renaissance-movie-lens_0
[2024-11-21T13:53:45.126Z] Running test renaissance-movie-lens_0 ...
[2024-11-21T13:53:45.126Z] ===============================================
[2024-11-21T13:53:45.126Z] renaissance-movie-lens_0 Start Time: Thu Nov 21 13:53:44 2024 Epoch Time (ms): 1732197224594
[2024-11-21T13:53:45.126Z] variation: NoOptions
[2024-11-21T13:53:45.126Z] JVM_OPTIONS:
[2024-11-21T13:53:45.126Z] { \
[2024-11-21T13:53:45.126Z] echo ""; echo "TEST SETUP:"; \
[2024-11-21T13:53:45.126Z] echo "Nothing to be done for setup."; \
[2024-11-21T13:53:45.126Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17321935947162/renaissance-movie-lens_0"; \
[2024-11-21T13:53:45.126Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17321935947162/renaissance-movie-lens_0"; \
[2024-11-21T13:53:45.126Z] echo ""; echo "TESTING:"; \
[2024-11-21T13:53:45.126Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/jdkbinary/j2sdk-image/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 "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17321935947162/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-21T13:53:45.126Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17321935947162/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-21T13:53:45.126Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-21T13:53:45.126Z] echo "Nothing to be done for teardown."; \
[2024-11-21T13:53:45.126Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17321935947162/TestTargetResult";
[2024-11-21T13:53:45.126Z]
[2024-11-21T13:53:45.126Z] TEST SETUP:
[2024-11-21T13:53:45.126Z] Nothing to be done for setup.
[2024-11-21T13:53:45.126Z]
[2024-11-21T13:53:45.126Z] TESTING:
[2024-11-21T13:53:54.649Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-21T13:54:02.846Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads.
[2024-11-21T13:54:16.716Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-21T13:54:18.987Z] Training: 60056, validation: 20285, test: 19854
[2024-11-21T13:54:18.987Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-21T13:54:18.987Z] GC before operation: completed in 650.678 ms, heap usage 111.173 MB -> 36.455 MB.
[2024-11-21T13:54:55.618Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T13:55:08.917Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T13:55:27.894Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T13:55:37.152Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T13:55:45.032Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T13:55:54.772Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T13:56:02.816Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T13:56:13.269Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T13:56:14.040Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T13:56:14.040Z] The best model improves the baseline by 14.34%.
[2024-11-21T13:56:14.896Z] Movies recommended for you:
[2024-11-21T13:56:14.896Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T13:56:14.896Z] There is no way to check that no silent failure occurred.
[2024-11-21T13:56:14.896Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (115719.342 ms) ======
[2024-11-21T13:56:14.896Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-21T13:56:15.608Z] GC before operation: completed in 571.432 ms, heap usage 227.151 MB -> 53.132 MB.
[2024-11-21T13:56:29.707Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T13:56:39.951Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T13:56:53.851Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T13:57:05.036Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T13:57:11.825Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T13:57:18.804Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T13:57:27.733Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T13:57:34.371Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T13:57:34.371Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T13:57:35.154Z] The best model improves the baseline by 14.34%.
[2024-11-21T13:57:35.154Z] Movies recommended for you:
[2024-11-21T13:57:35.154Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T13:57:35.154Z] There is no way to check that no silent failure occurred.
[2024-11-21T13:57:35.154Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (79811.333 ms) ======
[2024-11-21T13:57:35.154Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-21T13:57:37.530Z] GC before operation: completed in 1829.605 ms, heap usage 136.940 MB -> 48.369 MB.
[2024-11-21T13:57:51.535Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T13:58:04.913Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T13:58:17.152Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T13:58:25.436Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T13:58:33.681Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T13:58:42.255Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T13:58:49.046Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T13:58:55.427Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T13:58:57.049Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T13:58:57.049Z] The best model improves the baseline by 14.34%.
[2024-11-21T13:58:57.049Z] Movies recommended for you:
[2024-11-21T13:58:57.049Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T13:58:57.050Z] There is no way to check that no silent failure occurred.
[2024-11-21T13:58:57.050Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (79952.298 ms) ======
[2024-11-21T13:58:57.050Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-21T13:58:57.767Z] GC before operation: completed in 660.277 ms, heap usage 238.990 MB -> 48.727 MB.
[2024-11-21T13:59:09.426Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T13:59:23.262Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T13:59:34.718Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T13:59:44.116Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T13:59:50.787Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T13:59:57.755Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:00:04.937Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:00:10.029Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:00:10.860Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T14:00:10.860Z] The best model improves the baseline by 14.34%.
[2024-11-21T14:00:12.606Z] Movies recommended for you:
[2024-11-21T14:00:12.606Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:00:12.606Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:00:12.606Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (74331.365 ms) ======
[2024-11-21T14:00:12.606Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-21T14:00:12.606Z] GC before operation: completed in 516.261 ms, heap usage 60.842 MB -> 52.320 MB.
[2024-11-21T14:00:26.256Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:00:37.696Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:00:49.314Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:00:58.957Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:01:05.421Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:01:09.927Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:01:15.580Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:01:19.780Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:01:21.280Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T14:01:21.280Z] The best model improves the baseline by 14.34%.
[2024-11-21T14:01:21.280Z] Movies recommended for you:
[2024-11-21T14:01:21.280Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:01:21.280Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:01:21.280Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (68766.350 ms) ======
[2024-11-21T14:01:21.280Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-21T14:01:22.098Z] GC before operation: completed in 838.671 ms, heap usage 202.211 MB -> 49.187 MB.
[2024-11-21T14:01:33.780Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:01:41.972Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:01:55.585Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:02:05.527Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:02:10.874Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:02:15.740Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:02:21.221Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:02:25.436Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:02:25.436Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T14:02:26.225Z] The best model improves the baseline by 14.34%.
[2024-11-21T14:02:26.225Z] Movies recommended for you:
[2024-11-21T14:02:26.225Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:02:26.225Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:02:26.225Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (64031.708 ms) ======
[2024-11-21T14:02:26.225Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-21T14:02:26.917Z] GC before operation: completed in 397.784 ms, heap usage 189.029 MB -> 49.116 MB.
[2024-11-21T14:02:38.407Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:02:48.262Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:02:58.132Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:03:07.770Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:03:12.843Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:03:21.201Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:03:23.911Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:03:27.257Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:03:29.897Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T14:03:29.897Z] The best model improves the baseline by 14.34%.
[2024-11-21T14:03:29.897Z] Movies recommended for you:
[2024-11-21T14:03:29.897Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:03:29.897Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:03:29.897Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (63443.409 ms) ======
[2024-11-21T14:03:29.897Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-21T14:03:30.709Z] GC before operation: completed in 607.349 ms, heap usage 234.242 MB -> 49.425 MB.
[2024-11-21T14:03:40.056Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:03:50.411Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:03:59.904Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:04:06.356Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:04:12.851Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:04:15.828Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:04:20.163Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:04:27.501Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:04:28.360Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T14:04:28.360Z] The best model improves the baseline by 14.34%.
[2024-11-21T14:04:28.360Z] Movies recommended for you:
[2024-11-21T14:04:28.360Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:04:28.360Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:04:28.360Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (57365.011 ms) ======
[2024-11-21T14:04:28.360Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-21T14:04:28.360Z] GC before operation: completed in 356.956 ms, heap usage 186.974 MB -> 49.553 MB.
[2024-11-21T14:04:37.799Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:04:47.070Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:04:58.539Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:05:05.081Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:05:10.472Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:05:13.737Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:05:18.918Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:05:23.005Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:05:23.647Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T14:05:23.647Z] The best model improves the baseline by 14.34%.
[2024-11-21T14:05:24.375Z] Movies recommended for you:
[2024-11-21T14:05:24.375Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:05:24.375Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:05:24.375Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (55695.189 ms) ======
[2024-11-21T14:05:24.375Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-21T14:05:24.375Z] GC before operation: completed in 473.086 ms, heap usage 280.332 MB -> 50.790 MB.
[2024-11-21T14:05:33.832Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:05:40.614Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:05:49.984Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:05:57.682Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:06:01.835Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:06:05.159Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:06:10.652Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:06:14.962Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:06:16.703Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T14:06:16.703Z] The best model improves the baseline by 14.34%.
[2024-11-21T14:06:16.703Z] Movies recommended for you:
[2024-11-21T14:06:16.703Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:06:16.703Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:06:16.703Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (52215.250 ms) ======
[2024-11-21T14:06:16.703Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-21T14:06:17.425Z] GC before operation: completed in 300.080 ms, heap usage 193.970 MB -> 49.498 MB.
[2024-11-21T14:06:26.782Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:06:36.149Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:06:45.208Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:06:51.759Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:06:57.113Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:07:01.353Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:07:08.231Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:07:13.791Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:07:15.471Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T14:07:15.471Z] The best model improves the baseline by 14.34%.
[2024-11-21T14:07:15.471Z] Movies recommended for you:
[2024-11-21T14:07:15.471Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:07:15.471Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:07:15.471Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (58458.053 ms) ======
[2024-11-21T14:07:15.471Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-21T14:07:16.145Z] GC before operation: completed in 565.109 ms, heap usage 341.341 MB -> 52.665 MB.
[2024-11-21T14:07:27.255Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:07:33.545Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:07:43.315Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:07:52.910Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:07:57.250Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:08:01.348Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:08:09.382Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:08:15.002Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:08:15.708Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T14:08:15.708Z] The best model improves the baseline by 14.34%.
[2024-11-21T14:08:15.708Z] Movies recommended for you:
[2024-11-21T14:08:15.708Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:08:15.708Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:08:15.708Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (59641.599 ms) ======
[2024-11-21T14:08:15.708Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-21T14:08:16.425Z] GC before operation: completed in 548.329 ms, heap usage 154.456 MB -> 49.423 MB.
[2024-11-21T14:08:28.262Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:08:37.631Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:08:45.495Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:08:51.608Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:08:55.797Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:08:59.841Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:09:06.931Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:09:11.068Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:09:11.746Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T14:09:11.746Z] The best model improves the baseline by 14.34%.
[2024-11-21T14:09:12.384Z] Movies recommended for you:
[2024-11-21T14:09:12.384Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:09:12.384Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:09:12.384Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (55746.292 ms) ======
[2024-11-21T14:09:12.384Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-21T14:09:12.384Z] GC before operation: completed in 454.053 ms, heap usage 100.877 MB -> 51.239 MB.
[2024-11-21T14:09:25.617Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:09:33.492Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:09:41.463Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:09:46.576Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:09:50.809Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:09:54.734Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:09:59.085Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:10:04.492Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:10:05.189Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T14:10:05.189Z] The best model improves the baseline by 14.34%.
[2024-11-21T14:10:06.019Z] Movies recommended for you:
[2024-11-21T14:10:06.019Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:10:06.019Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:10:06.019Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (53353.019 ms) ======
[2024-11-21T14:10:06.019Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-21T14:10:06.684Z] GC before operation: completed in 661.189 ms, heap usage 119.093 MB -> 46.981 MB.
[2024-11-21T14:10:16.214Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:10:23.990Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:10:29.090Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:10:35.712Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:10:38.978Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:10:43.401Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:10:49.208Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:10:54.686Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:10:56.797Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T14:10:56.797Z] The best model improves the baseline by 14.34%.
[2024-11-21T14:10:56.797Z] Movies recommended for you:
[2024-11-21T14:10:56.797Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:10:56.797Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:10:56.797Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (50047.893 ms) ======
[2024-11-21T14:10:56.797Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-21T14:10:56.797Z] GC before operation: completed in 417.152 ms, heap usage 215.408 MB -> 47.125 MB.
[2024-11-21T14:11:04.781Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:11:11.933Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:11:21.574Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:11:29.440Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:11:34.804Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:11:41.558Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:11:47.706Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:11:51.859Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:11:52.603Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T14:11:52.603Z] The best model improves the baseline by 14.34%.
[2024-11-21T14:11:53.415Z] Movies recommended for you:
[2024-11-21T14:11:53.415Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:11:53.415Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:11:53.415Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (56080.613 ms) ======
[2024-11-21T14:11:53.415Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-21T14:11:53.415Z] GC before operation: completed in 510.754 ms, heap usage 80.644 MB -> 48.287 MB.
[2024-11-21T14:12:02.203Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:12:11.917Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:12:17.188Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:12:23.447Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:12:27.408Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:12:30.639Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:12:34.726Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:12:38.891Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:12:39.686Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T14:12:39.686Z] The best model improves the baseline by 14.34%.
[2024-11-21T14:12:40.439Z] Movies recommended for you:
[2024-11-21T14:12:40.439Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:12:40.439Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:12:40.439Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (46726.861 ms) ======
[2024-11-21T14:12:40.439Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-21T14:12:41.105Z] GC before operation: completed in 533.293 ms, heap usage 236.978 MB -> 47.480 MB.
[2024-11-21T14:12:50.502Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:12:57.064Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:13:05.751Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:13:13.761Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:13:17.006Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:13:21.043Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:13:27.974Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:13:30.319Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:13:31.059Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T14:13:31.059Z] The best model improves the baseline by 14.34%.
[2024-11-21T14:13:31.059Z] Movies recommended for you:
[2024-11-21T14:13:31.059Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:13:31.059Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:13:31.059Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (50284.232 ms) ======
[2024-11-21T14:13:31.059Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-21T14:13:31.713Z] GC before operation: completed in 626.361 ms, heap usage 58.372 MB -> 50.241 MB.
[2024-11-21T14:13:38.045Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:13:47.805Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:13:54.291Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:14:00.802Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:14:05.011Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:14:08.445Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:14:12.689Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:14:16.937Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:14:17.693Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T14:14:17.693Z] The best model improves the baseline by 14.34%.
[2024-11-21T14:14:18.368Z] Movies recommended for you:
[2024-11-21T14:14:18.368Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:14:18.368Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:14:18.368Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (46219.370 ms) ======
[2024-11-21T14:14:18.368Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-21T14:14:18.368Z] GC before operation: completed in 407.523 ms, heap usage 244.358 MB -> 47.148 MB.
[2024-11-21T14:14:26.339Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-21T14:14:37.669Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-21T14:14:44.216Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-21T14:14:51.098Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-21T14:14:56.542Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-21T14:14:59.956Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-21T14:15:03.945Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-21T14:15:07.486Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-21T14:15:08.267Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-21T14:15:09.029Z] The best model improves the baseline by 14.34%.
[2024-11-21T14:15:09.029Z] Movies recommended for you:
[2024-11-21T14:15:09.029Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-21T14:15:09.029Z] There is no way to check that no silent failure occurred.
[2024-11-21T14:15:09.029Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (50389.454 ms) ======
[2024-11-21T14:15:09.748Z] -----------------------------------
[2024-11-21T14:15:09.748Z] renaissance-movie-lens_0_PASSED
[2024-11-21T14:15:09.748Z] -----------------------------------
[2024-11-21T14:15:09.748Z]
[2024-11-21T14:15:09.748Z] TEST TEARDOWN:
[2024-11-21T14:15:09.748Z] Nothing to be done for teardown.
[2024-11-21T14:15:09.748Z] renaissance-movie-lens_0 Finish Time: Thu Nov 21 14:15:09 2024 Epoch Time (ms): 1732198509683