renaissance-movie-lens_0
[2025-01-10T21:46:12.420Z] Running test renaissance-movie-lens_0 ...
[2025-01-10T21:46:12.420Z] ===============================================
[2025-01-10T21:46:12.420Z] renaissance-movie-lens_0 Start Time: Fri Jan 10 21:46:11 2025 Epoch Time (ms): 1736545571811
[2025-01-10T21:46:12.420Z] variation: NoOptions
[2025-01-10T21:46:12.420Z] JVM_OPTIONS:
[2025-01-10T21:46:12.420Z] { \
[2025-01-10T21:46:12.420Z] echo ""; echo "TEST SETUP:"; \
[2025-01-10T21:46:12.420Z] echo "Nothing to be done for setup."; \
[2025-01-10T21:46:12.420Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17365447424385/renaissance-movie-lens_0"; \
[2025-01-10T21:46:12.420Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17365447424385/renaissance-movie-lens_0"; \
[2025-01-10T21:46:12.420Z] echo ""; echo "TESTING:"; \
[2025-01-10T21:46:12.420Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix/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_ppc64_aix/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17365447424385/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-01-10T21:46:12.420Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17365447424385/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-01-10T21:46:12.420Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-01-10T21:46:12.420Z] echo "Nothing to be done for teardown."; \
[2025-01-10T21:46:12.420Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17365447424385/TestTargetResult";
[2025-01-10T21:46:12.420Z]
[2025-01-10T21:46:12.420Z] TEST SETUP:
[2025-01-10T21:46:12.420Z] Nothing to be done for setup.
[2025-01-10T21:46:12.420Z]
[2025-01-10T21:46:12.420Z] TESTING:
[2025-01-10T21:46:16.899Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-01-10T21:46:19.510Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 24) threads.
[2025-01-10T21:46:21.995Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-01-10T21:46:21.995Z] Training: 60056, validation: 20285, test: 19854
[2025-01-10T21:46:21.995Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-01-10T21:46:22.768Z] GC before operation: completed in 56.703 ms, heap usage 190.939 MB -> 37.471 MB.
[2025-01-10T21:46:27.248Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:46:30.688Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:46:34.137Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:46:36.618Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:46:38.218Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:46:39.814Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:46:41.415Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:46:43.024Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:46:43.805Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-01-10T21:46:43.805Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:46:43.805Z] Movies recommended for you:
[2025-01-10T21:46:43.805Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:46:43.805Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:46:43.805Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (21244.382 ms) ======
[2025-01-10T21:46:43.805Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-01-10T21:46:43.805Z] GC before operation: completed in 86.653 ms, heap usage 2.363 GB -> 55.583 MB.
[2025-01-10T21:46:46.287Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:46:48.775Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:46:52.218Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:46:54.725Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:46:56.323Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:46:57.919Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:46:59.517Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:47:01.121Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:47:01.121Z] 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.
[2025-01-10T21:47:01.121Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:47:01.121Z] Movies recommended for you:
[2025-01-10T21:47:01.121Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:47:01.121Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:47:01.121Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17733.821 ms) ======
[2025-01-10T21:47:01.121Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-01-10T21:47:01.907Z] GC before operation: completed in 78.730 ms, heap usage 98.774 MB -> 55.028 MB.
[2025-01-10T21:47:04.389Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:47:06.873Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:47:10.327Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:47:11.928Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:47:13.540Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:47:15.138Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:47:16.739Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:47:18.347Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:47:19.122Z] 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.
[2025-01-10T21:47:19.122Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:47:19.122Z] Movies recommended for you:
[2025-01-10T21:47:19.122Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:47:19.122Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:47:19.122Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17370.350 ms) ======
[2025-01-10T21:47:19.122Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-01-10T21:47:19.122Z] GC before operation: completed in 72.588 ms, heap usage 106.860 MB -> 54.521 MB.
[2025-01-10T21:47:21.609Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:47:24.271Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:47:26.768Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:47:29.249Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:47:30.847Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:47:32.455Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:47:34.167Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:47:35.890Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:47:35.890Z] 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.
[2025-01-10T21:47:35.890Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:47:35.890Z] Movies recommended for you:
[2025-01-10T21:47:35.890Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:47:35.890Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:47:35.890Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (17256.193 ms) ======
[2025-01-10T21:47:35.890Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-01-10T21:47:36.837Z] GC before operation: completed in 87.931 ms, heap usage 256.417 MB -> 51.777 MB.
[2025-01-10T21:47:39.332Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:47:41.836Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:47:44.320Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:47:46.805Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:47:48.412Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:47:50.014Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:47:51.620Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:47:53.230Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:47:53.230Z] 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.
[2025-01-10T21:47:53.230Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:47:53.230Z] Movies recommended for you:
[2025-01-10T21:47:53.230Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:47:53.230Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:47:53.230Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (17149.713 ms) ======
[2025-01-10T21:47:53.230Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-01-10T21:47:53.230Z] GC before operation: completed in 82.749 ms, heap usage 1.336 GB -> 56.438 MB.
[2025-01-10T21:47:56.675Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:47:59.158Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:48:01.662Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:48:04.157Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:48:05.760Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:48:07.395Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:48:08.995Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:48:10.596Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:48:10.596Z] 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.
[2025-01-10T21:48:10.596Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:48:10.596Z] Movies recommended for you:
[2025-01-10T21:48:10.596Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:48:10.596Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:48:10.596Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (17165.548 ms) ======
[2025-01-10T21:48:10.596Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-01-10T21:48:10.596Z] GC before operation: completed in 80.128 ms, heap usage 110.512 MB -> 55.591 MB.
[2025-01-10T21:48:13.098Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:48:15.580Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:48:19.035Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:48:21.517Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:48:23.116Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:48:23.901Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:48:25.501Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:48:27.113Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:48:27.888Z] 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.
[2025-01-10T21:48:27.888Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:48:27.888Z] Movies recommended for you:
[2025-01-10T21:48:27.888Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:48:27.888Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:48:27.888Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (16922.320 ms) ======
[2025-01-10T21:48:27.888Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-01-10T21:48:27.888Z] GC before operation: completed in 84.834 ms, heap usage 1.743 GB -> 56.805 MB.
[2025-01-10T21:48:30.373Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:48:32.865Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:48:35.353Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:48:37.877Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:48:39.483Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:48:41.086Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:48:42.684Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:48:44.284Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:48:44.284Z] 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.
[2025-01-10T21:48:44.284Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:48:45.058Z] Movies recommended for you:
[2025-01-10T21:48:45.058Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:48:45.058Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:48:45.058Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (16884.163 ms) ======
[2025-01-10T21:48:45.058Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-01-10T21:48:45.058Z] GC before operation: completed in 85.970 ms, heap usage 801.958 MB -> 55.902 MB.
[2025-01-10T21:48:47.543Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:48:50.033Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:48:52.537Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:48:55.031Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:48:56.631Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:48:58.233Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:48:59.830Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:49:01.442Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:49:01.443Z] 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.
[2025-01-10T21:49:01.443Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:49:01.443Z] Movies recommended for you:
[2025-01-10T21:49:01.443Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:49:01.443Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:49:01.443Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (16947.138 ms) ======
[2025-01-10T21:49:01.443Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-01-10T21:49:02.227Z] GC before operation: completed in 80.958 ms, heap usage 808.545 MB -> 55.758 MB.
[2025-01-10T21:49:04.708Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:49:07.201Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:49:09.721Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:49:12.208Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:49:13.811Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:49:15.407Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:49:17.004Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:49:18.602Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:49:18.602Z] 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.
[2025-01-10T21:49:18.602Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:49:18.602Z] Movies recommended for you:
[2025-01-10T21:49:18.602Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:49:18.602Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:49:18.602Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (16985.204 ms) ======
[2025-01-10T21:49:18.602Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-01-10T21:49:18.602Z] GC before operation: completed in 85.465 ms, heap usage 2.782 GB -> 57.255 MB.
[2025-01-10T21:49:22.041Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:49:24.535Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:49:27.020Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:49:29.505Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:49:31.106Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:49:32.886Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:49:34.489Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:49:36.097Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:49:36.097Z] 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.
[2025-01-10T21:49:36.097Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:49:36.915Z] Movies recommended for you:
[2025-01-10T21:49:36.915Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:49:36.915Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:49:36.915Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (17576.605 ms) ======
[2025-01-10T21:49:36.915Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-01-10T21:49:36.915Z] GC before operation: completed in 85.693 ms, heap usage 217.923 MB -> 51.935 MB.
[2025-01-10T21:49:39.407Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:49:41.900Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:49:44.409Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:49:47.854Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:49:48.639Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:49:50.249Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:49:51.847Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:49:53.452Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:49:54.224Z] 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.
[2025-01-10T21:49:54.224Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:49:54.224Z] Movies recommended for you:
[2025-01-10T21:49:54.224Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:49:54.224Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:49:54.224Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (17523.639 ms) ======
[2025-01-10T21:49:54.224Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-01-10T21:49:54.224Z] GC before operation: completed in 89.860 ms, heap usage 2.657 GB -> 57.131 MB.
[2025-01-10T21:49:56.727Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:49:59.266Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:50:02.723Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:50:05.262Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:50:06.037Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:50:07.631Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:50:09.224Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:50:10.840Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:50:11.612Z] 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.
[2025-01-10T21:50:11.612Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:50:11.612Z] Movies recommended for you:
[2025-01-10T21:50:11.612Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:50:11.612Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:50:11.612Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (17330.058 ms) ======
[2025-01-10T21:50:11.612Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-01-10T21:50:11.612Z] GC before operation: completed in 79.936 ms, heap usage 958.518 MB -> 56.337 MB.
[2025-01-10T21:50:14.098Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:50:16.576Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:50:20.025Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:50:22.526Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:50:23.314Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:50:24.913Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:50:26.514Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:50:28.109Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:50:28.883Z] 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.
[2025-01-10T21:50:28.884Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:50:28.884Z] Movies recommended for you:
[2025-01-10T21:50:28.884Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:50:28.884Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:50:28.884Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (17256.039 ms) ======
[2025-01-10T21:50:28.884Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-01-10T21:50:28.884Z] GC before operation: completed in 84.650 ms, heap usage 495.231 MB -> 52.240 MB.
[2025-01-10T21:50:31.421Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:50:33.899Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:50:37.503Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:50:39.108Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:50:40.704Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:50:42.307Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:50:43.915Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:50:45.529Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:50:46.304Z] 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.
[2025-01-10T21:50:46.304Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:50:46.304Z] Movies recommended for you:
[2025-01-10T21:50:46.304Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:50:46.304Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:50:46.304Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (17172.306 ms) ======
[2025-01-10T21:50:46.304Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-01-10T21:50:46.304Z] GC before operation: completed in 81.502 ms, heap usage 94.279 MB -> 54.816 MB.
[2025-01-10T21:50:48.785Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:50:51.268Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:50:53.749Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:50:56.236Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:50:57.856Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:50:59.466Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:51:01.067Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:51:02.668Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:51:02.668Z] 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.
[2025-01-10T21:51:02.668Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:51:02.668Z] Movies recommended for you:
[2025-01-10T21:51:02.668Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:51:02.668Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:51:02.668Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (16749.550 ms) ======
[2025-01-10T21:51:02.668Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-01-10T21:51:02.668Z] GC before operation: completed in 83.178 ms, heap usage 266.537 MB -> 52.320 MB.
[2025-01-10T21:51:06.109Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:51:08.616Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:51:11.106Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:51:13.647Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:51:15.248Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:51:16.025Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:51:18.569Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:51:19.700Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:51:19.700Z] 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.
[2025-01-10T21:51:19.700Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:51:20.656Z] Movies recommended for you:
[2025-01-10T21:51:20.656Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:51:20.656Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:51:20.656Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (16759.282 ms) ======
[2025-01-10T21:51:20.656Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-01-10T21:51:20.656Z] GC before operation: completed in 96.518 ms, heap usage 1.535 GB -> 56.957 MB.
[2025-01-10T21:51:22.716Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:51:25.216Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:51:27.710Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:51:30.195Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:51:31.805Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:51:33.419Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:51:35.024Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:51:36.621Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:51:36.621Z] 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.
[2025-01-10T21:51:36.621Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:51:36.621Z] Movies recommended for you:
[2025-01-10T21:51:36.621Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:51:36.621Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:51:36.621Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (16709.677 ms) ======
[2025-01-10T21:51:36.621Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-01-10T21:51:36.621Z] GC before operation: completed in 85.465 ms, heap usage 1.230 GB -> 56.644 MB.
[2025-01-10T21:51:39.194Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:51:41.680Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:51:44.174Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:51:46.660Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:51:48.289Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:51:49.889Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:51:51.492Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:51:53.114Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:51:53.114Z] 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.
[2025-01-10T21:51:53.114Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:51:53.114Z] Movies recommended for you:
[2025-01-10T21:51:53.114Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:51:53.114Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:51:53.114Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (16712.671 ms) ======
[2025-01-10T21:51:53.114Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-01-10T21:51:53.114Z] GC before operation: completed in 91.266 ms, heap usage 337.318 MB -> 52.483 MB.
[2025-01-10T21:51:55.644Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-01-10T21:51:59.091Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-01-10T21:52:01.572Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-01-10T21:52:04.066Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-01-10T21:52:05.666Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-01-10T21:52:06.440Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-01-10T21:52:08.101Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-01-10T21:52:09.711Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-01-10T21:52:10.484Z] 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.
[2025-01-10T21:52:10.484Z] The best model improves the baseline by 14.43%.
[2025-01-10T21:52:10.484Z] Movies recommended for you:
[2025-01-10T21:52:10.484Z] WARNING: This benchmark provides no result that can be validated.
[2025-01-10T21:52:10.484Z] There is no way to check that no silent failure occurred.
[2025-01-10T21:52:10.484Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (16819.261 ms) ======
[2025-01-10T21:52:10.484Z] -----------------------------------
[2025-01-10T21:52:10.484Z] renaissance-movie-lens_0_PASSED
[2025-01-10T21:52:10.484Z] -----------------------------------
[2025-01-10T21:52:10.484Z]
[2025-01-10T21:52:10.484Z] TEST TEARDOWN:
[2025-01-10T21:52:10.484Z] Nothing to be done for teardown.
[2025-01-10T21:52:10.484Z] renaissance-movie-lens_0 Finish Time: Fri Jan 10 21:52:10 2025 Epoch Time (ms): 1736545930335