renaissance-movie-lens_0
[2024-09-25T21:41:56.791Z] Running test renaissance-movie-lens_0 ...
[2024-09-25T21:41:56.791Z] ===============================================
[2024-09-25T21:41:56.791Z] renaissance-movie-lens_0 Start Time: Wed Sep 25 21:41:55 2024 Epoch Time (ms): 1727300515749
[2024-09-25T21:41:56.791Z] variation: NoOptions
[2024-09-25T21:41:56.791Z] JVM_OPTIONS:
[2024-09-25T21:41:56.791Z] { \
[2024-09-25T21:41:56.791Z] echo ""; echo "TEST SETUP:"; \
[2024-09-25T21:41:56.791Z] echo "Nothing to be done for setup."; \
[2024-09-25T21:41:56.791Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_1727299738973/renaissance-movie-lens_0"; \
[2024-09-25T21:41:56.791Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_1727299738973/renaissance-movie-lens_0"; \
[2024-09-25T21:41:56.791Z] echo ""; echo "TESTING:"; \
[2024-09-25T21:41:56.791Z] "/home/jenkins/workspace/Test_openjdk11_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_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_1727299738973/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-09-25T21:41:56.791Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_1727299738973/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-09-25T21:41:56.791Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-09-25T21:41:56.791Z] echo "Nothing to be done for teardown."; \
[2024-09-25T21:41:56.791Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_1727299738973/TestTargetResult";
[2024-09-25T21:41:56.791Z]
[2024-09-25T21:41:56.791Z] TEST SETUP:
[2024-09-25T21:41:56.791Z] Nothing to be done for setup.
[2024-09-25T21:41:56.791Z]
[2024-09-25T21:41:56.791Z] TESTING:
[2024-09-25T21:41:58.829Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-09-25T21:42:00.883Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2024-09-25T21:42:05.268Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-09-25T21:42:05.268Z] Training: 60056, validation: 20285, test: 19854
[2024-09-25T21:42:05.268Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-09-25T21:42:05.268Z] GC before operation: completed in 54.875 ms, heap usage 160.386 MB -> 37.179 MB.
[2024-09-25T21:42:10.603Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:42:13.764Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:42:16.803Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:42:19.788Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:42:20.732Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:42:22.667Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:42:23.611Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:42:25.546Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:42:25.546Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-09-25T21:42:25.546Z] The best model improves the baseline by 14.43%.
[2024-09-25T21:42:25.546Z] Movies recommended for you:
[2024-09-25T21:42:25.546Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:42:25.546Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:42:25.546Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (20467.822 ms) ======
[2024-09-25T21:42:25.546Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-09-25T21:42:25.546Z] GC before operation: completed in 138.630 ms, heap usage 272.847 MB -> 49.564 MB.
[2024-09-25T21:42:27.493Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:42:30.135Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:42:32.072Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:42:35.057Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:42:36.000Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:42:36.943Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:42:37.883Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:42:39.825Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:42:39.825Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-09-25T21:42:39.825Z] The best model improves the baseline by 14.43%.
[2024-09-25T21:42:39.825Z] Movies recommended for you:
[2024-09-25T21:42:39.825Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:42:39.825Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:42:39.825Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (14293.139 ms) ======
[2024-09-25T21:42:39.825Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-09-25T21:42:39.825Z] GC before operation: completed in 136.830 ms, heap usage 262.262 MB -> 50.975 MB.
[2024-09-25T21:42:41.760Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:42:43.693Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:42:46.684Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:42:47.624Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:42:49.559Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:42:50.500Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:42:51.442Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:42:52.384Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:42:53.325Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-09-25T21:42:53.325Z] The best model improves the baseline by 14.43%.
[2024-09-25T21:42:53.325Z] Movies recommended for you:
[2024-09-25T21:42:53.325Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:42:53.326Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:42:53.326Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (13126.951 ms) ======
[2024-09-25T21:42:53.326Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-09-25T21:42:53.326Z] GC before operation: completed in 128.181 ms, heap usage 251.421 MB -> 51.312 MB.
[2024-09-25T21:42:55.258Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:42:57.191Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:42:59.123Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:43:01.056Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:43:01.997Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:43:02.938Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:43:03.881Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:43:05.811Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:43:05.811Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-09-25T21:43:05.811Z] The best model improves the baseline by 14.43%.
[2024-09-25T21:43:05.811Z] Movies recommended for you:
[2024-09-25T21:43:05.811Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:43:05.811Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:43:05.811Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (12397.464 ms) ======
[2024-09-25T21:43:05.811Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-09-25T21:43:05.811Z] GC before operation: completed in 136.968 ms, heap usage 121.990 MB -> 51.590 MB.
[2024-09-25T21:43:07.744Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:43:09.676Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:43:11.615Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:43:13.607Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:43:14.549Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:43:15.491Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:43:16.433Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:43:17.377Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:43:17.377Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-09-25T21:43:18.320Z] The best model improves the baseline by 14.43%.
[2024-09-25T21:43:18.320Z] Movies recommended for you:
[2024-09-25T21:43:18.320Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:43:18.320Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:43:18.320Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (12166.050 ms) ======
[2024-09-25T21:43:18.320Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-09-25T21:43:18.320Z] GC before operation: completed in 147.658 ms, heap usage 178.326 MB -> 51.834 MB.
[2024-09-25T21:43:20.255Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:43:22.193Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:43:24.129Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:43:25.071Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:43:27.002Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:43:27.944Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:43:28.885Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:43:29.827Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:43:29.827Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-09-25T21:43:29.827Z] The best model improves the baseline by 14.43%.
[2024-09-25T21:43:29.827Z] Movies recommended for you:
[2024-09-25T21:43:29.827Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:43:29.827Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:43:29.827Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (12099.982 ms) ======
[2024-09-25T21:43:29.827Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-09-25T21:43:30.768Z] GC before operation: completed in 135.885 ms, heap usage 573.350 MB -> 55.330 MB.
[2024-09-25T21:43:31.710Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:43:33.645Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:43:35.576Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:43:37.516Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:43:38.459Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:43:39.401Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:43:41.336Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:43:42.278Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:43:42.278Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-09-25T21:43:42.278Z] The best model improves the baseline by 14.43%.
[2024-09-25T21:43:42.278Z] Movies recommended for you:
[2024-09-25T21:43:42.278Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:43:42.278Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:43:42.278Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (12013.393 ms) ======
[2024-09-25T21:43:42.278Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-09-25T21:43:42.278Z] GC before operation: completed in 134.814 ms, heap usage 268.739 MB -> 52.000 MB.
[2024-09-25T21:43:44.210Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:43:45.880Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:43:47.817Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:43:49.756Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:43:50.700Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:43:51.644Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:43:53.586Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:43:54.527Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:43:54.527Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-09-25T21:43:54.527Z] The best model improves the baseline by 14.43%.
[2024-09-25T21:43:54.527Z] Movies recommended for you:
[2024-09-25T21:43:54.527Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:43:54.527Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:43:54.527Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (12026.638 ms) ======
[2024-09-25T21:43:54.527Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-09-25T21:43:54.527Z] GC before operation: completed in 146.247 ms, heap usage 193.657 MB -> 52.204 MB.
[2024-09-25T21:43:56.462Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:43:58.399Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:44:00.508Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:44:01.451Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:44:03.387Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:44:04.330Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:44:05.273Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:44:06.215Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:44:06.215Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-09-25T21:44:06.215Z] The best model improves the baseline by 14.43%.
[2024-09-25T21:44:06.215Z] Movies recommended for you:
[2024-09-25T21:44:06.215Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:44:06.216Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:44:06.216Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (11913.128 ms) ======
[2024-09-25T21:44:06.216Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-09-25T21:44:07.159Z] GC before operation: completed in 143.471 ms, heap usage 236.451 MB -> 52.025 MB.
[2024-09-25T21:44:09.092Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:44:10.033Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:44:11.967Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:44:13.926Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:44:14.866Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:44:15.808Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:44:16.748Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:44:18.690Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:44:18.690Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-09-25T21:44:18.690Z] The best model improves the baseline by 14.43%.
[2024-09-25T21:44:18.690Z] Movies recommended for you:
[2024-09-25T21:44:18.690Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:44:18.690Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:44:18.691Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (11834.654 ms) ======
[2024-09-25T21:44:18.691Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-09-25T21:44:18.691Z] GC before operation: completed in 149.704 ms, heap usage 177.089 MB -> 52.140 MB.
[2024-09-25T21:44:20.623Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:44:22.556Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:44:24.490Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:44:25.433Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:44:27.371Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:44:28.314Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:44:29.255Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:44:30.197Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:44:30.197Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-09-25T21:44:30.197Z] The best model improves the baseline by 14.43%.
[2024-09-25T21:44:30.197Z] Movies recommended for you:
[2024-09-25T21:44:30.197Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:44:30.197Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:44:30.197Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (11687.883 ms) ======
[2024-09-25T21:44:30.197Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-09-25T21:44:30.197Z] GC before operation: completed in 143.801 ms, heap usage 236.675 MB -> 51.907 MB.
[2024-09-25T21:44:32.127Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:44:34.061Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:44:35.993Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:44:37.928Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:44:38.869Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:44:39.813Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:44:40.754Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:44:41.696Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:44:42.638Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-09-25T21:44:42.638Z] The best model improves the baseline by 14.43%.
[2024-09-25T21:44:42.638Z] Movies recommended for you:
[2024-09-25T21:44:42.638Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:44:42.638Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:44:42.638Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (11767.388 ms) ======
[2024-09-25T21:44:42.638Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-09-25T21:44:42.638Z] GC before operation: completed in 137.545 ms, heap usage 124.467 MB -> 52.038 MB.
[2024-09-25T21:44:44.571Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:44:46.506Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:44:48.437Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:44:49.379Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:44:50.319Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:44:52.256Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:44:53.197Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:44:54.138Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:44:54.138Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-09-25T21:44:54.138Z] The best model improves the baseline by 14.43%.
[2024-09-25T21:44:54.138Z] Movies recommended for you:
[2024-09-25T21:44:54.138Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:44:54.138Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:44:54.138Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (11964.963 ms) ======
[2024-09-25T21:44:54.138Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-09-25T21:44:54.138Z] GC before operation: completed in 142.735 ms, heap usage 167.446 MB -> 52.176 MB.
[2024-09-25T21:44:56.107Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:44:58.039Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:45:00.675Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:45:01.616Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:45:02.556Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:45:03.505Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:45:04.445Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:45:06.376Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:45:06.376Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-09-25T21:45:06.376Z] The best model improves the baseline by 14.43%.
[2024-09-25T21:45:06.376Z] Movies recommended for you:
[2024-09-25T21:45:06.376Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:45:06.376Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:45:06.376Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (11697.415 ms) ======
[2024-09-25T21:45:06.376Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-09-25T21:45:06.376Z] GC before operation: completed in 140.105 ms, heap usage 150.579 MB -> 51.888 MB.
[2024-09-25T21:45:08.308Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:45:10.241Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:45:12.168Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:45:13.109Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:45:15.057Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:45:15.998Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:45:16.938Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:45:17.878Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:45:17.878Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-09-25T21:45:17.878Z] The best model improves the baseline by 14.43%.
[2024-09-25T21:45:17.878Z] Movies recommended for you:
[2024-09-25T21:45:17.878Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:45:17.878Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:45:17.878Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (11706.856 ms) ======
[2024-09-25T21:45:17.878Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-09-25T21:45:17.878Z] GC before operation: completed in 152.161 ms, heap usage 230.748 MB -> 52.192 MB.
[2024-09-25T21:45:19.836Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:45:21.766Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:45:23.695Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:45:25.626Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:45:26.568Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:45:27.509Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:45:28.454Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:45:29.395Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:45:30.337Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-09-25T21:45:30.337Z] The best model improves the baseline by 14.43%.
[2024-09-25T21:45:30.337Z] Movies recommended for you:
[2024-09-25T21:45:30.337Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:45:30.337Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:45:30.337Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (11774.684 ms) ======
[2024-09-25T21:45:30.337Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-09-25T21:45:30.337Z] GC before operation: completed in 137.005 ms, heap usage 163.644 MB -> 52.206 MB.
[2024-09-25T21:45:32.266Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:45:34.196Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:45:35.136Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:45:37.064Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:45:38.020Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:45:38.966Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:45:40.902Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:45:41.843Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:45:41.843Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-09-25T21:45:41.844Z] The best model improves the baseline by 14.43%.
[2024-09-25T21:45:41.844Z] Movies recommended for you:
[2024-09-25T21:45:41.844Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:45:41.844Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:45:41.844Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (11611.248 ms) ======
[2024-09-25T21:45:41.844Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-09-25T21:45:41.844Z] GC before operation: completed in 138.395 ms, heap usage 150.698 MB -> 52.060 MB.
[2024-09-25T21:45:43.780Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:45:45.712Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:45:47.644Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:45:49.701Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:45:49.701Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:45:51.639Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:45:52.580Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:45:53.524Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:45:53.524Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-09-25T21:45:53.524Z] The best model improves the baseline by 14.43%.
[2024-09-25T21:45:53.524Z] Movies recommended for you:
[2024-09-25T21:45:53.524Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:45:53.524Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:45:53.524Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (11808.856 ms) ======
[2024-09-25T21:45:53.524Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-09-25T21:45:53.524Z] GC before operation: completed in 134.175 ms, heap usage 309.113 MB -> 52.173 MB.
[2024-09-25T21:45:55.454Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:45:57.387Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:45:59.319Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:46:01.255Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:46:02.200Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:46:03.142Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:46:04.083Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:46:05.025Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:46:05.025Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-09-25T21:46:05.972Z] The best model improves the baseline by 14.43%.
[2024-09-25T21:46:05.972Z] Movies recommended for you:
[2024-09-25T21:46:05.972Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:46:05.972Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:46:05.972Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (11747.955 ms) ======
[2024-09-25T21:46:05.972Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-09-25T21:46:05.972Z] GC before operation: completed in 134.763 ms, heap usage 203.881 MB -> 52.332 MB.
[2024-09-25T21:46:07.906Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:46:10.536Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:46:11.479Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:46:13.418Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:46:14.360Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:46:15.303Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:46:16.245Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:46:17.189Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:46:17.189Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-09-25T21:46:17.189Z] The best model improves the baseline by 14.43%.
[2024-09-25T21:46:17.189Z] Movies recommended for you:
[2024-09-25T21:46:17.189Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:46:17.189Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:46:17.189Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (11808.329 ms) ======
[2024-09-25T21:46:19.126Z] -----------------------------------
[2024-09-25T21:46:19.126Z] renaissance-movie-lens_0_PASSED
[2024-09-25T21:46:19.126Z] -----------------------------------
[2024-09-25T21:46:19.126Z]
[2024-09-25T21:46:19.126Z] TEST TEARDOWN:
[2024-09-25T21:46:19.126Z] Nothing to be done for teardown.
[2024-09-25T21:46:19.126Z] renaissance-movie-lens_0 Finish Time: Wed Sep 25 21:46:18 2024 Epoch Time (ms): 1727300778119