[2025-02-20T19:40:25.445Z] Running test renaissance-movie-lens_0 ... [2025-02-20T19:40:25.445Z] =============================================== [2025-02-20T19:40:25.445Z] renaissance-movie-lens_0 Start Time: Thu Feb 20 19:40:25 2025 Epoch Time (ms): 1740080425242 [2025-02-20T19:40:25.445Z] variation: NoOptions [2025-02-20T19:40:25.445Z] JVM_OPTIONS: [2025-02-20T19:40:25.445Z] { \ [2025-02-20T19:40:25.445Z] echo ""; echo "TEST SETUP:"; \ [2025-02-20T19:40:25.445Z] echo "Nothing to be done for setup."; \ [2025-02-20T19:40:25.445Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17400760084674/renaissance-movie-lens_0"; \ [2025-02-20T19:40:25.445Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17400760084674/renaissance-movie-lens_0"; \ [2025-02-20T19:40:25.445Z] echo ""; echo "TESTING:"; \ [2025-02-20T19:40:25.445Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17400760084674/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-02-20T19:40:25.445Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17400760084674/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-02-20T19:40:25.445Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-02-20T19:40:25.445Z] echo "Nothing to be done for teardown."; \ [2025-02-20T19:40:25.445Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17400760084674/TestTargetResult"; [2025-02-20T19:40:25.445Z] [2025-02-20T19:40:25.445Z] TEST SETUP: [2025-02-20T19:40:25.445Z] Nothing to be done for setup. [2025-02-20T19:40:25.445Z] [2025-02-20T19:40:25.445Z] TESTING: [2025-02-20T19:40:34.460Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2025-02-20T19:40:42.597Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-02-20T19:40:57.562Z] Got 100004 ratings from 671 users on 9066 movies. [2025-02-20T19:40:58.414Z] Training: 60056, validation: 20285, test: 19854 [2025-02-20T19:40:58.414Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-02-20T19:40:58.414Z] GC before operation: completed in 202.580 ms, heap usage 132.160 MB -> 37.186 MB. [2025-02-20T19:41:30.261Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T19:41:53.718Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T19:42:10.949Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T19:42:26.472Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T19:42:35.666Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T19:42:44.754Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T19:42:53.791Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T19:42:59.992Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T19:43:01.788Z] 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. [2025-02-20T19:43:01.788Z] The best model improves the baseline by 14.52%. [2025-02-20T19:43:02.666Z] Movies recommended for you: [2025-02-20T19:43:02.666Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T19:43:02.666Z] There is no way to check that no silent failure occurred. [2025-02-20T19:43:02.666Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (124765.690 ms) ====== [2025-02-20T19:43:02.666Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-02-20T19:43:03.512Z] GC before operation: completed in 424.351 ms, heap usage 219.705 MB -> 49.257 MB. [2025-02-20T19:43:14.493Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T19:43:27.252Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T19:43:39.629Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T19:43:49.750Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T19:43:55.499Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T19:44:02.085Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T19:44:09.210Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T19:44:14.150Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T19:44:15.824Z] 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. [2025-02-20T19:44:15.824Z] The best model improves the baseline by 14.52%. [2025-02-20T19:44:16.606Z] Movies recommended for you: [2025-02-20T19:44:16.606Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T19:44:16.606Z] There is no way to check that no silent failure occurred. [2025-02-20T19:44:16.606Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (73245.451 ms) ====== [2025-02-20T19:44:16.606Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-02-20T19:44:16.606Z] GC before operation: completed in 397.686 ms, heap usage 124.067 MB -> 49.576 MB. [2025-02-20T19:44:28.788Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T19:44:40.657Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T19:44:54.674Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T19:45:05.443Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T19:45:14.024Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T19:45:21.277Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T19:45:29.657Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T19:45:38.191Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T19:45:38.994Z] 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. [2025-02-20T19:45:38.994Z] The best model improves the baseline by 14.52%. [2025-02-20T19:45:38.994Z] Movies recommended for you: [2025-02-20T19:45:38.994Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T19:45:38.994Z] There is no way to check that no silent failure occurred. [2025-02-20T19:45:38.994Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (82634.151 ms) ====== [2025-02-20T19:45:38.994Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-02-20T19:45:39.789Z] GC before operation: completed in 419.083 ms, heap usage 70.493 MB -> 51.432 MB. [2025-02-20T19:45:51.654Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T19:46:01.679Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T19:46:15.071Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T19:46:30.290Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T19:46:37.275Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T19:46:44.290Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T19:46:51.449Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T19:46:58.408Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T19:46:59.185Z] 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. [2025-02-20T19:46:59.185Z] The best model improves the baseline by 14.52%. [2025-02-20T19:46:59.966Z] Movies recommended for you: [2025-02-20T19:46:59.966Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T19:46:59.966Z] There is no way to check that no silent failure occurred. [2025-02-20T19:46:59.966Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (79896.316 ms) ====== [2025-02-20T19:46:59.966Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-02-20T19:46:59.966Z] GC before operation: completed in 369.432 ms, heap usage 321.729 MB -> 50.347 MB. [2025-02-20T19:47:13.934Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T19:47:24.055Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T19:47:36.740Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T19:47:50.726Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T19:47:57.876Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T19:48:04.897Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T19:48:10.674Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T19:48:16.515Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T19:48:18.274Z] 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. [2025-02-20T19:48:18.274Z] The best model improves the baseline by 14.52%. [2025-02-20T19:48:18.274Z] Movies recommended for you: [2025-02-20T19:48:18.274Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T19:48:18.274Z] There is no way to check that no silent failure occurred. [2025-02-20T19:48:18.275Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (78505.287 ms) ====== [2025-02-20T19:48:18.275Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-02-20T19:48:19.053Z] GC before operation: completed in 349.197 ms, heap usage 426.275 MB -> 53.841 MB. [2025-02-20T19:48:29.053Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T19:48:41.481Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T19:48:53.457Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T19:49:01.991Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T19:49:07.819Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T19:49:14.903Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T19:49:20.754Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T19:49:26.542Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T19:49:27.338Z] 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. [2025-02-20T19:49:27.338Z] The best model improves the baseline by 14.52%. [2025-02-20T19:49:28.138Z] Movies recommended for you: [2025-02-20T19:49:28.138Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T19:49:28.138Z] There is no way to check that no silent failure occurred. [2025-02-20T19:49:28.138Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (69089.074 ms) ====== [2025-02-20T19:49:28.138Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-02-20T19:49:28.138Z] GC before operation: completed in 311.753 ms, heap usage 93.067 MB -> 50.425 MB. [2025-02-20T19:49:38.248Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T19:49:48.825Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T19:50:00.725Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T19:50:09.231Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T19:50:16.295Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T19:50:22.164Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T19:50:27.935Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T19:50:32.588Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T19:50:33.362Z] 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. [2025-02-20T19:50:33.362Z] The best model improves the baseline by 14.52%. [2025-02-20T19:50:34.141Z] Movies recommended for you: [2025-02-20T19:50:34.141Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T19:50:34.141Z] There is no way to check that no silent failure occurred. [2025-02-20T19:50:34.141Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (65427.704 ms) ====== [2025-02-20T19:50:34.141Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-02-20T19:50:34.141Z] GC before operation: completed in 302.752 ms, heap usage 424.076 MB -> 53.959 MB. [2025-02-20T19:50:42.840Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T19:50:51.319Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T19:51:01.444Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T19:51:09.996Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T19:51:14.558Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T19:51:20.376Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T19:51:26.078Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T19:51:31.732Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T19:51:32.560Z] 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. [2025-02-20T19:51:32.560Z] The best model improves the baseline by 14.52%. [2025-02-20T19:51:32.560Z] Movies recommended for you: [2025-02-20T19:51:32.560Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T19:51:32.560Z] There is no way to check that no silent failure occurred. [2025-02-20T19:51:32.560Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (58526.325 ms) ====== [2025-02-20T19:51:32.560Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-02-20T19:51:33.356Z] GC before operation: completed in 383.170 ms, heap usage 282.893 MB -> 50.897 MB. [2025-02-20T19:51:41.931Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T19:51:50.378Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T19:52:02.361Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T19:52:12.414Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T19:52:16.997Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T19:52:22.833Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T19:52:30.014Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T19:52:35.712Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T19:52:37.365Z] 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. [2025-02-20T19:52:37.365Z] The best model improves the baseline by 14.52%. [2025-02-20T19:52:37.365Z] Movies recommended for you: [2025-02-20T19:52:37.365Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T19:52:37.365Z] There is no way to check that no silent failure occurred. [2025-02-20T19:52:37.365Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (64423.766 ms) ====== [2025-02-20T19:52:37.365Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-02-20T19:52:37.365Z] GC before operation: completed in 337.478 ms, heap usage 205.057 MB -> 51.295 MB. [2025-02-20T19:52:48.037Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T19:52:58.133Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T19:53:09.995Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T19:53:19.989Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T19:53:26.952Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T19:53:32.618Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T19:53:40.938Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T19:53:46.613Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T19:53:48.225Z] 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. [2025-02-20T19:53:48.225Z] The best model improves the baseline by 14.52%. [2025-02-20T19:53:49.343Z] Movies recommended for you: [2025-02-20T19:53:49.343Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T19:53:49.343Z] There is no way to check that no silent failure occurred. [2025-02-20T19:53:49.343Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (71098.138 ms) ====== [2025-02-20T19:53:49.343Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-02-20T19:53:49.343Z] GC before operation: completed in 449.950 ms, heap usage 69.389 MB -> 54.383 MB. [2025-02-20T19:54:01.128Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T19:54:11.117Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T19:54:25.199Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T19:54:33.725Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T19:54:43.742Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T19:54:49.450Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T19:54:57.000Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T19:55:03.977Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T19:55:04.756Z] 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. [2025-02-20T19:55:04.756Z] The best model improves the baseline by 14.52%. [2025-02-20T19:55:04.756Z] Movies recommended for you: [2025-02-20T19:55:04.756Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T19:55:04.756Z] There is no way to check that no silent failure occurred. [2025-02-20T19:55:04.756Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (75609.271 ms) ====== [2025-02-20T19:55:04.756Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-02-20T19:55:05.532Z] GC before operation: completed in 427.377 ms, heap usage 318.152 MB -> 50.637 MB. [2025-02-20T19:55:16.992Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T19:55:30.430Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T19:55:41.803Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T19:55:51.400Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T19:55:55.736Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T19:56:01.740Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T19:56:08.395Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T19:56:13.906Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T19:56:15.431Z] 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. [2025-02-20T19:56:15.431Z] The best model improves the baseline by 14.52%. [2025-02-20T19:56:16.171Z] Movies recommended for you: [2025-02-20T19:56:16.171Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T19:56:16.171Z] There is no way to check that no silent failure occurred. [2025-02-20T19:56:16.171Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (70834.198 ms) ====== [2025-02-20T19:56:16.171Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-02-20T19:56:16.171Z] GC before operation: completed in 369.772 ms, heap usage 219.961 MB -> 50.764 MB. [2025-02-20T19:56:25.995Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T19:56:35.613Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T19:56:45.219Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T19:56:53.211Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T19:56:59.825Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T19:57:05.847Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T19:57:11.382Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T19:57:18.098Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T19:57:18.836Z] 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. [2025-02-20T19:57:18.836Z] The best model improves the baseline by 14.52%. [2025-02-20T19:57:19.586Z] Movies recommended for you: [2025-02-20T19:57:19.586Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T19:57:19.586Z] There is no way to check that no silent failure occurred. [2025-02-20T19:57:19.586Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (62896.298 ms) ====== [2025-02-20T19:57:19.586Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-02-20T19:57:19.586Z] GC before operation: completed in 288.065 ms, heap usage 121.420 MB -> 50.986 MB. [2025-02-20T19:57:31.248Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T19:57:40.851Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T19:57:52.285Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T19:58:02.009Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T19:58:10.583Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T19:58:16.043Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T19:58:22.675Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T19:58:26.971Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T19:58:27.714Z] 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. [2025-02-20T19:58:27.714Z] The best model improves the baseline by 14.52%. [2025-02-20T19:58:28.457Z] Movies recommended for you: [2025-02-20T19:58:28.457Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T19:58:28.457Z] There is no way to check that no silent failure occurred. [2025-02-20T19:58:28.457Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (68616.636 ms) ====== [2025-02-20T19:58:28.457Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-02-20T19:58:28.457Z] GC before operation: completed in 304.452 ms, heap usage 194.337 MB -> 51.531 MB. [2025-02-20T19:58:38.087Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T19:58:47.962Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T19:58:59.927Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T19:59:09.627Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T19:59:16.417Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T19:59:23.227Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T19:59:29.919Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T19:59:34.248Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T19:59:35.817Z] 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. [2025-02-20T19:59:35.817Z] The best model improves the baseline by 14.52%. [2025-02-20T19:59:36.650Z] Movies recommended for you: [2025-02-20T19:59:36.650Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T19:59:36.650Z] There is no way to check that no silent failure occurred. [2025-02-20T19:59:36.650Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (67605.137 ms) ====== [2025-02-20T19:59:36.650Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-02-20T19:59:36.650Z] GC before operation: completed in 330.789 ms, heap usage 69.712 MB -> 53.899 MB. [2025-02-20T19:59:46.651Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T19:59:55.244Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T20:00:05.896Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T20:00:15.525Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T20:00:25.589Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T20:00:31.272Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T20:00:36.888Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T20:00:42.721Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T20:00:43.500Z] 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. [2025-02-20T20:00:43.500Z] The best model improves the baseline by 14.52%. [2025-02-20T20:00:43.500Z] Movies recommended for you: [2025-02-20T20:00:43.500Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T20:00:43.500Z] There is no way to check that no silent failure occurred. [2025-02-20T20:00:43.500Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (66934.769 ms) ====== [2025-02-20T20:00:43.500Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-02-20T20:00:43.501Z] GC before operation: completed in 340.108 ms, heap usage 395.350 MB -> 54.806 MB. [2025-02-20T20:00:53.534Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T20:01:01.970Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T20:01:13.842Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T20:01:22.482Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T20:01:27.117Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T20:01:31.753Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T20:01:36.864Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T20:01:42.559Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T20:01:43.338Z] 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. [2025-02-20T20:01:43.338Z] The best model improves the baseline by 14.52%. [2025-02-20T20:01:43.338Z] Movies recommended for you: [2025-02-20T20:01:43.338Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T20:01:43.338Z] There is no way to check that no silent failure occurred. [2025-02-20T20:01:43.338Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (59516.997 ms) ====== [2025-02-20T20:01:43.338Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-02-20T20:01:43.338Z] GC before operation: completed in 251.101 ms, heap usage 428.364 MB -> 54.118 MB. [2025-02-20T20:01:54.351Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T20:02:04.358Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T20:02:12.877Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T20:02:21.441Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T20:02:27.109Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T20:02:32.035Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T20:02:37.759Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T20:02:42.333Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T20:02:43.125Z] 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. [2025-02-20T20:02:43.125Z] The best model improves the baseline by 14.52%. [2025-02-20T20:02:43.898Z] Movies recommended for you: [2025-02-20T20:02:43.898Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T20:02:43.898Z] There is no way to check that no silent failure occurred. [2025-02-20T20:02:43.898Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (60026.059 ms) ====== [2025-02-20T20:02:43.898Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-02-20T20:02:43.898Z] GC before operation: completed in 326.850 ms, heap usage 212.819 MB -> 50.837 MB. [2025-02-20T20:02:50.888Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T20:02:57.876Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T20:03:07.940Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T20:03:15.013Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T20:03:19.641Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T20:03:24.136Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T20:03:28.691Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T20:03:37.275Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T20:03:38.049Z] 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. [2025-02-20T20:03:38.923Z] The best model improves the baseline by 14.52%. [2025-02-20T20:03:39.727Z] Movies recommended for you: [2025-02-20T20:03:39.727Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T20:03:39.727Z] There is no way to check that no silent failure occurred. [2025-02-20T20:03:39.727Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (55527.401 ms) ====== [2025-02-20T20:03:39.727Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-02-20T20:03:39.727Z] GC before operation: completed in 428.523 ms, heap usage 424.414 MB -> 54.350 MB. [2025-02-20T20:03:51.479Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-20T20:03:59.882Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-20T20:04:08.236Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-20T20:04:16.732Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-20T20:04:21.430Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-20T20:04:25.965Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-20T20:04:31.686Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-20T20:04:36.195Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-20T20:04:37.812Z] 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. [2025-02-20T20:04:37.812Z] The best model improves the baseline by 14.52%. [2025-02-20T20:04:37.812Z] Movies recommended for you: [2025-02-20T20:04:37.812Z] WARNING: This benchmark provides no result that can be validated. [2025-02-20T20:04:37.812Z] There is no way to check that no silent failure occurred. [2025-02-20T20:04:37.812Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (58240.196 ms) ====== [2025-02-20T20:04:39.435Z] ----------------------------------- [2025-02-20T20:04:39.435Z] renaissance-movie-lens_0_PASSED [2025-02-20T20:04:39.435Z] ----------------------------------- [2025-02-20T20:04:39.435Z] [2025-02-20T20:04:39.435Z] TEST TEARDOWN: [2025-02-20T20:04:39.435Z] Nothing to be done for teardown. [2025-02-20T20:04:39.435Z] renaissance-movie-lens_0 Finish Time: Thu Feb 20 20:04:39 2025 Epoch Time (ms): 1740081879247