[2024-08-10T06:58:04.111Z] Running test renaissance-movie-lens_0 ... [2024-08-10T06:58:04.424Z] =============================================== [2024-08-10T06:58:04.425Z] renaissance-movie-lens_0 Start Time: Sat Aug 10 06:58:04 2024 Epoch Time (ms): 1723273084333 [2024-08-10T06:58:04.425Z] variation: NoOptions [2024-08-10T06:58:04.728Z] JVM_OPTIONS: [2024-08-10T06:58:04.728Z] { \ [2024-08-10T06:58:04.728Z] echo ""; echo "TEST SETUP:"; \ [2024-08-10T06:58:04.728Z] echo "Nothing to be done for setup."; \ [2024-08-10T06:58:04.728Z] mkdir -p "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17232721172834\\renaissance-movie-lens_0"; \ [2024-08-10T06:58:04.728Z] cd "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17232721172834\\renaissance-movie-lens_0"; \ [2024-08-10T06:58:04.728Z] echo ""; echo "TESTING:"; \ [2024-08-10T06:58:04.728Z] "c:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_testList_0/jdkbinary/j2sdk-image\\bin\\java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_testList_0/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17232721172834\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2024-08-10T06:58:04.728Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17232721172834\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-10T06:58:04.728Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-10T06:58:04.728Z] echo "Nothing to be done for teardown."; \ [2024-08-10T06:58:04.728Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17232721172834\\TestTargetResult"; [2024-08-10T06:58:05.045Z] [2024-08-10T06:58:05.045Z] TEST SETUP: [2024-08-10T06:58:05.045Z] Nothing to be done for setup. [2024-08-10T06:58:05.045Z] [2024-08-10T06:58:05.045Z] TESTING: [2024-08-10T06:58:15.747Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-10T06:58:16.838Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-08-10T06:58:19.826Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-10T06:58:20.339Z] Training: 60056, validation: 20285, test: 19854 [2024-08-10T06:58:20.339Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-10T06:58:20.339Z] GC before operation: completed in 49.015 ms, heap usage 55.452 MB -> 37.636 MB. [2024-08-10T06:58:33.300Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T06:58:40.312Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T06:58:47.327Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T06:58:54.378Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T06:58:58.000Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T06:59:02.577Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T06:59:06.192Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T06:59:09.828Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T06:59:10.564Z] 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. [2024-08-10T06:59:10.564Z] The best model improves the baseline by 14.52%. [2024-08-10T06:59:10.564Z] Movies recommended for you: [2024-08-10T06:59:10.564Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T06:59:10.564Z] There is no way to check that no silent failure occurred. [2024-08-10T06:59:10.564Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (50456.819 ms) ====== [2024-08-10T06:59:10.564Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-10T06:59:10.564Z] GC before operation: completed in 62.186 ms, heap usage 302.715 MB -> 56.613 MB. [2024-08-10T06:59:17.621Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T06:59:24.668Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T06:59:31.723Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T06:59:37.476Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T06:59:41.211Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T06:59:44.900Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T06:59:49.477Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T06:59:53.162Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T06:59:53.162Z] 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. [2024-08-10T06:59:53.162Z] The best model improves the baseline by 14.52%. [2024-08-10T06:59:53.162Z] Movies recommended for you: [2024-08-10T06:59:53.162Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T06:59:53.162Z] There is no way to check that no silent failure occurred. [2024-08-10T06:59:53.162Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (42583.838 ms) ====== [2024-08-10T06:59:53.162Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-10T06:59:53.162Z] GC before operation: completed in 64.744 ms, heap usage 94.126 MB -> 50.046 MB. [2024-08-10T07:00:00.204Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T07:00:07.221Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T07:00:14.257Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T07:00:19.940Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T07:00:23.559Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T07:00:27.173Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T07:00:30.790Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T07:00:34.398Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T07:00:34.398Z] 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. [2024-08-10T07:00:34.398Z] The best model improves the baseline by 14.52%. [2024-08-10T07:00:34.712Z] Movies recommended for you: [2024-08-10T07:00:34.712Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T07:00:34.712Z] There is no way to check that no silent failure occurred. [2024-08-10T07:00:34.712Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (41385.960 ms) ====== [2024-08-10T07:00:34.712Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-10T07:00:34.712Z] GC before operation: completed in 68.306 ms, heap usage 74.990 MB -> 50.330 MB. [2024-08-10T07:00:41.763Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T07:00:47.457Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T07:00:54.496Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T07:01:01.523Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T07:01:04.406Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T07:01:08.038Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T07:01:11.662Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T07:01:15.278Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T07:01:15.617Z] 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. [2024-08-10T07:01:15.617Z] The best model improves the baseline by 14.52%. [2024-08-10T07:01:15.617Z] Movies recommended for you: [2024-08-10T07:01:15.617Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T07:01:15.617Z] There is no way to check that no silent failure occurred. [2024-08-10T07:01:15.617Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (40982.706 ms) ====== [2024-08-10T07:01:15.617Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-10T07:01:15.940Z] GC before operation: completed in 59.142 ms, heap usage 125.577 MB -> 50.803 MB. [2024-08-10T07:01:22.998Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T07:01:28.735Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T07:01:35.796Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T07:01:41.483Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T07:01:46.039Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T07:01:48.880Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T07:01:53.454Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T07:01:57.099Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T07:01:57.099Z] 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. [2024-08-10T07:01:57.099Z] The best model improves the baseline by 14.52%. [2024-08-10T07:01:57.099Z] Movies recommended for you: [2024-08-10T07:01:57.099Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T07:01:57.099Z] There is no way to check that no silent failure occurred. [2024-08-10T07:01:57.099Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (41330.356 ms) ====== [2024-08-10T07:01:57.099Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-10T07:01:57.099Z] GC before operation: completed in 58.943 ms, heap usage 347.116 MB -> 51.132 MB. [2024-08-10T07:02:04.212Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T07:02:09.932Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T07:02:16.994Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T07:02:22.708Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T07:02:26.379Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T07:02:29.998Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T07:02:34.563Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T07:02:37.380Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T07:02:37.716Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-10T07:02:37.716Z] The best model improves the baseline by 14.52%. [2024-08-10T07:02:38.034Z] Movies recommended for you: [2024-08-10T07:02:38.034Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T07:02:38.034Z] There is no way to check that no silent failure occurred. [2024-08-10T07:02:38.034Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (40761.768 ms) ====== [2024-08-10T07:02:38.034Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-10T07:02:38.034Z] GC before operation: completed in 63.387 ms, heap usage 251.383 MB -> 51.012 MB. [2024-08-10T07:02:45.092Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T07:02:50.777Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T07:02:57.832Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T07:03:03.530Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T07:03:07.149Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T07:03:10.785Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T07:03:14.399Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T07:03:18.014Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T07:03:18.323Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-10T07:03:18.323Z] The best model improves the baseline by 14.52%. [2024-08-10T07:03:18.654Z] Movies recommended for you: [2024-08-10T07:03:18.654Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T07:03:18.654Z] There is no way to check that no silent failure occurred. [2024-08-10T07:03:18.654Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (40520.673 ms) ====== [2024-08-10T07:03:18.654Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-10T07:03:18.654Z] GC before operation: completed in 58.471 ms, heap usage 213.791 MB -> 51.147 MB. [2024-08-10T07:03:25.702Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T07:03:31.471Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T07:03:38.501Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T07:03:44.190Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T07:03:47.810Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T07:03:51.437Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T07:03:55.059Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T07:03:58.674Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T07:03:58.988Z] 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. [2024-08-10T07:03:58.988Z] The best model improves the baseline by 14.52%. [2024-08-10T07:03:59.319Z] Movies recommended for you: [2024-08-10T07:03:59.320Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T07:03:59.320Z] There is no way to check that no silent failure occurred. [2024-08-10T07:03:59.320Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (40651.445 ms) ====== [2024-08-10T07:03:59.320Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-10T07:03:59.320Z] GC before operation: completed in 67.320 ms, heap usage 218.713 MB -> 51.404 MB. [2024-08-10T07:04:06.396Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T07:04:12.101Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T07:04:19.148Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T07:04:24.849Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T07:04:28.476Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T07:04:32.095Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T07:04:35.730Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T07:04:39.359Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T07:04:39.672Z] 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. [2024-08-10T07:04:39.672Z] The best model improves the baseline by 14.52%. [2024-08-10T07:04:39.999Z] Movies recommended for you: [2024-08-10T07:04:39.999Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T07:04:39.999Z] There is no way to check that no silent failure occurred. [2024-08-10T07:04:39.999Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (40561.854 ms) ====== [2024-08-10T07:04:39.999Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-10T07:04:39.999Z] GC before operation: completed in 56.867 ms, heap usage 79.933 MB -> 51.281 MB. [2024-08-10T07:04:47.066Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T07:04:52.772Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T07:04:59.813Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T07:05:05.494Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T07:05:09.117Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T07:05:12.757Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T07:05:16.380Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T07:05:20.008Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T07:05:20.008Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-10T07:05:20.008Z] The best model improves the baseline by 14.52%. [2024-08-10T07:05:20.320Z] Movies recommended for you: [2024-08-10T07:05:20.320Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T07:05:20.320Z] There is no way to check that no silent failure occurred. [2024-08-10T07:05:20.320Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (40350.181 ms) ====== [2024-08-10T07:05:20.320Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-10T07:05:20.320Z] GC before operation: completed in 60.397 ms, heap usage 120.460 MB -> 51.216 MB. [2024-08-10T07:05:27.421Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T07:05:33.112Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T07:05:40.134Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T07:05:45.812Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T07:05:49.440Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T07:05:53.051Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T07:05:56.693Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T07:06:00.311Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T07:06:00.311Z] 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. [2024-08-10T07:06:00.617Z] The best model improves the baseline by 14.52%. [2024-08-10T07:06:00.617Z] Movies recommended for you: [2024-08-10T07:06:00.617Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T07:06:00.617Z] There is no way to check that no silent failure occurred. [2024-08-10T07:06:00.617Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (40254.650 ms) ====== [2024-08-10T07:06:00.618Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-10T07:06:00.618Z] GC before operation: completed in 66.624 ms, heap usage 307.281 MB -> 51.181 MB. [2024-08-10T07:06:07.640Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T07:06:13.341Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T07:06:20.401Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T07:06:26.135Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T07:06:29.737Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T07:06:33.348Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T07:06:37.932Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T07:06:40.736Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T07:06:41.052Z] 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. [2024-08-10T07:06:41.367Z] The best model improves the baseline by 14.52%. [2024-08-10T07:06:41.367Z] Movies recommended for you: [2024-08-10T07:06:41.367Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T07:06:41.367Z] There is no way to check that no silent failure occurred. [2024-08-10T07:06:41.367Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (40682.470 ms) ====== [2024-08-10T07:06:41.367Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-10T07:06:41.367Z] GC before operation: completed in 58.147 ms, heap usage 125.369 MB -> 51.186 MB. [2024-08-10T07:06:48.476Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T07:06:54.163Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T07:07:01.199Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T07:07:06.902Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T07:07:10.521Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T07:07:14.142Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T07:07:17.750Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T07:07:21.400Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T07:07:21.400Z] 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. [2024-08-10T07:07:21.400Z] The best model improves the baseline by 14.52%. [2024-08-10T07:07:21.714Z] Movies recommended for you: [2024-08-10T07:07:21.714Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T07:07:21.714Z] There is no way to check that no silent failure occurred. [2024-08-10T07:07:21.714Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (40271.160 ms) ====== [2024-08-10T07:07:21.714Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-10T07:07:21.714Z] GC before operation: completed in 62.468 ms, heap usage 59.588 MB -> 51.311 MB. [2024-08-10T07:07:28.740Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T07:07:34.433Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T07:07:41.467Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T07:07:47.158Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T07:07:50.773Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T07:07:54.403Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T07:07:58.023Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T07:08:01.659Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T07:08:01.659Z] 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. [2024-08-10T07:08:01.659Z] The best model improves the baseline by 14.52%. [2024-08-10T07:08:01.659Z] Movies recommended for you: [2024-08-10T07:08:01.659Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T07:08:01.659Z] There is no way to check that no silent failure occurred. [2024-08-10T07:08:01.659Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (40018.985 ms) ====== [2024-08-10T07:08:01.659Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-10T07:08:01.972Z] GC before operation: completed in 59.616 ms, heap usage 119.109 MB -> 51.081 MB. [2024-08-10T07:08:09.014Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T07:08:14.715Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T07:08:21.755Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T07:08:27.436Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T07:08:31.059Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T07:08:34.693Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T07:08:38.310Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T07:08:41.924Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T07:08:42.261Z] 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. [2024-08-10T07:08:42.262Z] The best model improves the baseline by 14.52%. [2024-08-10T07:08:42.262Z] Movies recommended for you: [2024-08-10T07:08:42.262Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T07:08:42.262Z] There is no way to check that no silent failure occurred. [2024-08-10T07:08:42.262Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (40549.471 ms) ====== [2024-08-10T07:08:42.262Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-10T07:08:42.578Z] GC before operation: completed in 63.036 ms, heap usage 345.302 MB -> 51.480 MB. [2024-08-10T07:08:49.637Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T07:08:55.365Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T07:09:02.391Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T07:09:08.078Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T07:09:11.686Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T07:09:14.521Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T07:09:19.144Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T07:09:22.783Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T07:09:22.783Z] 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. [2024-08-10T07:09:22.783Z] The best model improves the baseline by 14.52%. [2024-08-10T07:09:23.111Z] Movies recommended for you: [2024-08-10T07:09:23.112Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T07:09:23.112Z] There is no way to check that no silent failure occurred. [2024-08-10T07:09:23.112Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (40465.552 ms) ====== [2024-08-10T07:09:23.112Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-10T07:09:23.112Z] GC before operation: completed in 62.577 ms, heap usage 203.316 MB -> 51.444 MB. [2024-08-10T07:09:30.156Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T07:09:35.859Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T07:09:42.894Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T07:09:48.583Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T07:09:52.182Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T07:09:55.804Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T07:09:59.447Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T07:10:03.059Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T07:10:03.739Z] 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. [2024-08-10T07:10:03.739Z] The best model improves the baseline by 14.52%. [2024-08-10T07:10:03.739Z] Movies recommended for you: [2024-08-10T07:10:03.739Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T07:10:03.739Z] There is no way to check that no silent failure occurred. [2024-08-10T07:10:03.739Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (40735.984 ms) ====== [2024-08-10T07:10:03.739Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-10T07:10:03.739Z] GC before operation: completed in 58.674 ms, heap usage 268.805 MB -> 51.373 MB. [2024-08-10T07:10:10.765Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T07:10:16.454Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T07:10:23.496Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T07:10:29.181Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T07:10:32.795Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T07:10:36.423Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T07:10:40.050Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T07:10:43.666Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T07:10:43.666Z] 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. [2024-08-10T07:10:43.666Z] The best model improves the baseline by 14.52%. [2024-08-10T07:10:43.666Z] Movies recommended for you: [2024-08-10T07:10:43.666Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T07:10:43.666Z] There is no way to check that no silent failure occurred. [2024-08-10T07:10:43.666Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (39955.472 ms) ====== [2024-08-10T07:10:43.666Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-10T07:10:43.666Z] GC before operation: completed in 58.373 ms, heap usage 125.564 MB -> 51.331 MB. [2024-08-10T07:10:50.695Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T07:10:56.375Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T07:11:03.403Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T07:11:09.076Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T07:11:12.683Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T07:11:16.291Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T07:11:20.861Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T07:11:23.680Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T07:11:23.993Z] 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. [2024-08-10T07:11:23.993Z] The best model improves the baseline by 14.52%. [2024-08-10T07:11:24.307Z] Movies recommended for you: [2024-08-10T07:11:24.307Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T07:11:24.307Z] There is no way to check that no silent failure occurred. [2024-08-10T07:11:24.307Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (40463.712 ms) ====== [2024-08-10T07:11:24.307Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-10T07:11:24.307Z] GC before operation: completed in 60.775 ms, heap usage 347.021 MB -> 51.640 MB. [2024-08-10T07:11:31.346Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T07:11:37.040Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T07:11:44.084Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T07:11:49.775Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T07:11:53.400Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T07:11:56.210Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T07:12:00.794Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T07:12:03.628Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T07:12:03.939Z] 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. [2024-08-10T07:12:03.939Z] The best model improves the baseline by 14.52%. [2024-08-10T07:12:04.258Z] Movies recommended for you: [2024-08-10T07:12:04.258Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T07:12:04.258Z] There is no way to check that no silent failure occurred. [2024-08-10T07:12:04.258Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (39832.862 ms) ====== [2024-08-10T07:12:04.587Z] ----------------------------------- [2024-08-10T07:12:04.587Z] renaissance-movie-lens_0_PASSED [2024-08-10T07:12:04.587Z] ----------------------------------- [2024-08-10T07:12:04.889Z] [2024-08-10T07:12:04.889Z] TEST TEARDOWN: [2024-08-10T07:12:04.889Z] Nothing to be done for teardown. [2024-08-10T07:12:05.301Z] renaissance-movie-lens_0 Finish Time: Sat Aug 10 07:12:04 2024 Epoch Time (ms): 1723273924914