[2024-08-08T04:47:00.604Z] Running test renaissance-movie-lens_0 ... [2024-08-08T04:47:00.604Z] =============================================== [2024-08-08T04:47:00.604Z] renaissance-movie-lens_0 Start Time: Wed Aug 7 21:46:58 2024 Epoch Time (ms): 1723092418696 [2024-08-08T04:47:00.604Z] variation: NoOptions [2024-08-08T04:47:00.604Z] JVM_OPTIONS: [2024-08-08T04:47:00.604Z] { \ [2024-08-08T04:47:00.604Z] echo ""; echo "TEST SETUP:"; \ [2024-08-08T04:47:00.604Z] echo "Nothing to be done for setup."; \ [2024-08-08T04:47:00.604Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17230910596973/renaissance-movie-lens_0"; \ [2024-08-08T04:47:00.604Z] cd "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17230910596973/renaissance-movie-lens_0"; \ [2024-08-08T04:47:00.604Z] echo ""; echo "TESTING:"; \ [2024-08-08T04:47:00.604Z] "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/jdkbinary/j2sdk-image/Contents/Home/bin/..//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 "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17230910596973/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-08-08T04:47:00.604Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17230910596973/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-08T04:47:00.604Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-08T04:47:00.604Z] echo "Nothing to be done for teardown."; \ [2024-08-08T04:47:00.604Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17230910596973/TestTargetResult"; [2024-08-08T04:47:00.604Z] [2024-08-08T04:47:00.604Z] TEST SETUP: [2024-08-08T04:47:00.604Z] Nothing to be done for setup. [2024-08-08T04:47:00.604Z] [2024-08-08T04:47:00.604Z] TESTING: [2024-08-08T04:47:09.603Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-08T04:47:14.039Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads. [2024-08-08T04:47:23.310Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-08T04:47:25.035Z] Training: 60056, validation: 20285, test: 19854 [2024-08-08T04:47:25.035Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-08T04:47:25.035Z] GC before operation: completed in 194.394 ms, heap usage 77.441 MB -> 37.793 MB. [2024-08-08T04:47:46.907Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:48:02.207Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:48:17.595Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:48:31.047Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:48:38.206Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:48:45.808Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:48:53.334Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:49:00.423Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:49:00.423Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-08T04:49:00.963Z] The best model improves the baseline by 14.52%. [2024-08-08T04:49:00.963Z] Movies recommended for you: [2024-08-08T04:49:00.963Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:49:00.963Z] There is no way to check that no silent failure occurred. [2024-08-08T04:49:00.963Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (95912.221 ms) ====== [2024-08-08T04:49:00.963Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-08T04:49:01.538Z] GC before operation: completed in 296.275 ms, heap usage 268.792 MB -> 49.730 MB. [2024-08-08T04:49:14.059Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:49:25.225Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:49:35.941Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:49:48.726Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:49:52.744Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:50:00.560Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:50:06.461Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:50:13.568Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:50:15.170Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-08T04:50:15.170Z] The best model improves the baseline by 14.52%. [2024-08-08T04:50:15.170Z] Movies recommended for you: [2024-08-08T04:50:15.170Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:50:15.170Z] There is no way to check that no silent failure occurred. [2024-08-08T04:50:15.170Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (74078.940 ms) ====== [2024-08-08T04:50:15.170Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-08T04:50:15.631Z] GC before operation: completed in 335.577 ms, heap usage 229.251 MB -> 50.007 MB. [2024-08-08T04:50:27.970Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:50:38.708Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:50:49.457Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:51:01.645Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:51:09.046Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:51:14.912Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:51:20.856Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:51:28.625Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:51:30.153Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-08T04:51:30.153Z] The best model improves the baseline by 14.52%. [2024-08-08T04:51:30.153Z] Movies recommended for you: [2024-08-08T04:51:30.153Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:51:30.153Z] There is no way to check that no silent failure occurred. [2024-08-08T04:51:30.153Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (74491.221 ms) ====== [2024-08-08T04:51:30.153Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-08T04:51:30.153Z] GC before operation: completed in 201.061 ms, heap usage 289.127 MB -> 50.368 MB. [2024-08-08T04:51:45.425Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:51:55.842Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:52:06.533Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:52:16.833Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:52:21.438Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:52:27.480Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:52:33.127Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:52:38.898Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:52:39.849Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-08T04:52:40.293Z] The best model improves the baseline by 14.52%. [2024-08-08T04:52:40.293Z] Movies recommended for you: [2024-08-08T04:52:40.293Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:52:40.293Z] There is no way to check that no silent failure occurred. [2024-08-08T04:52:40.293Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (69945.416 ms) ====== [2024-08-08T04:52:40.293Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-08T04:52:40.753Z] GC before operation: completed in 184.636 ms, heap usage 319.795 MB -> 50.727 MB. [2024-08-08T04:52:53.728Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:53:04.088Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:53:14.828Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:53:25.379Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:53:32.333Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:53:37.102Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:53:42.919Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:53:48.818Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:53:49.882Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-08T04:53:49.882Z] The best model improves the baseline by 14.52%. [2024-08-08T04:53:49.883Z] Movies recommended for you: [2024-08-08T04:53:49.883Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:53:49.883Z] There is no way to check that no silent failure occurred. [2024-08-08T04:53:49.883Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (69556.138 ms) ====== [2024-08-08T04:53:49.883Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-08T04:53:50.579Z] GC before operation: completed in 295.323 ms, heap usage 281.607 MB -> 52.123 MB. [2024-08-08T04:54:02.970Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:54:15.442Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:54:28.010Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:54:35.242Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:54:42.650Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:54:47.554Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:54:54.727Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:55:01.698Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:55:02.373Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-08T04:55:02.802Z] The best model improves the baseline by 14.52%. [2024-08-08T04:55:02.802Z] Movies recommended for you: [2024-08-08T04:55:02.802Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:55:02.802Z] There is no way to check that no silent failure occurred. [2024-08-08T04:55:02.802Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (72558.642 ms) ====== [2024-08-08T04:55:02.802Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-08T04:55:03.264Z] GC before operation: completed in 211.107 ms, heap usage 240.430 MB -> 51.107 MB. [2024-08-08T04:55:15.607Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:55:26.075Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:55:34.647Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:55:45.193Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:55:52.372Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:55:59.154Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:56:06.377Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:56:12.529Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:56:13.550Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-08T04:56:13.550Z] The best model improves the baseline by 14.52%. [2024-08-08T04:56:13.550Z] Movies recommended for you: [2024-08-08T04:56:13.550Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:56:13.550Z] There is no way to check that no silent failure occurred. [2024-08-08T04:56:13.550Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (70313.304 ms) ====== [2024-08-08T04:56:13.550Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-08T04:56:13.550Z] GC before operation: completed in 176.436 ms, heap usage 404.099 MB -> 54.356 MB. [2024-08-08T04:56:25.448Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:56:35.678Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:56:48.351Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:56:58.740Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:57:05.033Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:57:12.636Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:57:19.533Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:57:26.902Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:57:26.902Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-08T04:57:27.367Z] The best model improves the baseline by 14.52%. [2024-08-08T04:57:27.367Z] Movies recommended for you: [2024-08-08T04:57:27.367Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:57:27.367Z] There is no way to check that no silent failure occurred. [2024-08-08T04:57:27.367Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (73900.272 ms) ====== [2024-08-08T04:57:27.367Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-08T04:57:27.878Z] GC before operation: completed in 282.330 ms, heap usage 67.850 MB -> 54.897 MB. [2024-08-08T04:57:40.155Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:57:48.801Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:57:57.451Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:58:07.623Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:58:12.280Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:58:18.468Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:58:23.934Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:58:29.106Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:58:31.347Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-08T04:58:31.347Z] The best model improves the baseline by 14.52%. [2024-08-08T04:58:31.347Z] Movies recommended for you: [2024-08-08T04:58:31.347Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:58:31.347Z] There is no way to check that no silent failure occurred. [2024-08-08T04:58:31.347Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (63511.096 ms) ====== [2024-08-08T04:58:31.347Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-08T04:58:31.347Z] GC before operation: completed in 131.686 ms, heap usage 363.484 MB -> 51.182 MB. [2024-08-08T04:58:44.127Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:58:54.468Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T04:59:04.496Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T04:59:13.113Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T04:59:19.159Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T04:59:24.854Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T04:59:29.811Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T04:59:36.820Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T04:59:36.820Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-08T04:59:36.820Z] The best model improves the baseline by 14.52%. [2024-08-08T04:59:36.820Z] Movies recommended for you: [2024-08-08T04:59:36.820Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T04:59:36.820Z] There is no way to check that no silent failure occurred. [2024-08-08T04:59:36.820Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (65191.447 ms) ====== [2024-08-08T04:59:36.820Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-08T04:59:36.820Z] GC before operation: completed in 221.527 ms, heap usage 413.508 MB -> 55.775 MB. [2024-08-08T04:59:46.858Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T04:59:57.229Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T05:00:07.223Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T05:00:17.708Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T05:00:22.521Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T05:00:29.575Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T05:00:35.366Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T05:00:40.986Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T05:00:42.432Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-08T05:00:42.432Z] The best model improves the baseline by 14.52%. [2024-08-08T05:00:42.432Z] Movies recommended for you: [2024-08-08T05:00:42.432Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T05:00:42.432Z] There is no way to check that no silent failure occurred. [2024-08-08T05:00:42.432Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (65573.373 ms) ====== [2024-08-08T05:00:42.432Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-08T05:00:42.869Z] GC before operation: completed in 235.679 ms, heap usage 207.897 MB -> 50.925 MB. [2024-08-08T05:00:55.348Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T05:01:03.903Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T05:01:16.973Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T05:01:25.422Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T05:01:31.164Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T05:01:36.956Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T05:01:43.048Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T05:01:48.785Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T05:01:49.795Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-08T05:01:49.795Z] The best model improves the baseline by 14.52%. [2024-08-08T05:01:50.350Z] Movies recommended for you: [2024-08-08T05:01:50.350Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T05:01:50.350Z] There is no way to check that no silent failure occurred. [2024-08-08T05:01:50.350Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (67383.062 ms) ====== [2024-08-08T05:01:50.350Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-08T05:01:50.855Z] GC before operation: completed in 262.240 ms, heap usage 165.648 MB -> 51.067 MB. [2024-08-08T05:02:01.072Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T05:02:11.943Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T05:02:22.640Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T05:02:33.464Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T05:02:38.618Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T05:02:44.217Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T05:02:51.117Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T05:02:57.002Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T05:02:58.108Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-08T05:02:58.108Z] The best model improves the baseline by 14.52%. [2024-08-08T05:02:58.546Z] Movies recommended for you: [2024-08-08T05:02:58.546Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T05:02:58.546Z] There is no way to check that no silent failure occurred. [2024-08-08T05:02:58.546Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (68189.665 ms) ====== [2024-08-08T05:02:58.546Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-08T05:02:59.036Z] GC before operation: completed in 234.939 ms, heap usage 355.004 MB -> 52.609 MB. [2024-08-08T05:03:11.461Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T05:03:21.855Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T05:03:32.712Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T05:03:43.296Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T05:03:49.372Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T05:03:55.245Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T05:04:01.062Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T05:04:08.015Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T05:04:09.074Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-08T05:04:09.074Z] The best model improves the baseline by 14.52%. [2024-08-08T05:04:09.074Z] Movies recommended for you: [2024-08-08T05:04:09.074Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T05:04:09.074Z] There is no way to check that no silent failure occurred. [2024-08-08T05:04:09.074Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (70343.236 ms) ====== [2024-08-08T05:04:09.074Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-08T05:04:09.538Z] GC before operation: completed in 189.691 ms, heap usage 210.976 MB -> 51.016 MB. [2024-08-08T05:04:20.326Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T05:04:30.478Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T05:04:39.235Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T05:04:47.888Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T05:04:53.444Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T05:05:00.219Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T05:05:04.826Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T05:05:12.231Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T05:05:12.729Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-08T05:05:12.729Z] The best model improves the baseline by 14.52%. [2024-08-08T05:05:12.729Z] Movies recommended for you: [2024-08-08T05:05:12.729Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T05:05:12.729Z] There is no way to check that no silent failure occurred. [2024-08-08T05:05:12.729Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (63510.788 ms) ====== [2024-08-08T05:05:12.729Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-08T05:05:13.171Z] GC before operation: completed in 236.537 ms, heap usage 260.848 MB -> 52.459 MB. [2024-08-08T05:05:26.110Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T05:05:38.312Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T05:05:50.480Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T05:06:00.899Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T05:06:07.281Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T05:06:14.527Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T05:06:20.512Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T05:06:27.451Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T05:06:28.393Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-08T05:06:28.393Z] The best model improves the baseline by 14.52%. [2024-08-08T05:06:28.393Z] Movies recommended for you: [2024-08-08T05:06:28.393Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T05:06:28.393Z] There is no way to check that no silent failure occurred. [2024-08-08T05:06:28.393Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (75493.314 ms) ====== [2024-08-08T05:06:28.393Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-08T05:06:28.897Z] GC before operation: completed in 243.860 ms, heap usage 257.845 MB -> 51.332 MB. [2024-08-08T05:06:41.630Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T05:06:51.867Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T05:07:02.112Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T05:07:12.987Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T05:07:17.542Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T05:07:23.234Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T05:07:29.591Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T05:07:36.642Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T05:07:36.642Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-08T05:07:36.642Z] The best model improves the baseline by 14.52%. [2024-08-08T05:07:37.373Z] Movies recommended for you: [2024-08-08T05:07:37.373Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T05:07:37.373Z] There is no way to check that no silent failure occurred. [2024-08-08T05:07:37.373Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (68470.367 ms) ====== [2024-08-08T05:07:37.373Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-08T05:07:37.872Z] GC before operation: completed in 421.698 ms, heap usage 132.143 MB -> 51.039 MB. [2024-08-08T05:07:50.283Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T05:08:02.695Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T05:08:13.310Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T05:08:21.985Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T05:08:30.602Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T05:08:36.424Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T05:08:42.296Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T05:08:48.530Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T05:08:50.016Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-08T05:08:50.016Z] The best model improves the baseline by 14.52%. [2024-08-08T05:08:50.016Z] Movies recommended for you: [2024-08-08T05:08:50.016Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T05:08:50.016Z] There is no way to check that no silent failure occurred. [2024-08-08T05:08:50.017Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (72306.271 ms) ====== [2024-08-08T05:08:50.017Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-08T05:08:50.017Z] GC before operation: completed in 191.057 ms, heap usage 470.768 MB -> 55.815 MB. [2024-08-08T05:09:02.863Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T05:09:13.561Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T05:09:23.852Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T05:09:32.840Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T05:09:38.615Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T05:09:44.224Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T05:09:49.924Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T05:09:55.770Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T05:09:56.930Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-08T05:09:56.930Z] The best model improves the baseline by 14.52%. [2024-08-08T05:09:57.355Z] Movies recommended for you: [2024-08-08T05:09:57.355Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T05:09:57.355Z] There is no way to check that no silent failure occurred. [2024-08-08T05:09:57.355Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (67169.010 ms) ====== [2024-08-08T05:09:57.355Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-08T05:09:57.355Z] GC before operation: completed in 164.333 ms, heap usage 322.220 MB -> 51.486 MB. [2024-08-08T05:10:07.834Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T05:10:18.216Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T05:10:28.635Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T05:10:39.198Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T05:10:45.384Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T05:10:50.196Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T05:10:56.140Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T05:11:01.916Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T05:11:02.941Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2024-08-08T05:11:02.941Z] The best model improves the baseline by 14.52%. [2024-08-08T05:11:02.941Z] Movies recommended for you: [2024-08-08T05:11:02.941Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T05:11:02.941Z] There is no way to check that no silent failure occurred. [2024-08-08T05:11:02.941Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (65564.891 ms) ====== [2024-08-08T05:11:06.247Z] ----------------------------------- [2024-08-08T05:11:06.247Z] renaissance-movie-lens_0_PASSED [2024-08-08T05:11:06.247Z] ----------------------------------- [2024-08-08T05:11:06.247Z] [2024-08-08T05:11:06.247Z] TEST TEARDOWN: [2024-08-08T05:11:06.247Z] Nothing to be done for teardown. [2024-08-08T05:11:06.645Z] renaissance-movie-lens_0 Finish Time: Wed Aug 7 22:11:04 2024 Epoch Time (ms): 1723093864971