renaissance-movie-lens_0
[2024-11-21T07:56:02.571Z] Running test renaissance-movie-lens_0 ...
[2024-11-21T07:56:02.571Z] ===============================================
[2024-11-21T07:56:02.571Z] renaissance-movie-lens_0 Start Time: Wed Nov 20 23:56:01 2024 Epoch Time (ms): 1732175761359
[2024-11-21T07:56:03.030Z] variation: NoOptions
[2024-11-21T07:56:03.030Z] JVM_OPTIONS:
[2024-11-21T07:56:03.030Z] { \
[2024-11-21T07:56:03.030Z] echo ""; echo "TEST SETUP:"; \
[2024-11-21T07:56:03.030Z] echo "Nothing to be done for setup."; \
[2024-11-21T07:56:03.030Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17321734849362/renaissance-movie-lens_0"; \
[2024-11-21T07:56:03.031Z] cd "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17321734849362/renaissance-movie-lens_0"; \
[2024-11-21T07:56:03.031Z] echo ""; echo "TESTING:"; \
[2024-11-21T07:56:03.031Z] "/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_17321734849362/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-21T07:56:03.031Z] 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_17321734849362/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-21T07:56:03.031Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-21T07:56:03.031Z] echo "Nothing to be done for teardown."; \
[2024-11-21T07:56:03.031Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17321734849362/TestTargetResult";
[2024-11-21T07:56:03.456Z]
[2024-11-21T07:56:03.456Z] TEST SETUP:
[2024-11-21T07:56:03.456Z] Nothing to be done for setup.
[2024-11-21T07:56:03.456Z]
[2024-11-21T07:56:03.456Z] TESTING:
[2024-11-21T07:56:17.065Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-21T07:56:24.273Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2024-11-21T07:56:40.680Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-21T07:56:41.105Z] Training: 60056, validation: 20285, test: 19854
[2024-11-21T07:56:41.105Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-21T07:56:41.105Z] GC before operation: completed in 145.307 ms, heap usage 100.678 MB -> 37.583 MB.
[2024-11-21T07:57:19.740Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T07:57:51.920Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T07:58:15.466Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T07:58:38.702Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T07:58:52.204Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T07:59:06.160Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T07:59:17.895Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T07:59:27.984Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T07:59:30.558Z] 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.
[2024-11-21T07:59:30.558Z] The best model improves the baseline by 14.52%.
[2024-11-21T07:59:31.031Z] Movies recommended for you:
[2024-11-21T07:59:31.031Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T07:59:31.031Z] There is no way to check that no silent failure occurred.
[2024-11-21T07:59:31.031Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (169667.763 ms) ======
[2024-11-21T07:59:31.031Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-21T07:59:32.074Z] GC before operation: completed in 340.939 ms, heap usage 362.807 MB -> 49.755 MB.
[2024-11-21T07:59:51.902Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T08:00:14.812Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T08:00:30.899Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T08:00:48.010Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T08:00:57.291Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T08:01:09.670Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T08:01:17.360Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T08:01:27.366Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T08:01:29.999Z] 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.
[2024-11-21T08:01:29.999Z] The best model improves the baseline by 14.52%.
[2024-11-21T08:01:30.571Z] Movies recommended for you:
[2024-11-21T08:01:30.571Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T08:01:30.571Z] There is no way to check that no silent failure occurred.
[2024-11-21T08:01:30.571Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (118966.458 ms) ======
[2024-11-21T08:01:30.571Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-21T08:01:30.571Z] GC before operation: completed in 186.809 ms, heap usage 258.103 MB -> 49.888 MB.
[2024-11-21T08:01:49.913Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T08:02:06.239Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T08:02:25.542Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T08:02:41.564Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T08:02:50.883Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T08:03:00.017Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T08:03:08.384Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T08:03:20.652Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T08:03:22.301Z] 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.
[2024-11-21T08:03:22.301Z] The best model improves the baseline by 14.52%.
[2024-11-21T08:03:22.301Z] Movies recommended for you:
[2024-11-21T08:03:22.301Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T08:03:22.301Z] There is no way to check that no silent failure occurred.
[2024-11-21T08:03:22.301Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (111859.991 ms) ======
[2024-11-21T08:03:22.301Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-21T08:03:22.720Z] GC before operation: completed in 249.703 ms, heap usage 265.238 MB -> 50.202 MB.
[2024-11-21T08:03:41.681Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T08:03:57.914Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T08:04:14.310Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T08:04:30.625Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T08:04:40.439Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T08:04:51.978Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T08:05:03.482Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T08:05:13.481Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T08:05:14.012Z] 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.
[2024-11-21T08:05:14.408Z] The best model improves the baseline by 14.52%.
[2024-11-21T08:05:14.408Z] Movies recommended for you:
[2024-11-21T08:05:14.408Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T08:05:14.408Z] There is no way to check that no silent failure occurred.
[2024-11-21T08:05:14.408Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (111882.191 ms) ======
[2024-11-21T08:05:14.408Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-21T08:05:14.792Z] GC before operation: completed in 202.517 ms, heap usage 410.176 MB -> 53.797 MB.
[2024-11-21T08:05:33.179Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T08:05:49.585Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T08:06:06.388Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T08:06:29.530Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T08:06:38.735Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T08:06:50.087Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T08:07:04.130Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T08:07:23.737Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T08:07:23.737Z] 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.
[2024-11-21T08:07:23.737Z] The best model improves the baseline by 14.52%.
[2024-11-21T08:07:23.737Z] Movies recommended for you:
[2024-11-21T08:07:23.737Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T08:07:23.737Z] There is no way to check that no silent failure occurred.
[2024-11-21T08:07:23.737Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (128565.820 ms) ======
[2024-11-21T08:07:23.737Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-21T08:07:23.737Z] GC before operation: completed in 298.785 ms, heap usage 494.744 MB -> 54.062 MB.
[2024-11-21T08:07:43.313Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T08:08:02.974Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T08:08:25.383Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T08:08:43.001Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T08:08:52.890Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T08:09:04.042Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T08:09:15.200Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T08:09:24.659Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T08:09:26.623Z] 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.
[2024-11-21T08:09:27.113Z] The best model improves the baseline by 14.52%.
[2024-11-21T08:09:27.114Z] Movies recommended for you:
[2024-11-21T08:09:27.114Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T08:09:27.114Z] There is no way to check that no silent failure occurred.
[2024-11-21T08:09:27.114Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (123577.791 ms) ======
[2024-11-21T08:09:27.114Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-21T08:09:27.114Z] GC before operation: completed in 206.697 ms, heap usage 184.126 MB -> 50.537 MB.
[2024-11-21T08:09:45.748Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T08:10:05.055Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T08:10:24.756Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T08:10:43.815Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T08:10:51.119Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T08:11:01.925Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T08:11:12.851Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T08:11:24.354Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T08:11:26.741Z] 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.
[2024-11-21T08:11:26.741Z] The best model improves the baseline by 14.52%.
[2024-11-21T08:11:27.165Z] Movies recommended for you:
[2024-11-21T08:11:27.165Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T08:11:27.165Z] There is no way to check that no silent failure occurred.
[2024-11-21T08:11:27.165Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (119691.178 ms) ======
[2024-11-21T08:11:27.165Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-21T08:11:27.165Z] GC before operation: completed in 273.223 ms, heap usage 261.923 MB -> 50.769 MB.
[2024-11-21T08:11:45.923Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T08:12:04.519Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T08:12:20.451Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T08:12:37.002Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T08:12:48.307Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T08:13:02.171Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T08:13:08.714Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T08:13:21.896Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T08:13:21.896Z] 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.
[2024-11-21T08:13:21.896Z] The best model improves the baseline by 14.52%.
[2024-11-21T08:13:21.896Z] Movies recommended for you:
[2024-11-21T08:13:21.896Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T08:13:21.896Z] There is no way to check that no silent failure occurred.
[2024-11-21T08:13:21.896Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (113828.342 ms) ======
[2024-11-21T08:13:21.896Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-21T08:13:22.463Z] GC before operation: completed in 1247.974 ms, heap usage 314.894 MB -> 51.190 MB.
[2024-11-21T08:13:41.051Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T08:14:04.444Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T08:14:22.408Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T08:14:38.855Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T08:14:48.935Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T08:14:58.543Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T08:15:12.065Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T08:15:19.549Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T08:15:20.542Z] 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.
[2024-11-21T08:15:20.973Z] The best model improves the baseline by 14.52%.
[2024-11-21T08:15:21.430Z] Movies recommended for you:
[2024-11-21T08:15:21.430Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T08:15:21.430Z] There is no way to check that no silent failure occurred.
[2024-11-21T08:15:21.430Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (119050.653 ms) ======
[2024-11-21T08:15:21.430Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-21T08:15:21.926Z] GC before operation: completed in 198.076 ms, heap usage 131.437 MB -> 50.745 MB.
[2024-11-21T08:15:44.500Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T08:16:04.150Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T08:16:23.137Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T08:16:39.231Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T08:16:48.347Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T08:16:57.592Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T08:17:06.848Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T08:17:16.101Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T08:17:16.101Z] 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.
[2024-11-21T08:17:16.101Z] The best model improves the baseline by 14.52%.
[2024-11-21T08:17:16.697Z] Movies recommended for you:
[2024-11-21T08:17:16.697Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T08:17:16.697Z] There is no way to check that no silent failure occurred.
[2024-11-21T08:17:16.697Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (114691.688 ms) ======
[2024-11-21T08:17:16.697Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-21T08:17:17.502Z] GC before operation: completed in 606.541 ms, heap usage 449.610 MB -> 54.514 MB.
[2024-11-21T08:17:35.967Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T08:17:52.421Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T08:18:08.307Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T08:18:23.910Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T08:18:35.279Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T08:18:44.837Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T08:19:04.039Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T08:19:11.442Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T08:19:11.442Z] 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.
[2024-11-21T08:19:11.904Z] The best model improves the baseline by 14.52%.
[2024-11-21T08:19:11.904Z] Movies recommended for you:
[2024-11-21T08:19:11.904Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T08:19:11.904Z] There is no way to check that no silent failure occurred.
[2024-11-21T08:19:11.904Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (115007.019 ms) ======
[2024-11-21T08:19:11.904Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-21T08:19:12.350Z] GC before operation: completed in 227.096 ms, heap usage 431.277 MB -> 54.033 MB.
[2024-11-21T08:19:34.948Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T08:19:54.012Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T08:20:17.829Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T08:20:34.218Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T08:20:43.558Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T08:20:53.381Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T08:21:04.543Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T08:21:13.683Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T08:21:13.683Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-11-21T08:21:13.683Z] The best model improves the baseline by 14.52%.
[2024-11-21T08:21:14.193Z] Movies recommended for you:
[2024-11-21T08:21:14.193Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T08:21:14.193Z] There is no way to check that no silent failure occurred.
[2024-11-21T08:21:14.193Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (121745.096 ms) ======
[2024-11-21T08:21:14.193Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-21T08:21:14.193Z] GC before operation: completed in 188.836 ms, heap usage 609.144 MB -> 54.559 MB.
[2024-11-21T08:21:33.021Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T08:21:51.437Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T08:22:07.717Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T08:22:27.627Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T08:22:38.632Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T08:22:50.202Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T08:23:00.175Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T08:23:09.941Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T08:23:09.941Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-11-21T08:23:09.941Z] The best model improves the baseline by 14.52%.
[2024-11-21T08:23:10.403Z] Movies recommended for you:
[2024-11-21T08:23:10.403Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T08:23:10.403Z] There is no way to check that no silent failure occurred.
[2024-11-21T08:23:10.403Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (116254.580 ms) ======
[2024-11-21T08:23:10.403Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-21T08:23:10.799Z] GC before operation: completed in 251.590 ms, heap usage 78.123 MB -> 52.919 MB.
[2024-11-21T08:23:29.959Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T08:23:46.694Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T08:24:02.973Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T08:24:19.327Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T08:24:30.789Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T08:24:38.447Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T08:24:49.725Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T08:24:58.799Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T08:24:59.334Z] 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.
[2024-11-21T08:24:59.334Z] The best model improves the baseline by 14.52%.
[2024-11-21T08:24:59.334Z] Movies recommended for you:
[2024-11-21T08:24:59.334Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T08:24:59.334Z] There is no way to check that no silent failure occurred.
[2024-11-21T08:24:59.334Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (108862.558 ms) ======
[2024-11-21T08:24:59.334Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-21T08:24:59.782Z] GC before operation: completed in 199.770 ms, heap usage 278.475 MB -> 50.848 MB.
[2024-11-21T08:25:15.883Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T08:25:34.687Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T08:25:53.574Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T08:26:11.914Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T08:26:21.415Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T08:26:30.738Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T08:26:40.011Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T08:26:51.958Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T08:26:53.681Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-11-21T08:26:54.272Z] The best model improves the baseline by 14.52%.
[2024-11-21T08:26:54.760Z] Movies recommended for you:
[2024-11-21T08:26:54.760Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T08:26:54.760Z] There is no way to check that no silent failure occurred.
[2024-11-21T08:26:54.760Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (114886.276 ms) ======
[2024-11-21T08:26:54.760Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-21T08:26:54.760Z] GC before operation: completed in 283.783 ms, heap usage 641.622 MB -> 54.654 MB.
[2024-11-21T08:27:11.484Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T08:27:30.178Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T08:27:52.242Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T08:28:08.620Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T08:28:18.159Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T08:28:25.812Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T08:28:45.447Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T08:28:53.167Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T08:28:53.770Z] 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.
[2024-11-21T08:28:53.770Z] The best model improves the baseline by 14.52%.
[2024-11-21T08:28:55.623Z] Movies recommended for you:
[2024-11-21T08:28:55.623Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T08:28:55.623Z] There is no way to check that no silent failure occurred.
[2024-11-21T08:28:55.623Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (120335.027 ms) ======
[2024-11-21T08:28:55.623Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-21T08:28:55.623Z] GC before operation: completed in 202.402 ms, heap usage 954.570 MB -> 55.692 MB.
[2024-11-21T08:29:14.787Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T08:29:31.234Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T08:29:50.572Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T08:30:03.857Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T08:30:11.723Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T08:30:21.198Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T08:30:30.244Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T08:30:40.220Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T08:30:40.220Z] 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.
[2024-11-21T08:30:40.220Z] The best model improves the baseline by 14.52%.
[2024-11-21T08:30:41.751Z] Movies recommended for you:
[2024-11-21T08:30:41.751Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T08:30:41.751Z] There is no way to check that no silent failure occurred.
[2024-11-21T08:30:42.147Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (106257.896 ms) ======
[2024-11-21T08:30:42.147Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-21T08:30:42.147Z] GC before operation: completed in 429.895 ms, heap usage 107.481 MB -> 52.106 MB.
[2024-11-21T08:31:04.355Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T08:31:18.626Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T08:31:37.604Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T08:31:53.884Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T08:32:01.944Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T08:32:12.102Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T08:32:25.491Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T08:32:34.622Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T08:32:35.737Z] 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.
[2024-11-21T08:32:35.737Z] The best model improves the baseline by 14.52%.
[2024-11-21T08:32:36.408Z] Movies recommended for you:
[2024-11-21T08:32:36.408Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T08:32:36.408Z] There is no way to check that no silent failure occurred.
[2024-11-21T08:32:36.408Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (113815.730 ms) ======
[2024-11-21T08:32:36.408Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-21T08:32:36.926Z] GC before operation: completed in 902.428 ms, heap usage 442.269 MB -> 54.360 MB.
[2024-11-21T08:32:55.445Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T08:33:11.407Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T08:33:30.690Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T08:33:50.116Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T08:33:59.381Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T08:34:09.251Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T08:34:19.186Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T08:34:28.471Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T08:34:31.022Z] 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.
[2024-11-21T08:34:31.022Z] The best model improves the baseline by 14.52%.
[2024-11-21T08:34:31.607Z] Movies recommended for you:
[2024-11-21T08:34:31.607Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T08:34:31.607Z] There is no way to check that no silent failure occurred.
[2024-11-21T08:34:31.608Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (114391.459 ms) ======
[2024-11-21T08:34:31.608Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-21T08:34:31.608Z] GC before operation: completed in 207.101 ms, heap usage 189.114 MB -> 51.117 MB.
[2024-11-21T08:34:50.869Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T08:35:06.015Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T08:35:24.533Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T08:35:40.040Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T08:35:52.239Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T08:36:00.687Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T08:36:10.123Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T08:36:18.172Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T08:36:18.689Z] 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.
[2024-11-21T08:36:18.689Z] The best model improves the baseline by 14.52%.
[2024-11-21T08:36:19.147Z] Movies recommended for you:
[2024-11-21T08:36:19.147Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T08:36:19.147Z] There is no way to check that no silent failure occurred.
[2024-11-21T08:36:19.147Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (107734.924 ms) ======
[2024-11-21T08:36:24.808Z] -----------------------------------
[2024-11-21T08:36:24.808Z] renaissance-movie-lens_0_PASSED
[2024-11-21T08:36:24.808Z] -----------------------------------
[2024-11-21T08:36:24.808Z]
[2024-11-21T08:36:24.808Z] TEST TEARDOWN:
[2024-11-21T08:36:24.808Z] Nothing to be done for teardown.
[2024-11-21T08:36:24.808Z] renaissance-movie-lens_0 Finish Time: Thu Nov 21 00:36:23 2024 Epoch Time (ms): 1732178183684