renaissance-movie-lens_0
[2024-08-21T21:25:00.411Z] Running test renaissance-movie-lens_0 ...
[2024-08-21T21:25:00.411Z] ===============================================
[2024-08-21T21:25:00.411Z] renaissance-movie-lens_0 Start Time: Wed Aug 21 21:24:59 2024 Epoch Time (ms): 1724275499761
[2024-08-21T21:25:00.411Z] variation: NoOptions
[2024-08-21T21:25:00.411Z] JVM_OPTIONS:
[2024-08-21T21:25:00.411Z] { \
[2024-08-21T21:25:00.411Z] echo ""; echo "TEST SETUP:"; \
[2024-08-21T21:25:00.411Z] echo "Nothing to be done for setup."; \
[2024-08-21T21:25:00.411Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17242745915982/renaissance-movie-lens_0"; \
[2024-08-21T21:25:00.411Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17242745915982/renaissance-movie-lens_0"; \
[2024-08-21T21:25:00.411Z] echo ""; echo "TESTING:"; \
[2024-08-21T21:25:00.411Z] "/home/jenkins/workspace/Test_openjdk17_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_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17242745915982/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-21T21:25:00.411Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17242745915982/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-21T21:25:00.411Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-21T21:25:00.411Z] echo "Nothing to be done for teardown."; \
[2024-08-21T21:25:00.411Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17242745915982/TestTargetResult";
[2024-08-21T21:25:00.411Z]
[2024-08-21T21:25:00.411Z] TEST SETUP:
[2024-08-21T21:25:00.411Z] Nothing to be done for setup.
[2024-08-21T21:25:00.411Z]
[2024-08-21T21:25:00.411Z] TESTING:
[2024-08-21T21:25:04.513Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-21T21:25:07.487Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2024-08-21T21:25:11.586Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-21T21:25:11.586Z] Training: 60056, validation: 20285, test: 19854
[2024-08-21T21:25:11.586Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-21T21:25:11.586Z] GC before operation: completed in 63.983 ms, heap usage 99.786 MB -> 39.500 MB.
[2024-08-21T21:25:19.648Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:25:23.742Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:25:26.723Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:25:30.830Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:25:32.756Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:25:33.699Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:25:36.677Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:25:37.616Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:25:38.564Z] 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.
[2024-08-21T21:25:38.564Z] The best model improves the baseline by 14.43%.
[2024-08-21T21:25:38.564Z] Movies recommended for you:
[2024-08-21T21:25:38.564Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:25:38.564Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:25:38.564Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (26960.573 ms) ======
[2024-08-21T21:25:38.564Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-21T21:25:38.564Z] GC before operation: completed in 120.861 ms, heap usage 454.312 MB -> 54.278 MB.
[2024-08-21T21:25:41.348Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:25:44.330Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:25:47.310Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:25:49.240Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:25:51.171Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:25:52.111Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:25:54.041Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:25:55.973Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:25:55.973Z] 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.
[2024-08-21T21:25:55.973Z] The best model improves the baseline by 14.43%.
[2024-08-21T21:25:55.973Z] Movies recommended for you:
[2024-08-21T21:25:55.973Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:25:55.973Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:25:55.973Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17325.261 ms) ======
[2024-08-21T21:25:55.973Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-21T21:25:55.973Z] GC before operation: completed in 99.608 ms, heap usage 316.612 MB -> 53.283 MB.
[2024-08-21T21:25:58.961Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:26:00.891Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:26:02.821Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:26:05.799Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:26:06.739Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:26:08.671Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:26:09.612Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:26:11.545Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:26:11.545Z] 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.
[2024-08-21T21:26:11.545Z] The best model improves the baseline by 14.43%.
[2024-08-21T21:26:11.545Z] Movies recommended for you:
[2024-08-21T21:26:11.545Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:26:11.545Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:26:11.545Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (15420.909 ms) ======
[2024-08-21T21:26:11.545Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-21T21:26:11.545Z] GC before operation: completed in 88.813 ms, heap usage 470.949 MB -> 53.799 MB.
[2024-08-21T21:26:13.488Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:26:16.466Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:26:18.394Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:26:20.324Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:26:21.368Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:26:22.307Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:26:24.240Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:26:25.179Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:26:25.179Z] 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.
[2024-08-21T21:26:25.179Z] The best model improves the baseline by 14.43%.
[2024-08-21T21:26:26.119Z] Movies recommended for you:
[2024-08-21T21:26:26.119Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:26:26.119Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:26:26.119Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (14171.741 ms) ======
[2024-08-21T21:26:26.119Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-21T21:26:26.119Z] GC before operation: completed in 88.784 ms, heap usage 513.621 MB -> 57.406 MB.
[2024-08-21T21:26:28.047Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:26:29.978Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:26:31.910Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:26:34.905Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:26:36.837Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:26:37.775Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:26:39.702Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:26:40.641Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:26:40.642Z] 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.
[2024-08-21T21:26:40.642Z] The best model improves the baseline by 14.43%.
[2024-08-21T21:26:40.642Z] Movies recommended for you:
[2024-08-21T21:26:40.642Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:26:40.642Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:26:40.642Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15072.823 ms) ======
[2024-08-21T21:26:40.642Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-21T21:26:40.642Z] GC before operation: completed in 170.299 ms, heap usage 2.301 GB -> 59.152 MB.
[2024-08-21T21:26:43.619Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:26:45.546Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:26:47.476Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:26:49.404Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:26:50.342Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:26:52.272Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:26:53.210Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:26:54.846Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:26:55.793Z] 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.
[2024-08-21T21:26:55.793Z] The best model improves the baseline by 14.43%.
[2024-08-21T21:26:55.793Z] Movies recommended for you:
[2024-08-21T21:26:55.793Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:26:55.793Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:26:55.793Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (13819.105 ms) ======
[2024-08-21T21:26:55.793Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-21T21:26:55.793Z] GC before operation: completed in 93.414 ms, heap usage 310.859 MB -> 54.137 MB.
[2024-08-21T21:26:57.721Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:26:59.649Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:27:01.578Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:27:03.508Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:27:04.448Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:27:06.381Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:27:07.322Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:27:08.263Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:27:08.263Z] 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.
[2024-08-21T21:27:08.263Z] The best model improves the baseline by 14.43%.
[2024-08-21T21:27:09.203Z] Movies recommended for you:
[2024-08-21T21:27:09.203Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:27:09.203Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:27:09.203Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (13820.135 ms) ======
[2024-08-21T21:27:09.203Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-21T21:27:09.203Z] GC before operation: completed in 95.136 ms, heap usage 1.115 GB -> 58.622 MB.
[2024-08-21T21:27:11.134Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:27:13.064Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:27:14.998Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:27:16.929Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:27:18.858Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:27:19.800Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:27:20.747Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:27:22.677Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:27:22.677Z] 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.
[2024-08-21T21:27:22.677Z] The best model improves the baseline by 14.43%.
[2024-08-21T21:27:22.677Z] Movies recommended for you:
[2024-08-21T21:27:22.677Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:27:22.677Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:27:22.677Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (13647.769 ms) ======
[2024-08-21T21:27:22.677Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-21T21:27:22.677Z] GC before operation: completed in 92.244 ms, heap usage 357.094 MB -> 54.562 MB.
[2024-08-21T21:27:24.607Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:27:26.541Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:27:29.521Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:27:31.449Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:27:32.389Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:27:33.328Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:27:34.266Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:27:36.197Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:27:36.197Z] 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.
[2024-08-21T21:27:36.197Z] The best model improves the baseline by 14.43%.
[2024-08-21T21:27:36.197Z] Movies recommended for you:
[2024-08-21T21:27:36.197Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:27:36.197Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:27:36.197Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (13511.485 ms) ======
[2024-08-21T21:27:36.197Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-21T21:27:36.197Z] GC before operation: completed in 103.097 ms, heap usage 489.423 MB -> 57.650 MB.
[2024-08-21T21:27:38.133Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:27:40.063Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:27:41.992Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:27:44.974Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:27:45.913Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:27:46.862Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:27:47.801Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:27:49.735Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:27:49.735Z] 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.
[2024-08-21T21:27:49.735Z] The best model improves the baseline by 14.43%.
[2024-08-21T21:27:49.735Z] Movies recommended for you:
[2024-08-21T21:27:49.735Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:27:49.735Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:27:49.735Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (13376.813 ms) ======
[2024-08-21T21:27:49.735Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-21T21:27:49.735Z] GC before operation: completed in 96.313 ms, heap usage 377.809 MB -> 54.433 MB.
[2024-08-21T21:27:51.676Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:27:53.604Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:27:55.534Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:27:57.478Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:27:59.408Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:28:00.348Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:28:01.286Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:28:02.225Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:28:03.165Z] 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.
[2024-08-21T21:28:03.165Z] The best model improves the baseline by 14.43%.
[2024-08-21T21:28:03.165Z] Movies recommended for you:
[2024-08-21T21:28:03.165Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:28:03.165Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:28:03.165Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (13237.011 ms) ======
[2024-08-21T21:28:03.165Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-21T21:28:03.165Z] GC before operation: completed in 95.298 ms, heap usage 785.299 MB -> 57.616 MB.
[2024-08-21T21:28:05.095Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:28:07.716Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:28:09.657Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:28:11.590Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:28:12.531Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:28:13.474Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:28:14.414Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:28:16.344Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:28:16.344Z] 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.
[2024-08-21T21:28:16.344Z] The best model improves the baseline by 14.43%.
[2024-08-21T21:28:16.344Z] Movies recommended for you:
[2024-08-21T21:28:16.344Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:28:16.344Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:28:16.344Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (13467.237 ms) ======
[2024-08-21T21:28:16.344Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-21T21:28:16.344Z] GC before operation: completed in 95.506 ms, heap usage 618.311 MB -> 57.834 MB.
[2024-08-21T21:28:19.329Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:28:21.259Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:28:23.190Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:28:25.121Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:28:26.061Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:28:27.006Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:28:28.935Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:28:29.877Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:28:29.877Z] 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.
[2024-08-21T21:28:29.877Z] The best model improves the baseline by 14.43%.
[2024-08-21T21:28:29.877Z] Movies recommended for you:
[2024-08-21T21:28:29.877Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:28:29.877Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:28:29.877Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (13572.432 ms) ======
[2024-08-21T21:28:29.877Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-21T21:28:29.877Z] GC before operation: completed in 90.109 ms, heap usage 381.912 MB -> 54.731 MB.
[2024-08-21T21:28:32.857Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:28:34.789Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:28:36.720Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:28:38.651Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:28:39.591Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:28:41.524Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:28:42.462Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:28:43.420Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:28:43.420Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-21T21:28:43.420Z] The best model improves the baseline by 14.43%.
[2024-08-21T21:28:43.420Z] Movies recommended for you:
[2024-08-21T21:28:43.420Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:28:43.420Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:28:43.420Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (13425.814 ms) ======
[2024-08-21T21:28:43.420Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-21T21:28:43.420Z] GC before operation: completed in 92.172 ms, heap usage 789.479 MB -> 57.819 MB.
[2024-08-21T21:28:46.401Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:28:48.331Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:28:50.261Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:28:52.190Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:28:53.129Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:28:54.069Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:28:56.019Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:28:57.094Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:28:57.094Z] 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.
[2024-08-21T21:28:57.094Z] The best model improves the baseline by 14.43%.
[2024-08-21T21:28:57.094Z] Movies recommended for you:
[2024-08-21T21:28:57.094Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:28:57.094Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:28:57.094Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (13371.332 ms) ======
[2024-08-21T21:28:57.094Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-21T21:28:57.094Z] GC before operation: completed in 96.333 ms, heap usage 475.109 MB -> 54.602 MB.
[2024-08-21T21:28:59.022Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:29:00.951Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:29:03.931Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:29:05.883Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:29:06.822Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:29:07.761Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:29:09.688Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:29:10.628Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:29:10.628Z] 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.
[2024-08-21T21:29:10.628Z] The best model improves the baseline by 14.43%.
[2024-08-21T21:29:10.628Z] Movies recommended for you:
[2024-08-21T21:29:10.628Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:29:10.628Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:29:10.628Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (13601.857 ms) ======
[2024-08-21T21:29:10.628Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-21T21:29:10.628Z] GC before operation: completed in 91.053 ms, heap usage 378.131 MB -> 54.656 MB.
[2024-08-21T21:29:13.603Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:29:15.532Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:29:17.459Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:29:19.397Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:29:20.338Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:29:21.276Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:29:22.918Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:29:23.857Z] RMSE (validation) = 0.9001440981626696 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:29:24.797Z] 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.
[2024-08-21T21:29:24.797Z] The best model improves the baseline by 14.43%.
[2024-08-21T21:29:24.797Z] Movies recommended for you:
[2024-08-21T21:29:24.797Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:29:24.797Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:29:24.797Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (13553.076 ms) ======
[2024-08-21T21:29:24.797Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-21T21:29:24.797Z] GC before operation: completed in 92.187 ms, heap usage 435.086 MB -> 54.468 MB.
[2024-08-21T21:29:26.725Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:29:28.660Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:29:30.586Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:29:32.516Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:29:34.448Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:29:35.388Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:29:36.329Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:29:38.262Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:29:38.262Z] 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.
[2024-08-21T21:29:38.262Z] The best model improves the baseline by 14.43%.
[2024-08-21T21:29:38.262Z] Movies recommended for you:
[2024-08-21T21:29:38.262Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:29:38.262Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:29:38.262Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (13649.768 ms) ======
[2024-08-21T21:29:38.262Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-21T21:29:38.262Z] GC before operation: completed in 90.701 ms, heap usage 436.144 MB -> 54.571 MB.
[2024-08-21T21:29:40.202Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:29:43.184Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:29:45.113Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:29:47.041Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:29:48.001Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:29:48.941Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:29:50.872Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:29:51.814Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:29:51.814Z] 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.
[2024-08-21T21:29:51.814Z] The best model improves the baseline by 14.43%.
[2024-08-21T21:29:51.814Z] Movies recommended for you:
[2024-08-21T21:29:51.814Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:29:51.814Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:29:51.814Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (13768.441 ms) ======
[2024-08-21T21:29:51.814Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-21T21:29:51.814Z] GC before operation: completed in 99.768 ms, heap usage 1010.460 MB -> 58.683 MB.
[2024-08-21T21:29:54.795Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:29:56.900Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:29:58.833Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:30:00.764Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:30:01.702Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:30:02.660Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:30:03.599Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:30:05.527Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:30:05.527Z] 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.
[2024-08-21T21:30:05.527Z] The best model improves the baseline by 14.43%.
[2024-08-21T21:30:05.527Z] Movies recommended for you:
[2024-08-21T21:30:05.527Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:30:05.527Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:30:05.527Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (13242.798 ms) ======
[2024-08-21T21:30:06.466Z] -----------------------------------
[2024-08-21T21:30:06.467Z] renaissance-movie-lens_0_PASSED
[2024-08-21T21:30:06.467Z] -----------------------------------
[2024-08-21T21:30:06.467Z]
[2024-08-21T21:30:06.467Z] TEST TEARDOWN:
[2024-08-21T21:30:06.467Z] Nothing to be done for teardown.
[2024-08-21T21:30:06.467Z] renaissance-movie-lens_0 Finish Time: Wed Aug 21 21:30:06 2024 Epoch Time (ms): 1724275806358