renaissance-movie-lens_0
[2025-02-12T21:51:46.541Z] Running test renaissance-movie-lens_0 ...
[2025-02-12T21:51:46.541Z] ===============================================
[2025-02-12T21:51:46.541Z] renaissance-movie-lens_0 Start Time: Wed Feb 12 21:51:45 2025 Epoch Time (ms): 1739397105558
[2025-02-12T21:51:46.541Z] variation: NoOptions
[2025-02-12T21:51:46.541Z] JVM_OPTIONS:
[2025-02-12T21:51:46.541Z] { \
[2025-02-12T21:51:46.541Z] echo ""; echo "TEST SETUP:"; \
[2025-02-12T21:51:46.541Z] echo "Nothing to be done for setup."; \
[2025-02-12T21:51:46.541Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17393961392082/renaissance-movie-lens_0"; \
[2025-02-12T21:51:46.541Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17393961392082/renaissance-movie-lens_0"; \
[2025-02-12T21:51:46.541Z] echo ""; echo "TESTING:"; \
[2025-02-12T21:51:46.541Z] "/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_17393961392082/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-02-12T21:51:46.541Z] 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_17393961392082/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-02-12T21:51:46.541Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-02-12T21:51:46.541Z] echo "Nothing to be done for teardown."; \
[2025-02-12T21:51:46.541Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17393961392082/TestTargetResult";
[2025-02-12T21:51:46.541Z]
[2025-02-12T21:51:46.541Z] TEST SETUP:
[2025-02-12T21:51:46.541Z] Nothing to be done for setup.
[2025-02-12T21:51:46.541Z]
[2025-02-12T21:51:46.541Z] TESTING:
[2025-02-12T21:51:50.762Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-02-12T21:51:56.159Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2025-02-12T21:52:01.559Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-02-12T21:52:01.559Z] Training: 60056, validation: 20285, test: 19854
[2025-02-12T21:52:01.559Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-02-12T21:52:01.559Z] GC before operation: completed in 70.293 ms, heap usage 68.905 MB -> 39.337 MB.
[2025-02-12T21:52:11.356Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:52:15.540Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:52:20.942Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:52:23.979Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:52:27.019Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:52:28.984Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:52:32.022Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:52:33.991Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:52:33.991Z] 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.
[2025-02-12T21:52:34.952Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:52:34.952Z] Movies recommended for you:
[2025-02-12T21:52:34.952Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:52:34.952Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:52:34.952Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (33045.394 ms) ======
[2025-02-12T21:52:34.952Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-02-12T21:52:34.952Z] GC before operation: completed in 130.690 ms, heap usage 412.655 MB -> 52.419 MB.
[2025-02-12T21:52:39.133Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:52:42.171Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:52:45.240Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:52:49.003Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:52:50.978Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:52:52.946Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:52:54.914Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:52:56.915Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:52:57.876Z] 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.
[2025-02-12T21:52:57.876Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:52:57.876Z] Movies recommended for you:
[2025-02-12T21:52:57.876Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:52:57.876Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:52:57.876Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (22754.171 ms) ======
[2025-02-12T21:52:57.876Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-02-12T21:52:57.876Z] GC before operation: completed in 113.328 ms, heap usage 326.431 MB -> 53.338 MB.
[2025-02-12T21:53:00.911Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:53:05.097Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:53:08.166Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:53:11.209Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:53:13.180Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:53:14.140Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:53:16.109Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:53:18.079Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:53:19.038Z] 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.
[2025-02-12T21:53:19.038Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:53:19.038Z] Movies recommended for you:
[2025-02-12T21:53:19.038Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:53:19.038Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:53:19.038Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (21259.612 ms) ======
[2025-02-12T21:53:19.038Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-02-12T21:53:19.038Z] GC before operation: completed in 118.470 ms, heap usage 451.913 MB -> 53.571 MB.
[2025-02-12T21:53:22.080Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:53:25.114Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:53:28.196Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:53:31.244Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:53:32.205Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:53:34.183Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:53:36.150Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:53:38.120Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:53:38.120Z] 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.
[2025-02-12T21:53:38.120Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:53:39.086Z] Movies recommended for you:
[2025-02-12T21:53:39.086Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:53:39.086Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:53:39.086Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (19636.366 ms) ======
[2025-02-12T21:53:39.086Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-02-12T21:53:39.086Z] GC before operation: completed in 124.651 ms, heap usage 895.214 MB -> 57.679 MB.
[2025-02-12T21:53:42.118Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:53:45.156Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:53:48.197Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:53:51.232Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:53:52.189Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:53:54.158Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:53:56.124Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:53:58.095Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:53:58.095Z] 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.
[2025-02-12T21:53:58.095Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:53:58.095Z] Movies recommended for you:
[2025-02-12T21:53:58.095Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:53:58.095Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:53:58.095Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (19578.493 ms) ======
[2025-02-12T21:53:58.095Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-02-12T21:53:59.055Z] GC before operation: completed in 125.059 ms, heap usage 385.505 MB -> 54.055 MB.
[2025-02-12T21:54:02.100Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:54:05.145Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:54:08.328Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:54:12.117Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:54:13.075Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:54:15.046Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:54:17.091Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:54:18.050Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:54:19.010Z] 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.
[2025-02-12T21:54:19.010Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:54:19.010Z] Movies recommended for you:
[2025-02-12T21:54:19.010Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:54:19.010Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:54:19.010Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (20397.850 ms) ======
[2025-02-12T21:54:19.011Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-02-12T21:54:19.011Z] GC before operation: completed in 123.955 ms, heap usage 1.030 GB -> 58.189 MB.
[2025-02-12T21:54:22.050Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:54:25.100Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:54:28.147Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:54:31.191Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:54:33.155Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:54:35.124Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:54:37.091Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:54:38.052Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:54:39.016Z] 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.
[2025-02-12T21:54:39.016Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:54:39.016Z] Movies recommended for you:
[2025-02-12T21:54:39.016Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:54:39.016Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:54:39.016Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (19953.413 ms) ======
[2025-02-12T21:54:39.016Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-02-12T21:54:39.016Z] GC before operation: completed in 124.917 ms, heap usage 446.539 MB -> 54.192 MB.
[2025-02-12T21:54:42.058Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:54:45.114Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:54:48.160Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:54:51.263Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:54:52.225Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:54:54.198Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:54:56.169Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:54:58.141Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:54:58.141Z] 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.
[2025-02-12T21:54:58.141Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:54:58.141Z] Movies recommended for you:
[2025-02-12T21:54:58.141Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:54:58.141Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:54:58.141Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (19301.959 ms) ======
[2025-02-12T21:54:58.141Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-02-12T21:54:58.141Z] GC before operation: completed in 129.738 ms, heap usage 496.673 MB -> 54.578 MB.
[2025-02-12T21:55:02.331Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:55:04.304Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:55:07.436Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:55:10.518Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:55:12.498Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:55:13.525Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:55:15.528Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:55:17.499Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:55:17.499Z] 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.
[2025-02-12T21:55:17.499Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:55:17.499Z] Movies recommended for you:
[2025-02-12T21:55:17.499Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:55:17.499Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:55:17.499Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (19079.950 ms) ======
[2025-02-12T21:55:17.499Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-02-12T21:55:17.499Z] GC before operation: completed in 125.743 ms, heap usage 556.708 MB -> 57.687 MB.
[2025-02-12T21:55:20.560Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:55:23.687Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:55:26.728Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:55:28.704Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:55:30.679Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:55:32.656Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:55:34.631Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:55:35.591Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:55:36.551Z] 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.
[2025-02-12T21:55:36.551Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:55:36.551Z] Movies recommended for you:
[2025-02-12T21:55:36.551Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:55:36.551Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:55:36.551Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (18822.472 ms) ======
[2025-02-12T21:55:36.551Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-02-12T21:55:36.551Z] GC before operation: completed in 127.766 ms, heap usage 358.960 MB -> 54.334 MB.
[2025-02-12T21:55:40.485Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:55:42.637Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:55:45.689Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:55:48.736Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:55:49.740Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:55:51.717Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:55:53.694Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:55:55.668Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:55:55.668Z] 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.
[2025-02-12T21:55:55.668Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:55:55.668Z] Movies recommended for you:
[2025-02-12T21:55:55.669Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:55:55.669Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:55:55.669Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (19135.641 ms) ======
[2025-02-12T21:55:55.669Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-02-12T21:55:55.669Z] GC before operation: completed in 127.625 ms, heap usage 386.416 MB -> 54.119 MB.
[2025-02-12T21:55:58.715Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:56:01.764Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:56:04.811Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:56:07.876Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:56:08.891Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:56:12.009Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:56:12.971Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:56:14.941Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:56:15.904Z] 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.
[2025-02-12T21:56:15.904Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:56:15.904Z] Movies recommended for you:
[2025-02-12T21:56:15.905Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:56:15.905Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:56:15.905Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (19715.385 ms) ======
[2025-02-12T21:56:15.905Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-02-12T21:56:15.905Z] GC before operation: completed in 124.003 ms, heap usage 413.883 MB -> 54.367 MB.
[2025-02-12T21:56:18.950Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:56:22.009Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:56:25.066Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:56:27.039Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:56:29.017Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:56:30.994Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:56:32.966Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:56:34.937Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:56:34.937Z] 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.
[2025-02-12T21:56:34.937Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:56:34.937Z] Movies recommended for you:
[2025-02-12T21:56:34.937Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:56:34.937Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:56:34.937Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (19403.425 ms) ======
[2025-02-12T21:56:34.937Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-02-12T21:56:34.937Z] GC before operation: completed in 124.097 ms, heap usage 672.165 MB -> 57.907 MB.
[2025-02-12T21:56:39.225Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:56:41.194Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:56:44.247Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:56:47.290Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:56:49.277Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:56:51.249Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:56:52.210Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:56:54.178Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:56:55.137Z] 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.
[2025-02-12T21:56:55.137Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:56:55.137Z] Movies recommended for you:
[2025-02-12T21:56:55.137Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:56:55.137Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:56:55.137Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (19630.839 ms) ======
[2025-02-12T21:56:55.137Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-02-12T21:56:55.137Z] GC before operation: completed in 125.017 ms, heap usage 389.101 MB -> 54.205 MB.
[2025-02-12T21:56:58.346Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:57:01.396Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:57:03.841Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:57:06.953Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:57:08.923Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:57:09.885Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:57:11.855Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:57:13.844Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:57:14.804Z] 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.
[2025-02-12T21:57:14.804Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:57:14.804Z] Movies recommended for you:
[2025-02-12T21:57:14.804Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:57:14.804Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:57:14.804Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (19641.969 ms) ======
[2025-02-12T21:57:14.804Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-02-12T21:57:14.804Z] GC before operation: completed in 120.245 ms, heap usage 379.000 MB -> 54.336 MB.
[2025-02-12T21:57:17.847Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:57:20.891Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:57:23.936Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:57:26.976Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:57:28.945Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:57:29.933Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:57:32.974Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:57:33.936Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:57:34.896Z] 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.
[2025-02-12T21:57:34.896Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:57:34.896Z] Movies recommended for you:
[2025-02-12T21:57:34.896Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:57:34.896Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:57:34.896Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (19998.173 ms) ======
[2025-02-12T21:57:34.896Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-02-12T21:57:34.896Z] GC before operation: completed in 113.904 ms, heap usage 380.953 MB -> 54.570 MB.
[2025-02-12T21:57:37.944Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:57:41.003Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:57:44.042Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:57:46.017Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:57:47.984Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:57:49.965Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:57:52.033Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:57:52.993Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:57:53.953Z] 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.
[2025-02-12T21:57:53.953Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:57:53.953Z] Movies recommended for you:
[2025-02-12T21:57:53.953Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:57:53.953Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:57:53.953Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (19070.899 ms) ======
[2025-02-12T21:57:53.953Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-02-12T21:57:53.953Z] GC before operation: completed in 116.053 ms, heap usage 384.978 MB -> 54.250 MB.
[2025-02-12T21:57:56.999Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:58:00.046Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:58:03.093Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:58:06.134Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:58:07.097Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:58:09.071Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:58:11.041Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:58:13.010Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:58:13.010Z] 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.
[2025-02-12T21:58:13.010Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:58:13.972Z] Movies recommended for you:
[2025-02-12T21:58:13.973Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:58:13.973Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:58:13.973Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (19291.798 ms) ======
[2025-02-12T21:58:13.973Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-02-12T21:58:13.973Z] GC before operation: completed in 128.432 ms, heap usage 788.911 MB -> 57.921 MB.
[2025-02-12T21:58:17.017Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:58:18.990Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:58:22.034Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:58:25.072Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:58:27.041Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:58:29.015Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:58:29.987Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:58:31.680Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:58:32.641Z] 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.
[2025-02-12T21:58:32.641Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:58:32.641Z] Movies recommended for you:
[2025-02-12T21:58:32.641Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:58:32.641Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:58:32.641Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (19138.805 ms) ======
[2025-02-12T21:58:32.641Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-02-12T21:58:32.641Z] GC before operation: completed in 127.396 ms, heap usage 381.736 MB -> 54.587 MB.
[2025-02-12T21:58:35.737Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:58:38.777Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:58:41.823Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:58:43.798Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:58:45.772Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:58:47.869Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:58:49.842Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:58:50.804Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:58:51.767Z] 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.
[2025-02-12T21:58:51.767Z] The best model improves the baseline by 14.43%.
[2025-02-12T21:58:51.767Z] Movies recommended for you:
[2025-02-12T21:58:51.767Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:58:51.767Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:58:51.767Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (18830.608 ms) ======
[2025-02-12T21:58:53.751Z] -----------------------------------
[2025-02-12T21:58:53.751Z] renaissance-movie-lens_0_PASSED
[2025-02-12T21:58:53.751Z] -----------------------------------
[2025-02-12T21:58:53.751Z]
[2025-02-12T21:58:53.751Z] TEST TEARDOWN:
[2025-02-12T21:58:53.751Z] Nothing to be done for teardown.
[2025-02-12T21:58:53.751Z] renaissance-movie-lens_0 Finish Time: Wed Feb 12 21:58:53 2025 Epoch Time (ms): 1739397533335