renaissance-movie-lens_0
[2024-08-01T00:46:55.506Z] Running test renaissance-movie-lens_0 ...
[2024-08-01T00:46:55.506Z] ===============================================
[2024-08-01T00:46:55.506Z] renaissance-movie-lens_0 Start Time: Thu Aug 1 00:46:55 2024 Epoch Time (ms): 1722473215243
[2024-08-01T00:46:55.506Z] variation: NoOptions
[2024-08-01T00:46:55.506Z] JVM_OPTIONS:
[2024-08-01T00:46:55.506Z] { \
[2024-08-01T00:46:55.506Z] echo ""; echo "TEST SETUP:"; \
[2024-08-01T00:46:55.506Z] echo "Nothing to be done for setup."; \
[2024-08-01T00:46:55.506Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17224722299498/renaissance-movie-lens_0"; \
[2024-08-01T00:46:55.506Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17224722299498/renaissance-movie-lens_0"; \
[2024-08-01T00:46:55.506Z] echo ""; echo "TESTING:"; \
[2024-08-01T00:46:55.506Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/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_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17224722299498/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-01T00:46:55.506Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17224722299498/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-01T00:46:55.506Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-01T00:46:55.506Z] echo "Nothing to be done for teardown."; \
[2024-08-01T00:46:55.506Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17224722299498/TestTargetResult";
[2024-08-01T00:46:55.506Z]
[2024-08-01T00:46:55.506Z] TEST SETUP:
[2024-08-01T00:46:55.506Z] Nothing to be done for setup.
[2024-08-01T00:46:55.506Z]
[2024-08-01T00:46:55.506Z] TESTING:
[2024-08-01T00:46:59.607Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-01T00:47:02.584Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2024-08-01T00:47:05.582Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-01T00:47:06.521Z] Training: 60056, validation: 20285, test: 19854
[2024-08-01T00:47:06.521Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-01T00:47:06.521Z] GC before operation: completed in 67.987 ms, heap usage 163.259 MB -> 37.255 MB.
[2024-08-01T00:47:14.585Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T00:47:18.686Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T00:47:22.786Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T00:47:25.766Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T00:47:28.745Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T00:47:30.672Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T00:47:32.600Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T00:47:34.528Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T00:47:34.528Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-01T00:47:35.464Z] The best model improves the baseline by 14.43%.
[2024-08-01T00:47:35.464Z] Movies recommended for you:
[2024-08-01T00:47:35.464Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T00:47:35.464Z] There is no way to check that no silent failure occurred.
[2024-08-01T00:47:35.464Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (29130.558 ms) ======
[2024-08-01T00:47:35.464Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-01T00:47:35.464Z] GC before operation: completed in 168.700 ms, heap usage 319.342 MB -> 51.101 MB.
[2024-08-01T00:47:39.558Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T00:47:42.532Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T00:47:45.507Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T00:47:48.479Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T00:47:51.451Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T00:47:53.380Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T00:47:55.307Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T00:47:57.235Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T00:47:57.235Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-01T00:47:57.235Z] The best model improves the baseline by 14.43%.
[2024-08-01T00:47:57.235Z] Movies recommended for you:
[2024-08-01T00:47:57.235Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T00:47:57.235Z] There is no way to check that no silent failure occurred.
[2024-08-01T00:47:57.235Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (21897.439 ms) ======
[2024-08-01T00:47:57.235Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-01T00:47:57.235Z] GC before operation: completed in 164.065 ms, heap usage 168.266 MB -> 50.868 MB.
[2024-08-01T00:48:01.335Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T00:48:04.318Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T00:48:07.311Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T00:48:10.298Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T00:48:12.229Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T00:48:14.163Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T00:48:16.103Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T00:48:18.751Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T00:48:18.751Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-01T00:48:18.751Z] The best model improves the baseline by 14.43%.
[2024-08-01T00:48:18.751Z] Movies recommended for you:
[2024-08-01T00:48:18.751Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T00:48:18.751Z] There is no way to check that no silent failure occurred.
[2024-08-01T00:48:18.751Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (21112.559 ms) ======
[2024-08-01T00:48:18.751Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-01T00:48:18.751Z] GC before operation: completed in 152.840 ms, heap usage 199.860 MB -> 51.330 MB.
[2024-08-01T00:48:21.737Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T00:48:24.725Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T00:48:27.704Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T00:48:30.686Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T00:48:32.616Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T00:48:34.548Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T00:48:36.507Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T00:48:38.440Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T00:48:38.440Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-01T00:48:38.440Z] The best model improves the baseline by 14.43%.
[2024-08-01T00:48:38.440Z] Movies recommended for you:
[2024-08-01T00:48:38.440Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T00:48:38.440Z] There is no way to check that no silent failure occurred.
[2024-08-01T00:48:38.440Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (19893.554 ms) ======
[2024-08-01T00:48:38.440Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-01T00:48:39.382Z] GC before operation: completed in 144.238 ms, heap usage 215.546 MB -> 54.865 MB.
[2024-08-01T00:48:42.370Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T00:48:45.355Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T00:48:48.342Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T00:48:51.326Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T00:48:53.256Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T00:48:55.191Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T00:48:56.133Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T00:48:58.068Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T00:48:58.068Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-01T00:48:59.008Z] The best model improves the baseline by 14.43%.
[2024-08-01T00:48:59.008Z] Movies recommended for you:
[2024-08-01T00:48:59.008Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T00:48:59.008Z] There is no way to check that no silent failure occurred.
[2024-08-01T00:48:59.008Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (19753.720 ms) ======
[2024-08-01T00:48:59.008Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-01T00:48:59.008Z] GC before operation: completed in 167.163 ms, heap usage 457.072 MB -> 51.935 MB.
[2024-08-01T00:49:01.990Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T00:49:04.980Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T00:49:07.962Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T00:49:09.897Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T00:49:11.831Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T00:49:13.771Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T00:49:15.704Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T00:49:17.638Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T00:49:17.638Z] 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.
[2024-08-01T00:49:17.638Z] The best model improves the baseline by 14.43%.
[2024-08-01T00:49:17.638Z] Movies recommended for you:
[2024-08-01T00:49:17.638Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T00:49:17.638Z] There is no way to check that no silent failure occurred.
[2024-08-01T00:49:17.638Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (19139.428 ms) ======
[2024-08-01T00:49:17.638Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-01T00:49:18.580Z] GC before operation: completed in 153.704 ms, heap usage 219.320 MB -> 51.716 MB.
[2024-08-01T00:49:21.566Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T00:49:23.500Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T00:49:27.609Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T00:49:30.592Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T00:49:31.535Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T00:49:34.510Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T00:49:35.448Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T00:49:37.375Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T00:49:38.314Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-01T00:49:38.314Z] The best model improves the baseline by 14.43%.
[2024-08-01T00:49:38.314Z] Movies recommended for you:
[2024-08-01T00:49:38.314Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T00:49:38.314Z] There is no way to check that no silent failure occurred.
[2024-08-01T00:49:38.314Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (19922.864 ms) ======
[2024-08-01T00:49:38.314Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-01T00:49:38.314Z] GC before operation: completed in 153.320 ms, heap usage 218.316 MB -> 51.925 MB.
[2024-08-01T00:49:40.693Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T00:49:43.675Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T00:49:46.659Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T00:49:49.772Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T00:49:51.704Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T00:49:53.637Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T00:49:54.577Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T00:49:56.507Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T00:49:56.507Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-01T00:49:56.507Z] The best model improves the baseline by 14.43%.
[2024-08-01T00:49:57.449Z] Movies recommended for you:
[2024-08-01T00:49:57.449Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T00:49:57.449Z] There is no way to check that no silent failure occurred.
[2024-08-01T00:49:57.449Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (18852.611 ms) ======
[2024-08-01T00:49:57.449Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-01T00:49:57.449Z] GC before operation: completed in 155.738 ms, heap usage 128.082 MB -> 52.110 MB.
[2024-08-01T00:50:00.433Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T00:50:03.419Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T00:50:06.399Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T00:50:09.378Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T00:50:11.306Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T00:50:13.236Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T00:50:15.163Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T00:50:16.102Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T00:50:16.102Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-01T00:50:16.102Z] The best model improves the baseline by 14.43%.
[2024-08-01T00:50:17.042Z] Movies recommended for you:
[2024-08-01T00:50:17.042Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T00:50:17.042Z] There is no way to check that no silent failure occurred.
[2024-08-01T00:50:17.042Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (19436.715 ms) ======
[2024-08-01T00:50:17.042Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-01T00:50:17.042Z] GC before operation: completed in 137.659 ms, heap usage 220.139 MB -> 52.070 MB.
[2024-08-01T00:50:18.971Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T00:50:22.126Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T00:50:25.110Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T00:50:27.042Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T00:50:28.970Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T00:50:30.902Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T00:50:32.831Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T00:50:33.774Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T00:50:34.716Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-01T00:50:34.716Z] The best model improves the baseline by 14.43%.
[2024-08-01T00:50:34.716Z] Movies recommended for you:
[2024-08-01T00:50:34.716Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T00:50:34.716Z] There is no way to check that no silent failure occurred.
[2024-08-01T00:50:34.716Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (17749.640 ms) ======
[2024-08-01T00:50:34.716Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-01T00:50:34.716Z] GC before operation: completed in 183.242 ms, heap usage 558.535 MB -> 55.632 MB.
[2024-08-01T00:50:37.698Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T00:50:40.679Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T00:50:43.657Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T00:50:45.588Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T00:50:47.518Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T00:50:49.450Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T00:50:50.530Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T00:50:52.461Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T00:50:52.461Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-01T00:50:52.461Z] The best model improves the baseline by 14.43%.
[2024-08-01T00:50:52.461Z] Movies recommended for you:
[2024-08-01T00:50:52.461Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T00:50:52.461Z] There is no way to check that no silent failure occurred.
[2024-08-01T00:50:52.461Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (18174.594 ms) ======
[2024-08-01T00:50:52.461Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-01T00:50:53.401Z] GC before operation: completed in 160.103 ms, heap usage 320.388 MB -> 51.949 MB.
[2024-08-01T00:50:56.378Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T00:50:59.001Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T00:51:01.984Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T00:51:04.960Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T00:51:06.891Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T00:51:07.846Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T00:51:09.780Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T00:51:11.712Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T00:51:11.712Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-01T00:51:11.712Z] The best model improves the baseline by 14.43%.
[2024-08-01T00:51:11.712Z] Movies recommended for you:
[2024-08-01T00:51:11.712Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T00:51:11.712Z] There is no way to check that no silent failure occurred.
[2024-08-01T00:51:11.712Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (19075.314 ms) ======
[2024-08-01T00:51:11.712Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-01T00:51:12.653Z] GC before operation: completed in 153.685 ms, heap usage 237.954 MB -> 52.085 MB.
[2024-08-01T00:51:15.652Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T00:51:17.595Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T00:51:20.583Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T00:51:23.579Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T00:51:25.523Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T00:51:27.467Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T00:51:28.408Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T00:51:30.344Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T00:51:31.290Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-01T00:51:31.290Z] The best model improves the baseline by 14.43%.
[2024-08-01T00:51:31.290Z] Movies recommended for you:
[2024-08-01T00:51:31.290Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T00:51:31.290Z] There is no way to check that no silent failure occurred.
[2024-08-01T00:51:31.290Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (18788.163 ms) ======
[2024-08-01T00:51:31.290Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-01T00:51:31.290Z] GC before operation: completed in 155.032 ms, heap usage 209.258 MB -> 52.262 MB.
[2024-08-01T00:51:34.292Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T00:51:37.277Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T00:51:40.263Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T00:51:43.247Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T00:51:44.189Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T00:51:46.119Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T00:51:48.049Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T00:51:48.990Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T00:51:49.955Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-01T00:51:49.955Z] The best model improves the baseline by 14.43%.
[2024-08-01T00:51:49.955Z] Movies recommended for you:
[2024-08-01T00:51:49.955Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T00:51:49.955Z] There is no way to check that no silent failure occurred.
[2024-08-01T00:51:49.955Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (18549.120 ms) ======
[2024-08-01T00:51:49.955Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-01T00:51:49.955Z] GC before operation: completed in 152.787 ms, heap usage 180.751 MB -> 51.947 MB.
[2024-08-01T00:51:52.935Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T00:51:55.916Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T00:51:57.848Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T00:52:00.832Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T00:52:02.763Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T00:52:04.695Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T00:52:05.638Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T00:52:07.567Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T00:52:07.567Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-01T00:52:07.567Z] The best model improves the baseline by 14.43%.
[2024-08-01T00:52:07.567Z] Movies recommended for you:
[2024-08-01T00:52:07.567Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T00:52:07.567Z] There is no way to check that no silent failure occurred.
[2024-08-01T00:52:07.567Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (18020.995 ms) ======
[2024-08-01T00:52:07.567Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-01T00:52:08.507Z] GC before operation: completed in 143.818 ms, heap usage 136.220 MB -> 52.076 MB.
[2024-08-01T00:52:10.441Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T00:52:13.422Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T00:52:16.406Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T00:52:20.254Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T00:52:21.200Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T00:52:23.129Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T00:52:24.069Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T00:52:26.001Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T00:52:26.001Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-01T00:52:26.001Z] The best model improves the baseline by 14.43%.
[2024-08-01T00:52:26.942Z] Movies recommended for you:
[2024-08-01T00:52:26.942Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T00:52:26.942Z] There is no way to check that no silent failure occurred.
[2024-08-01T00:52:26.942Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (18412.783 ms) ======
[2024-08-01T00:52:26.942Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-01T00:52:26.942Z] GC before operation: completed in 172.861 ms, heap usage 107.110 MB -> 52.345 MB.
[2024-08-01T00:52:29.925Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T00:52:31.855Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T00:52:34.849Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T00:52:37.829Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T00:52:38.769Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T00:52:40.696Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T00:52:42.622Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T00:52:44.555Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T00:52:44.555Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-01T00:52:44.555Z] The best model improves the baseline by 14.43%.
[2024-08-01T00:52:44.555Z] Movies recommended for you:
[2024-08-01T00:52:44.555Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T00:52:44.555Z] There is no way to check that no silent failure occurred.
[2024-08-01T00:52:44.555Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (17886.792 ms) ======
[2024-08-01T00:52:44.555Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-01T00:52:44.555Z] GC before operation: completed in 147.672 ms, heap usage 167.308 MB -> 52.050 MB.
[2024-08-01T00:52:47.531Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T00:52:50.666Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T00:52:53.696Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T00:52:56.677Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T00:52:58.608Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T00:52:59.549Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T00:53:01.478Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T00:53:02.417Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T00:53:02.417Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-01T00:53:02.417Z] The best model improves the baseline by 14.43%.
[2024-08-01T00:53:02.417Z] Movies recommended for you:
[2024-08-01T00:53:02.417Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T00:53:02.417Z] There is no way to check that no silent failure occurred.
[2024-08-01T00:53:02.417Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (17888.204 ms) ======
[2024-08-01T00:53:02.417Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-01T00:53:02.417Z] GC before operation: completed in 147.424 ms, heap usage 262.152 MB -> 52.165 MB.
[2024-08-01T00:53:05.398Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T00:53:07.330Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T00:53:09.260Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T00:53:11.189Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T00:53:12.129Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T00:53:13.071Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T00:53:15.001Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T00:53:15.940Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T00:53:15.940Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-01T00:53:15.940Z] The best model improves the baseline by 14.43%.
[2024-08-01T00:53:15.940Z] Movies recommended for you:
[2024-08-01T00:53:15.940Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T00:53:15.940Z] There is no way to check that no silent failure occurred.
[2024-08-01T00:53:15.940Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (13508.462 ms) ======
[2024-08-01T00:53:15.940Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-01T00:53:16.879Z] GC before operation: completed in 143.205 ms, heap usage 182.727 MB -> 52.366 MB.
[2024-08-01T00:53:18.808Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T00:53:20.735Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T00:53:22.664Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T00:53:24.598Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T00:53:26.535Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T00:53:27.480Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T00:53:29.421Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T00:53:30.365Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T00:53:31.309Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-01T00:53:31.309Z] The best model improves the baseline by 14.43%.
[2024-08-01T00:53:31.309Z] Movies recommended for you:
[2024-08-01T00:53:31.309Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T00:53:31.309Z] There is no way to check that no silent failure occurred.
[2024-08-01T00:53:31.309Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14709.396 ms) ======
[2024-08-01T00:53:32.249Z] -----------------------------------
[2024-08-01T00:53:32.249Z] renaissance-movie-lens_0_PASSED
[2024-08-01T00:53:32.249Z] -----------------------------------
[2024-08-01T00:53:32.249Z]
[2024-08-01T00:53:32.249Z] TEST TEARDOWN:
[2024-08-01T00:53:32.249Z] Nothing to be done for teardown.
[2024-08-01T00:53:32.249Z] renaissance-movie-lens_0 Finish Time: Thu Aug 1 00:53:32 2024 Epoch Time (ms): 1722473612064