:31.900Z] The best model improves the baseline by 14.34%.
[2024-08-28T21:26:31.900Z] Movies recommended for you:
[2024-08-28T21:26:31.900Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:26:31.900Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:26:31.900Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (25294.993 ms) ======
[2024-08-28T21:26:31.900Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-28T21:26:31.900Z] GC before operation: completed in 95.385 ms, heap usage 310.226 MB -> 49.098 MB.
[2024-08-28T21:26:35.704Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:26:39.464Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:26:43.169Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:26:46.854Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:26:48.888Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:26:50.983Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:26:53.903Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:26:56.826Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:26:57.445Z] 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.
[2024-08-28T21:26:57.445Z] The best model improves the baseline by 14.34%.
[2024-08-28T21:26:57.445Z] Movies recommended for you:
[2024-08-28T21:26:57.445Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:26:57.445Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:26:57.445Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (25547.012 ms) ======
[2024-08-28T21:26:57.445Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-28T21:26:57.445Z] GC before operation: completed in 120.156 ms, heap usage 60.536 MB -> 49.113 MB.
[2024-08-28T21:27:01.141Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:27:04.903Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:27:09.571Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:27:12.453Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:27:14.472Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:27:16.490Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:27:18.542Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:27:20.612Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:27:21.224Z] 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.
[2024-08-28T21:27:21.224Z] The best model improves the baseline by 14.34%.
[2024-08-28T21:27:21.224Z] Movies recommended for you:
[2024-08-28T21:27:21.224Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:27:21.224Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:27:21.224Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (23458.085 ms) ======
[2024-08-28T21:27:21.224Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-28T21:27:21.224Z] GC before operation: completed in 87.148 ms, heap usage 176.049 MB -> 49.550 MB.
[2024-08-28T21:27:24.970Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:27:28.787Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:27:32.458Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:27:36.169Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:27:38.179Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:27:40.231Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:27:43.143Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:27:44.461Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:27:44.461Z] 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.
[2024-08-28T21:27:45.077Z] The best model improves the baseline by 14.34%.
[2024-08-28T21:27:45.077Z] Movies recommended for you:
[2024-08-28T21:27:45.077Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:27:45.077Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:27:45.077Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (23631.866 ms) ======
[2024-08-28T21:27:45.077Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-28T21:27:45.077Z] GC before operation: completed in 121.561 ms, heap usage 226.115 MB -> 49.852 MB.
[2024-08-28T21:27:47.870Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:27:50.702Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:27:53.897Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:27:56.725Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:27:58.750Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:28:00.844Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:28:02.900Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:28:04.979Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:28:05.592Z] 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.
[2024-08-28T21:28:05.592Z] The best model improves the baseline by 14.34%.
[2024-08-28T21:28:05.592Z] Movies recommended for you:
[2024-08-28T21:28:05.592Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:28:05.592Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:28:05.592Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (20641.074 ms) ======
[2024-08-28T21:28:05.592Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-28T21:28:05.592Z] GC before operation: completed in 121.207 ms, heap usage 277.178 MB -> 49.885 MB.
[2024-08-28T21:28:09.285Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:28:12.187Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:28:15.928Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:28:19.745Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:28:21.833Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:28:23.867Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:28:25.893Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:28:28.009Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:28:28.632Z] 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.
[2024-08-28T21:28:28.632Z] The best model improves the baseline by 14.34%.
[2024-08-28T21:28:28.632Z] Movies recommended for you:
[2024-08-28T21:28:28.632Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:28:28.632Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:28:28.632Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (23054.788 ms) ======
[2024-08-28T21:28:28.632Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-28T21:28:29.294Z] GC before operation: completed in 127.374 ms, heap usage 276.602 MB -> 50.230 MB.
[2024-08-28T21:28:33.468Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:28:36.334Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:28:40.039Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:28:43.752Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:28:45.805Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:28:47.779Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:28:49.769Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:28:51.746Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:28:52.357Z] 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.
[2024-08-28T21:28:52.357Z] The best model improves the baseline by 14.34%.
[2024-08-28T21:28:52.357Z] Movies recommended for you:
[2024-08-28T21:28:52.357Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:28:52.357Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:28:52.357Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (23432.287 ms) ======
[2024-08-28T21:28:52.357Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-28T21:28:52.357Z] GC before operation: completed in 162.382 ms, heap usage 225.113 MB -> 50.283 MB.
[2024-08-28T21:28:56.090Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:28:58.929Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:29:02.774Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:29:05.644Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:29:07.665Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:29:09.687Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:29:11.757Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:29:13.787Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:29:14.420Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-08-28T21:29:14.420Z] The best model improves the baseline by 14.34%.
[2024-08-28T21:29:14.420Z] Movies recommended for you:
[2024-08-28T21:29:14.420Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:29:14.420Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:29:14.420Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (21842.598 ms) ======
[2024-08-28T21:29:14.420Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-28T21:29:14.420Z] GC before operation: completed in 142.815 ms, heap usage 249.272 MB -> 50.206 MB.
[2024-08-28T21:29:17.655Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:29:21.324Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:29:24.970Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:29:27.807Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:29:29.837Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:29:31.936Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:29:33.253Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:29:35.294Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:29:35.911Z] 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.
[2024-08-28T21:29:35.911Z] The best model improves the baseline by 14.34%.
[2024-08-28T21:29:35.911Z] Movies recommended for you:
[2024-08-28T21:29:35.911Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:29:35.911Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:29:35.911Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (21406.420 ms) ======
[2024-08-28T21:29:35.911Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-28T21:29:35.911Z] GC before operation: completed in 120.088 ms, heap usage 276.888 MB -> 50.251 MB.
[2024-08-28T21:29:39.655Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:29:43.413Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:29:46.249Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:29:49.340Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:29:51.327Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:29:53.368Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:29:55.335Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:29:57.370Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:29:57.370Z] 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.
[2024-08-28T21:29:57.370Z] The best model improves the baseline by 14.34%.
[2024-08-28T21:29:57.370Z] Movies recommended for you:
[2024-08-28T21:29:57.370Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:29:57.370Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:29:57.370Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (21556.148 ms) ======
[2024-08-28T21:29:57.370Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-28T21:29:57.991Z] GC before operation: completed in 112.367 ms, heap usage 277.126 MB -> 50.106 MB.
[2024-08-28T21:30:00.804Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:30:05.609Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:30:08.467Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:30:12.261Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:30:13.563Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:30:16.390Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:30:18.493Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:30:21.356Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:30:21.356Z] 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.
[2024-08-28T21:30:21.356Z] The best model improves the baseline by 14.34%.
[2024-08-28T21:30:21.964Z] Movies recommended for you:
[2024-08-28T21:30:21.964Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:30:21.964Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:30:21.964Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (23889.400 ms) ======
[2024-08-28T21:30:21.964Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-28T21:30:21.964Z] GC before operation: completed in 151.052 ms, heap usage 129.026 MB -> 50.129 MB.
[2024-08-28T21:30:24.759Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:30:28.451Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:30:32.506Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:30:35.409Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:30:37.499Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:30:39.555Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:30:41.621Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:30:43.672Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:30:43.672Z] 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.
[2024-08-28T21:30:43.672Z] The best model improves the baseline by 14.34%.
[2024-08-28T21:30:43.672Z] Movies recommended for you:
[2024-08-28T21:30:43.672Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:30:43.672Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:30:43.672Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (22090.913 ms) ======
[2024-08-28T21:30:43.672Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-28T21:30:44.297Z] GC before operation: completed in 128.942 ms, heap usage 248.484 MB -> 50.337 MB.
[2024-08-28T21:30:47.154Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:30:49.955Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:30:52.789Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:30:55.578Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:30:57.616Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:30:58.879Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:31:00.857Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:31:02.861Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:31:02.861Z] 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.
[2024-08-28T21:31:02.861Z] The best model improves the baseline by 14.34%.
[2024-08-28T21:31:03.458Z] Movies recommended for you:
[2024-08-28T21:31:03.458Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:31:03.458Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:31:03.458Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (19186.613 ms) ======
[2024-08-28T21:31:03.458Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-28T21:31:03.458Z] GC before operation: completed in 175.114 ms, heap usage 114.595 MB -> 49.945 MB.
[2024-08-28T21:31:05.918Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:31:08.742Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:31:11.531Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:31:14.341Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:31:16.320Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:31:17.599Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:31:19.615Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:31:21.631Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:31:21.631Z] 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.
[2024-08-28T21:31:21.631Z] The best model improves the baseline by 14.34%.
[2024-08-28T21:31:21.631Z] Movies recommended for you:
[2024-08-28T21:31:21.631Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:31:21.631Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:31:21.631Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (18283.306 ms) ======
[2024-08-28T21:31:21.631Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-28T21:31:21.631Z] GC before operation: completed in 146.843 ms, heap usage 70.092 MB -> 50.085 MB.
[2024-08-28T21:31:24.495Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:31:27.304Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:31:30.991Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:31:34.762Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:31:36.056Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:31:38.064Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:31:41.112Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:31:42.466Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:31:43.101Z] 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.
[2024-08-28T21:31:43.101Z] The best model improves the baseline by 14.34%.
[2024-08-28T21:31:43.101Z] Movies recommended for you:
[2024-08-28T21:31:43.101Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:31:43.101Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:31:43.101Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (21206.802 ms) ======
[2024-08-28T21:31:43.101Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-28T21:31:43.101Z] GC before operation: completed in 167.065 ms, heap usage 245.976 MB -> 50.455 MB.
[2024-08-28T21:31:46.886Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:31:50.624Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:31:55.357Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:31:58.173Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:32:00.192Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:32:02.222Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:32:04.233Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:32:06.310Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:32:06.310Z] 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.
[2024-08-28T21:32:06.310Z] The best model improves the baseline by 14.34%.
[2024-08-28T21:32:06.310Z] Movies recommended for you:
[2024-08-28T21:32:06.310Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:32:06.310Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:32:06.310Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (23227.551 ms) ======
[2024-08-28T21:32:06.310Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-28T21:32:06.310Z] GC before operation: completed in 122.862 ms, heap usage 227.524 MB -> 50.198 MB.
[2024-08-28T21:32:09.987Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:32:12.874Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:32:16.654Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:32:20.398Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:32:22.009Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:32:24.042Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:32:26.942Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:32:28.957Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:32:28.957Z] 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.
[2024-08-28T21:32:28.957Z] The best model improves the baseline by 14.34%.
[2024-08-28T21:32:28.957Z] Movies recommended for you:
[2024-08-28T21:32:28.957Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:32:28.957Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:32:28.957Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (22597.987 ms) ======
[2024-08-28T21:32:28.957Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-28T21:32:28.957Z] GC before operation: completed in 110.656 ms, heap usage 77.908 MB -> 52.887 MB.
[2024-08-28T21:32:32.685Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:32:36.471Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:32:40.169Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:32:42.971Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:32:45.085Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:32:47.100Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:32:49.153Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:32:51.180Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:32:51.783Z] 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.
[2024-08-28T21:32:51.783Z] The best model improves the baseline by 14.34%.
[2024-08-28T21:32:51.783Z] Movies recommended for you:
[2024-08-28T21:32:51.783Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:32:51.783Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:32:51.783Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (22670.130 ms) ======
[2024-08-28T21:32:51.783Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-28T21:32:51.783Z] GC before operation: completed in 111.669 ms, heap usage 143.574 MB -> 50.376 MB.
[2024-08-28T21:32:55.514Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-28T21:32:59.463Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-28T21:33:03.305Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-28T21:33:06.172Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-28T21:33:08.249Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-28T21:33:10.288Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-28T21:33:12.355Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-28T21:33:14.432Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-28T21:33:15.131Z] 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.
[2024-08-28T21:33:15.131Z] The best model improves the baseline by 14.34%.
[2024-08-28T21:33:15.131Z] Movies recommended for you:
[2024-08-28T21:33:15.131Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-28T21:33:15.131Z] There is no way to check that no silent failure occurred.
[2024-08-28T21:33:15.131Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (23188.099 ms) ======
[2024-08-28T21:33:15.772Z] -----------------------------------
[2024-08-28T21:33:15.772Z] renaissance-movie-lens_0_PASSED
[2024-08-28T21:33:15.772Z] -----------------------------------
[2024-08-28T21:33:15.772Z]
[2024-08-28T21:33:15.772Z] TEST TEARDOWN:
[2024-08-28T21:33:15.772Z] Nothing to be done for teardown.
[2024-08-28T21:33:15.772Z] renaissance-movie-lens_0 Finish Time: Wed Aug 28 21:33:15 2024 Epoch Time (ms): 1724880795579