[2024-09-02T10:59:38.315Z] Running test renaissance-movie-lens_0 ... [2024-09-02T10:59:38.315Z] =============================================== [2024-09-02T10:59:38.316Z] renaissance-movie-lens_0 Start Time: Mon Sep 2 03:59:37 2024 Epoch Time (ms): 1725274777875 [2024-09-02T10:59:38.316Z] variation: NoOptions [2024-09-02T10:59:38.316Z] JVM_OPTIONS: [2024-09-02T10:59:38.316Z] { \ [2024-09-02T10:59:38.316Z] echo ""; echo "TEST SETUP:"; \ [2024-09-02T10:59:38.316Z] echo "Nothing to be done for setup."; \ [2024-09-02T10:59:38.316Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17252714445277/renaissance-movie-lens_0"; \ [2024-09-02T10:59:38.316Z] cd "/Users/admin/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17252714445277/renaissance-movie-lens_0"; \ [2024-09-02T10:59:38.316Z] echo ""; echo "TESTING:"; \ [2024-09-02T10:59:38.316Z] "/Users/admin/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_mac/jdkbinary/j2sdk-image/Contents/Home/bin/..//bin/java" -jar "/Users/admin/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17252714445277/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-09-02T10:59:38.316Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17252714445277/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-09-02T10:59:38.316Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-09-02T10:59:38.316Z] echo "Nothing to be done for teardown."; \ [2024-09-02T10:59:38.316Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17252714445277/TestTargetResult"; [2024-09-02T10:59:38.316Z] [2024-09-02T10:59:38.316Z] TEST SETUP: [2024-09-02T10:59:38.316Z] Nothing to be done for setup. [2024-09-02T10:59:38.316Z] [2024-09-02T10:59:38.316Z] TESTING: [2024-09-02T10:59:43.816Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-09-02T10:59:45.929Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads. [2024-09-02T10:59:53.212Z] Got 100004 ratings from 671 users on 9066 movies. [2024-09-02T10:59:53.212Z] Training: 60056, validation: 20285, test: 19854 [2024-09-02T10:59:53.212Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-09-02T10:59:54.269Z] GC before operation: completed in 1023.769 ms, heap usage 130.281 MB -> 25.929 MB. [2024-09-02T11:00:15.700Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-02T11:00:20.130Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-02T11:00:27.260Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-02T11:00:45.425Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-02T11:00:46.961Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-02T11:00:51.577Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-02T11:00:52.934Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-02T11:00:55.735Z] RMSE (validation) = 0.8982232235186749 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-02T11:00:55.735Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328526. [2024-09-02T11:00:55.735Z] The best model improves the baseline by 14.52%. [2024-09-02T11:00:56.216Z] Movies recommended for you: [2024-09-02T11:00:56.216Z] WARNING: This benchmark provides no result that can be validated. [2024-09-02T11:00:56.216Z] There is no way to check that no silent failure occurred. [2024-09-02T11:00:56.216Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (62039.106 ms) ====== [2024-09-02T11:00:56.216Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-09-02T11:00:57.556Z] GC before operation: completed in 1356.937 ms, heap usage 961.797 MB -> 47.721 MB. [2024-09-02T11:01:04.733Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-02T11:01:17.729Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-02T11:01:21.995Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-02T11:01:23.851Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-02T11:01:26.464Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-02T11:01:30.109Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-02T11:01:33.595Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-02T11:01:37.317Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-02T11:01:37.784Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525. [2024-09-02T11:01:37.784Z] The best model improves the baseline by 14.52%. [2024-09-02T11:01:37.784Z] Movies recommended for you: [2024-09-02T11:01:37.784Z] WARNING: This benchmark provides no result that can be validated. [2024-09-02T11:01:37.784Z] There is no way to check that no silent failure occurred. [2024-09-02T11:01:37.784Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (40252.080 ms) ====== [2024-09-02T11:01:37.784Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-09-02T11:01:38.261Z] GC before operation: completed in 260.747 ms, heap usage 976.058 MB -> 48.440 MB. [2024-09-02T11:01:45.047Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-02T11:01:53.414Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-02T11:01:57.838Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-02T11:02:03.470Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-02T11:02:07.076Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-02T11:02:09.987Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-02T11:02:12.897Z] RMSE (validation) = 0.9259652471505186 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-02T11:02:15.701Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-02T11:02:16.117Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328526. [2024-09-02T11:02:16.117Z] The best model improves the baseline by 14.52%. [2024-09-02T11:02:16.515Z] Movies recommended for you: [2024-09-02T11:02:16.515Z] WARNING: This benchmark provides no result that can be validated. [2024-09-02T11:02:16.515Z] There is no way to check that no silent failure occurred. [2024-09-02T11:02:16.515Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (38372.182 ms) ====== [2024-09-02T11:02:16.515Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-09-02T11:02:16.515Z] GC before operation: completed in 171.047 ms, heap usage 924.564 MB -> 47.834 MB. [2024-09-02T11:02:24.740Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-02T11:02:29.209Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-02T11:02:35.995Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-02T11:02:39.733Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-02T11:02:45.628Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-02T11:03:00.884Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-02T11:03:04.505Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-02T11:03:06.587Z] RMSE (validation) = 0.8982232235186749 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-02T11:03:06.989Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525. [2024-09-02T11:03:06.989Z] The best model improves the baseline by 14.52%. [2024-09-02T11:03:07.406Z] Movies recommended for you: [2024-09-02T11:03:07.406Z] WARNING: This benchmark provides no result that can be validated. [2024-09-02T11:03:07.406Z] There is no way to check that no silent failure occurred. [2024-09-02T11:03:07.406Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (50739.066 ms) ====== [2024-09-02T11:03:07.406Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-09-02T11:03:07.406Z] GC before operation: completed in 175.024 ms, heap usage 881.862 MB -> 47.327 MB. [2024-09-02T11:03:12.912Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-02T11:03:17.141Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-02T11:03:20.447Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-02T11:03:23.096Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-02T11:03:25.768Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-02T11:03:27.168Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-02T11:03:29.834Z] RMSE (validation) = 0.9259652471505186 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-02T11:03:33.429Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-02T11:03:33.429Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328526. [2024-09-02T11:03:33.429Z] The best model improves the baseline by 14.52%. [2024-09-02T11:03:33.429Z] Movies recommended for you: [2024-09-02T11:03:33.429Z] WARNING: This benchmark provides no result that can be validated. [2024-09-02T11:03:33.429Z] There is no way to check that no silent failure occurred. [2024-09-02T11:03:33.429Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (25743.647 ms) ====== [2024-09-02T11:03:33.429Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-09-02T11:03:33.429Z] GC before operation: completed in 140.200 ms, heap usage 859.757 MB -> 47.570 MB. [2024-09-02T11:03:37.180Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-02T11:03:40.630Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-02T11:03:45.048Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-02T11:03:48.514Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-02T11:03:50.526Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-02T11:03:53.996Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-02T11:03:58.440Z] RMSE (validation) = 0.9259652471505186 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-02T11:04:01.210Z] RMSE (validation) = 0.8982232235186749 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-02T11:04:01.709Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525. [2024-09-02T11:04:01.709Z] The best model improves the baseline by 14.52%. [2024-09-02T11:04:01.709Z] Movies recommended for you: [2024-09-02T11:04:01.709Z] WARNING: This benchmark provides no result that can be validated. [2024-09-02T11:04:01.709Z] There is no way to check that no silent failure occurred. [2024-09-02T11:04:01.709Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (28258.318 ms) ====== [2024-09-02T11:04:01.709Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-09-02T11:04:01.709Z] GC before operation: completed in 189.706 ms, heap usage 864.633 MB -> 47.481 MB. [2024-09-02T11:04:12.474Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-02T11:04:21.066Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-02T11:04:25.532Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-02T11:04:32.560Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-02T11:04:34.740Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-02T11:04:37.427Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-02T11:04:41.894Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-02T11:04:46.700Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-02T11:04:46.700Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328526. [2024-09-02T11:04:46.700Z] The best model improves the baseline by 14.52%. [2024-09-02T11:04:47.110Z] Movies recommended for you: [2024-09-02T11:04:47.110Z] WARNING: This benchmark provides no result that can be validated. [2024-09-02T11:04:47.110Z] There is no way to check that no silent failure occurred. [2024-09-02T11:04:47.110Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (45237.646 ms) ====== [2024-09-02T11:04:47.110Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-09-02T11:04:47.110Z] GC before operation: completed in 238.939 ms, heap usage 867.702 MB -> 47.666 MB. [2024-09-02T11:04:55.381Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-02T11:04:58.956Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-02T11:05:05.698Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-02T11:05:11.061Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-02T11:05:13.752Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-02T11:05:18.169Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-02T11:05:22.838Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-02T11:05:28.394Z] RMSE (validation) = 0.8982232235186749 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-02T11:05:28.394Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525. [2024-09-02T11:05:28.394Z] The best model improves the baseline by 14.52%. [2024-09-02T11:05:28.394Z] Movies recommended for you: [2024-09-02T11:05:28.394Z] WARNING: This benchmark provides no result that can be validated. [2024-09-02T11:05:28.394Z] There is no way to check that no silent failure occurred. [2024-09-02T11:05:28.394Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (40956.707 ms) ====== [2024-09-02T11:05:28.394Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-09-02T11:05:28.394Z] GC before operation: completed in 273.283 ms, heap usage 838.500 MB -> 47.888 MB. [2024-09-02T11:05:35.360Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-02T11:05:42.151Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-02T11:05:46.578Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-02T11:05:53.500Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-02T11:05:56.224Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-02T11:05:58.987Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-02T11:06:03.496Z] RMSE (validation) = 0.9259652471505186 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-02T11:06:04.876Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-02T11:06:06.413Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525. [2024-09-02T11:06:06.413Z] The best model improves the baseline by 14.52%. [2024-09-02T11:06:06.413Z] Movies recommended for you: [2024-09-02T11:06:06.413Z] WARNING: This benchmark provides no result that can be validated. [2024-09-02T11:06:06.413Z] There is no way to check that no silent failure occurred. [2024-09-02T11:06:06.413Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (38013.046 ms) ====== [2024-09-02T11:06:06.413Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-09-02T11:06:06.413Z] GC before operation: completed in 75.673 ms, heap usage 859.668 MB -> 47.758 MB. [2024-09-02T11:06:11.676Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-02T11:06:15.129Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-02T11:06:19.484Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-02T11:06:26.221Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-02T11:06:29.809Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-02T11:06:34.223Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-02T11:06:37.654Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-02T11:06:42.002Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-02T11:06:42.002Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525. [2024-09-02T11:06:42.458Z] The best model improves the baseline by 14.52%. [2024-09-02T11:06:42.458Z] Movies recommended for you: [2024-09-02T11:06:42.458Z] WARNING: This benchmark provides no result that can be validated. [2024-09-02T11:06:42.458Z] There is no way to check that no silent failure occurred. [2024-09-02T11:06:42.458Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (35913.651 ms) ====== [2024-09-02T11:06:42.458Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-09-02T11:06:42.915Z] GC before operation: completed in 201.030 ms, heap usage 846.145 MB -> 47.836 MB. [2024-09-02T11:06:53.037Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-02T11:06:58.569Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-02T11:07:06.890Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-02T11:07:16.865Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-02T11:07:20.589Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-02T11:07:26.225Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-02T11:07:31.052Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-02T11:07:35.723Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-02T11:07:36.609Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525. [2024-09-02T11:07:36.609Z] The best model improves the baseline by 14.52%. [2024-09-02T11:07:36.609Z] Movies recommended for you: [2024-09-02T11:07:36.609Z] WARNING: This benchmark provides no result that can be validated. [2024-09-02T11:07:36.609Z] There is no way to check that no silent failure occurred. [2024-09-02T11:07:36.609Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (53820.145 ms) ====== [2024-09-02T11:07:36.609Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-09-02T11:07:37.017Z] GC before operation: completed in 216.652 ms, heap usage 849.040 MB -> 47.521 MB. [2024-09-02T11:07:47.069Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-02T11:07:53.925Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-02T11:08:01.286Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-02T11:08:05.722Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-02T11:08:06.555Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-02T11:08:07.882Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-02T11:08:09.742Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-02T11:08:13.124Z] RMSE (validation) = 0.8982232235186749 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-02T11:08:13.510Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328526. [2024-09-02T11:08:13.510Z] The best model improves the baseline by 14.52%. [2024-09-02T11:08:13.510Z] Movies recommended for you: [2024-09-02T11:08:13.510Z] WARNING: This benchmark provides no result that can be validated. [2024-09-02T11:08:13.510Z] There is no way to check that no silent failure occurred. [2024-09-02T11:08:13.510Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (36739.930 ms) ====== [2024-09-02T11:08:13.510Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-09-02T11:08:13.510Z] GC before operation: completed in 89.025 ms, heap usage 849.177 MB -> 47.738 MB. [2024-09-02T11:08:16.882Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-02T11:08:21.367Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-02T11:08:25.947Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-02T11:08:29.528Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-02T11:08:31.401Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-02T11:08:34.896Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-02T11:08:39.321Z] RMSE (validation) = 0.9259652471505186 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-02T11:08:42.116Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-02T11:08:42.491Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328526. [2024-09-02T11:08:42.491Z] The best model improves the baseline by 14.52%. [2024-09-02T11:08:42.869Z] Movies recommended for you: [2024-09-02T11:08:42.869Z] WARNING: This benchmark provides no result that can be validated. [2024-09-02T11:08:42.869Z] There is no way to check that no silent failure occurred. [2024-09-02T11:08:42.869Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (29193.643 ms) ====== [2024-09-02T11:08:42.869Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-09-02T11:08:42.869Z] GC before operation: completed in 104.484 ms, heap usage 851.729 MB -> 47.963 MB. [2024-09-02T11:08:47.240Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-02T11:08:51.556Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-02T11:08:55.162Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-02T11:08:59.839Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-02T11:09:02.570Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-02T11:09:05.385Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-02T11:09:06.721Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-02T11:09:07.549Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-02T11:09:08.477Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525. [2024-09-02T11:09:08.477Z] The best model improves the baseline by 14.52%. [2024-09-02T11:09:08.477Z] Movies recommended for you: [2024-09-02T11:09:08.477Z] WARNING: This benchmark provides no result that can be validated. [2024-09-02T11:09:08.477Z] There is no way to check that no silent failure occurred. [2024-09-02T11:09:08.477Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (25640.408 ms) ====== [2024-09-02T11:09:08.477Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-09-02T11:09:08.477Z] GC before operation: completed in 72.596 ms, heap usage 837.450 MB -> 47.631 MB. [2024-09-02T11:09:11.902Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-02T11:09:15.529Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-02T11:09:18.837Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-02T11:09:23.267Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-02T11:09:25.205Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-02T11:09:26.506Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-02T11:09:27.820Z] RMSE (validation) = 0.9259652471505186 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-02T11:09:30.474Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-02T11:09:30.854Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328526. [2024-09-02T11:09:30.854Z] The best model improves the baseline by 14.52%. [2024-09-02T11:09:31.273Z] Movies recommended for you: [2024-09-02T11:09:31.273Z] WARNING: This benchmark provides no result that can be validated. [2024-09-02T11:09:31.273Z] There is no way to check that no silent failure occurred. [2024-09-02T11:09:31.273Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (22481.563 ms) ====== [2024-09-02T11:09:31.273Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-09-02T11:09:31.273Z] GC before operation: completed in 110.717 ms, heap usage 860.993 MB -> 47.885 MB. [2024-09-02T11:09:38.170Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-02T11:09:43.668Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-02T11:09:50.626Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-02T11:09:56.085Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-02T11:09:57.937Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-02T11:09:59.819Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-02T11:10:03.327Z] RMSE (validation) = 0.9259652471505186 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-02T11:10:06.809Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-02T11:10:07.217Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328526. [2024-09-02T11:10:07.217Z] The best model improves the baseline by 14.52%. [2024-09-02T11:10:07.636Z] Movies recommended for you: [2024-09-02T11:10:07.636Z] WARNING: This benchmark provides no result that can be validated. [2024-09-02T11:10:07.636Z] There is no way to check that no silent failure occurred. [2024-09-02T11:10:07.636Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (36288.661 ms) ====== [2024-09-02T11:10:07.636Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-09-02T11:10:07.636Z] GC before operation: completed in 103.843 ms, heap usage 859.374 MB -> 48.006 MB. [2024-09-02T11:10:13.186Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-02T11:10:18.783Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-02T11:10:24.364Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-02T11:10:31.584Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-02T11:10:34.339Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-02T11:10:36.936Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-02T11:10:41.395Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-02T11:10:44.907Z] RMSE (validation) = 0.8982232235186749 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-02T11:10:45.964Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525. [2024-09-02T11:10:45.964Z] The best model improves the baseline by 14.52%. [2024-09-02T11:10:46.406Z] Movies recommended for you: [2024-09-02T11:10:46.406Z] WARNING: This benchmark provides no result that can be validated. [2024-09-02T11:10:46.406Z] There is no way to check that no silent failure occurred. [2024-09-02T11:10:46.406Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (38616.842 ms) ====== [2024-09-02T11:10:46.406Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-09-02T11:10:46.406Z] GC before operation: completed in 159.188 ms, heap usage 837.626 MB -> 47.751 MB. [2024-09-02T11:10:50.702Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-02T11:10:55.347Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-02T11:11:01.036Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-02T11:11:04.411Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-02T11:11:06.494Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-02T11:11:09.221Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-02T11:11:12.526Z] RMSE (validation) = 0.9259652471505186 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-02T11:11:15.209Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-02T11:11:15.613Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525. [2024-09-02T11:11:15.613Z] The best model improves the baseline by 14.52%. [2024-09-02T11:11:15.613Z] Movies recommended for you: [2024-09-02T11:11:15.613Z] WARNING: This benchmark provides no result that can be validated. [2024-09-02T11:11:15.613Z] There is no way to check that no silent failure occurred. [2024-09-02T11:11:15.613Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (29408.314 ms) ====== [2024-09-02T11:11:15.613Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-09-02T11:11:16.058Z] GC before operation: completed in 393.092 ms, heap usage 853.927 MB -> 47.843 MB. [2024-09-02T11:11:20.227Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-02T11:11:22.778Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-02T11:11:26.049Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-02T11:11:32.957Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-02T11:11:34.317Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-02T11:11:37.785Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-02T11:11:39.308Z] RMSE (validation) = 0.9259652471505186 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-02T11:11:42.919Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-02T11:11:43.399Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328526. [2024-09-02T11:11:43.399Z] The best model improves the baseline by 14.52%. [2024-09-02T11:11:43.399Z] Movies recommended for you: [2024-09-02T11:11:43.399Z] WARNING: This benchmark provides no result that can be validated. [2024-09-02T11:11:43.399Z] There is no way to check that no silent failure occurred. [2024-09-02T11:11:43.399Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (27272.458 ms) ====== [2024-09-02T11:11:43.399Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-09-02T11:11:43.399Z] GC before operation: completed in 147.215 ms, heap usage 851.717 MB -> 48.045 MB. [2024-09-02T11:11:47.748Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-02T11:11:52.242Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-02T11:11:58.039Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-02T11:12:06.683Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-02T11:12:09.472Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-02T11:12:13.920Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-02T11:12:17.687Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-02T11:12:21.312Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-02T11:12:21.713Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525. [2024-09-02T11:12:21.713Z] The best model improves the baseline by 14.52%. [2024-09-02T11:12:22.142Z] Movies recommended for you: [2024-09-02T11:12:22.142Z] WARNING: This benchmark provides no result that can be validated. [2024-09-02T11:12:22.142Z] There is no way to check that no silent failure occurred. [2024-09-02T11:12:22.142Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (38359.439 ms) ====== [2024-09-02T11:12:23.021Z] ----------------------------------- [2024-09-02T11:12:23.021Z] renaissance-movie-lens_0_PASSED [2024-09-02T11:12:23.021Z] ----------------------------------- [2024-09-02T11:12:23.021Z] [2024-09-02T11:12:23.021Z] TEST TEARDOWN: [2024-09-02T11:12:23.021Z] Nothing to be done for teardown. [2024-09-02T11:12:23.021Z] renaissance-movie-lens_0 Finish Time: Mon Sep 2 04:12:22 2024 Epoch Time (ms): 1725275542552