[2024-08-24T02:19:03.251Z] Running test renaissance-movie-lens_0 ... [2024-08-24T02:19:03.251Z] =============================================== [2024-08-24T02:19:03.556Z] renaissance-movie-lens_0 Start Time: Sat Aug 24 02:19:03 2024 Epoch Time (ms): 1724465943291 [2024-08-24T02:19:03.869Z] variation: NoOptions [2024-08-24T02:19:03.869Z] JVM_OPTIONS: [2024-08-24T02:19:03.869Z] { \ [2024-08-24T02:19:03.869Z] echo ""; echo "TEST SETUP:"; \ [2024-08-24T02:19:03.869Z] echo "Nothing to be done for setup."; \ [2024-08-24T02:19:03.869Z] mkdir -p "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17244646614105\\renaissance-movie-lens_0"; \ [2024-08-24T02:19:03.869Z] cd "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17244646614105\\renaissance-movie-lens_0"; \ [2024-08-24T02:19:03.869Z] echo ""; echo "TESTING:"; \ [2024-08-24T02:19:03.870Z] "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_17244646614105\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2024-08-24T02:19:03.870Z] 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_17244646614105\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-24T02:19:03.870Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-24T02:19:03.870Z] echo "Nothing to be done for teardown."; \ [2024-08-24T02:19:03.870Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17244646614105\\TestTargetResult"; [2024-08-24T02:19:04.185Z] [2024-08-24T02:19:04.185Z] TEST SETUP: [2024-08-24T02:19:04.185Z] Nothing to be done for setup. [2024-08-24T02:19:04.185Z] [2024-08-24T02:19:04.185Z] TESTING: [2024-08-24T02:19:14.768Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-24T02:19:16.933Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-08-24T02:19:19.950Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-24T02:19:20.280Z] Training: 60056, validation: 20285, test: 19854 [2024-08-24T02:19:20.280Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-24T02:19:20.280Z] GC before operation: completed in 64.223 ms, heap usage 46.566 MB -> 36.909 MB. [2024-08-24T02:19:33.175Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-24T02:19:41.894Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-24T02:19:48.999Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-24T02:19:56.090Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-24T02:19:59.762Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-24T02:20:04.324Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-24T02:20:08.917Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-24T02:20:12.557Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-24T02:20:12.888Z] 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. [2024-08-24T02:20:12.888Z] The best model improves the baseline by 14.52%. [2024-08-24T02:20:13.208Z] Movies recommended for you: [2024-08-24T02:20:13.208Z] WARNING: This benchmark provides no result that can be validated. [2024-08-24T02:20:13.208Z] There is no way to check that no silent failure occurred. [2024-08-24T02:20:13.208Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (52800.479 ms) ====== [2024-08-24T02:20:13.208Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-24T02:20:13.208Z] GC before operation: completed in 93.685 ms, heap usage 297.913 MB -> 47.459 MB. [2024-08-24T02:20:20.264Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-24T02:20:27.305Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-24T02:20:35.969Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-24T02:20:41.679Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-24T02:20:46.260Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-24T02:20:49.942Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-24T02:20:54.511Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-24T02:20:58.140Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-24T02:20:58.140Z] 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. [2024-08-24T02:20:58.140Z] The best model improves the baseline by 14.52%. [2024-08-24T02:20:58.455Z] Movies recommended for you: [2024-08-24T02:20:58.455Z] WARNING: This benchmark provides no result that can be validated. [2024-08-24T02:20:58.455Z] There is no way to check that no silent failure occurred. [2024-08-24T02:20:58.455Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (45169.197 ms) ====== [2024-08-24T02:20:58.455Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-24T02:20:58.455Z] GC before operation: completed in 89.720 ms, heap usage 244.439 MB -> 49.630 MB. [2024-08-24T02:21:05.513Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-24T02:21:12.565Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-24T02:21:21.228Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-24T02:21:26.939Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-24T02:21:30.559Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-24T02:21:35.130Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-24T02:21:38.789Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-24T02:21:42.407Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-24T02:21:43.149Z] 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. [2024-08-24T02:21:43.149Z] The best model improves the baseline by 14.52%. [2024-08-24T02:21:43.149Z] Movies recommended for you: [2024-08-24T02:21:43.149Z] WARNING: This benchmark provides no result that can be validated. [2024-08-24T02:21:43.149Z] There is no way to check that no silent failure occurred. [2024-08-24T02:21:43.149Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (44576.205 ms) ====== [2024-08-24T02:21:43.149Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-24T02:21:43.149Z] GC before operation: completed in 92.301 ms, heap usage 262.153 MB -> 53.162 MB. [2024-08-24T02:21:50.237Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-24T02:21:57.287Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-24T02:22:04.334Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-24T02:22:11.376Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-24T02:22:15.956Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-24T02:22:19.582Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-24T02:22:23.202Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-24T02:22:26.843Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-24T02:22:27.226Z] 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. [2024-08-24T02:22:27.226Z] The best model improves the baseline by 14.52%. [2024-08-24T02:22:27.541Z] Movies recommended for you: [2024-08-24T02:22:27.541Z] WARNING: This benchmark provides no result that can be validated. [2024-08-24T02:22:27.541Z] There is no way to check that no silent failure occurred. [2024-08-24T02:22:27.541Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (44159.857 ms) ====== [2024-08-24T02:22:27.541Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-24T02:22:27.541Z] GC before operation: completed in 90.346 ms, heap usage 240.993 MB -> 53.415 MB. [2024-08-24T02:22:34.607Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-24T02:22:41.721Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-24T02:22:50.429Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-24T02:22:56.142Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-24T02:23:00.704Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-24T02:23:03.518Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-24T02:23:08.111Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-24T02:23:11.739Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-24T02:23:12.084Z] 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. [2024-08-24T02:23:12.084Z] The best model improves the baseline by 14.52%. [2024-08-24T02:23:12.084Z] Movies recommended for you: [2024-08-24T02:23:12.084Z] WARNING: This benchmark provides no result that can be validated. [2024-08-24T02:23:12.084Z] There is no way to check that no silent failure occurred. [2024-08-24T02:23:12.084Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (44740.105 ms) ====== [2024-08-24T02:23:12.084Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-24T02:23:12.401Z] GC before operation: completed in 100.387 ms, heap usage 281.036 MB -> 53.722 MB. [2024-08-24T02:23:19.440Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-24T02:23:26.557Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-24T02:23:33.623Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-24T02:23:40.653Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-24T02:23:44.276Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-24T02:23:47.929Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-24T02:23:52.494Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-24T02:23:56.167Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-24T02:23:56.167Z] 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. [2024-08-24T02:23:56.167Z] The best model improves the baseline by 14.52%. [2024-08-24T02:23:56.167Z] Movies recommended for you: [2024-08-24T02:23:56.167Z] WARNING: This benchmark provides no result that can be validated. [2024-08-24T02:23:56.167Z] There is no way to check that no silent failure occurred. [2024-08-24T02:23:56.167Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (43877.886 ms) ====== [2024-08-24T02:23:56.167Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-24T02:23:56.167Z] GC before operation: completed in 86.596 ms, heap usage 205.993 MB -> 53.460 MB. [2024-08-24T02:24:03.218Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-24T02:24:10.259Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-24T02:24:17.316Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-24T02:24:24.336Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-24T02:24:28.005Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-24T02:24:31.624Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-24T02:24:35.247Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-24T02:24:38.889Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-24T02:24:39.268Z] 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. [2024-08-24T02:24:39.268Z] The best model improves the baseline by 14.52%. [2024-08-24T02:24:39.588Z] Movies recommended for you: [2024-08-24T02:24:39.588Z] WARNING: This benchmark provides no result that can be validated. [2024-08-24T02:24:39.588Z] There is no way to check that no silent failure occurred. [2024-08-24T02:24:39.588Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (43145.187 ms) ====== [2024-08-24T02:24:39.588Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-24T02:24:39.588Z] GC before operation: completed in 98.150 ms, heap usage 207.444 MB -> 55.015 MB. [2024-08-24T02:24:46.610Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-24T02:24:53.650Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-24T02:25:00.690Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-24T02:25:06.409Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-24T02:25:10.033Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-24T02:25:13.663Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-24T02:25:18.230Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-24T02:25:21.961Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-24T02:25:21.961Z] 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. [2024-08-24T02:25:21.961Z] The best model improves the baseline by 14.52%. [2024-08-24T02:25:21.961Z] Movies recommended for you: [2024-08-24T02:25:21.961Z] WARNING: This benchmark provides no result that can be validated. [2024-08-24T02:25:21.961Z] There is no way to check that no silent failure occurred. [2024-08-24T02:25:21.961Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (42402.578 ms) ====== [2024-08-24T02:25:21.961Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-24T02:25:21.961Z] GC before operation: completed in 96.838 ms, heap usage 190.748 MB -> 53.976 MB. [2024-08-24T02:25:29.041Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-24T02:25:36.097Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-24T02:25:43.170Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-24T02:25:48.893Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-24T02:25:52.528Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-24T02:25:56.181Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-24T02:25:59.816Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-24T02:26:03.443Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-24T02:26:04.281Z] 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. [2024-08-24T02:26:04.281Z] The best model improves the baseline by 14.52%. [2024-08-24T02:26:04.281Z] Movies recommended for you: [2024-08-24T02:26:04.281Z] WARNING: This benchmark provides no result that can be validated. [2024-08-24T02:26:04.281Z] There is no way to check that no silent failure occurred. [2024-08-24T02:26:04.281Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (42172.028 ms) ====== [2024-08-24T02:26:04.281Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-24T02:26:04.281Z] GC before operation: completed in 90.071 ms, heap usage 132.350 MB -> 53.725 MB. [2024-08-24T02:26:11.309Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-24T02:26:18.371Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-24T02:26:25.441Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-24T02:26:31.153Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-24T02:26:35.733Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-24T02:26:39.379Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-24T02:26:43.958Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-24T02:26:46.807Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-24T02:26:47.123Z] 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. [2024-08-24T02:26:47.123Z] The best model improves the baseline by 14.52%. [2024-08-24T02:26:47.439Z] Movies recommended for you: [2024-08-24T02:26:47.439Z] WARNING: This benchmark provides no result that can be validated. [2024-08-24T02:26:47.440Z] There is no way to check that no silent failure occurred. [2024-08-24T02:26:47.440Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (43139.013 ms) ====== [2024-08-24T02:26:47.440Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-24T02:26:47.440Z] GC before operation: completed in 85.266 ms, heap usage 108.621 MB -> 52.334 MB. [2024-08-24T02:26:54.531Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-24T02:27:01.580Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-24T02:27:08.643Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-24T02:27:14.358Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-24T02:27:18.952Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-24T02:27:22.563Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-24T02:27:26.194Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-24T02:27:29.841Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-24T02:27:30.158Z] 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. [2024-08-24T02:27:30.158Z] The best model improves the baseline by 14.52%. [2024-08-24T02:27:30.493Z] Movies recommended for you: [2024-08-24T02:27:30.493Z] WARNING: This benchmark provides no result that can be validated. [2024-08-24T02:27:30.493Z] There is no way to check that no silent failure occurred. [2024-08-24T02:27:30.493Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (42899.246 ms) ====== [2024-08-24T02:27:30.493Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-24T02:27:30.493Z] GC before operation: completed in 90.224 ms, heap usage 213.914 MB -> 53.667 MB. [2024-08-24T02:27:37.556Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-24T02:27:44.609Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-24T02:27:51.657Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-24T02:27:57.374Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-24T02:28:01.013Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-24T02:28:04.632Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-24T02:28:09.227Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-24T02:28:12.854Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-24T02:28:12.854Z] 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. [2024-08-24T02:28:12.855Z] The best model improves the baseline by 14.52%. [2024-08-24T02:28:12.855Z] Movies recommended for you: [2024-08-24T02:28:12.855Z] WARNING: This benchmark provides no result that can be validated. [2024-08-24T02:28:12.855Z] There is no way to check that no silent failure occurred. [2024-08-24T02:28:12.855Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (42482.625 ms) ====== [2024-08-24T02:28:12.855Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-24T02:28:13.191Z] GC before operation: completed in 93.457 ms, heap usage 280.121 MB -> 55.142 MB. [2024-08-24T02:28:20.242Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-24T02:28:27.290Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-24T02:28:34.344Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-24T02:28:41.381Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-24T02:28:45.011Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-24T02:28:48.663Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-24T02:28:52.310Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-24T02:28:55.954Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-24T02:28:56.269Z] 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. [2024-08-24T02:28:56.269Z] The best model improves the baseline by 14.52%. [2024-08-24T02:28:56.583Z] Movies recommended for you: [2024-08-24T02:28:56.583Z] WARNING: This benchmark provides no result that can be validated. [2024-08-24T02:28:56.583Z] There is no way to check that no silent failure occurred. [2024-08-24T02:28:56.583Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (43454.741 ms) ====== [2024-08-24T02:28:56.583Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-24T02:28:56.583Z] GC before operation: completed in 94.720 ms, heap usage 273.580 MB -> 56.259 MB. [2024-08-24T02:29:03.658Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-24T02:29:10.698Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-24T02:29:17.744Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-24T02:29:24.787Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-24T02:29:27.633Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-24T02:29:31.279Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-24T02:29:34.914Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-24T02:29:39.512Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-24T02:29:39.512Z] 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. [2024-08-24T02:29:39.512Z] The best model improves the baseline by 14.52%. [2024-08-24T02:29:39.512Z] Movies recommended for you: [2024-08-24T02:29:39.512Z] WARNING: This benchmark provides no result that can be validated. [2024-08-24T02:29:39.512Z] There is no way to check that no silent failure occurred. [2024-08-24T02:29:39.512Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (42762.197 ms) ====== [2024-08-24T02:29:39.512Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-24T02:29:39.512Z] GC before operation: completed in 91.153 ms, heap usage 198.572 MB -> 53.673 MB. [2024-08-24T02:29:46.560Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-24T02:29:53.598Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-24T02:30:00.636Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-24T02:30:06.403Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-24T02:30:10.969Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-24T02:30:13.791Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-24T02:30:18.379Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-24T02:30:21.231Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-24T02:30:21.568Z] 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. [2024-08-24T02:30:21.568Z] The best model improves the baseline by 14.52%. [2024-08-24T02:30:21.883Z] Movies recommended for you: [2024-08-24T02:30:21.884Z] WARNING: This benchmark provides no result that can be validated. [2024-08-24T02:30:21.884Z] There is no way to check that no silent failure occurred. [2024-08-24T02:30:21.884Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (42342.655 ms) ====== [2024-08-24T02:30:21.884Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-24T02:30:21.884Z] GC before operation: completed in 96.037 ms, heap usage 182.596 MB -> 52.959 MB. [2024-08-24T02:30:28.939Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-24T02:30:35.985Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-24T02:30:43.027Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-24T02:30:48.732Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-24T02:30:53.315Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-24T02:30:56.934Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-24T02:31:00.549Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-24T02:31:04.179Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-24T02:31:04.534Z] 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. [2024-08-24T02:31:04.534Z] The best model improves the baseline by 14.52%. [2024-08-24T02:31:04.534Z] Movies recommended for you: [2024-08-24T02:31:04.534Z] WARNING: This benchmark provides no result that can be validated. [2024-08-24T02:31:04.534Z] There is no way to check that no silent failure occurred. [2024-08-24T02:31:04.534Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (42756.393 ms) ====== [2024-08-24T02:31:04.534Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-24T02:31:04.855Z] GC before operation: completed in 89.608 ms, heap usage 240.855 MB -> 53.980 MB. [2024-08-24T02:31:11.917Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-24T02:31:18.978Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-24T02:31:26.054Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-24T02:31:31.764Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-24T02:31:35.394Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-24T02:31:39.028Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-24T02:31:43.636Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-24T02:31:46.459Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-24T02:31:46.788Z] 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. [2024-08-24T02:31:47.147Z] The best model improves the baseline by 14.52%. [2024-08-24T02:31:47.147Z] Movies recommended for you: [2024-08-24T02:31:47.147Z] WARNING: This benchmark provides no result that can be validated. [2024-08-24T02:31:47.147Z] There is no way to check that no silent failure occurred. [2024-08-24T02:31:47.147Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (42352.565 ms) ====== [2024-08-24T02:31:47.147Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-24T02:31:47.147Z] GC before operation: completed in 96.333 ms, heap usage 186.849 MB -> 52.766 MB. [2024-08-24T02:31:54.181Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-24T02:32:01.234Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-24T02:32:08.285Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-24T02:32:15.325Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-24T02:32:18.195Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-24T02:32:21.818Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-24T02:32:26.419Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-24T02:32:30.122Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-24T02:32:30.122Z] 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. [2024-08-24T02:32:30.122Z] The best model improves the baseline by 14.52%. [2024-08-24T02:32:30.444Z] Movies recommended for you: [2024-08-24T02:32:30.444Z] WARNING: This benchmark provides no result that can be validated. [2024-08-24T02:32:30.444Z] There is no way to check that no silent failure occurred. [2024-08-24T02:32:30.444Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (43054.714 ms) ====== [2024-08-24T02:32:30.444Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-24T02:32:30.444Z] GC before operation: completed in 87.782 ms, heap usage 181.861 MB -> 52.429 MB. [2024-08-24T02:32:37.488Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-24T02:32:44.522Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-24T02:32:51.582Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-24T02:32:57.295Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-24T02:33:00.916Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-24T02:33:05.485Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-24T02:33:09.119Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-24T02:33:12.754Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-24T02:33:13.426Z] 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. [2024-08-24T02:33:13.426Z] The best model improves the baseline by 14.52%. [2024-08-24T02:33:13.426Z] Movies recommended for you: [2024-08-24T02:33:13.426Z] WARNING: This benchmark provides no result that can be validated. [2024-08-24T02:33:13.426Z] There is no way to check that no silent failure occurred. [2024-08-24T02:33:13.426Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (43150.136 ms) ====== [2024-08-24T02:33:13.426Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-24T02:33:13.426Z] GC before operation: completed in 88.007 ms, heap usage 88.763 MB -> 50.665 MB. [2024-08-24T02:33:20.480Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-24T02:33:27.523Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-24T02:33:34.559Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-24T02:33:40.281Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-24T02:33:44.852Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-24T02:33:48.508Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-24T02:33:52.163Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-24T02:33:55.792Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-24T02:33:56.462Z] 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. [2024-08-24T02:33:56.462Z] The best model improves the baseline by 14.52%. [2024-08-24T02:33:56.462Z] Movies recommended for you: [2024-08-24T02:33:56.462Z] WARNING: This benchmark provides no result that can be validated. [2024-08-24T02:33:56.462Z] There is no way to check that no silent failure occurred. [2024-08-24T02:33:56.462Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (42891.926 ms) ====== [2024-08-24T02:33:56.776Z] ----------------------------------- [2024-08-24T02:33:56.776Z] renaissance-movie-lens_0_PASSED [2024-08-24T02:33:56.776Z] ----------------------------------- [2024-08-24T02:33:57.443Z] [2024-08-24T02:33:57.443Z] TEST TEARDOWN: [2024-08-24T02:33:57.443Z] Nothing to be done for teardown. [2024-08-24T02:33:57.443Z] renaissance-movie-lens_0 Finish Time: Sat Aug 24 02:33:57 2024 Epoch Time (ms): 1724466837408