renaissance-movie-lens_0
[2024-08-02T07:47:31.159Z] Running test renaissance-movie-lens_0 ...
[2024-08-02T07:47:31.159Z] ===============================================
[2024-08-02T07:47:31.159Z] renaissance-movie-lens_0 Start Time: Fri Aug 2 00:47:29 2024 Epoch Time (ms): 1722584849217
[2024-08-02T07:47:31.159Z] variation: NoOptions
[2024-08-02T07:47:31.159Z] JVM_OPTIONS:
[2024-08-02T07:47:31.159Z] { \
[2024-08-02T07:47:31.159Z] echo ""; echo "TEST SETUP:"; \
[2024-08-02T07:47:31.159Z] echo "Nothing to be done for setup."; \
[2024-08-02T07:47:31.159Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17225828174357/renaissance-movie-lens_0"; \
[2024-08-02T07:47:31.159Z] cd "/Users/admin/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17225828174357/renaissance-movie-lens_0"; \
[2024-08-02T07:47:31.159Z] echo ""; echo "TESTING:"; \
[2024-08-02T07:47:31.159Z] "/Users/admin/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_mac_testList_0/jdkbinary/j2sdk-image/Contents/Home/bin/..//bin/java" -jar "/Users/admin/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17225828174357/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-02T07:47:31.159Z] 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_testList_0/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17225828174357/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-02T07:47:31.159Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-02T07:47:31.159Z] echo "Nothing to be done for teardown."; \
[2024-08-02T07:47:31.159Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17225828174357/TestTargetResult";
[2024-08-02T07:47:31.159Z]
[2024-08-02T07:47:31.159Z] TEST SETUP:
[2024-08-02T07:47:31.159Z] Nothing to be done for setup.
[2024-08-02T07:47:31.159Z]
[2024-08-02T07:47:31.159Z] TESTING:
[2024-08-02T07:47:35.515Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-02T07:47:36.875Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2024-08-02T07:47:42.762Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-02T07:47:43.751Z] Training: 60056, validation: 20285, test: 19854
[2024-08-02T07:47:43.751Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-02T07:47:44.181Z] GC before operation: completed in 262.078 ms, heap usage 227.289 MB -> 26.363 MB.
[2024-08-02T07:47:59.199Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T07:48:06.650Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T07:48:12.456Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T07:48:18.278Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T07:48:21.035Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T07:48:22.979Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T07:48:25.722Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T07:48:27.062Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T07:48:27.516Z] 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.
[2024-08-02T07:48:27.974Z] The best model improves the baseline by 14.52%.
[2024-08-02T07:48:27.974Z] Movies recommended for you:
[2024-08-02T07:48:27.974Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T07:48:27.974Z] There is no way to check that no silent failure occurred.
[2024-08-02T07:48:27.974Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (43882.484 ms) ======
[2024-08-02T07:48:27.974Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-02T07:48:28.390Z] GC before operation: completed in 259.177 ms, heap usage 231.468 MB -> 50.401 MB.
[2024-08-02T07:48:32.768Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T07:48:38.554Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T07:48:42.030Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T07:48:44.782Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T07:48:48.711Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T07:48:53.176Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T07:48:55.883Z] RMSE (validation) = 0.9259652471505186 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T07:48:59.483Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T07:48:59.483Z] 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.
[2024-08-02T07:48:59.483Z] The best model improves the baseline by 14.52%.
[2024-08-02T07:48:59.915Z] Movies recommended for you:
[2024-08-02T07:48:59.915Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T07:48:59.915Z] There is no way to check that no silent failure occurred.
[2024-08-02T07:48:59.915Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (31609.942 ms) ======
[2024-08-02T07:48:59.915Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-02T07:48:59.915Z] GC before operation: completed in 194.535 ms, heap usage 715.527 MB -> 46.054 MB.
[2024-08-02T07:49:06.939Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T07:49:13.890Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T07:49:18.489Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T07:49:23.872Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T07:49:25.910Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T07:49:27.769Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T07:49:31.388Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T07:49:34.874Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T07:49:34.874Z] 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.
[2024-08-02T07:49:34.874Z] The best model improves the baseline by 14.52%.
[2024-08-02T07:49:35.271Z] Movies recommended for you:
[2024-08-02T07:49:35.271Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T07:49:35.271Z] There is no way to check that no silent failure occurred.
[2024-08-02T07:49:35.271Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (35185.033 ms) ======
[2024-08-02T07:49:35.271Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-02T07:49:35.271Z] GC before operation: completed in 196.351 ms, heap usage 650.329 MB -> 45.999 MB.
[2024-08-02T07:49:40.826Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T07:49:49.655Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T07:49:59.905Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T07:50:05.848Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T07:50:10.815Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T07:50:16.458Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T07:50:20.446Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T07:50:26.150Z] RMSE (validation) = 0.8982232235186749 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T07:50:26.150Z] 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.
[2024-08-02T07:50:26.150Z] The best model improves the baseline by 14.52%.
[2024-08-02T07:50:26.150Z] Movies recommended for you:
[2024-08-02T07:50:26.150Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T07:50:26.150Z] There is no way to check that no silent failure occurred.
[2024-08-02T07:50:26.150Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (50587.263 ms) ======
[2024-08-02T07:50:26.150Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-02T07:50:26.150Z] GC before operation: completed in 174.612 ms, heap usage 620.669 MB -> 46.216 MB.
[2024-08-02T07:50:34.605Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T07:50:40.077Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T07:50:44.691Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T07:50:53.173Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T07:50:56.969Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T07:51:00.678Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T07:51:03.458Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T07:51:08.119Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T07:51:08.119Z] 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.
[2024-08-02T07:51:08.119Z] The best model improves the baseline by 14.52%.
[2024-08-02T07:51:08.692Z] Movies recommended for you:
[2024-08-02T07:51:08.692Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T07:51:08.692Z] There is no way to check that no silent failure occurred.
[2024-08-02T07:51:08.692Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (42360.813 ms) ======
[2024-08-02T07:51:08.692Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-02T07:51:09.119Z] GC before operation: completed in 651.595 ms, heap usage 588.893 MB -> 46.271 MB.
[2024-08-02T07:51:17.772Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T07:51:35.982Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T07:51:41.520Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T07:51:51.758Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T07:52:07.388Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T07:52:08.793Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T07:52:12.254Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T07:52:18.163Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T07:52:18.606Z] 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.
[2024-08-02T07:52:18.606Z] The best model improves the baseline by 14.52%.
[2024-08-02T07:52:19.006Z] Movies recommended for you:
[2024-08-02T07:52:19.006Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T07:52:19.006Z] There is no way to check that no silent failure occurred.
[2024-08-02T07:52:19.006Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (69647.675 ms) ======
[2024-08-02T07:52:19.006Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-02T07:52:19.006Z] GC before operation: completed in 231.019 ms, heap usage 581.610 MB -> 46.175 MB.
[2024-08-02T07:52:29.335Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T07:52:37.977Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T07:52:53.284Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T07:52:57.605Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T07:53:01.633Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T07:53:06.572Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T07:53:15.490Z] RMSE (validation) = 0.9259652471505186 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T07:53:22.551Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T07:53:22.941Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525.
[2024-08-02T07:53:22.942Z] The best model improves the baseline by 14.52%.
[2024-08-02T07:53:22.942Z] Movies recommended for you:
[2024-08-02T07:53:22.942Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T07:53:22.942Z] There is no way to check that no silent failure occurred.
[2024-08-02T07:53:22.942Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (63845.008 ms) ======
[2024-08-02T07:53:22.942Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-02T07:53:22.942Z] GC before operation: completed in 142.148 ms, heap usage 563.377 MB -> 46.285 MB.
[2024-08-02T07:53:28.574Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T07:53:35.397Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T07:53:42.427Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T07:53:50.765Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T07:53:57.113Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T07:54:07.628Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T07:54:10.269Z] RMSE (validation) = 0.9259652471505186 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T07:54:12.353Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T07:54:12.782Z] 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.
[2024-08-02T07:54:12.782Z] The best model improves the baseline by 14.52%.
[2024-08-02T07:54:12.782Z] Movies recommended for you:
[2024-08-02T07:54:12.782Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T07:54:12.782Z] There is no way to check that no silent failure occurred.
[2024-08-02T07:54:12.782Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (49678.834 ms) ======
[2024-08-02T07:54:12.782Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-02T07:54:12.782Z] GC before operation: completed in 172.332 ms, heap usage 567.200 MB -> 46.581 MB.
[2024-08-02T07:54:21.030Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T07:54:26.904Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T07:54:32.655Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T07:54:38.164Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T07:54:41.716Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T07:54:43.835Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T07:54:49.074Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T07:54:53.656Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T07:54:54.683Z] 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.
[2024-08-02T07:54:54.683Z] The best model improves the baseline by 14.52%.
[2024-08-02T07:54:55.658Z] Movies recommended for you:
[2024-08-02T07:54:55.658Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T07:54:55.658Z] There is no way to check that no silent failure occurred.
[2024-08-02T07:54:55.658Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (42518.102 ms) ======
[2024-08-02T07:54:55.658Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-02T07:54:55.658Z] GC before operation: completed in 158.272 ms, heap usage 556.133 MB -> 46.280 MB.
[2024-08-02T07:55:04.276Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T07:55:22.780Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T07:55:29.571Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T07:55:38.098Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T07:55:42.119Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T07:55:44.185Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T07:55:46.064Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T07:55:48.920Z] RMSE (validation) = 0.8982232235186749 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T07:55:48.920Z] 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.
[2024-08-02T07:55:48.920Z] The best model improves the baseline by 14.52%.
[2024-08-02T07:55:48.920Z] Movies recommended for you:
[2024-08-02T07:55:48.920Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T07:55:48.920Z] There is no way to check that no silent failure occurred.
[2024-08-02T07:55:48.920Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (53262.480 ms) ======
[2024-08-02T07:55:48.920Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-02T07:55:48.920Z] GC before operation: completed in 102.732 ms, heap usage 561.138 MB -> 46.449 MB.
[2024-08-02T07:55:51.503Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T07:55:54.788Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T07:55:59.069Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T07:56:07.727Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T07:56:10.889Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T07:56:16.502Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T07:56:19.385Z] RMSE (validation) = 0.9259652471505186 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T07:56:21.322Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T07:56:21.799Z] 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.
[2024-08-02T07:56:21.799Z] The best model improves the baseline by 14.52%.
[2024-08-02T07:56:22.189Z] Movies recommended for you:
[2024-08-02T07:56:22.190Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T07:56:22.190Z] There is no way to check that no silent failure occurred.
[2024-08-02T07:56:22.190Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (33161.373 ms) ======
[2024-08-02T07:56:22.190Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-02T07:56:22.190Z] GC before operation: completed in 146.635 ms, heap usage 546.299 MB -> 45.954 MB.
[2024-08-02T07:56:25.513Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T07:56:28.060Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T07:56:31.731Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T07:56:35.237Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T07:56:36.616Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T07:56:38.077Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T07:56:40.776Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T07:56:42.702Z] RMSE (validation) = 0.8982232235186749 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T07:56:42.702Z] 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.
[2024-08-02T07:56:42.702Z] The best model improves the baseline by 14.52%.
[2024-08-02T07:56:42.702Z] Movies recommended for you:
[2024-08-02T07:56:42.702Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T07:56:42.702Z] There is no way to check that no silent failure occurred.
[2024-08-02T07:56:42.702Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (20565.362 ms) ======
[2024-08-02T07:56:42.702Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-02T07:56:43.095Z] GC before operation: completed in 74.604 ms, heap usage 552.854 MB -> 46.330 MB.
[2024-08-02T07:56:47.340Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T07:56:50.095Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T07:56:54.407Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T07:56:57.670Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T07:56:59.710Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T07:57:01.642Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T07:57:02.993Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T07:57:05.015Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T07:57:05.015Z] 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.
[2024-08-02T07:57:05.015Z] The best model improves the baseline by 14.52%.
[2024-08-02T07:57:05.015Z] Movies recommended for you:
[2024-08-02T07:57:05.015Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T07:57:05.015Z] There is no way to check that no silent failure occurred.
[2024-08-02T07:57:05.015Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (22165.448 ms) ======
[2024-08-02T07:57:05.015Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-02T07:57:05.015Z] GC before operation: completed in 75.464 ms, heap usage 558.709 MB -> 46.550 MB.
[2024-08-02T07:57:08.502Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T07:57:14.065Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T07:57:18.720Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T07:57:23.038Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T07:57:25.773Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T07:57:30.498Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T07:57:33.414Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T07:57:37.932Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T07:57:38.816Z] 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.
[2024-08-02T07:57:38.816Z] The best model improves the baseline by 14.52%.
[2024-08-02T07:57:38.816Z] Movies recommended for you:
[2024-08-02T07:57:38.816Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T07:57:38.816Z] There is no way to check that no silent failure occurred.
[2024-08-02T07:57:38.816Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (33792.542 ms) ======
[2024-08-02T07:57:38.816Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-02T07:57:39.238Z] GC before operation: completed in 132.198 ms, heap usage 567.571 MB -> 46.309 MB.
[2024-08-02T07:57:43.446Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T07:57:46.044Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T07:57:50.553Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T07:57:54.896Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T07:57:57.674Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T07:57:59.722Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T07:58:02.521Z] RMSE (validation) = 0.9259652471505186 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T07:58:05.288Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T07:58:05.681Z] 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.
[2024-08-02T07:58:05.681Z] The best model improves the baseline by 14.52%.
[2024-08-02T07:58:06.078Z] Movies recommended for you:
[2024-08-02T07:58:06.078Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T07:58:06.078Z] There is no way to check that no silent failure occurred.
[2024-08-02T07:58:06.078Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (26829.407 ms) ======
[2024-08-02T07:58:06.078Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-02T07:58:06.078Z] GC before operation: completed in 132.015 ms, heap usage 535.750 MB -> 46.299 MB.
[2024-08-02T07:58:08.606Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T07:58:11.953Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T07:58:15.341Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T07:58:17.875Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T07:58:20.721Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T07:58:25.258Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T07:58:26.643Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T07:58:28.659Z] RMSE (validation) = 0.8982232235186749 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T07:58:28.659Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525.
[2024-08-02T07:58:28.659Z] The best model improves the baseline by 14.52%.
[2024-08-02T07:58:28.659Z] Movies recommended for you:
[2024-08-02T07:58:28.659Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T07:58:28.659Z] There is no way to check that no silent failure occurred.
[2024-08-02T07:58:28.659Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (22745.350 ms) ======
[2024-08-02T07:58:28.659Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-02T07:58:29.138Z] GC before operation: completed in 342.727 ms, heap usage 566.199 MB -> 46.633 MB.
[2024-08-02T07:58:34.596Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T07:58:37.161Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T07:58:39.726Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T07:58:44.261Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T07:58:46.218Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T07:58:50.638Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T07:58:53.522Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T07:58:56.151Z] RMSE (validation) = 0.8982232235186749 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T07:58:56.151Z] 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.
[2024-08-02T07:58:56.151Z] The best model improves the baseline by 14.52%.
[2024-08-02T07:58:56.151Z] Movies recommended for you:
[2024-08-02T07:58:56.151Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T07:58:56.151Z] There is no way to check that no silent failure occurred.
[2024-08-02T07:58:56.151Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (26868.022 ms) ======
[2024-08-02T07:58:56.151Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-02T07:58:56.151Z] GC before operation: completed in 103.339 ms, heap usage 559.500 MB -> 46.395 MB.
[2024-08-02T07:59:01.705Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T07:59:08.786Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T07:59:14.260Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T07:59:20.249Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T07:59:24.580Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T07:59:26.578Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T07:59:28.779Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T07:59:31.617Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T07:59:32.008Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525.
[2024-08-02T07:59:32.008Z] The best model improves the baseline by 14.52%.
[2024-08-02T07:59:32.008Z] Movies recommended for you:
[2024-08-02T07:59:32.008Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T07:59:32.008Z] There is no way to check that no silent failure occurred.
[2024-08-02T07:59:32.008Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (35848.578 ms) ======
[2024-08-02T07:59:32.008Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-02T07:59:32.008Z] GC before operation: completed in 75.483 ms, heap usage 554.714 MB -> 46.272 MB.
[2024-08-02T07:59:34.576Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T07:59:38.930Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T07:59:41.479Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T07:59:44.909Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T07:59:46.818Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T07:59:48.133Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T07:59:50.058Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T07:59:53.682Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T07:59:54.093Z] 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.
[2024-08-02T07:59:54.093Z] The best model improves the baseline by 14.52%.
[2024-08-02T07:59:54.093Z] Movies recommended for you:
[2024-08-02T07:59:54.093Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T07:59:54.093Z] There is no way to check that no silent failure occurred.
[2024-08-02T07:59:54.093Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (22119.957 ms) ======
[2024-08-02T07:59:54.093Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-02T07:59:54.093Z] GC before operation: completed in 82.370 ms, heap usage 555.612 MB -> 46.638 MB.
[2024-08-02T07:59:56.672Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T07:59:58.603Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T08:00:04.088Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T08:00:09.595Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T08:00:12.480Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T08:00:14.454Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T08:00:17.977Z] RMSE (validation) = 0.9259652471505186 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T08:00:22.646Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T08:00:23.037Z] 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.
[2024-08-02T08:00:23.037Z] The best model improves the baseline by 14.52%.
[2024-08-02T08:00:23.037Z] Movies recommended for you:
[2024-08-02T08:00:23.037Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T08:00:23.037Z] There is no way to check that no silent failure occurred.
[2024-08-02T08:00:23.037Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (28827.269 ms) ======
[2024-08-02T08:00:25.094Z] -----------------------------------
[2024-08-02T08:00:25.094Z] renaissance-movie-lens_0_PASSED
[2024-08-02T08:00:25.094Z] -----------------------------------
[2024-08-02T08:00:25.094Z]
[2024-08-02T08:00:25.094Z] TEST TEARDOWN:
[2024-08-02T08:00:25.094Z] Nothing to be done for teardown.
[2024-08-02T08:00:25.515Z] renaissance-movie-lens_0 Finish Time: Fri Aug 2 01:00:23 2024 Epoch Time (ms): 1722585623703