renaissance-movie-lens_0
[2024-11-17T22:25:43.829Z] Running test renaissance-movie-lens_0 ...
[2024-11-17T22:25:43.829Z] ===============================================
[2024-11-17T22:25:43.829Z] renaissance-movie-lens_0 Start Time: Sun Nov 17 22:25:43 2024 Epoch Time (ms): 1731882343369
[2024-11-17T22:25:43.829Z] variation: NoOptions
[2024-11-17T22:25:43.829Z] JVM_OPTIONS:
[2024-11-17T22:25:43.829Z] { \
[2024-11-17T22:25:43.829Z] echo ""; echo "TEST SETUP:"; \
[2024-11-17T22:25:43.829Z] echo "Nothing to be done for setup."; \
[2024-11-17T22:25:43.829Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17318813106595/renaissance-movie-lens_0"; \
[2024-11-17T22:25:43.829Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17318813106595/renaissance-movie-lens_0"; \
[2024-11-17T22:25:43.829Z] echo ""; echo "TESTING:"; \
[2024-11-17T22:25:43.829Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/jdkbinary/j2sdk-image/jdk-11.0.26+1/bin/..//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_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17318813106595/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-17T22:25:43.829Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17318813106595/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-17T22:25:43.829Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-17T22:25:43.829Z] echo "Nothing to be done for teardown."; \
[2024-11-17T22:25:43.829Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17318813106595/TestTargetResult";
[2024-11-17T22:25:43.829Z]
[2024-11-17T22:25:43.829Z] TEST SETUP:
[2024-11-17T22:25:43.829Z] Nothing to be done for setup.
[2024-11-17T22:25:43.829Z]
[2024-11-17T22:25:43.829Z] TESTING:
[2024-11-17T22:25:45.928Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-17T22:25:47.999Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads.
[2024-11-17T22:25:51.782Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-17T22:25:51.782Z] Training: 60056, validation: 20285, test: 19854
[2024-11-17T22:25:51.782Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-17T22:25:51.782Z] GC before operation: completed in 73.647 ms, heap usage 87.666 MB -> 36.338 MB.
[2024-11-17T22:25:58.974Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-17T22:26:02.762Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-17T22:26:06.540Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-17T22:26:08.605Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-17T22:26:10.664Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-17T22:26:11.984Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-17T22:26:13.307Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-17T22:26:15.002Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-17T22:26:15.646Z] 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.
[2024-11-17T22:26:15.646Z] The best model improves the baseline by 14.34%.
[2024-11-17T22:26:15.646Z] Movies recommended for you:
[2024-11-17T22:26:15.646Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-17T22:26:15.646Z] There is no way to check that no silent failure occurred.
[2024-11-17T22:26:15.646Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (23826.827 ms) ======
[2024-11-17T22:26:15.646Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-17T22:26:15.646Z] GC before operation: completed in 115.215 ms, heap usage 153.994 MB -> 46.472 MB.
[2024-11-17T22:26:18.525Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-17T22:26:20.581Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-17T22:26:23.469Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-17T22:26:25.532Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-17T22:26:26.852Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-17T22:26:28.168Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-17T22:26:29.486Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-17T22:26:30.798Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-17T22:26:30.798Z] 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.
[2024-11-17T22:26:30.798Z] The best model improves the baseline by 14.34%.
[2024-11-17T22:26:31.431Z] Movies recommended for you:
[2024-11-17T22:26:31.431Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-17T22:26:31.431Z] There is no way to check that no silent failure occurred.
[2024-11-17T22:26:31.431Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (15433.408 ms) ======
[2024-11-17T22:26:31.431Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-17T22:26:31.431Z] GC before operation: completed in 92.937 ms, heap usage 90.040 MB -> 48.280 MB.
[2024-11-17T22:26:33.490Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-17T22:26:35.549Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-17T22:26:38.413Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-17T22:26:40.469Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-17T22:26:41.105Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-17T22:26:42.422Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-17T22:26:43.738Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-17T22:26:45.052Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-17T22:26:45.684Z] 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.
[2024-11-17T22:26:45.684Z] The best model improves the baseline by 14.34%.
[2024-11-17T22:26:45.684Z] Movies recommended for you:
[2024-11-17T22:26:45.684Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-17T22:26:45.684Z] There is no way to check that no silent failure occurred.
[2024-11-17T22:26:45.684Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (14207.680 ms) ======
[2024-11-17T22:26:45.684Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-17T22:26:45.684Z] GC before operation: completed in 96.135 ms, heap usage 228.655 MB -> 48.722 MB.
[2024-11-17T22:26:47.767Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-17T22:26:49.821Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-17T22:26:51.877Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-17T22:26:54.327Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-17T22:26:54.960Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-17T22:26:56.273Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-17T22:26:57.588Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-17T22:26:58.221Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-17T22:26:58.221Z] 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.
[2024-11-17T22:26:58.221Z] The best model improves the baseline by 14.34%.
[2024-11-17T22:26:58.855Z] Movies recommended for you:
[2024-11-17T22:26:58.855Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-17T22:26:58.855Z] There is no way to check that no silent failure occurred.
[2024-11-17T22:26:58.855Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (13009.927 ms) ======
[2024-11-17T22:26:58.855Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-17T22:26:58.855Z] GC before operation: completed in 101.430 ms, heap usage 249.119 MB -> 49.054 MB.
[2024-11-17T22:27:00.919Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-17T22:27:02.981Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-17T22:27:05.044Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-17T22:27:07.106Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-17T22:27:07.740Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-17T22:27:09.055Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-17T22:27:10.380Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-17T22:27:11.699Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-17T22:27:11.699Z] 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.
[2024-11-17T22:27:11.699Z] The best model improves the baseline by 14.34%.
[2024-11-17T22:27:11.699Z] Movies recommended for you:
[2024-11-17T22:27:11.699Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-17T22:27:11.699Z] There is no way to check that no silent failure occurred.
[2024-11-17T22:27:11.699Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (13080.656 ms) ======
[2024-11-17T22:27:11.699Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-17T22:27:11.699Z] GC before operation: completed in 104.252 ms, heap usage 334.247 MB -> 52.488 MB.
[2024-11-17T22:27:13.759Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-17T22:27:15.817Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-17T22:27:17.916Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-17T22:27:19.984Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-17T22:27:21.299Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-17T22:27:21.931Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-17T22:27:23.248Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-17T22:27:24.569Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-17T22:27:24.569Z] 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.
[2024-11-17T22:27:24.569Z] The best model improves the baseline by 14.34%.
[2024-11-17T22:27:24.569Z] Movies recommended for you:
[2024-11-17T22:27:24.569Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-17T22:27:24.569Z] There is no way to check that no silent failure occurred.
[2024-11-17T22:27:24.569Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (12995.502 ms) ======
[2024-11-17T22:27:24.569Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-17T22:27:25.201Z] GC before operation: completed in 95.418 ms, heap usage 88.558 MB -> 49.027 MB.
[2024-11-17T22:27:26.602Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-17T22:27:28.661Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-17T22:27:30.715Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-17T22:27:32.771Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-17T22:27:34.471Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-17T22:27:35.105Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-17T22:27:36.425Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-17T22:27:37.741Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-17T22:27:37.742Z] 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.
[2024-11-17T22:27:37.742Z] The best model improves the baseline by 14.34%.
[2024-11-17T22:27:37.742Z] Movies recommended for you:
[2024-11-17T22:27:37.742Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-17T22:27:37.742Z] There is no way to check that no silent failure occurred.
[2024-11-17T22:27:37.742Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (13010.705 ms) ======
[2024-11-17T22:27:37.742Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-17T22:27:37.742Z] GC before operation: completed in 104.737 ms, heap usage 109.096 MB -> 49.699 MB.
[2024-11-17T22:27:39.854Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-17T22:27:41.912Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-17T22:27:44.069Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-17T22:27:45.385Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-17T22:27:46.700Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-17T22:27:47.332Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-17T22:27:49.394Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-17T22:27:50.709Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-17T22:27:50.709Z] 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.
[2024-11-17T22:27:50.709Z] The best model improves the baseline by 14.34%.
[2024-11-17T22:27:50.709Z] Movies recommended for you:
[2024-11-17T22:27:50.709Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-17T22:27:50.709Z] There is no way to check that no silent failure occurred.
[2024-11-17T22:27:50.709Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (12931.220 ms) ======
[2024-11-17T22:27:50.709Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-17T22:27:51.340Z] GC before operation: completed in 178.395 ms, heap usage 116.845 MB -> 49.458 MB.
[2024-11-17T22:27:53.396Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-17T22:27:54.711Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-17T22:27:56.772Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-17T22:27:58.834Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-17T22:28:00.148Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-17T22:28:00.782Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-17T22:28:02.858Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-17T22:28:04.172Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-17T22:28:04.173Z] 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.
[2024-11-17T22:28:04.173Z] The best model improves the baseline by 14.34%.
[2024-11-17T22:28:04.173Z] Movies recommended for you:
[2024-11-17T22:28:04.173Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-17T22:28:04.173Z] There is no way to check that no silent failure occurred.
[2024-11-17T22:28:04.173Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (13072.850 ms) ======
[2024-11-17T22:28:04.173Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-17T22:28:04.173Z] GC before operation: completed in 99.158 ms, heap usage 114.146 MB -> 49.318 MB.
[2024-11-17T22:28:07.045Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-17T22:28:08.362Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-17T22:28:10.829Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-17T22:28:12.150Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-17T22:28:13.487Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-17T22:28:14.802Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-17T22:28:15.432Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-17T22:28:16.796Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-17T22:28:16.796Z] 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.
[2024-11-17T22:28:16.796Z] The best model improves the baseline by 14.34%.
[2024-11-17T22:28:16.796Z] Movies recommended for you:
[2024-11-17T22:28:16.796Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-17T22:28:16.796Z] There is no way to check that no silent failure occurred.
[2024-11-17T22:28:16.796Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (12596.468 ms) ======
[2024-11-17T22:28:16.796Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-17T22:28:16.796Z] GC before operation: completed in 106.341 ms, heap usage 223.554 MB -> 49.593 MB.
[2024-11-17T22:28:18.859Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-17T22:28:20.926Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-17T22:28:22.984Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-17T22:28:24.301Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-17T22:28:25.613Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-17T22:28:26.247Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-17T22:28:27.567Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-17T22:28:28.884Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-17T22:28:28.884Z] 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.
[2024-11-17T22:28:28.884Z] The best model improves the baseline by 14.34%.
[2024-11-17T22:28:28.884Z] Movies recommended for you:
[2024-11-17T22:28:28.884Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-17T22:28:28.884Z] There is no way to check that no silent failure occurred.
[2024-11-17T22:28:28.884Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (11969.882 ms) ======
[2024-11-17T22:28:28.885Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-17T22:28:28.885Z] GC before operation: completed in 94.007 ms, heap usage 111.020 MB -> 49.128 MB.
[2024-11-17T22:28:30.946Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-17T22:28:33.099Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-17T22:28:34.413Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-17T22:28:35.730Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-17T22:28:37.055Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-17T22:28:37.686Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-17T22:28:39.003Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-17T22:28:39.635Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-17T22:28:39.635Z] 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.
[2024-11-17T22:28:40.268Z] The best model improves the baseline by 14.34%.
[2024-11-17T22:28:40.268Z] Movies recommended for you:
[2024-11-17T22:28:40.268Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-17T22:28:40.268Z] There is no way to check that no silent failure occurred.
[2024-11-17T22:28:40.268Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (10921.565 ms) ======
[2024-11-17T22:28:40.268Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-17T22:28:40.268Z] GC before operation: completed in 107.545 ms, heap usage 366.606 MB -> 52.788 MB.
[2024-11-17T22:28:42.400Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-17T22:28:43.806Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-17T22:28:45.860Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-17T22:28:48.054Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-17T22:28:48.703Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-17T22:28:50.019Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-17T22:28:51.334Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-17T22:28:52.651Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-17T22:28:52.651Z] 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.
[2024-11-17T22:28:52.651Z] The best model improves the baseline by 14.34%.
[2024-11-17T22:28:52.651Z] Movies recommended for you:
[2024-11-17T22:28:52.651Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-17T22:28:52.651Z] There is no way to check that no silent failure occurred.
[2024-11-17T22:28:52.651Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (12644.841 ms) ======
[2024-11-17T22:28:52.651Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-17T22:28:52.651Z] GC before operation: completed in 93.949 ms, heap usage 93.702 MB -> 49.479 MB.
[2024-11-17T22:28:54.710Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-17T22:28:56.768Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-17T22:28:58.835Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-17T22:29:00.152Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-17T22:29:01.471Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-17T22:29:02.106Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-17T22:29:03.423Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-17T22:29:04.739Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-17T22:29:04.739Z] 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.
[2024-11-17T22:29:04.739Z] The best model improves the baseline by 14.34%.
[2024-11-17T22:29:04.739Z] Movies recommended for you:
[2024-11-17T22:29:04.739Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-17T22:29:04.739Z] There is no way to check that no silent failure occurred.
[2024-11-17T22:29:04.739Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (12027.202 ms) ======
[2024-11-17T22:29:04.739Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-17T22:29:04.739Z] GC before operation: completed in 95.735 ms, heap usage 108.356 MB -> 49.279 MB.
[2024-11-17T22:29:06.800Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-17T22:29:08.856Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-17T22:29:10.913Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-17T22:29:12.225Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-17T22:29:13.549Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-17T22:29:14.184Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-17T22:29:15.496Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-17T22:29:16.129Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-17T22:29:16.761Z] 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.
[2024-11-17T22:29:16.761Z] The best model improves the baseline by 14.34%.
[2024-11-17T22:29:16.761Z] Movies recommended for you:
[2024-11-17T22:29:16.761Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-17T22:29:16.761Z] There is no way to check that no silent failure occurred.
[2024-11-17T22:29:16.761Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (11669.389 ms) ======
[2024-11-17T22:29:16.761Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-17T22:29:16.761Z] GC before operation: completed in 99.261 ms, heap usage 210.030 MB -> 49.626 MB.
[2024-11-17T22:29:18.822Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-17T22:29:20.884Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-17T22:29:22.198Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-17T22:29:24.267Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-17T22:29:25.280Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-17T22:29:25.910Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-17T22:29:27.230Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-17T22:29:28.548Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-17T22:29:28.548Z] 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.
[2024-11-17T22:29:28.548Z] The best model improves the baseline by 14.34%.
[2024-11-17T22:29:28.548Z] Movies recommended for you:
[2024-11-17T22:29:28.548Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-17T22:29:28.548Z] There is no way to check that no silent failure occurred.
[2024-11-17T22:29:28.548Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (11870.046 ms) ======
[2024-11-17T22:29:28.548Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-17T22:29:28.548Z] GC before operation: completed in 94.296 ms, heap usage 107.111 MB -> 49.464 MB.
[2024-11-17T22:29:30.604Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-17T22:29:32.668Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-17T22:29:34.726Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-17T22:29:36.046Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-17T22:29:37.363Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-17T22:29:37.996Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-17T22:29:39.312Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-17T22:29:39.949Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-17T22:29:40.583Z] 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.
[2024-11-17T22:29:40.583Z] The best model improves the baseline by 14.34%.
[2024-11-17T22:29:40.583Z] Movies recommended for you:
[2024-11-17T22:29:40.583Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-17T22:29:40.583Z] There is no way to check that no silent failure occurred.
[2024-11-17T22:29:40.583Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (11655.619 ms) ======
[2024-11-17T22:29:40.583Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-17T22:29:40.583Z] GC before operation: completed in 98.161 ms, heap usage 212.069 MB -> 49.470 MB.
[2024-11-17T22:29:42.639Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-17T22:29:43.962Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-17T22:29:46.019Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-17T22:29:48.075Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-17T22:29:48.709Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-17T22:29:49.341Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-17T22:29:50.660Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-17T22:29:51.292Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-17T22:29:51.931Z] 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.
[2024-11-17T22:29:51.931Z] The best model improves the baseline by 14.34%.
[2024-11-17T22:29:51.931Z] Movies recommended for you:
[2024-11-17T22:29:51.931Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-17T22:29:51.931Z] There is no way to check that no silent failure occurred.
[2024-11-17T22:29:51.931Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (11347.163 ms) ======
[2024-11-17T22:29:51.931Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-17T22:29:51.931Z] GC before operation: completed in 102.307 ms, heap usage 61.780 MB -> 52.118 MB.
[2024-11-17T22:29:53.991Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-17T22:29:56.054Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-17T22:29:57.380Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-17T22:29:59.437Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-17T22:30:00.070Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-17T22:30:01.386Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-17T22:30:02.702Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-17T22:30:03.728Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-17T22:30:03.728Z] 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.
[2024-11-17T22:30:03.728Z] The best model improves the baseline by 14.34%.
[2024-11-17T22:30:03.728Z] Movies recommended for you:
[2024-11-17T22:30:03.728Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-17T22:30:03.728Z] There is no way to check that no silent failure occurred.
[2024-11-17T22:30:03.728Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (11734.758 ms) ======
[2024-11-17T22:30:03.728Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-17T22:30:03.728Z] GC before operation: completed in 94.709 ms, heap usage 71.498 MB -> 51.006 MB.
[2024-11-17T22:30:05.787Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-17T22:30:07.101Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-17T22:30:09.159Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-17T22:30:11.217Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-17T22:30:11.849Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-17T22:30:13.166Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-17T22:30:13.797Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-17T22:30:15.111Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-17T22:30:15.111Z] 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.
[2024-11-17T22:30:15.111Z] The best model improves the baseline by 14.34%.
[2024-11-17T22:30:15.111Z] Movies recommended for you:
[2024-11-17T22:30:15.111Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-17T22:30:15.111Z] There is no way to check that no silent failure occurred.
[2024-11-17T22:30:15.111Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (11539.524 ms) ======
[2024-11-17T22:30:15.745Z] -----------------------------------
[2024-11-17T22:30:15.745Z] renaissance-movie-lens_0_PASSED
[2024-11-17T22:30:15.745Z] -----------------------------------
[2024-11-17T22:30:15.745Z]
[2024-11-17T22:30:15.745Z] TEST TEARDOWN:
[2024-11-17T22:30:15.745Z] Nothing to be done for teardown.
[2024-11-17T22:30:15.745Z] renaissance-movie-lens_0 Finish Time: Sun Nov 17 22:30:15 2024 Epoch Time (ms): 1731882615407