renaissance-movie-lens_0
[2024-08-22T01:22:03.252Z] Running test renaissance-movie-lens_0 ...
[2024-08-22T01:22:03.252Z] ===============================================
[2024-08-22T01:22:03.252Z] renaissance-movie-lens_0 Start Time: Wed Aug 21 20:22:02 2024 Epoch Time (ms): 1724289722725
[2024-08-22T01:22:03.252Z] variation: NoOptions
[2024-08-22T01:22:03.252Z] JVM_OPTIONS:
[2024-08-22T01:22:03.252Z] { \
[2024-08-22T01:22:03.252Z] echo ""; echo "TEST SETUP:"; \
[2024-08-22T01:22:03.252Z] echo "Nothing to be done for setup."; \
[2024-08-22T01:22:03.252Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17242890937648/renaissance-movie-lens_0"; \
[2024-08-22T01:22:03.252Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17242890937648/renaissance-movie-lens_0"; \
[2024-08-22T01:22:03.252Z] echo ""; echo "TESTING:"; \
[2024-08-22T01:22:03.252Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/jdkbinary/j2sdk-image/jdk-17.0.13+4/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_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17242890937648/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-22T01:22:03.252Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17242890937648/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-22T01:22:03.252Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-22T01:22:03.252Z] echo "Nothing to be done for teardown."; \
[2024-08-22T01:22:03.252Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17242890937648/TestTargetResult";
[2024-08-22T01:22:03.252Z]
[2024-08-22T01:22:03.252Z] TEST SETUP:
[2024-08-22T01:22:03.252Z] Nothing to be done for setup.
[2024-08-22T01:22:03.252Z]
[2024-08-22T01:22:03.252Z] TESTING:
[2024-08-22T01:22:05.438Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-22T01:22:07.624Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2024-08-22T01:22:10.792Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-22T01:22:10.792Z] Training: 60056, validation: 20285, test: 19854
[2024-08-22T01:22:10.792Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-22T01:22:10.792Z] GC before operation: completed in 60.075 ms, heap usage 85.945 MB -> 37.807 MB.
[2024-08-22T01:22:19.833Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T01:22:22.865Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T01:22:25.935Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T01:22:28.962Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T01:22:30.386Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T01:22:31.792Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T01:22:34.003Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T01:22:35.428Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T01:22:36.115Z] 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.
[2024-08-22T01:22:36.115Z] The best model improves the baseline by 14.43%.
[2024-08-22T01:22:36.115Z] Movies recommended for you:
[2024-08-22T01:22:36.115Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T01:22:36.115Z] There is no way to check that no silent failure occurred.
[2024-08-22T01:22:36.115Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (25172.245 ms) ======
[2024-08-22T01:22:36.115Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-22T01:22:36.115Z] GC before operation: completed in 141.801 ms, heap usage 496.321 MB -> 56.790 MB.
[2024-08-22T01:22:40.117Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T01:22:42.318Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T01:22:44.975Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T01:22:48.055Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T01:22:49.468Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T01:22:50.891Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T01:22:52.317Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T01:22:53.737Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T01:22:54.425Z] 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.
[2024-08-22T01:22:54.425Z] The best model improves the baseline by 14.43%.
[2024-08-22T01:22:54.425Z] Movies recommended for you:
[2024-08-22T01:22:54.425Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T01:22:54.425Z] There is no way to check that no silent failure occurred.
[2024-08-22T01:22:54.425Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (18100.316 ms) ======
[2024-08-22T01:22:54.425Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-22T01:22:54.425Z] GC before operation: completed in 59.728 ms, heap usage 428.983 MB -> 51.674 MB.
[2024-08-22T01:22:57.494Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T01:23:00.560Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T01:23:02.745Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T01:23:04.940Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T01:23:06.334Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T01:23:07.737Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T01:23:09.153Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T01:23:10.614Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T01:23:11.284Z] 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.
[2024-08-22T01:23:11.284Z] The best model improves the baseline by 14.43%.
[2024-08-22T01:23:11.284Z] Movies recommended for you:
[2024-08-22T01:23:11.284Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T01:23:11.284Z] There is no way to check that no silent failure occurred.
[2024-08-22T01:23:11.284Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16838.843 ms) ======
[2024-08-22T01:23:11.284Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-22T01:23:11.284Z] GC before operation: completed in 65.079 ms, heap usage 469.327 MB -> 55.485 MB.
[2024-08-22T01:23:14.324Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T01:23:16.503Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T01:23:18.712Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T01:23:20.901Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T01:23:22.294Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T01:23:23.700Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T01:23:25.111Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T01:23:26.510Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T01:23:27.183Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-22T01:23:27.183Z] The best model improves the baseline by 14.43%.
[2024-08-22T01:23:27.183Z] Movies recommended for you:
[2024-08-22T01:23:27.183Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T01:23:27.183Z] There is no way to check that no silent failure occurred.
[2024-08-22T01:23:27.183Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (15700.418 ms) ======
[2024-08-22T01:23:27.183Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-22T01:23:27.183Z] GC before operation: completed in 56.852 ms, heap usage 345.603 MB -> 52.440 MB.
[2024-08-22T01:23:30.228Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T01:23:32.435Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T01:23:34.642Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T01:23:36.841Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T01:23:37.935Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T01:23:39.353Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T01:23:40.763Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T01:23:42.168Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T01:23:42.168Z] 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.
[2024-08-22T01:23:42.168Z] The best model improves the baseline by 14.43%.
[2024-08-22T01:23:42.168Z] Movies recommended for you:
[2024-08-22T01:23:42.168Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T01:23:42.168Z] There is no way to check that no silent failure occurred.
[2024-08-22T01:23:42.168Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15389.721 ms) ======
[2024-08-22T01:23:42.168Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-22T01:23:42.842Z] GC before operation: completed in 53.482 ms, heap usage 230.511 MB -> 52.629 MB.
[2024-08-22T01:23:45.034Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T01:23:47.220Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T01:23:49.429Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T01:23:51.626Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T01:23:53.026Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T01:23:54.443Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T01:23:56.640Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T01:23:57.332Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T01:23:58.014Z] 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.
[2024-08-22T01:23:58.015Z] The best model improves the baseline by 14.43%.
[2024-08-22T01:23:58.015Z] Movies recommended for you:
[2024-08-22T01:23:58.015Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T01:23:58.015Z] There is no way to check that no silent failure occurred.
[2024-08-22T01:23:58.015Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15434.801 ms) ======
[2024-08-22T01:23:58.015Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-22T01:23:58.015Z] GC before operation: completed in 89.523 ms, heap usage 315.030 MB -> 52.595 MB.
[2024-08-22T01:24:00.196Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T01:24:02.387Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T01:24:05.461Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T01:24:06.885Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T01:24:08.320Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T01:24:09.746Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T01:24:11.157Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T01:24:12.596Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T01:24:12.596Z] 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.
[2024-08-22T01:24:12.596Z] The best model improves the baseline by 14.43%.
[2024-08-22T01:24:12.597Z] Movies recommended for you:
[2024-08-22T01:24:12.597Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T01:24:12.597Z] There is no way to check that no silent failure occurred.
[2024-08-22T01:24:12.597Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (14790.755 ms) ======
[2024-08-22T01:24:12.597Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-22T01:24:12.597Z] GC before operation: completed in 75.731 ms, heap usage 268.627 MB -> 52.633 MB.
[2024-08-22T01:24:15.624Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T01:24:17.800Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T01:24:19.995Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T01:24:22.181Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T01:24:23.576Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T01:24:24.969Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T01:24:26.372Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T01:24:27.764Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T01:24:27.764Z] 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.
[2024-08-22T01:24:27.764Z] The best model improves the baseline by 14.43%.
[2024-08-22T01:24:28.436Z] Movies recommended for you:
[2024-08-22T01:24:28.436Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T01:24:28.436Z] There is no way to check that no silent failure occurred.
[2024-08-22T01:24:28.436Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15184.783 ms) ======
[2024-08-22T01:24:28.436Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-22T01:24:28.436Z] GC before operation: completed in 62.491 ms, heap usage 395.075 MB -> 53.078 MB.
[2024-08-22T01:24:30.617Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T01:24:32.821Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T01:24:35.038Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T01:24:37.224Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T01:24:38.630Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T01:24:40.030Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T01:24:41.432Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T01:24:42.838Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T01:24:42.838Z] 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.
[2024-08-22T01:24:42.838Z] The best model improves the baseline by 14.43%.
[2024-08-22T01:24:43.507Z] Movies recommended for you:
[2024-08-22T01:24:43.507Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T01:24:43.507Z] There is no way to check that no silent failure occurred.
[2024-08-22T01:24:43.507Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15100.125 ms) ======
[2024-08-22T01:24:43.507Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-22T01:24:43.507Z] GC before operation: completed in 63.081 ms, heap usage 295.619 MB -> 52.790 MB.
[2024-08-22T01:24:45.703Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T01:24:47.903Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T01:24:50.081Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T01:24:52.278Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T01:24:53.693Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T01:24:55.091Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T01:24:56.486Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T01:24:57.910Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T01:24:58.583Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-22T01:24:58.583Z] The best model improves the baseline by 14.43%.
[2024-08-22T01:24:58.583Z] Movies recommended for you:
[2024-08-22T01:24:58.583Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T01:24:58.583Z] There is no way to check that no silent failure occurred.
[2024-08-22T01:24:58.583Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15177.922 ms) ======
[2024-08-22T01:24:58.583Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-22T01:24:58.583Z] GC before operation: completed in 85.491 ms, heap usage 191.349 MB -> 52.922 MB.
[2024-08-22T01:25:01.607Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T01:25:03.003Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T01:25:06.050Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T01:25:08.235Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T01:25:08.912Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T01:25:10.398Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T01:25:11.923Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T01:25:13.330Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T01:25:13.330Z] 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.
[2024-08-22T01:25:14.004Z] The best model improves the baseline by 14.43%.
[2024-08-22T01:25:14.004Z] Movies recommended for you:
[2024-08-22T01:25:14.004Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T01:25:14.004Z] There is no way to check that no silent failure occurred.
[2024-08-22T01:25:14.004Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15191.934 ms) ======
[2024-08-22T01:25:14.004Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-22T01:25:14.004Z] GC before operation: completed in 76.737 ms, heap usage 224.802 MB -> 52.677 MB.
[2024-08-22T01:25:16.228Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T01:25:18.585Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T01:25:20.790Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T01:25:22.974Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T01:25:24.405Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T01:25:25.830Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T01:25:27.221Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T01:25:27.892Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T01:25:28.563Z] 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.
[2024-08-22T01:25:28.563Z] The best model improves the baseline by 14.43%.
[2024-08-22T01:25:28.563Z] Movies recommended for you:
[2024-08-22T01:25:28.563Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T01:25:28.563Z] There is no way to check that no silent failure occurred.
[2024-08-22T01:25:28.563Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14743.647 ms) ======
[2024-08-22T01:25:28.563Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-22T01:25:28.563Z] GC before operation: completed in 88.863 ms, heap usage 213.534 MB -> 52.889 MB.
[2024-08-22T01:25:30.779Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T01:25:32.984Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T01:25:36.019Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T01:25:38.225Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T01:25:39.628Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T01:25:41.017Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T01:25:42.413Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T01:25:43.824Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T01:25:43.824Z] 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.
[2024-08-22T01:25:43.824Z] The best model improves the baseline by 14.43%.
[2024-08-22T01:25:43.824Z] Movies recommended for you:
[2024-08-22T01:25:43.824Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T01:25:43.824Z] There is no way to check that no silent failure occurred.
[2024-08-22T01:25:43.824Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15414.517 ms) ======
[2024-08-22T01:25:43.824Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-22T01:25:44.496Z] GC before operation: completed in 82.535 ms, heap usage 824.788 MB -> 57.013 MB.
[2024-08-22T01:25:46.679Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T01:25:48.891Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T01:25:51.069Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T01:25:53.250Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T01:25:54.654Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T01:25:56.051Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T01:25:57.452Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T01:25:58.858Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T01:25:58.858Z] 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.
[2024-08-22T01:25:58.858Z] The best model improves the baseline by 14.43%.
[2024-08-22T01:25:58.858Z] Movies recommended for you:
[2024-08-22T01:25:58.858Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T01:25:58.858Z] There is no way to check that no silent failure occurred.
[2024-08-22T01:25:58.858Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14877.152 ms) ======
[2024-08-22T01:25:58.859Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-22T01:25:58.859Z] GC before operation: completed in 82.158 ms, heap usage 373.263 MB -> 56.123 MB.
[2024-08-22T01:26:01.890Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T01:26:04.071Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T01:26:06.261Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T01:26:08.443Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T01:26:09.862Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T01:26:11.287Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T01:26:12.713Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T01:26:13.381Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T01:26:14.058Z] 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.
[2024-08-22T01:26:14.058Z] The best model improves the baseline by 14.43%.
[2024-08-22T01:26:14.058Z] Movies recommended for you:
[2024-08-22T01:26:14.058Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T01:26:14.058Z] There is no way to check that no silent failure occurred.
[2024-08-22T01:26:14.058Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14896.258 ms) ======
[2024-08-22T01:26:14.058Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-22T01:26:14.058Z] GC before operation: completed in 59.006 ms, heap usage 579.810 MB -> 56.311 MB.
[2024-08-22T01:26:17.146Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T01:26:19.313Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T01:26:21.491Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T01:26:23.659Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T01:26:24.340Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T01:26:26.167Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T01:26:27.565Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T01:26:28.975Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T01:26:28.975Z] 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.
[2024-08-22T01:26:28.975Z] The best model improves the baseline by 14.43%.
[2024-08-22T01:26:28.975Z] Movies recommended for you:
[2024-08-22T01:26:28.975Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T01:26:28.975Z] There is no way to check that no silent failure occurred.
[2024-08-22T01:26:28.975Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15111.809 ms) ======
[2024-08-22T01:26:28.975Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-22T01:26:28.975Z] GC before operation: completed in 86.767 ms, heap usage 556.613 MB -> 56.400 MB.
[2024-08-22T01:26:32.027Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T01:26:34.211Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T01:26:36.488Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T01:26:38.678Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T01:26:39.385Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T01:26:40.804Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T01:26:42.213Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T01:26:43.610Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T01:26:43.610Z] 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.
[2024-08-22T01:26:43.610Z] The best model improves the baseline by 14.43%.
[2024-08-22T01:26:44.286Z] Movies recommended for you:
[2024-08-22T01:26:44.286Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T01:26:44.286Z] There is no way to check that no silent failure occurred.
[2024-08-22T01:26:44.286Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14731.152 ms) ======
[2024-08-22T01:26:44.286Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-22T01:26:44.286Z] GC before operation: completed in 62.816 ms, heap usage 268.669 MB -> 52.757 MB.
[2024-08-22T01:26:46.484Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T01:26:49.530Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T01:26:50.934Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T01:26:53.140Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T01:26:54.537Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T01:26:55.935Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T01:26:57.354Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T01:26:58.748Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T01:26:58.748Z] 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.
[2024-08-22T01:26:59.417Z] The best model improves the baseline by 14.43%.
[2024-08-22T01:26:59.417Z] Movies recommended for you:
[2024-08-22T01:26:59.417Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T01:26:59.417Z] There is no way to check that no silent failure occurred.
[2024-08-22T01:26:59.417Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (15111.347 ms) ======
[2024-08-22T01:26:59.417Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-22T01:26:59.417Z] GC before operation: completed in 97.991 ms, heap usage 846.918 MB -> 56.912 MB.
[2024-08-22T01:27:01.585Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T01:27:03.809Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T01:27:06.011Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T01:27:08.192Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T01:27:09.614Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T01:27:11.022Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T01:27:12.422Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T01:27:13.818Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T01:27:13.818Z] 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.
[2024-08-22T01:27:13.818Z] The best model improves the baseline by 14.43%.
[2024-08-22T01:27:13.818Z] Movies recommended for you:
[2024-08-22T01:27:13.818Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T01:27:13.818Z] There is no way to check that no silent failure occurred.
[2024-08-22T01:27:13.818Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14722.473 ms) ======
[2024-08-22T01:27:13.818Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-22T01:27:13.818Z] GC before operation: completed in 71.953 ms, heap usage 84.464 MB -> 56.301 MB.
[2024-08-22T01:27:16.856Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T01:27:19.038Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T01:27:21.206Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T01:27:23.398Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T01:27:24.791Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T01:27:26.190Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T01:27:26.868Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T01:27:28.298Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T01:27:29.014Z] 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.
[2024-08-22T01:27:29.014Z] The best model improves the baseline by 14.43%.
[2024-08-22T01:27:29.014Z] Movies recommended for you:
[2024-08-22T01:27:29.014Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T01:27:29.014Z] There is no way to check that no silent failure occurred.
[2024-08-22T01:27:29.014Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14749.834 ms) ======
[2024-08-22T01:27:30.409Z] -----------------------------------
[2024-08-22T01:27:30.409Z] renaissance-movie-lens_0_PASSED
[2024-08-22T01:27:30.409Z] -----------------------------------
[2024-08-22T01:27:30.409Z]
[2024-08-22T01:27:30.409Z] TEST TEARDOWN:
[2024-08-22T01:27:30.409Z] Nothing to be done for teardown.
[2024-08-22T01:27:30.409Z] renaissance-movie-lens_0 Finish Time: Wed Aug 21 20:27:29 2024 Epoch Time (ms): 1724290049721