renaissance-movie-lens_0
[2024-08-16T19:55:24.605Z] Running test renaissance-movie-lens_0 ...
[2024-08-16T19:55:24.605Z] ===============================================
[2024-08-16T19:55:24.605Z] renaissance-movie-lens_0 Start Time: Fri Aug 16 19:55:24 2024 Epoch Time (ms): 1723838124492
[2024-08-16T19:55:24.605Z] variation: NoOptions
[2024-08-16T19:55:24.605Z] JVM_OPTIONS:
[2024-08-16T19:55:24.605Z] { \
[2024-08-16T19:55:24.605Z] echo ""; echo "TEST SETUP:"; \
[2024-08-16T19:55:24.605Z] echo "Nothing to be done for setup."; \
[2024-08-16T19:55:24.606Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17238372633630/renaissance-movie-lens_0"; \
[2024-08-16T19:55:24.606Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17238372633630/renaissance-movie-lens_0"; \
[2024-08-16T19:55:24.606Z] echo ""; echo "TESTING:"; \
[2024-08-16T19:55:24.606Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_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_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17238372633630/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-16T19:55:24.606Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17238372633630/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-16T19:55:24.606Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-16T19:55:24.606Z] echo "Nothing to be done for teardown."; \
[2024-08-16T19:55:24.606Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17238372633630/TestTargetResult";
[2024-08-16T19:55:24.606Z]
[2024-08-16T19:55:24.606Z] TEST SETUP:
[2024-08-16T19:55:24.606Z] Nothing to be done for setup.
[2024-08-16T19:55:24.606Z]
[2024-08-16T19:55:24.606Z] TESTING:
[2024-08-16T19:55:27.526Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-16T19:55:29.424Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-08-16T19:55:32.402Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-16T19:55:32.402Z] Training: 60056, validation: 20285, test: 19854
[2024-08-16T19:55:32.402Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-16T19:55:32.402Z] GC before operation: completed in 52.368 ms, heap usage 76.098 MB -> 37.310 MB.
[2024-08-16T19:55:37.630Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:55:40.582Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:55:43.526Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:55:45.449Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:55:47.343Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:55:48.263Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:55:50.155Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:55:51.073Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:55:52.001Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-16T19:55:52.001Z] The best model improves the baseline by 14.52%.
[2024-08-16T19:55:52.001Z] Movies recommended for you:
[2024-08-16T19:55:52.001Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:55:52.001Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:55:52.001Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (19177.781 ms) ======
[2024-08-16T19:55:52.001Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-16T19:55:52.001Z] GC before operation: completed in 79.792 ms, heap usage 143.266 MB -> 52.629 MB.
[2024-08-16T19:55:53.889Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:55:56.808Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:55:58.702Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:56:00.591Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:56:01.510Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:56:03.399Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:56:04.318Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:56:05.403Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:56:06.323Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-16T19:56:06.323Z] The best model improves the baseline by 14.52%.
[2024-08-16T19:56:06.324Z] Movies recommended for you:
[2024-08-16T19:56:06.324Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:56:06.324Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:56:06.324Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (14199.546 ms) ======
[2024-08-16T19:56:06.324Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-16T19:56:06.324Z] GC before operation: completed in 82.070 ms, heap usage 214.043 MB -> 49.781 MB.
[2024-08-16T19:56:08.215Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:56:10.106Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:56:11.998Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:56:14.941Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:56:15.859Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:56:16.778Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:56:18.670Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:56:19.590Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:56:19.590Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-16T19:56:19.590Z] The best model improves the baseline by 14.52%.
[2024-08-16T19:56:19.590Z] Movies recommended for you:
[2024-08-16T19:56:19.590Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:56:19.590Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:56:19.590Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (13545.415 ms) ======
[2024-08-16T19:56:19.590Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-16T19:56:19.590Z] GC before operation: completed in 61.928 ms, heap usage 417.014 MB -> 53.459 MB.
[2024-08-16T19:56:21.481Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:56:24.044Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:56:25.957Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:56:27.846Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:56:28.767Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:56:29.686Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:56:31.577Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:56:32.502Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:56:32.502Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-16T19:56:32.502Z] The best model improves the baseline by 14.52%.
[2024-08-16T19:56:32.502Z] Movies recommended for you:
[2024-08-16T19:56:32.502Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:56:32.502Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:56:32.502Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (13112.224 ms) ======
[2024-08-16T19:56:32.502Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-16T19:56:33.430Z] GC before operation: completed in 78.576 ms, heap usage 79.119 MB -> 50.336 MB.
[2024-08-16T19:56:35.322Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:56:37.211Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:56:39.102Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:56:40.993Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:56:41.917Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:56:42.842Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:56:44.734Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:56:45.656Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:56:45.657Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-16T19:56:45.657Z] The best model improves the baseline by 14.52%.
[2024-08-16T19:56:45.657Z] Movies recommended for you:
[2024-08-16T19:56:45.657Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:56:45.657Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:56:45.657Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (13084.602 ms) ======
[2024-08-16T19:56:45.657Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-16T19:56:46.577Z] GC before operation: completed in 74.669 ms, heap usage 422.878 MB -> 54.007 MB.
[2024-08-16T19:56:47.498Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:56:49.397Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:56:51.289Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:56:53.181Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:56:55.077Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:56:55.998Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:56:56.920Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:56:57.842Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:56:58.764Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-16T19:56:58.764Z] The best model improves the baseline by 14.52%.
[2024-08-16T19:56:58.764Z] Movies recommended for you:
[2024-08-16T19:56:58.764Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:56:58.764Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:56:58.764Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (12327.893 ms) ======
[2024-08-16T19:56:58.764Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-16T19:56:58.764Z] GC before operation: completed in 73.515 ms, heap usage 73.604 MB -> 51.894 MB.
[2024-08-16T19:57:00.665Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:57:02.576Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:57:04.507Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:57:06.400Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:57:07.322Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:57:08.242Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:57:09.164Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:57:10.086Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:57:11.008Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-16T19:57:11.008Z] The best model improves the baseline by 14.52%.
[2024-08-16T19:57:11.008Z] Movies recommended for you:
[2024-08-16T19:57:11.008Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:57:11.008Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:57:11.008Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (12198.734 ms) ======
[2024-08-16T19:57:11.008Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-16T19:57:11.008Z] GC before operation: completed in 61.099 ms, heap usage 410.008 MB -> 54.148 MB.
[2024-08-16T19:57:12.902Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:57:14.794Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:57:16.686Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:57:18.582Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:57:19.502Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:57:20.425Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:57:21.348Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:57:22.280Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:57:23.200Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-16T19:57:23.200Z] The best model improves the baseline by 14.52%.
[2024-08-16T19:57:23.200Z] Movies recommended for you:
[2024-08-16T19:57:23.200Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:57:23.200Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:57:23.200Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (12233.542 ms) ======
[2024-08-16T19:57:23.200Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-16T19:57:23.200Z] GC before operation: completed in 70.012 ms, heap usage 86.140 MB -> 50.896 MB.
[2024-08-16T19:57:25.092Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:57:26.683Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:57:28.601Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:57:30.498Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:57:31.420Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:57:32.344Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:57:34.236Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:57:35.158Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:57:35.158Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-16T19:57:35.158Z] The best model improves the baseline by 14.52%.
[2024-08-16T19:57:35.158Z] Movies recommended for you:
[2024-08-16T19:57:35.158Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:57:35.158Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:57:35.158Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (12227.078 ms) ======
[2024-08-16T19:57:35.158Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-16T19:57:35.158Z] GC before operation: completed in 70.043 ms, heap usage 408.794 MB -> 54.332 MB.
[2024-08-16T19:57:37.051Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:57:38.945Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:57:40.837Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:57:42.730Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:57:43.653Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:57:44.576Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:57:45.496Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:57:47.388Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:57:47.388Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-16T19:57:47.388Z] The best model improves the baseline by 14.52%.
[2024-08-16T19:57:47.388Z] Movies recommended for you:
[2024-08-16T19:57:47.388Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:57:47.388Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:57:47.388Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (11961.928 ms) ======
[2024-08-16T19:57:47.388Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-16T19:57:47.388Z] GC before operation: completed in 73.095 ms, heap usage 209.379 MB -> 50.944 MB.
[2024-08-16T19:57:49.281Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:57:51.180Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:57:53.087Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:57:54.987Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:57:55.916Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:57:56.849Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:57:57.771Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:57:59.670Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:57:59.670Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-16T19:57:59.670Z] The best model improves the baseline by 14.52%.
[2024-08-16T19:57:59.670Z] Movies recommended for you:
[2024-08-16T19:57:59.670Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:57:59.670Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:57:59.670Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (12116.637 ms) ======
[2024-08-16T19:57:59.670Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-16T19:57:59.670Z] GC before operation: completed in 68.834 ms, heap usage 410.634 MB -> 54.125 MB.
[2024-08-16T19:58:01.570Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:58:03.577Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:58:05.506Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:58:06.426Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:58:08.322Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:58:09.242Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:58:10.163Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:58:11.084Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:58:11.084Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-16T19:58:12.007Z] The best model improves the baseline by 14.52%.
[2024-08-16T19:58:12.007Z] Movies recommended for you:
[2024-08-16T19:58:12.007Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:58:12.007Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:58:12.007Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (12035.732 ms) ======
[2024-08-16T19:58:12.007Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-16T19:58:12.007Z] GC before operation: completed in 73.631 ms, heap usage 313.506 MB -> 51.062 MB.
[2024-08-16T19:58:13.944Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:58:14.866Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:58:16.765Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:58:18.658Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:58:20.557Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:58:21.478Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:58:22.463Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:58:23.384Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:58:24.330Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-16T19:58:24.330Z] The best model improves the baseline by 14.52%.
[2024-08-16T19:58:24.330Z] Movies recommended for you:
[2024-08-16T19:58:24.330Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:58:24.330Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:58:24.330Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (12276.002 ms) ======
[2024-08-16T19:58:24.330Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-16T19:58:24.330Z] GC before operation: completed in 67.275 ms, heap usage 410.226 MB -> 54.529 MB.
[2024-08-16T19:58:26.221Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:58:28.116Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:58:30.008Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:58:31.777Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:58:32.744Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:58:33.667Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:58:34.590Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:58:35.512Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:58:36.436Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-16T19:58:36.436Z] The best model improves the baseline by 14.52%.
[2024-08-16T19:58:36.436Z] Movies recommended for you:
[2024-08-16T19:58:36.436Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:58:36.436Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:58:36.436Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (12157.412 ms) ======
[2024-08-16T19:58:36.436Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-16T19:58:36.436Z] GC before operation: completed in 93.449 ms, heap usage 79.311 MB -> 50.658 MB.
[2024-08-16T19:58:38.328Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:58:40.225Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:58:42.119Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:58:43.041Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:58:44.933Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:58:45.856Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:58:46.779Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:58:47.705Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:58:47.706Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-16T19:58:48.638Z] The best model improves the baseline by 14.52%.
[2024-08-16T19:58:48.638Z] Movies recommended for you:
[2024-08-16T19:58:48.638Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:58:48.638Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:58:48.638Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (11949.324 ms) ======
[2024-08-16T19:58:48.638Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-16T19:58:48.638Z] GC before operation: completed in 75.639 ms, heap usage 409.561 MB -> 54.445 MB.
[2024-08-16T19:58:50.532Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:58:52.427Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:58:54.320Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:58:55.242Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:58:57.136Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:58:58.058Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:58:58.982Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:58:59.904Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:59:00.842Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-16T19:59:00.842Z] The best model improves the baseline by 14.52%.
[2024-08-16T19:59:00.842Z] Movies recommended for you:
[2024-08-16T19:59:00.842Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:59:00.842Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:59:00.842Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (12165.811 ms) ======
[2024-08-16T19:59:00.842Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-16T19:59:00.842Z] GC before operation: completed in 65.011 ms, heap usage 378.702 MB -> 53.514 MB.
[2024-08-16T19:59:02.779Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:59:04.670Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:59:06.562Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:59:08.472Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:59:10.365Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:59:11.286Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:59:12.208Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:59:13.228Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:59:14.151Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-16T19:59:14.151Z] The best model improves the baseline by 14.52%.
[2024-08-16T19:59:14.151Z] Movies recommended for you:
[2024-08-16T19:59:14.151Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:59:14.151Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:59:14.151Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (13220.217 ms) ======
[2024-08-16T19:59:14.151Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-16T19:59:14.151Z] GC before operation: completed in 62.538 ms, heap usage 457.430 MB -> 54.536 MB.
[2024-08-16T19:59:16.045Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:59:17.940Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:59:19.832Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:59:21.726Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:59:22.648Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:59:23.571Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:59:25.462Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:59:26.386Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:59:26.386Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-16T19:59:26.386Z] The best model improves the baseline by 14.52%.
[2024-08-16T19:59:26.386Z] Movies recommended for you:
[2024-08-16T19:59:26.386Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:59:26.386Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:59:26.386Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (12695.239 ms) ======
[2024-08-16T19:59:26.386Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-16T19:59:26.386Z] GC before operation: completed in 65.337 ms, heap usage 618.653 MB -> 57.018 MB.
[2024-08-16T19:59:28.280Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:59:30.187Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:59:32.477Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:59:34.406Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:59:35.328Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:59:36.252Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:59:37.178Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:59:38.099Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:59:39.020Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-16T19:59:39.020Z] The best model improves the baseline by 14.52%.
[2024-08-16T19:59:39.020Z] Movies recommended for you:
[2024-08-16T19:59:39.020Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:59:39.020Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:59:39.020Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (12157.686 ms) ======
[2024-08-16T19:59:39.020Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-16T19:59:39.020Z] GC before operation: completed in 64.119 ms, heap usage 363.395 MB -> 51.368 MB.
[2024-08-16T19:59:40.921Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-16T19:59:42.816Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-16T19:59:44.713Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-16T19:59:46.612Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-16T19:59:47.531Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-16T19:59:48.452Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-16T19:59:50.376Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-16T19:59:51.305Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-16T19:59:51.305Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-16T19:59:51.305Z] The best model improves the baseline by 14.52%.
[2024-08-16T19:59:51.305Z] Movies recommended for you:
[2024-08-16T19:59:51.305Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-16T19:59:51.305Z] There is no way to check that no silent failure occurred.
[2024-08-16T19:59:51.305Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (12679.972 ms) ======
[2024-08-16T19:59:52.225Z] -----------------------------------
[2024-08-16T19:59:52.225Z] renaissance-movie-lens_0_PASSED
[2024-08-16T19:59:52.225Z] -----------------------------------
[2024-08-16T19:59:52.225Z]
[2024-08-16T19:59:52.225Z] TEST TEARDOWN:
[2024-08-16T19:59:52.225Z] Nothing to be done for teardown.
[2024-08-16T19:59:52.225Z] renaissance-movie-lens_0 Finish Time: Fri Aug 16 19:59:51 2024 Epoch Time (ms): 1723838391504