renaissance-movie-lens_0
[2025-03-05T22:39:48.812Z] Running test renaissance-movie-lens_0 ...
[2025-03-05T22:39:48.812Z] ===============================================
[2025-03-05T22:39:48.812Z] renaissance-movie-lens_0 Start Time: Wed Mar 5 16:39:48 2025 Epoch Time (ms): 1741214388789
[2025-03-05T22:39:48.812Z] variation: NoOptions
[2025-03-05T22:39:48.812Z] JVM_OPTIONS:
[2025-03-05T22:39:48.812Z] { \
[2025-03-05T22:39:48.812Z] echo ""; echo "TEST SETUP:"; \
[2025-03-05T22:39:48.812Z] echo "Nothing to be done for setup."; \
[2025-03-05T22:39:48.812Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17412135226863/renaissance-movie-lens_0"; \
[2025-03-05T22:39:48.812Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17412135226863/renaissance-movie-lens_0"; \
[2025-03-05T22:39:48.812Z] echo ""; echo "TESTING:"; \
[2025-03-05T22:39:48.812Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17412135226863/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-03-05T22:39:48.812Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17412135226863/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-03-05T22:39:48.812Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-03-05T22:39:48.812Z] echo "Nothing to be done for teardown."; \
[2025-03-05T22:39:48.812Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17412135226863/TestTargetResult";
[2025-03-05T22:39:48.812Z]
[2025-03-05T22:39:48.812Z] TEST SETUP:
[2025-03-05T22:39:48.812Z] Nothing to be done for setup.
[2025-03-05T22:39:48.812Z]
[2025-03-05T22:39:48.812Z] TESTING:
[2025-03-05T22:39:51.931Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-03-05T22:39:53.357Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2025-03-05T22:39:57.415Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-03-05T22:39:57.415Z] Training: 60056, validation: 20285, test: 19854
[2025-03-05T22:39:57.415Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-03-05T22:39:57.415Z] GC before operation: completed in 54.296 ms, heap usage 98.138 MB -> 37.167 MB.
[2025-03-05T22:40:03.748Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T22:40:08.891Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T22:40:12.032Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T22:40:15.126Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T22:40:17.371Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T22:40:18.820Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T22:40:21.100Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T22:40:22.577Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T22:40:23.269Z] 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.
[2025-03-05T22:40:23.269Z] The best model improves the baseline by 14.43%.
[2025-03-05T22:40:23.269Z] Movies recommended for you:
[2025-03-05T22:40:23.269Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T22:40:23.269Z] There is no way to check that no silent failure occurred.
[2025-03-05T22:40:23.269Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (25924.115 ms) ======
[2025-03-05T22:40:23.269Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-03-05T22:40:23.270Z] GC before operation: completed in 123.118 ms, heap usage 215.055 MB -> 48.254 MB.
[2025-03-05T22:40:26.511Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T22:40:29.637Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T22:40:32.752Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T22:40:34.985Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T22:40:36.421Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T22:40:38.647Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T22:40:40.096Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T22:40:41.575Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T22:40:42.261Z] 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.
[2025-03-05T22:40:42.261Z] The best model improves the baseline by 14.43%.
[2025-03-05T22:40:42.261Z] Movies recommended for you:
[2025-03-05T22:40:42.261Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T22:40:42.261Z] There is no way to check that no silent failure occurred.
[2025-03-05T22:40:42.261Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (18874.115 ms) ======
[2025-03-05T22:40:42.261Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-03-05T22:40:42.261Z] GC before operation: completed in 122.270 ms, heap usage 390.004 MB -> 51.077 MB.
[2025-03-05T22:40:45.408Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T22:40:48.529Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T22:40:50.749Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T22:40:53.830Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T22:40:56.072Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T22:40:57.495Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T22:40:58.929Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T22:41:01.169Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T22:41:01.169Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-03-05T22:41:01.169Z] The best model improves the baseline by 14.43%.
[2025-03-05T22:41:01.169Z] Movies recommended for you:
[2025-03-05T22:41:01.169Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T22:41:01.169Z] There is no way to check that no silent failure occurred.
[2025-03-05T22:41:01.169Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (18878.953 ms) ======
[2025-03-05T22:41:01.169Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-03-05T22:41:01.169Z] GC before operation: completed in 116.033 ms, heap usage 422.989 MB -> 51.468 MB.
[2025-03-05T22:41:04.284Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T22:41:06.565Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T22:41:09.677Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T22:41:11.943Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T22:41:13.363Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T22:41:14.795Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T22:41:16.228Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T22:41:17.663Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T22:41:17.664Z] 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.
[2025-03-05T22:41:17.664Z] The best model improves the baseline by 14.43%.
[2025-03-05T22:41:17.664Z] Movies recommended for you:
[2025-03-05T22:41:17.664Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T22:41:17.664Z] There is no way to check that no silent failure occurred.
[2025-03-05T22:41:17.664Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16515.182 ms) ======
[2025-03-05T22:41:17.664Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-03-05T22:41:17.664Z] GC before operation: completed in 121.636 ms, heap usage 233.224 MB -> 51.737 MB.
[2025-03-05T22:41:20.773Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T22:41:23.055Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T22:41:25.293Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T22:41:28.441Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T22:41:29.882Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T22:41:31.333Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T22:41:33.598Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T22:41:34.315Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T22:41:35.003Z] 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.
[2025-03-05T22:41:35.003Z] The best model improves the baseline by 14.43%.
[2025-03-05T22:41:35.003Z] Movies recommended for you:
[2025-03-05T22:41:35.003Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T22:41:35.003Z] There is no way to check that no silent failure occurred.
[2025-03-05T22:41:35.003Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16803.537 ms) ======
[2025-03-05T22:41:35.003Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-03-05T22:41:35.003Z] GC before operation: completed in 143.981 ms, heap usage 167.165 MB -> 51.828 MB.
[2025-03-05T22:41:38.104Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T22:41:40.474Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T22:41:42.809Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T22:41:45.045Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T22:41:46.469Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T22:41:47.910Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T22:41:50.153Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T22:41:51.580Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T22:41:51.580Z] 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.
[2025-03-05T22:41:51.580Z] The best model improves the baseline by 14.43%.
[2025-03-05T22:41:51.580Z] Movies recommended for you:
[2025-03-05T22:41:51.580Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T22:41:51.580Z] There is no way to check that no silent failure occurred.
[2025-03-05T22:41:51.580Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (16685.505 ms) ======
[2025-03-05T22:41:51.580Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-03-05T22:41:51.580Z] GC before operation: completed in 127.954 ms, heap usage 190.379 MB -> 51.762 MB.
[2025-03-05T22:41:54.708Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T22:41:56.972Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T22:42:00.092Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T22:42:01.540Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T22:42:02.977Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T22:42:05.245Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T22:42:06.688Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T22:42:08.132Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T22:42:08.132Z] 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.
[2025-03-05T22:42:08.132Z] The best model improves the baseline by 14.43%.
[2025-03-05T22:42:08.132Z] Movies recommended for you:
[2025-03-05T22:42:08.132Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T22:42:08.132Z] There is no way to check that no silent failure occurred.
[2025-03-05T22:42:08.132Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (16471.608 ms) ======
[2025-03-05T22:42:08.132Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-03-05T22:42:08.132Z] GC before operation: completed in 123.905 ms, heap usage 389.094 MB -> 52.129 MB.
[2025-03-05T22:42:11.231Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T22:42:13.452Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T22:42:15.693Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T22:42:17.943Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T22:42:19.402Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T22:42:20.840Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T22:42:22.323Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T22:42:23.863Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T22:42:24.550Z] 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.
[2025-03-05T22:42:24.550Z] The best model improves the baseline by 14.43%.
[2025-03-05T22:42:24.550Z] Movies recommended for you:
[2025-03-05T22:42:24.550Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T22:42:24.550Z] There is no way to check that no silent failure occurred.
[2025-03-05T22:42:24.550Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (16160.340 ms) ======
[2025-03-05T22:42:24.550Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-03-05T22:42:24.550Z] GC before operation: completed in 110.283 ms, heap usage 128.932 MB -> 52.174 MB.
[2025-03-05T22:42:27.819Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T22:42:30.094Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T22:42:32.385Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T22:42:34.614Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T22:42:36.037Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T22:42:37.468Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T22:42:38.944Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T22:42:40.455Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T22:42:40.455Z] 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.
[2025-03-05T22:42:40.455Z] The best model improves the baseline by 14.43%.
[2025-03-05T22:42:40.455Z] Movies recommended for you:
[2025-03-05T22:42:40.455Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T22:42:40.455Z] There is no way to check that no silent failure occurred.
[2025-03-05T22:42:40.455Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (16033.919 ms) ======
[2025-03-05T22:42:40.455Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-03-05T22:42:41.170Z] GC before operation: completed in 135.829 ms, heap usage 308.157 MB -> 52.096 MB.
[2025-03-05T22:42:43.408Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T22:42:45.697Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T22:42:48.012Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T22:42:51.110Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T22:42:52.543Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T22:42:54.010Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T22:42:55.444Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T22:42:56.898Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T22:42:56.898Z] 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.
[2025-03-05T22:42:56.898Z] The best model improves the baseline by 14.43%.
[2025-03-05T22:42:56.898Z] Movies recommended for you:
[2025-03-05T22:42:56.898Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T22:42:56.898Z] There is no way to check that no silent failure occurred.
[2025-03-05T22:42:56.898Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (16318.551 ms) ======
[2025-03-05T22:42:56.898Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-03-05T22:42:57.586Z] GC before operation: completed in 121.999 ms, heap usage 103.832 MB -> 53.743 MB.
[2025-03-05T22:42:59.821Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T22:43:02.063Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T22:43:04.308Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T22:43:06.538Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T22:43:07.981Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T22:43:09.407Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T22:43:10.835Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T22:43:12.275Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T22:43:12.959Z] 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.
[2025-03-05T22:43:12.959Z] The best model improves the baseline by 14.43%.
[2025-03-05T22:43:12.959Z] Movies recommended for you:
[2025-03-05T22:43:12.959Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T22:43:12.959Z] There is no way to check that no silent failure occurred.
[2025-03-05T22:43:12.959Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15579.628 ms) ======
[2025-03-05T22:43:12.959Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-03-05T22:43:12.959Z] GC before operation: completed in 124.402 ms, heap usage 253.425 MB -> 51.865 MB.
[2025-03-05T22:43:16.070Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T22:43:18.359Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T22:43:20.581Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T22:43:22.819Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T22:43:24.255Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T22:43:25.687Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T22:43:27.119Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T22:43:28.550Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T22:43:28.550Z] 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.
[2025-03-05T22:43:29.237Z] The best model improves the baseline by 14.43%.
[2025-03-05T22:43:29.237Z] Movies recommended for you:
[2025-03-05T22:43:29.237Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T22:43:29.237Z] There is no way to check that no silent failure occurred.
[2025-03-05T22:43:29.237Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (16065.562 ms) ======
[2025-03-05T22:43:29.237Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-03-05T22:43:29.237Z] GC before operation: completed in 138.233 ms, heap usage 266.191 MB -> 55.224 MB.
[2025-03-05T22:43:32.329Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T22:43:34.565Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T22:43:36.798Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T22:43:39.120Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T22:43:41.347Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T22:43:42.046Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T22:43:43.491Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T22:43:45.764Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T22:43:45.764Z] 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.
[2025-03-05T22:43:45.764Z] The best model improves the baseline by 14.43%.
[2025-03-05T22:43:45.764Z] Movies recommended for you:
[2025-03-05T22:43:45.764Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T22:43:45.764Z] There is no way to check that no silent failure occurred.
[2025-03-05T22:43:45.764Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (16579.447 ms) ======
[2025-03-05T22:43:45.764Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-03-05T22:43:45.764Z] GC before operation: completed in 122.514 ms, heap usage 427.389 MB -> 52.340 MB.
[2025-03-05T22:43:48.877Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T22:43:51.132Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T22:43:53.377Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T22:43:55.628Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T22:43:57.871Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T22:43:59.312Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T22:44:00.746Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T22:44:02.172Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T22:44:02.172Z] 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.
[2025-03-05T22:44:02.172Z] The best model improves the baseline by 14.43%.
[2025-03-05T22:44:02.172Z] Movies recommended for you:
[2025-03-05T22:44:02.172Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T22:44:02.172Z] There is no way to check that no silent failure occurred.
[2025-03-05T22:44:02.172Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (16451.888 ms) ======
[2025-03-05T22:44:02.172Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-03-05T22:44:02.172Z] GC before operation: completed in 119.161 ms, heap usage 395.288 MB -> 52.044 MB.
[2025-03-05T22:44:05.255Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T22:44:07.054Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T22:44:09.404Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T22:44:11.640Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T22:44:13.094Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T22:44:14.527Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T22:44:16.748Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T22:44:17.457Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T22:44:18.169Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-03-05T22:44:18.169Z] The best model improves the baseline by 14.43%.
[2025-03-05T22:44:18.169Z] Movies recommended for you:
[2025-03-05T22:44:18.169Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T22:44:18.169Z] There is no way to check that no silent failure occurred.
[2025-03-05T22:44:18.169Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (15646.507 ms) ======
[2025-03-05T22:44:18.169Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-03-05T22:44:18.169Z] GC before operation: completed in 129.149 ms, heap usage 89.329 MB -> 55.280 MB.
[2025-03-05T22:44:20.392Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T22:44:22.632Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T22:44:25.767Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T22:44:27.979Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T22:44:29.420Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T22:44:30.840Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T22:44:33.128Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T22:44:34.556Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T22:44:34.557Z] 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.
[2025-03-05T22:44:34.557Z] The best model improves the baseline by 14.43%.
[2025-03-05T22:44:34.557Z] Movies recommended for you:
[2025-03-05T22:44:34.557Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T22:44:34.557Z] There is no way to check that no silent failure occurred.
[2025-03-05T22:44:34.557Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (16598.250 ms) ======
[2025-03-05T22:44:34.557Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-03-05T22:44:35.244Z] GC before operation: completed in 118.413 ms, heap usage 231.546 MB -> 52.258 MB.
[2025-03-05T22:44:37.477Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T22:44:39.812Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T22:44:42.052Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T22:44:44.301Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T22:44:45.730Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T22:44:47.965Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T22:44:49.417Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T22:44:50.846Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T22:44:50.846Z] 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.
[2025-03-05T22:44:50.846Z] The best model improves the baseline by 14.43%.
[2025-03-05T22:44:50.846Z] Movies recommended for you:
[2025-03-05T22:44:50.846Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T22:44:50.846Z] There is no way to check that no silent failure occurred.
[2025-03-05T22:44:50.846Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (16179.431 ms) ======
[2025-03-05T22:44:50.846Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-03-05T22:44:51.533Z] GC before operation: completed in 104.275 ms, heap usage 303.914 MB -> 52.135 MB.
[2025-03-05T22:44:53.766Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T22:44:56.054Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T22:44:58.313Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T22:45:00.542Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T22:45:02.778Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T22:45:04.218Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T22:45:05.651Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T22:45:07.095Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T22:45:07.095Z] 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.
[2025-03-05T22:45:07.095Z] The best model improves the baseline by 14.43%.
[2025-03-05T22:45:07.095Z] Movies recommended for you:
[2025-03-05T22:45:07.095Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T22:45:07.095Z] There is no way to check that no silent failure occurred.
[2025-03-05T22:45:07.095Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (16030.554 ms) ======
[2025-03-05T22:45:07.095Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-03-05T22:45:07.095Z] GC before operation: completed in 113.514 ms, heap usage 165.397 MB -> 52.103 MB.
[2025-03-05T22:45:10.186Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T22:45:12.416Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T22:45:15.518Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T22:45:16.952Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T22:45:19.193Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T22:45:20.630Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T22:45:22.093Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T22:45:23.538Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T22:45:23.538Z] 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.
[2025-03-05T22:45:23.538Z] The best model improves the baseline by 14.43%.
[2025-03-05T22:45:23.538Z] Movies recommended for you:
[2025-03-05T22:45:23.538Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T22:45:23.538Z] There is no way to check that no silent failure occurred.
[2025-03-05T22:45:23.538Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (16361.354 ms) ======
[2025-03-05T22:45:23.538Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-03-05T22:45:23.538Z] GC before operation: completed in 111.345 ms, heap usage 95.943 MB -> 55.709 MB.
[2025-03-05T22:45:26.775Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-05T22:45:29.030Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-05T22:45:31.276Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-05T22:45:33.508Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-05T22:45:34.937Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-05T22:45:36.375Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-05T22:45:38.601Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-05T22:45:40.082Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-05T22:45:40.082Z] 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.
[2025-03-05T22:45:40.082Z] The best model improves the baseline by 14.43%.
[2025-03-05T22:45:40.082Z] Movies recommended for you:
[2025-03-05T22:45:40.082Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-05T22:45:40.082Z] There is no way to check that no silent failure occurred.
[2025-03-05T22:45:40.082Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (16282.647 ms) ======
[2025-03-05T22:45:42.886Z] -----------------------------------
[2025-03-05T22:45:42.886Z] renaissance-movie-lens_0_PASSED
[2025-03-05T22:45:42.886Z] -----------------------------------
[2025-03-05T22:45:42.886Z]
[2025-03-05T22:45:42.886Z] TEST TEARDOWN:
[2025-03-05T22:45:42.886Z] Nothing to be done for teardown.
[2025-03-05T22:45:42.886Z] renaissance-movie-lens_0 Finish Time: Wed Mar 5 16:45:41 2025 Epoch Time (ms): 1741214741249