renaissance-movie-lens_0
[2024-08-10T01:56:57.139Z] Running test renaissance-movie-lens_0 ...
[2024-08-10T01:56:57.139Z] ===============================================
[2024-08-10T01:56:57.639Z] renaissance-movie-lens_0 Start Time: Fri Aug 9 18:56:56 2024 Epoch Time (ms): 1723255016203
[2024-08-10T01:56:57.639Z] variation: NoOptions
[2024-08-10T01:56:57.639Z] JVM_OPTIONS:
[2024-08-10T01:56:57.639Z] { \
[2024-08-10T01:56:57.639Z] echo ""; echo "TEST SETUP:"; \
[2024-08-10T01:56:57.639Z] echo "Nothing to be done for setup."; \
[2024-08-10T01:56:57.639Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17232536105496/renaissance-movie-lens_0"; \
[2024-08-10T01:56:57.639Z] cd "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17232536105496/renaissance-movie-lens_0"; \
[2024-08-10T01:56:57.639Z] echo ""; echo "TESTING:"; \
[2024-08-10T01:56:57.639Z] "/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_17232536105496/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-10T01:56:57.639Z] 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_17232536105496/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-10T01:56:57.639Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-10T01:56:57.639Z] echo "Nothing to be done for teardown."; \
[2024-08-10T01:56:57.639Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17232536105496/TestTargetResult";
[2024-08-10T01:56:57.639Z]
[2024-08-10T01:56:57.639Z] TEST SETUP:
[2024-08-10T01:56:57.639Z] Nothing to be done for setup.
[2024-08-10T01:56:57.639Z]
[2024-08-10T01:56:57.639Z] TESTING:
[2024-08-10T01:57:08.329Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-10T01:57:12.931Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2024-08-10T01:57:22.288Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-10T01:57:23.447Z] Training: 60056, validation: 20285, test: 19854
[2024-08-10T01:57:23.447Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-10T01:57:24.064Z] GC before operation: completed in 249.808 ms, heap usage 145.800 MB -> 37.657 MB.
[2024-08-10T01:57:49.718Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T01:57:59.105Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T01:58:14.550Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T01:58:27.740Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T01:58:36.991Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T01:58:44.647Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T01:58:52.366Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T01:59:00.271Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T01:59:00.840Z] 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.
[2024-08-10T01:59:00.840Z] The best model improves the baseline by 14.52%.
[2024-08-10T01:59:01.339Z] Movies recommended for you:
[2024-08-10T01:59:01.339Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T01:59:01.339Z] There is no way to check that no silent failure occurred.
[2024-08-10T01:59:01.339Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (97634.069 ms) ======
[2024-08-10T01:59:01.339Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-10T01:59:01.872Z] GC before operation: completed in 445.055 ms, heap usage 165.564 MB -> 49.643 MB.
[2024-08-10T01:59:14.190Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T01:59:23.094Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T01:59:31.814Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T01:59:42.031Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T01:59:46.910Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T01:59:51.995Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T01:59:58.298Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:00:05.370Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:00:06.099Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-10T02:00:06.099Z] The best model improves the baseline by 14.52%.
[2024-08-10T02:00:06.596Z] Movies recommended for you:
[2024-08-10T02:00:06.596Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:00:06.596Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:00:06.596Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (64691.301 ms) ======
[2024-08-10T02:00:06.596Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-10T02:00:06.596Z] GC before operation: completed in 213.023 ms, heap usage 362.732 MB -> 50.022 MB.
[2024-08-10T02:00:17.497Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:00:28.045Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:00:36.876Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:00:47.469Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:00:51.535Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:00:56.924Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:01:04.361Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:01:10.666Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:01:11.087Z] 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.
[2024-08-10T02:01:11.641Z] The best model improves the baseline by 14.52%.
[2024-08-10T02:01:11.641Z] Movies recommended for you:
[2024-08-10T02:01:11.641Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:01:11.641Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:01:11.641Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (64985.300 ms) ======
[2024-08-10T02:01:11.641Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-10T02:01:12.093Z] GC before operation: completed in 254.644 ms, heap usage 121.320 MB -> 51.208 MB.
[2024-08-10T02:01:22.646Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:01:33.611Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:01:46.569Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:01:54.333Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:01:59.109Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:02:03.881Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:02:10.060Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:02:14.942Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:02:15.352Z] 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.
[2024-08-10T02:02:15.352Z] The best model improves the baseline by 14.52%.
[2024-08-10T02:02:15.811Z] Movies recommended for you:
[2024-08-10T02:02:15.811Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:02:15.811Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:02:15.811Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (63909.012 ms) ======
[2024-08-10T02:02:15.811Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-10T02:02:15.811Z] GC before operation: completed in 118.250 ms, heap usage 122.293 MB -> 50.374 MB.
[2024-08-10T02:02:26.441Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:02:39.591Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:02:48.662Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:02:59.499Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:03:06.798Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:03:14.402Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:03:20.481Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:03:25.465Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:03:26.395Z] 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.
[2024-08-10T02:03:26.395Z] The best model improves the baseline by 14.52%.
[2024-08-10T02:03:26.879Z] Movies recommended for you:
[2024-08-10T02:03:26.880Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:03:26.880Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:03:26.880Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (70722.000 ms) ======
[2024-08-10T02:03:26.880Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-10T02:03:26.880Z] GC before operation: completed in 207.224 ms, heap usage 94.775 MB -> 53.851 MB.
[2024-08-10T02:03:41.646Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:03:50.625Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:04:01.056Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:04:12.124Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:04:16.729Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:04:24.094Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:04:29.282Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:04:36.601Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:04:36.601Z] 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.
[2024-08-10T02:04:36.601Z] The best model improves the baseline by 14.52%.
[2024-08-10T02:04:37.087Z] Movies recommended for you:
[2024-08-10T02:04:37.087Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:04:37.087Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:04:37.087Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (70147.257 ms) ======
[2024-08-10T02:04:37.087Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-10T02:04:37.559Z] GC before operation: completed in 217.794 ms, heap usage 218.042 MB -> 50.611 MB.
[2024-08-10T02:04:49.558Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:04:59.511Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:05:11.602Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:05:20.529Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:05:26.538Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:05:32.660Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:05:39.691Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:05:46.528Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:05:46.528Z] 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.
[2024-08-10T02:05:46.528Z] The best model improves the baseline by 14.52%.
[2024-08-10T02:05:46.962Z] Movies recommended for you:
[2024-08-10T02:05:46.962Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:05:46.962Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:05:46.962Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (69667.080 ms) ======
[2024-08-10T02:05:46.962Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-10T02:05:47.365Z] GC before operation: completed in 361.533 ms, heap usage 549.649 MB -> 54.299 MB.
[2024-08-10T02:05:59.989Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:06:10.199Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:06:20.783Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:06:31.537Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:06:38.456Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:06:45.903Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:06:53.259Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:07:00.057Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:07:01.171Z] 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.
[2024-08-10T02:07:01.171Z] The best model improves the baseline by 14.52%.
[2024-08-10T02:07:01.171Z] Movies recommended for you:
[2024-08-10T02:07:01.171Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:07:01.171Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:07:01.171Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (73994.086 ms) ======
[2024-08-10T02:07:01.171Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-10T02:07:01.659Z] GC before operation: completed in 208.305 ms, heap usage 314.945 MB -> 51.199 MB.
[2024-08-10T02:07:13.730Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:07:23.848Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:07:36.212Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:07:47.147Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:07:51.919Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:07:57.600Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:08:02.287Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:08:07.962Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:08:08.372Z] 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.
[2024-08-10T02:08:08.812Z] The best model improves the baseline by 14.52%.
[2024-08-10T02:08:09.326Z] Movies recommended for you:
[2024-08-10T02:08:09.326Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:08:09.326Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:08:09.326Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (67438.292 ms) ======
[2024-08-10T02:08:09.326Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-10T02:08:09.326Z] GC before operation: completed in 199.481 ms, heap usage 261.640 MB -> 51.070 MB.
[2024-08-10T02:08:21.570Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:08:34.392Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:08:49.481Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:08:58.282Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:09:05.127Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:09:10.086Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:09:17.432Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:09:23.164Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:09:23.574Z] 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.
[2024-08-10T02:09:23.574Z] The best model improves the baseline by 14.52%.
[2024-08-10T02:09:24.521Z] Movies recommended for you:
[2024-08-10T02:09:24.521Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:09:24.521Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:09:24.521Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (74723.519 ms) ======
[2024-08-10T02:09:24.521Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-10T02:09:24.521Z] GC before operation: completed in 273.310 ms, heap usage 1005.059 MB -> 55.656 MB.
[2024-08-10T02:09:36.774Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:09:47.642Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:09:57.774Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:10:10.201Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:10:15.339Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:10:21.545Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:10:28.776Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:10:37.209Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:10:37.209Z] 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.
[2024-08-10T02:10:37.209Z] The best model improves the baseline by 14.52%.
[2024-08-10T02:10:37.620Z] Movies recommended for you:
[2024-08-10T02:10:37.620Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:10:37.620Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:10:37.620Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (73283.930 ms) ======
[2024-08-10T02:10:37.620Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-10T02:10:37.620Z] GC before operation: completed in 227.684 ms, heap usage 243.660 MB -> 50.883 MB.
[2024-08-10T02:10:52.703Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:11:01.247Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:11:13.926Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:11:24.269Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:11:28.945Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:11:36.046Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:11:42.340Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:11:48.328Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:11:49.341Z] 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.
[2024-08-10T02:11:49.341Z] The best model improves the baseline by 14.52%.
[2024-08-10T02:11:49.766Z] Movies recommended for you:
[2024-08-10T02:11:49.766Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:11:49.766Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:11:49.766Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (71997.492 ms) ======
[2024-08-10T02:11:49.766Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-10T02:11:49.766Z] GC before operation: completed in 169.478 ms, heap usage 255.015 MB -> 51.055 MB.
[2024-08-10T02:12:02.183Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:12:14.427Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:12:23.100Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:12:33.804Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:12:39.483Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:12:45.162Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:12:52.133Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:12:57.746Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:12:57.746Z] 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.
[2024-08-10T02:12:58.268Z] The best model improves the baseline by 14.52%.
[2024-08-10T02:12:58.268Z] Movies recommended for you:
[2024-08-10T02:12:58.268Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:12:58.268Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:12:58.268Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (68233.804 ms) ======
[2024-08-10T02:12:58.268Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-10T02:12:58.268Z] GC before operation: completed in 273.141 ms, heap usage 400.968 MB -> 54.520 MB.
[2024-08-10T02:13:10.454Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:13:22.607Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:13:32.936Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:13:43.235Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:13:49.110Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:13:55.189Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:14:01.249Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:14:08.208Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:14:09.215Z] 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.
[2024-08-10T02:14:09.634Z] The best model improves the baseline by 14.52%.
[2024-08-10T02:14:09.634Z] Movies recommended for you:
[2024-08-10T02:14:09.634Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:14:09.634Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:14:09.634Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (71368.572 ms) ======
[2024-08-10T02:14:09.634Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-10T02:14:10.026Z] GC before operation: completed in 295.966 ms, heap usage 341.469 MB -> 50.996 MB.
[2024-08-10T02:14:22.481Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:14:33.096Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:14:43.811Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:14:54.313Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:15:00.144Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:15:06.972Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:15:12.682Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:15:17.027Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:15:17.964Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-10T02:15:17.964Z] The best model improves the baseline by 14.52%.
[2024-08-10T02:15:17.964Z] Movies recommended for you:
[2024-08-10T02:15:17.964Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:15:17.964Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:15:17.964Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (68062.400 ms) ======
[2024-08-10T02:15:17.964Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-10T02:15:18.500Z] GC before operation: completed in 151.124 ms, heap usage 92.250 MB -> 53.011 MB.
[2024-08-10T02:15:28.767Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:15:39.030Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:15:49.195Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:15:57.767Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:16:03.389Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:16:09.257Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:16:16.503Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:16:21.269Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:16:21.770Z] 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.
[2024-08-10T02:16:21.770Z] The best model improves the baseline by 14.52%.
[2024-08-10T02:16:22.272Z] Movies recommended for you:
[2024-08-10T02:16:22.272Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:16:22.272Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:16:22.272Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (63982.879 ms) ======
[2024-08-10T02:16:22.272Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-10T02:16:22.700Z] GC before operation: completed in 211.859 ms, heap usage 309.609 MB -> 51.212 MB.
[2024-08-10T02:16:33.256Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:16:45.490Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:16:57.562Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:17:06.452Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:17:11.083Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:17:16.835Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:17:22.427Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:17:26.842Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:17:27.761Z] 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.
[2024-08-10T02:17:27.761Z] The best model improves the baseline by 14.52%.
[2024-08-10T02:17:28.415Z] Movies recommended for you:
[2024-08-10T02:17:28.415Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:17:28.415Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:17:28.415Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (65492.547 ms) ======
[2024-08-10T02:17:28.415Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-10T02:17:28.415Z] GC before operation: completed in 203.074 ms, heap usage 381.110 MB -> 54.298 MB.
[2024-08-10T02:17:38.379Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:17:46.653Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:17:55.334Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:18:04.274Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:18:11.500Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:18:17.243Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:18:20.547Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:18:27.644Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:18:27.644Z] 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.
[2024-08-10T02:18:27.644Z] The best model improves the baseline by 14.52%.
[2024-08-10T02:18:27.644Z] Movies recommended for you:
[2024-08-10T02:18:27.644Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:18:27.644Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:18:27.644Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (59446.718 ms) ======
[2024-08-10T02:18:27.644Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-10T02:18:27.644Z] GC before operation: completed in 140.814 ms, heap usage 174.366 MB -> 51.007 MB.
[2024-08-10T02:18:37.684Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:18:50.227Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:18:59.139Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:19:09.132Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:19:14.860Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:19:17.452Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:19:23.315Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:19:28.005Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:19:28.442Z] 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.
[2024-08-10T02:19:28.442Z] The best model improves the baseline by 14.52%.
[2024-08-10T02:19:28.442Z] Movies recommended for you:
[2024-08-10T02:19:28.442Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:19:28.442Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:19:28.442Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (60715.592 ms) ======
[2024-08-10T02:19:28.442Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-10T02:19:28.874Z] GC before operation: completed in 167.517 ms, heap usage 209.243 MB -> 51.188 MB.
[2024-08-10T02:19:39.429Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T02:19:46.313Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T02:19:54.610Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T02:20:01.411Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T02:20:05.908Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T02:20:10.401Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T02:20:16.081Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T02:20:21.725Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T02:20:22.244Z] 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.
[2024-08-10T02:20:22.691Z] The best model improves the baseline by 14.52%.
[2024-08-10T02:20:22.692Z] Movies recommended for you:
[2024-08-10T02:20:22.692Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T02:20:22.692Z] There is no way to check that no silent failure occurred.
[2024-08-10T02:20:22.692Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (54054.801 ms) ======
[2024-08-10T02:20:26.047Z] -----------------------------------
[2024-08-10T02:20:26.048Z] renaissance-movie-lens_0_PASSED
[2024-08-10T02:20:26.048Z] -----------------------------------
[2024-08-10T02:20:26.048Z]
[2024-08-10T02:20:26.048Z] TEST TEARDOWN:
[2024-08-10T02:20:26.048Z] Nothing to be done for teardown.
[2024-08-10T02:20:26.048Z] renaissance-movie-lens_0 Finish Time: Fri Aug 9 19:20:24 2024 Epoch Time (ms): 1723256424657