[2025-02-21T03:38:29.167Z] Running test renaissance-movie-lens_0 ... [2025-02-21T03:38:29.167Z] =============================================== [2025-02-21T03:38:29.486Z] renaissance-movie-lens_0 Start Time: Fri Feb 21 03:38:29 2025 Epoch Time (ms): 1740109109219 [2025-02-21T03:38:29.486Z] variation: NoOptions [2025-02-21T03:38:29.836Z] JVM_OPTIONS: [2025-02-21T03:38:29.836Z] { \ [2025-02-21T03:38:29.836Z] echo ""; echo "TEST SETUP:"; \ [2025-02-21T03:38:29.836Z] echo "Nothing to be done for setup."; \ [2025-02-21T03:38:29.836Z] mkdir -p "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17401074737932\\renaissance-movie-lens_0"; \ [2025-02-21T03:38:29.836Z] cd "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17401074737932\\renaissance-movie-lens_0"; \ [2025-02-21T03:38:29.836Z] echo ""; echo "TESTING:"; \ [2025-02-21T03:38:29.837Z] "c:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/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 "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17401074737932\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2025-02-21T03:38:29.837Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17401074737932\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-02-21T03:38:29.837Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-02-21T03:38:29.837Z] echo "Nothing to be done for teardown."; \ [2025-02-21T03:38:29.837Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17401074737932\\TestTargetResult"; [2025-02-21T03:38:29.837Z] [2025-02-21T03:38:29.837Z] TEST SETUP: [2025-02-21T03:38:29.837Z] Nothing to be done for setup. [2025-02-21T03:38:29.837Z] [2025-02-21T03:38:29.837Z] TESTING: [2025-02-21T03:38:48.809Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2025-02-21T03:38:50.479Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-02-21T03:38:54.340Z] Got 100004 ratings from 671 users on 9066 movies. [2025-02-21T03:38:54.754Z] Training: 60056, validation: 20285, test: 19854 [2025-02-21T03:38:54.754Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-02-21T03:38:54.754Z] GC before operation: completed in 81.020 ms, heap usage 63.682 MB -> 36.981 MB. [2025-02-21T03:39:17.941Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-21T03:39:31.052Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-21T03:39:44.138Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-21T03:39:57.307Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-21T03:40:04.599Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-21T03:40:11.900Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-21T03:40:19.087Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-21T03:40:26.327Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-21T03:40:26.679Z] 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. [2025-02-21T03:40:27.058Z] The best model improves the baseline by 14.52%. [2025-02-21T03:40:27.058Z] Movies recommended for you: [2025-02-21T03:40:27.058Z] WARNING: This benchmark provides no result that can be validated. [2025-02-21T03:40:27.058Z] There is no way to check that no silent failure occurred. [2025-02-21T03:40:27.058Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (92398.120 ms) ====== [2025-02-21T03:40:27.058Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-02-21T03:40:27.393Z] GC before operation: completed in 123.097 ms, heap usage 267.333 MB -> 51.050 MB. [2025-02-21T03:40:40.520Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-21T03:40:51.422Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-21T03:41:04.640Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-21T03:41:15.692Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-21T03:41:22.979Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-21T03:41:28.894Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-21T03:41:36.216Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-21T03:41:43.432Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-21T03:41:43.432Z] 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. [2025-02-21T03:41:43.432Z] The best model improves the baseline by 14.52%. [2025-02-21T03:41:43.777Z] Movies recommended for you: [2025-02-21T03:41:43.777Z] WARNING: This benchmark provides no result that can be validated. [2025-02-21T03:41:43.777Z] There is no way to check that no silent failure occurred. [2025-02-21T03:41:43.777Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (76350.606 ms) ====== [2025-02-21T03:41:43.777Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-02-21T03:41:43.777Z] GC before operation: completed in 107.245 ms, heap usage 225.769 MB -> 52.724 MB. [2025-02-21T03:41:56.951Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-21T03:42:07.739Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-21T03:42:18.467Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-21T03:42:29.277Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-21T03:42:35.106Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-21T03:42:40.948Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-21T03:42:48.173Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-21T03:42:54.013Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-21T03:42:54.799Z] 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. [2025-02-21T03:42:54.799Z] The best model improves the baseline by 14.52%. [2025-02-21T03:42:55.143Z] Movies recommended for you: [2025-02-21T03:42:55.143Z] WARNING: This benchmark provides no result that can be validated. [2025-02-21T03:42:55.143Z] There is no way to check that no silent failure occurred. [2025-02-21T03:42:55.143Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (71167.890 ms) ====== [2025-02-21T03:42:55.143Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-02-21T03:42:55.143Z] GC before operation: completed in 120.583 ms, heap usage 316.774 MB -> 52.133 MB. [2025-02-21T03:43:05.898Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-21T03:43:16.703Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-21T03:43:29.719Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-21T03:43:40.524Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-21T03:43:46.358Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-21T03:43:52.313Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-21T03:43:59.551Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-21T03:44:04.319Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-21T03:44:05.683Z] 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. [2025-02-21T03:44:05.683Z] The best model improves the baseline by 14.52%. [2025-02-21T03:44:05.683Z] Movies recommended for you: [2025-02-21T03:44:05.683Z] WARNING: This benchmark provides no result that can be validated. [2025-02-21T03:44:05.683Z] There is no way to check that no silent failure occurred. [2025-02-21T03:44:05.683Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (70455.174 ms) ====== [2025-02-21T03:44:05.683Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-02-21T03:44:06.004Z] GC before operation: completed in 116.326 ms, heap usage 243.928 MB -> 53.390 MB. [2025-02-21T03:44:16.838Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-21T03:44:27.570Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-21T03:44:40.704Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-21T03:44:49.496Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-21T03:44:56.747Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-21T03:45:01.468Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-21T03:45:08.659Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-21T03:45:14.515Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-21T03:45:14.916Z] 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. [2025-02-21T03:45:14.916Z] The best model improves the baseline by 14.52%. [2025-02-21T03:45:14.916Z] Movies recommended for you: [2025-02-21T03:45:14.916Z] WARNING: This benchmark provides no result that can be validated. [2025-02-21T03:45:14.916Z] There is no way to check that no silent failure occurred. [2025-02-21T03:45:14.916Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (69421.124 ms) ====== [2025-02-21T03:45:14.917Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-02-21T03:45:15.298Z] GC before operation: completed in 115.991 ms, heap usage 160.143 MB -> 53.455 MB. [2025-02-21T03:45:26.165Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-21T03:45:36.945Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-21T03:45:47.723Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-21T03:45:56.630Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-21T03:46:02.499Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-21T03:46:07.283Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-21T03:46:14.488Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-21T03:46:19.193Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-21T03:46:19.945Z] 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. [2025-02-21T03:46:19.945Z] The best model improves the baseline by 14.52%. [2025-02-21T03:46:20.287Z] Movies recommended for you: [2025-02-21T03:46:20.287Z] WARNING: This benchmark provides no result that can be validated. [2025-02-21T03:46:20.287Z] There is no way to check that no silent failure occurred. [2025-02-21T03:46:20.287Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (65160.842 ms) ====== [2025-02-21T03:46:20.287Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-02-21T03:46:20.287Z] GC before operation: completed in 133.727 ms, heap usage 181.201 MB -> 50.247 MB. [2025-02-21T03:46:31.157Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-21T03:46:41.996Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-21T03:46:52.776Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-21T03:47:03.523Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-21T03:47:08.292Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-21T03:47:14.181Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-21T03:47:20.118Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-21T03:47:26.024Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-21T03:47:26.436Z] 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. [2025-02-21T03:47:26.436Z] The best model improves the baseline by 14.52%. [2025-02-21T03:47:26.436Z] Movies recommended for you: [2025-02-21T03:47:26.436Z] WARNING: This benchmark provides no result that can be validated. [2025-02-21T03:47:26.436Z] There is no way to check that no silent failure occurred. [2025-02-21T03:47:26.436Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (66102.586 ms) ====== [2025-02-21T03:47:26.436Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-02-21T03:47:26.820Z] GC before operation: completed in 113.499 ms, heap usage 167.947 MB -> 51.675 MB. [2025-02-21T03:47:37.565Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-21T03:47:48.310Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-21T03:47:59.080Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-21T03:48:07.912Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-21T03:48:13.747Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-21T03:48:18.501Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-21T03:48:25.693Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-21T03:48:31.612Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-21T03:48:31.612Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-02-21T03:48:31.612Z] The best model improves the baseline by 14.52%. [2025-02-21T03:48:31.612Z] Movies recommended for you: [2025-02-21T03:48:31.612Z] WARNING: This benchmark provides no result that can be validated. [2025-02-21T03:48:31.612Z] There is no way to check that no silent failure occurred. [2025-02-21T03:48:31.612Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (64874.378 ms) ====== [2025-02-21T03:48:31.612Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-02-21T03:48:31.612Z] GC before operation: completed in 110.400 ms, heap usage 220.637 MB -> 53.953 MB. [2025-02-21T03:48:42.444Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-21T03:48:53.247Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-21T03:49:04.040Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-21T03:49:14.740Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-21T03:49:19.526Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-21T03:49:25.456Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-21T03:49:31.368Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-21T03:49:37.213Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-21T03:49:37.917Z] 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. [2025-02-21T03:49:37.917Z] The best model improves the baseline by 14.52%. [2025-02-21T03:49:37.917Z] Movies recommended for you: [2025-02-21T03:49:37.917Z] WARNING: This benchmark provides no result that can be validated. [2025-02-21T03:49:37.917Z] There is no way to check that no silent failure occurred. [2025-02-21T03:49:37.917Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (66342.292 ms) ====== [2025-02-21T03:49:37.917Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-02-21T03:49:38.273Z] GC before operation: completed in 114.580 ms, heap usage 185.667 MB -> 53.726 MB. [2025-02-21T03:49:49.020Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-21T03:49:57.941Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-21T03:50:11.029Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-21T03:50:19.867Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-21T03:50:25.707Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-21T03:50:30.391Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-21T03:50:36.250Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-21T03:50:42.098Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-21T03:50:42.416Z] 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. [2025-02-21T03:50:42.416Z] The best model improves the baseline by 14.52%. [2025-02-21T03:50:42.763Z] Movies recommended for you: [2025-02-21T03:50:42.763Z] WARNING: This benchmark provides no result that can be validated. [2025-02-21T03:50:42.763Z] There is no way to check that no silent failure occurred. [2025-02-21T03:50:42.763Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (64540.760 ms) ====== [2025-02-21T03:50:42.763Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-02-21T03:50:42.763Z] GC before operation: completed in 103.063 ms, heap usage 253.391 MB -> 50.714 MB. [2025-02-21T03:50:53.481Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-21T03:51:04.324Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-21T03:51:15.061Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-21T03:51:23.892Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-21T03:51:28.617Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-21T03:51:34.594Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-21T03:51:40.437Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-21T03:51:46.312Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-21T03:51:46.652Z] 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. [2025-02-21T03:51:46.652Z] The best model improves the baseline by 14.52%. [2025-02-21T03:51:47.027Z] Movies recommended for you: [2025-02-21T03:51:47.027Z] WARNING: This benchmark provides no result that can be validated. [2025-02-21T03:51:47.027Z] There is no way to check that no silent failure occurred. [2025-02-21T03:51:47.027Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (64179.659 ms) ====== [2025-02-21T03:51:47.027Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-02-21T03:51:47.027Z] GC before operation: completed in 115.825 ms, heap usage 174.429 MB -> 50.345 MB. [2025-02-21T03:51:57.781Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-21T03:52:06.731Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-21T03:52:17.626Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-21T03:52:28.457Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-21T03:52:33.164Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-21T03:52:39.051Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-21T03:52:46.261Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-21T03:52:50.986Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-21T03:52:52.135Z] 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. [2025-02-21T03:52:52.135Z] The best model improves the baseline by 14.52%. [2025-02-21T03:52:52.135Z] Movies recommended for you: [2025-02-21T03:52:52.135Z] WARNING: This benchmark provides no result that can be validated. [2025-02-21T03:52:52.135Z] There is no way to check that no silent failure occurred. [2025-02-21T03:52:52.135Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (65168.254 ms) ====== [2025-02-21T03:52:52.135Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-02-21T03:52:52.454Z] GC before operation: completed in 100.072 ms, heap usage 193.378 MB -> 51.733 MB. [2025-02-21T03:53:03.401Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-21T03:53:14.155Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-21T03:53:24.895Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-21T03:53:33.752Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-21T03:53:39.718Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-21T03:53:45.584Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-21T03:53:51.413Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-21T03:53:57.319Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-21T03:53:57.319Z] 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. [2025-02-21T03:53:57.319Z] The best model improves the baseline by 14.52%. [2025-02-21T03:53:57.319Z] Movies recommended for you: [2025-02-21T03:53:57.319Z] WARNING: This benchmark provides no result that can be validated. [2025-02-21T03:53:57.319Z] There is no way to check that no silent failure occurred. [2025-02-21T03:53:57.319Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (64911.253 ms) ====== [2025-02-21T03:53:57.319Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-02-21T03:53:57.319Z] GC before operation: completed in 107.072 ms, heap usage 214.178 MB -> 53.962 MB. [2025-02-21T03:54:08.202Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-21T03:54:17.024Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-21T03:54:27.814Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-21T03:54:38.563Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-21T03:54:43.255Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-21T03:54:49.267Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-21T03:54:55.095Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-21T03:55:00.997Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-21T03:55:00.997Z] 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. [2025-02-21T03:55:00.997Z] The best model improves the baseline by 14.52%. [2025-02-21T03:55:00.997Z] Movies recommended for you: [2025-02-21T03:55:00.997Z] WARNING: This benchmark provides no result that can be validated. [2025-02-21T03:55:00.997Z] There is no way to check that no silent failure occurred. [2025-02-21T03:55:00.997Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (63756.046 ms) ====== [2025-02-21T03:55:00.997Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-02-21T03:55:01.339Z] GC before operation: completed in 106.594 ms, heap usage 243.123 MB -> 53.723 MB. [2025-02-21T03:55:12.069Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-21T03:55:20.931Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-21T03:55:31.699Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-21T03:55:42.442Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-21T03:55:46.186Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-21T03:55:52.084Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-21T03:55:57.972Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-21T03:56:02.707Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-21T03:56:03.643Z] 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. [2025-02-21T03:56:03.643Z] The best model improves the baseline by 14.52%. [2025-02-21T03:56:03.643Z] Movies recommended for you: [2025-02-21T03:56:03.643Z] WARNING: This benchmark provides no result that can be validated. [2025-02-21T03:56:03.643Z] There is no way to check that no silent failure occurred. [2025-02-21T03:56:03.643Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (62542.676 ms) ====== [2025-02-21T03:56:03.643Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-02-21T03:56:03.984Z] GC before operation: completed in 107.274 ms, heap usage 165.198 MB -> 53.780 MB. [2025-02-21T03:56:14.709Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-21T03:56:23.545Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-21T03:56:34.333Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-21T03:56:45.042Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-21T03:56:49.765Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-21T03:56:54.453Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-21T03:57:01.675Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-21T03:57:07.523Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-21T03:57:07.523Z] 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. [2025-02-21T03:57:07.523Z] The best model improves the baseline by 14.52%. [2025-02-21T03:57:07.523Z] Movies recommended for you: [2025-02-21T03:57:07.523Z] WARNING: This benchmark provides no result that can be validated. [2025-02-21T03:57:07.523Z] There is no way to check that no silent failure occurred. [2025-02-21T03:57:07.523Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (63711.197 ms) ====== [2025-02-21T03:57:07.523Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-02-21T03:57:07.523Z] GC before operation: completed in 104.486 ms, heap usage 242.290 MB -> 53.964 MB. [2025-02-21T03:57:18.354Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-21T03:57:29.159Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-21T03:57:39.880Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-21T03:57:48.667Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-21T03:57:54.494Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-21T03:57:59.209Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-21T03:58:06.410Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-21T03:58:11.183Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-21T03:58:11.534Z] 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. [2025-02-21T03:58:11.534Z] The best model improves the baseline by 14.52%. [2025-02-21T03:58:11.534Z] Movies recommended for you: [2025-02-21T03:58:11.534Z] WARNING: This benchmark provides no result that can be validated. [2025-02-21T03:58:11.534Z] There is no way to check that no silent failure occurred. [2025-02-21T03:58:11.534Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (63937.122 ms) ====== [2025-02-21T03:58:11.534Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-02-21T03:58:11.885Z] GC before operation: completed in 113.989 ms, heap usage 160.749 MB -> 52.705 MB. [2025-02-21T03:58:22.658Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-21T03:58:33.374Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-21T03:58:44.100Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-21T03:58:52.915Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-21T03:58:57.608Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-21T03:59:03.422Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-21T03:59:09.285Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-21T03:59:15.119Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-21T03:59:15.454Z] 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. [2025-02-21T03:59:15.454Z] The best model improves the baseline by 14.52%. [2025-02-21T03:59:15.793Z] Movies recommended for you: [2025-02-21T03:59:15.793Z] WARNING: This benchmark provides no result that can be validated. [2025-02-21T03:59:15.793Z] There is no way to check that no silent failure occurred. [2025-02-21T03:59:15.793Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (63959.943 ms) ====== [2025-02-21T03:59:15.793Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-02-21T03:59:15.793Z] GC before operation: completed in 105.098 ms, heap usage 152.585 MB -> 53.734 MB. [2025-02-21T03:59:26.582Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-21T03:59:37.389Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-21T03:59:48.158Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-21T03:59:56.974Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-21T04:00:02.907Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-21T04:00:08.760Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-21T04:00:14.579Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-21T04:00:20.391Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-21T04:00:20.742Z] 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. [2025-02-21T04:00:20.742Z] The best model improves the baseline by 14.52%. [2025-02-21T04:00:20.742Z] Movies recommended for you: [2025-02-21T04:00:20.742Z] WARNING: This benchmark provides no result that can be validated. [2025-02-21T04:00:20.742Z] There is no way to check that no silent failure occurred. [2025-02-21T04:00:20.742Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (65035.290 ms) ====== [2025-02-21T04:00:20.742Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-02-21T04:00:21.075Z] GC before operation: completed in 120.105 ms, heap usage 241.933 MB -> 54.061 MB. [2025-02-21T04:00:31.850Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-21T04:00:40.819Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-21T04:00:53.997Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-21T04:01:02.846Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-21T04:01:07.564Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-21T04:01:12.346Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-21T04:01:18.290Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-21T04:01:24.153Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-21T04:01:24.559Z] 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. [2025-02-21T04:01:24.560Z] The best model improves the baseline by 14.52%. [2025-02-21T04:01:24.896Z] Movies recommended for you: [2025-02-21T04:01:24.896Z] WARNING: This benchmark provides no result that can be validated. [2025-02-21T04:01:24.896Z] There is no way to check that no silent failure occurred. [2025-02-21T04:01:24.896Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (63929.268 ms) ====== [2025-02-21T04:01:25.602Z] ----------------------------------- [2025-02-21T04:01:25.602Z] renaissance-movie-lens_0_PASSED [2025-02-21T04:01:25.602Z] ----------------------------------- [2025-02-21T04:01:26.299Z] [2025-02-21T04:01:26.299Z] TEST TEARDOWN: [2025-02-21T04:01:26.299Z] Nothing to be done for teardown. [2025-02-21T04:01:26.299Z] renaissance-movie-lens_0 Finish Time: Fri Feb 21 04:01:26 2025 Epoch Time (ms): 1740110486131