renaissance-movie-lens_0
[2025-02-20T00:06:43.969Z] Running test renaissance-movie-lens_0 ...
[2025-02-20T00:06:43.969Z] ===============================================
[2025-02-20T00:06:43.969Z] renaissance-movie-lens_0 Start Time: Thu Feb 20 00:06:43 2025 Epoch Time (ms): 1740010003652
[2025-02-20T00:06:43.969Z] variation: NoOptions
[2025-02-20T00:06:43.969Z] JVM_OPTIONS:
[2025-02-20T00:06:43.969Z] { \
[2025-02-20T00:06:43.969Z] echo ""; echo "TEST SETUP:"; \
[2025-02-20T00:06:43.969Z] echo "Nothing to be done for setup."; \
[2025-02-20T00:06:43.969Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17400090911854/renaissance-movie-lens_0"; \
[2025-02-20T00:06:43.969Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17400090911854/renaissance-movie-lens_0"; \
[2025-02-20T00:06:43.969Z] echo ""; echo "TESTING:"; \
[2025-02-20T00:06:43.969Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_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_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17400090911854/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-02-20T00:06:43.969Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17400090911854/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-02-20T00:06:43.969Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-02-20T00:06:43.969Z] echo "Nothing to be done for teardown."; \
[2025-02-20T00:06:43.969Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17400090911854/TestTargetResult";
[2025-02-20T00:06:43.969Z]
[2025-02-20T00:06:43.969Z] TEST SETUP:
[2025-02-20T00:06:43.969Z] Nothing to be done for setup.
[2025-02-20T00:06:43.969Z]
[2025-02-20T00:06:43.969Z] TESTING:
[2025-02-20T00:06:47.660Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-02-20T00:06:50.669Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2025-02-20T00:06:54.809Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-02-20T00:06:55.758Z] Training: 60056, validation: 20285, test: 19854
[2025-02-20T00:06:55.758Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-02-20T00:06:55.758Z] GC before operation: completed in 83.644 ms, heap usage 202.443 MB -> 37.201 MB.
[2025-02-20T00:07:03.883Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T00:07:09.313Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T00:07:13.479Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T00:07:16.489Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T00:07:18.438Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T00:07:20.391Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T00:07:22.341Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T00:07:24.289Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T00:07:24.290Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T00:07:24.290Z] The best model improves the baseline by 14.43%.
[2025-02-20T00:07:25.241Z] Movies recommended for you:
[2025-02-20T00:07:25.241Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T00:07:25.241Z] There is no way to check that no silent failure occurred.
[2025-02-20T00:07:25.241Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (29499.707 ms) ======
[2025-02-20T00:07:25.241Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-02-20T00:07:25.241Z] GC before operation: completed in 175.412 ms, heap usage 337.864 MB -> 50.531 MB.
[2025-02-20T00:07:28.247Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T00:07:31.257Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T00:07:34.719Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T00:07:37.731Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T00:07:39.682Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T00:07:42.753Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T00:07:43.702Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T00:07:46.720Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T00:07:46.720Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T00:07:46.720Z] The best model improves the baseline by 14.43%.
[2025-02-20T00:07:46.720Z] Movies recommended for you:
[2025-02-20T00:07:46.720Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T00:07:46.720Z] There is no way to check that no silent failure occurred.
[2025-02-20T00:07:46.720Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (21774.703 ms) ======
[2025-02-20T00:07:46.720Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-02-20T00:07:46.720Z] GC before operation: completed in 173.962 ms, heap usage 269.516 MB -> 50.921 MB.
[2025-02-20T00:07:50.867Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T00:07:53.879Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T00:07:56.889Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T00:07:59.899Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T00:08:01.850Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T00:08:03.800Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T00:08:05.751Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T00:08:07.702Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T00:08:07.702Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T00:08:07.702Z] The best model improves the baseline by 14.43%.
[2025-02-20T00:08:07.702Z] Movies recommended for you:
[2025-02-20T00:08:07.702Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T00:08:07.702Z] There is no way to check that no silent failure occurred.
[2025-02-20T00:08:07.702Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (21046.246 ms) ======
[2025-02-20T00:08:07.702Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-02-20T00:08:08.651Z] GC before operation: completed in 146.158 ms, heap usage 344.045 MB -> 51.386 MB.
[2025-02-20T00:08:11.662Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T00:08:13.612Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T00:08:16.633Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T00:08:19.645Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T00:08:20.595Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T00:08:22.549Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T00:08:24.503Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T00:08:25.453Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T00:08:25.453Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T00:08:25.453Z] The best model improves the baseline by 14.43%.
[2025-02-20T00:08:25.453Z] Movies recommended for you:
[2025-02-20T00:08:25.453Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T00:08:25.453Z] There is no way to check that no silent failure occurred.
[2025-02-20T00:08:25.453Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (17585.135 ms) ======
[2025-02-20T00:08:25.453Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-02-20T00:08:26.403Z] GC before operation: completed in 149.224 ms, heap usage 254.448 MB -> 51.661 MB.
[2025-02-20T00:08:28.352Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T00:08:30.304Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T00:08:32.254Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T00:08:35.267Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T00:08:36.217Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T00:08:37.167Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T00:08:39.168Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T00:08:40.120Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T00:08:41.805Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T00:08:41.805Z] The best model improves the baseline by 14.43%.
[2025-02-20T00:08:41.805Z] Movies recommended for you:
[2025-02-20T00:08:41.805Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T00:08:41.805Z] There is no way to check that no silent failure occurred.
[2025-02-20T00:08:41.805Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (14815.528 ms) ======
[2025-02-20T00:08:41.805Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-02-20T00:08:41.805Z] GC before operation: completed in 143.637 ms, heap usage 186.025 MB -> 51.829 MB.
[2025-02-20T00:08:43.763Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T00:08:46.785Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T00:08:48.745Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T00:08:51.769Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T00:08:52.724Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T00:08:54.682Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T00:08:56.640Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T00:08:57.593Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T00:08:58.545Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T00:08:58.545Z] The best model improves the baseline by 14.43%.
[2025-02-20T00:08:58.545Z] Movies recommended for you:
[2025-02-20T00:08:58.545Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T00:08:58.545Z] There is no way to check that no silent failure occurred.
[2025-02-20T00:08:58.545Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (17356.589 ms) ======
[2025-02-20T00:08:58.545Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-02-20T00:08:58.545Z] GC before operation: completed in 144.170 ms, heap usage 359.689 MB -> 51.836 MB.
[2025-02-20T00:09:01.563Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T00:09:03.519Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T00:09:06.585Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T00:09:08.538Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T00:09:10.497Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T00:09:11.453Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T00:09:13.412Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T00:09:14.367Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T00:09:15.320Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T00:09:15.320Z] The best model improves the baseline by 14.43%.
[2025-02-20T00:09:15.320Z] Movies recommended for you:
[2025-02-20T00:09:15.320Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T00:09:15.320Z] There is no way to check that no silent failure occurred.
[2025-02-20T00:09:15.320Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (16803.487 ms) ======
[2025-02-20T00:09:15.320Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-02-20T00:09:15.320Z] GC before operation: completed in 185.093 ms, heap usage 214.148 MB -> 51.907 MB.
[2025-02-20T00:09:18.343Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T00:09:21.366Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T00:09:24.400Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T00:09:26.358Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T00:09:28.310Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T00:09:30.267Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T00:09:32.227Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T00:09:34.187Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T00:09:35.140Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T00:09:35.140Z] The best model improves the baseline by 14.43%.
[2025-02-20T00:09:35.140Z] Movies recommended for you:
[2025-02-20T00:09:35.140Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T00:09:35.140Z] There is no way to check that no silent failure occurred.
[2025-02-20T00:09:35.140Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (19467.316 ms) ======
[2025-02-20T00:09:35.140Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-02-20T00:09:35.140Z] GC before operation: completed in 146.734 ms, heap usage 306.220 MB -> 52.246 MB.
[2025-02-20T00:09:38.173Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T00:09:41.218Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T00:09:44.245Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T00:09:46.205Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T00:09:48.163Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T00:09:50.865Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T00:09:51.826Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T00:09:53.782Z] RMSE (validation) = 0.9001440981626696 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T00:09:54.731Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T00:09:54.731Z] The best model improves the baseline by 14.43%.
[2025-02-20T00:09:54.731Z] Movies recommended for you:
[2025-02-20T00:09:54.731Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T00:09:54.731Z] There is no way to check that no silent failure occurred.
[2025-02-20T00:09:54.731Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (19625.624 ms) ======
[2025-02-20T00:09:54.731Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-02-20T00:09:54.731Z] GC before operation: completed in 141.045 ms, heap usage 125.218 MB -> 51.958 MB.
[2025-02-20T00:09:57.739Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T00:09:59.687Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T00:10:02.702Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T00:10:04.651Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T00:10:05.600Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T00:10:07.582Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T00:10:09.532Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T00:10:10.482Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T00:10:11.432Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T00:10:11.432Z] The best model improves the baseline by 14.43%.
[2025-02-20T00:10:11.432Z] Movies recommended for you:
[2025-02-20T00:10:11.432Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T00:10:11.432Z] There is no way to check that no silent failure occurred.
[2025-02-20T00:10:11.432Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (16687.533 ms) ======
[2025-02-20T00:10:11.432Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-02-20T00:10:11.432Z] GC before operation: completed in 153.837 ms, heap usage 244.225 MB -> 52.167 MB.
[2025-02-20T00:10:14.442Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T00:10:16.390Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T00:10:19.399Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T00:10:22.421Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T00:10:23.370Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T00:10:25.319Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T00:10:27.269Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T00:10:28.219Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T00:10:29.169Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T00:10:29.169Z] The best model improves the baseline by 14.43%.
[2025-02-20T00:10:29.169Z] Movies recommended for you:
[2025-02-20T00:10:29.169Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T00:10:29.169Z] There is no way to check that no silent failure occurred.
[2025-02-20T00:10:29.169Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (17188.886 ms) ======
[2025-02-20T00:10:29.169Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-02-20T00:10:29.169Z] GC before operation: completed in 139.037 ms, heap usage 209.809 MB -> 51.857 MB.
[2025-02-20T00:10:31.119Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T00:10:33.087Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T00:10:34.035Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T00:10:35.984Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T00:10:36.934Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T00:10:38.882Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T00:10:39.922Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T00:10:40.872Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T00:10:40.872Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T00:10:40.872Z] The best model improves the baseline by 14.43%.
[2025-02-20T00:10:40.872Z] Movies recommended for you:
[2025-02-20T00:10:40.872Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T00:10:40.872Z] There is no way to check that no silent failure occurred.
[2025-02-20T00:10:40.872Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (12150.938 ms) ======
[2025-02-20T00:10:40.872Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-02-20T00:10:40.872Z] GC before operation: completed in 127.036 ms, heap usage 170.461 MB -> 52.021 MB.
[2025-02-20T00:10:42.821Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T00:10:44.770Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T00:10:46.719Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T00:10:48.675Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T00:10:49.624Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T00:10:51.609Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T00:10:52.559Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T00:10:53.509Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T00:10:53.509Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T00:10:53.509Z] The best model improves the baseline by 14.43%.
[2025-02-20T00:10:53.509Z] Movies recommended for you:
[2025-02-20T00:10:53.509Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T00:10:53.509Z] There is no way to check that no silent failure occurred.
[2025-02-20T00:10:53.509Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (12453.098 ms) ======
[2025-02-20T00:10:53.509Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-02-20T00:10:53.509Z] GC before operation: completed in 136.151 ms, heap usage 187.357 MB -> 52.268 MB.
[2025-02-20T00:10:55.460Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T00:10:57.416Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T00:10:59.092Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T00:11:01.043Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T00:11:01.996Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T00:11:03.952Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T00:11:04.902Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T00:11:05.853Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T00:11:05.853Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T00:11:05.853Z] The best model improves the baseline by 14.43%.
[2025-02-20T00:11:05.853Z] Movies recommended for you:
[2025-02-20T00:11:05.853Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T00:11:05.853Z] There is no way to check that no silent failure occurred.
[2025-02-20T00:11:05.853Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (12171.218 ms) ======
[2025-02-20T00:11:05.853Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-02-20T00:11:05.853Z] GC before operation: completed in 127.629 ms, heap usage 210.938 MB -> 51.950 MB.
[2025-02-20T00:11:08.860Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T00:11:10.816Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T00:11:13.822Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T00:11:15.821Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T00:11:17.773Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T00:11:18.723Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T00:11:20.674Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T00:11:22.623Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T00:11:22.623Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T00:11:22.623Z] The best model improves the baseline by 14.43%.
[2025-02-20T00:11:22.623Z] Movies recommended for you:
[2025-02-20T00:11:22.623Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T00:11:22.623Z] There is no way to check that no silent failure occurred.
[2025-02-20T00:11:22.623Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (16356.814 ms) ======
[2025-02-20T00:11:22.623Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-02-20T00:11:22.623Z] GC before operation: completed in 145.121 ms, heap usage 248.777 MB -> 52.193 MB.
[2025-02-20T00:11:24.608Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T00:11:27.617Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T00:11:29.777Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T00:11:32.789Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T00:11:33.740Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T00:11:35.688Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T00:11:36.640Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T00:11:38.589Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T00:11:38.589Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T00:11:38.589Z] The best model improves the baseline by 14.43%.
[2025-02-20T00:11:38.589Z] Movies recommended for you:
[2025-02-20T00:11:38.589Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T00:11:38.589Z] There is no way to check that no silent failure occurred.
[2025-02-20T00:11:38.589Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (16121.748 ms) ======
[2025-02-20T00:11:38.589Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-02-20T00:11:38.589Z] GC before operation: completed in 140.184 ms, heap usage 585.386 MB -> 55.678 MB.
[2025-02-20T00:11:41.620Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T00:11:43.574Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T00:11:46.617Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T00:11:48.567Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T00:11:50.518Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T00:11:51.468Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T00:11:53.419Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T00:11:54.369Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T00:11:54.369Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T00:11:55.318Z] The best model improves the baseline by 14.43%.
[2025-02-20T00:11:55.318Z] Movies recommended for you:
[2025-02-20T00:11:55.318Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T00:11:55.318Z] There is no way to check that no silent failure occurred.
[2025-02-20T00:11:55.318Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (16046.716 ms) ======
[2025-02-20T00:11:55.318Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-02-20T00:11:55.318Z] GC before operation: completed in 135.465 ms, heap usage 273.744 MB -> 52.048 MB.
[2025-02-20T00:11:57.270Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T00:12:00.283Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T00:12:02.232Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T00:12:05.246Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T00:12:06.647Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T00:12:07.597Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T00:12:09.548Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T00:12:10.517Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T00:12:11.466Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T00:12:11.466Z] The best model improves the baseline by 14.43%.
[2025-02-20T00:12:11.466Z] Movies recommended for you:
[2025-02-20T00:12:11.466Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T00:12:11.466Z] There is no way to check that no silent failure occurred.
[2025-02-20T00:12:11.466Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (16217.640 ms) ======
[2025-02-20T00:12:11.466Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-02-20T00:12:11.466Z] GC before operation: completed in 139.946 ms, heap usage 290.819 MB -> 52.147 MB.
[2025-02-20T00:12:14.478Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T00:12:16.427Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T00:12:19.441Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T00:12:21.403Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T00:12:23.353Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T00:12:24.303Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T00:12:26.255Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T00:12:27.205Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T00:12:27.205Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T00:12:27.205Z] The best model improves the baseline by 14.43%.
[2025-02-20T00:12:27.205Z] Movies recommended for you:
[2025-02-20T00:12:27.205Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T00:12:27.205Z] There is no way to check that no silent failure occurred.
[2025-02-20T00:12:27.205Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (16170.160 ms) ======
[2025-02-20T00:12:27.205Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-02-20T00:12:28.155Z] GC before operation: completed in 135.766 ms, heap usage 303.399 MB -> 52.383 MB.
[2025-02-20T00:12:30.108Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-20T00:12:33.124Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-20T00:12:35.111Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-20T00:12:37.065Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-20T00:12:39.168Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-20T00:12:40.124Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-20T00:12:42.089Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-20T00:12:43.039Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-20T00:12:43.992Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-02-20T00:12:43.992Z] The best model improves the baseline by 14.43%.
[2025-02-20T00:12:43.992Z] Movies recommended for you:
[2025-02-20T00:12:43.992Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-20T00:12:43.992Z] There is no way to check that no silent failure occurred.
[2025-02-20T00:12:43.992Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (15980.082 ms) ======
[2025-02-20T00:12:44.942Z] -----------------------------------
[2025-02-20T00:12:44.942Z] renaissance-movie-lens_0_PASSED
[2025-02-20T00:12:44.942Z] -----------------------------------
[2025-02-20T00:12:44.942Z]
[2025-02-20T00:12:44.942Z] TEST TEARDOWN:
[2025-02-20T00:12:44.942Z] Nothing to be done for teardown.
[2025-02-20T00:12:44.942Z] renaissance-movie-lens_0 Finish Time: Thu Feb 20 00:12:44 2025 Epoch Time (ms): 1740010364589