renaissance-movie-lens_0
[2024-11-24T21:08:41.965Z] Running test renaissance-movie-lens_0 ...
[2024-11-24T21:08:41.965Z] ===============================================
[2024-11-24T21:08:41.965Z] renaissance-movie-lens_0 Start Time: Sun Nov 24 21:08:41 2024 Epoch Time (ms): 1732482521394
[2024-11-24T21:08:41.965Z] variation: NoOptions
[2024-11-24T21:08:41.965Z] JVM_OPTIONS:
[2024-11-24T21:08:41.965Z] { \
[2024-11-24T21:08:41.965Z] echo ""; echo "TEST SETUP:"; \
[2024-11-24T21:08:41.965Z] echo "Nothing to be done for setup."; \
[2024-11-24T21:08:41.965Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17324810153759/renaissance-movie-lens_0"; \
[2024-11-24T21:08:41.965Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17324810153759/renaissance-movie-lens_0"; \
[2024-11-24T21:08:41.965Z] echo ""; echo "TESTING:"; \
[2024-11-24T21:08:41.965Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-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_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17324810153759/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-24T21:08:41.965Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17324810153759/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-24T21:08:41.965Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-24T21:08:41.965Z] echo "Nothing to be done for teardown."; \
[2024-11-24T21:08:41.965Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17324810153759/TestTargetResult";
[2024-11-24T21:08:41.965Z]
[2024-11-24T21:08:41.965Z] TEST SETUP:
[2024-11-24T21:08:41.965Z] Nothing to be done for setup.
[2024-11-24T21:08:41.965Z]
[2024-11-24T21:08:41.965Z] TESTING:
[2024-11-24T21:08:47.777Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-24T21:08:53.578Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-11-24T21:08:59.526Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-24T21:09:00.347Z] Training: 60056, validation: 20285, test: 19854
[2024-11-24T21:09:00.347Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-24T21:09:00.347Z] GC before operation: completed in 215.851 ms, heap usage 68.414 MB -> 36.998 MB.
[2024-11-24T21:09:19.802Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-24T21:09:30.130Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-24T21:09:49.441Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-24T21:09:59.732Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-24T21:10:06.970Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-24T21:10:12.865Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-24T21:10:18.660Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-24T21:10:23.352Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-24T21:10:25.049Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-24T21:10:25.049Z] The best model improves the baseline by 14.52%.
[2024-11-24T21:10:25.881Z] Movies recommended for you:
[2024-11-24T21:10:25.881Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-24T21:10:25.881Z] There is no way to check that no silent failure occurred.
[2024-11-24T21:10:25.881Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (84929.025 ms) ======
[2024-11-24T21:10:25.881Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-24T21:10:25.881Z] GC before operation: completed in 273.647 ms, heap usage 192.563 MB -> 51.041 MB.
[2024-11-24T21:10:36.164Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-24T21:10:46.780Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-24T21:10:55.440Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-24T21:11:05.750Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-24T21:11:10.504Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-24T21:11:15.205Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-24T21:11:19.905Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-24T21:11:24.615Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-24T21:11:25.439Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-24T21:11:26.258Z] The best model improves the baseline by 14.52%.
[2024-11-24T21:11:26.258Z] Movies recommended for you:
[2024-11-24T21:11:26.258Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-24T21:11:26.258Z] There is no way to check that no silent failure occurred.
[2024-11-24T21:11:26.258Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (60611.979 ms) ======
[2024-11-24T21:11:26.258Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-24T21:11:27.075Z] GC before operation: completed in 402.991 ms, heap usage 121.570 MB -> 49.447 MB.
[2024-11-24T21:11:37.331Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-24T21:11:48.137Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-24T21:11:58.429Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-24T21:12:07.087Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-24T21:12:17.289Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-24T21:12:25.333Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-24T21:12:33.380Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-24T21:12:40.521Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-24T21:12:40.521Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-24T21:12:40.521Z] The best model improves the baseline by 14.52%.
[2024-11-24T21:12:42.057Z] Movies recommended for you:
[2024-11-24T21:12:42.057Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-24T21:12:42.057Z] There is no way to check that no silent failure occurred.
[2024-11-24T21:12:42.057Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (74116.490 ms) ======
[2024-11-24T21:12:42.057Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-24T21:12:42.057Z] GC before operation: completed in 262.382 ms, heap usage 423.247 MB -> 53.282 MB.
[2024-11-24T21:12:58.540Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-24T21:13:10.755Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-24T21:13:27.398Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-24T21:13:33.312Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-24T21:13:38.138Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-24T21:13:44.001Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-24T21:13:48.361Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-24T21:13:53.036Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-24T21:13:53.036Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-24T21:13:53.036Z] The best model improves the baseline by 14.52%.
[2024-11-24T21:13:53.036Z] Movies recommended for you:
[2024-11-24T21:13:53.036Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-24T21:13:53.036Z] There is no way to check that no silent failure occurred.
[2024-11-24T21:13:53.036Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (72042.785 ms) ======
[2024-11-24T21:13:53.036Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-24T21:13:53.036Z] GC before operation: completed in 121.183 ms, heap usage 435.101 MB -> 53.574 MB.
[2024-11-24T21:14:00.159Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-24T21:14:10.257Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-24T21:14:14.799Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-24T21:14:31.307Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-24T21:14:38.374Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-24T21:14:46.999Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-24T21:14:57.081Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-24T21:15:04.764Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-24T21:15:05.565Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-24T21:15:05.565Z] The best model improves the baseline by 14.52%.
[2024-11-24T21:15:05.565Z] Movies recommended for you:
[2024-11-24T21:15:05.565Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-24T21:15:05.565Z] There is no way to check that no silent failure occurred.
[2024-11-24T21:15:05.565Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (72348.354 ms) ======
[2024-11-24T21:15:05.565Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-24T21:15:06.376Z] GC before operation: completed in 287.237 ms, heap usage 152.004 MB -> 50.513 MB.
[2024-11-24T21:15:16.431Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-24T21:15:28.262Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-24T21:15:42.345Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-24T21:15:52.451Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-24T21:15:59.698Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-24T21:16:08.843Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-24T21:16:17.866Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-24T21:16:25.041Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-24T21:16:26.720Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-24T21:16:26.720Z] The best model improves the baseline by 14.52%.
[2024-11-24T21:16:27.517Z] Movies recommended for you:
[2024-11-24T21:16:27.517Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-24T21:16:27.517Z] There is no way to check that no silent failure occurred.
[2024-11-24T21:16:27.517Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (81413.414 ms) ======
[2024-11-24T21:16:27.517Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-24T21:16:27.517Z] GC before operation: completed in 451.280 ms, heap usage 156.851 MB -> 50.288 MB.
[2024-11-24T21:16:43.958Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-24T21:16:56.126Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-24T21:17:08.206Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-24T21:17:22.928Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-24T21:17:28.652Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-24T21:17:34.401Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-24T21:17:40.182Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-24T21:17:48.729Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-24T21:17:50.412Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-24T21:17:50.412Z] The best model improves the baseline by 14.52%.
[2024-11-24T21:17:50.412Z] Movies recommended for you:
[2024-11-24T21:17:50.412Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-24T21:17:50.412Z] There is no way to check that no silent failure occurred.
[2024-11-24T21:17:50.412Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (82848.350 ms) ======
[2024-11-24T21:17:50.412Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-24T21:17:51.218Z] GC before operation: completed in 329.402 ms, heap usage 417.096 MB -> 54.033 MB.
[2024-11-24T21:17:59.946Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-24T21:18:14.330Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-24T21:18:25.283Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-24T21:18:37.521Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-24T21:18:43.626Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-24T21:18:50.803Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-24T21:18:56.733Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-24T21:19:02.724Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-24T21:19:05.345Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-24T21:19:05.345Z] The best model improves the baseline by 14.52%.
[2024-11-24T21:19:06.183Z] Movies recommended for you:
[2024-11-24T21:19:06.183Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-24T21:19:06.183Z] There is no way to check that no silent failure occurred.
[2024-11-24T21:19:06.183Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (75109.055 ms) ======
[2024-11-24T21:19:06.183Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-24T21:19:06.183Z] GC before operation: completed in 294.396 ms, heap usage 133.783 MB -> 50.693 MB.
[2024-11-24T21:19:22.788Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-24T21:19:33.441Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-24T21:19:43.799Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-24T21:19:55.908Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-24T21:20:04.631Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-24T21:20:14.771Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-24T21:20:23.345Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-24T21:20:30.471Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-24T21:20:30.471Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-24T21:20:30.471Z] The best model improves the baseline by 14.52%.
[2024-11-24T21:20:31.304Z] Movies recommended for you:
[2024-11-24T21:20:31.304Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-24T21:20:31.304Z] There is no way to check that no silent failure occurred.
[2024-11-24T21:20:31.304Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (84658.115 ms) ======
[2024-11-24T21:20:31.304Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-24T21:20:31.304Z] GC before operation: completed in 346.964 ms, heap usage 147.468 MB -> 51.157 MB.
[2024-11-24T21:20:45.723Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-24T21:20:59.930Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-24T21:21:16.493Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-24T21:21:33.066Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-24T21:21:41.737Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-24T21:21:54.474Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-24T21:22:04.879Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-24T21:22:13.475Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-24T21:22:15.176Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-24T21:22:15.176Z] The best model improves the baseline by 14.52%.
[2024-11-24T21:22:16.000Z] Movies recommended for you:
[2024-11-24T21:22:16.000Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-24T21:22:16.000Z] There is no way to check that no silent failure occurred.
[2024-11-24T21:22:16.000Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (104361.595 ms) ======
[2024-11-24T21:22:16.000Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-24T21:22:16.000Z] GC before operation: completed in 490.862 ms, heap usage 128.186 MB -> 50.677 MB.
[2024-11-24T21:22:34.123Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-24T21:22:53.743Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-24T21:23:08.852Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-24T21:23:21.069Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-24T21:23:31.527Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-24T21:23:38.992Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-24T21:23:47.829Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-24T21:23:56.539Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-24T21:23:57.337Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-24T21:23:57.337Z] The best model improves the baseline by 14.52%.
[2024-11-24T21:23:58.170Z] Movies recommended for you:
[2024-11-24T21:23:58.171Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-24T21:23:58.171Z] There is no way to check that no silent failure occurred.
[2024-11-24T21:23:58.171Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (101624.467 ms) ======
[2024-11-24T21:23:58.171Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-24T21:23:58.171Z] GC before operation: completed in 509.560 ms, heap usage 183.326 MB -> 50.589 MB.
[2024-11-24T21:24:14.947Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-24T21:24:32.398Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-24T21:24:49.297Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-24T21:25:01.606Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-24T21:25:10.306Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-24T21:25:19.160Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-24T21:25:29.532Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-24T21:25:40.614Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-24T21:25:42.409Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-24T21:25:43.257Z] The best model improves the baseline by 14.52%.
[2024-11-24T21:25:43.257Z] Movies recommended for you:
[2024-11-24T21:25:43.257Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-24T21:25:43.257Z] There is no way to check that no silent failure occurred.
[2024-11-24T21:25:43.257Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (104805.834 ms) ======
[2024-11-24T21:25:43.257Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-24T21:25:44.113Z] GC before operation: completed in 546.811 ms, heap usage 181.301 MB -> 50.740 MB.
[2024-11-24T21:26:01.257Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-24T21:26:15.722Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-24T21:26:32.574Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-24T21:26:47.221Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-24T21:26:57.780Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-24T21:27:07.324Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-24T21:27:19.549Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-24T21:27:31.614Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-24T21:27:33.297Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-24T21:27:33.297Z] The best model improves the baseline by 14.52%.
[2024-11-24T21:27:34.112Z] Movies recommended for you:
[2024-11-24T21:27:34.112Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-24T21:27:34.112Z] There is no way to check that no silent failure occurred.
[2024-11-24T21:27:34.112Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (110089.738 ms) ======
[2024-11-24T21:27:34.112Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-24T21:27:34.112Z] GC before operation: completed in 484.452 ms, heap usage 183.453 MB -> 50.880 MB.
[2024-11-24T21:27:53.702Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-24T21:28:10.623Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-24T21:28:30.887Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-24T21:28:47.661Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-24T21:28:59.822Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-24T21:29:10.110Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-24T21:29:22.471Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-24T21:29:33.066Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-24T21:29:35.027Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-24T21:29:35.027Z] The best model improves the baseline by 14.52%.
[2024-11-24T21:29:35.027Z] Movies recommended for you:
[2024-11-24T21:29:35.027Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-24T21:29:35.027Z] There is no way to check that no silent failure occurred.
[2024-11-24T21:29:35.027Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (120982.681 ms) ======
[2024-11-24T21:29:35.027Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-24T21:29:35.827Z] GC before operation: completed in 530.018 ms, heap usage 214.088 MB -> 50.616 MB.
[2024-11-24T21:29:55.232Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-24T21:30:14.544Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-24T21:30:37.231Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-24T21:30:53.955Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-24T21:31:03.214Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-24T21:31:13.720Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-24T21:31:24.109Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-24T21:31:32.721Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-24T21:31:35.326Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-24T21:31:35.326Z] The best model improves the baseline by 14.52%.
[2024-11-24T21:31:36.132Z] Movies recommended for you:
[2024-11-24T21:31:36.132Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-24T21:31:36.132Z] There is no way to check that no silent failure occurred.
[2024-11-24T21:31:36.132Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (120098.215 ms) ======
[2024-11-24T21:31:36.132Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-24T21:31:36.950Z] GC before operation: completed in 506.078 ms, heap usage 180.309 MB -> 50.808 MB.
[2024-11-24T21:31:56.646Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-24T21:32:14.063Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-24T21:32:30.683Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-24T21:32:47.452Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-24T21:32:57.960Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-24T21:33:10.301Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-24T21:33:22.582Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-24T21:33:33.559Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-24T21:33:34.411Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-24T21:33:34.411Z] The best model improves the baseline by 14.52%.
[2024-11-24T21:33:35.250Z] Movies recommended for you:
[2024-11-24T21:33:35.250Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-24T21:33:35.250Z] There is no way to check that no silent failure occurred.
[2024-11-24T21:33:35.250Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (118717.820 ms) ======
[2024-11-24T21:33:35.250Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-24T21:33:36.089Z] GC before operation: completed in 721.908 ms, heap usage 432.400 MB -> 52.186 MB.
[2024-11-24T21:33:55.672Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-24T21:34:15.083Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-24T21:34:34.441Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-24T21:34:53.745Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-24T21:35:04.800Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-24T21:35:16.648Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-24T21:35:26.804Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-24T21:35:38.772Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-24T21:35:39.564Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-24T21:35:40.408Z] The best model improves the baseline by 14.52%.
[2024-11-24T21:35:41.222Z] Movies recommended for you:
[2024-11-24T21:35:41.222Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-24T21:35:41.222Z] There is no way to check that no silent failure occurred.
[2024-11-24T21:35:41.222Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (124871.719 ms) ======
[2024-11-24T21:35:41.222Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-24T21:35:41.222Z] GC before operation: completed in 654.511 ms, heap usage 123.258 MB -> 48.898 MB.
[2024-11-24T21:36:03.542Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-24T21:36:23.298Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-24T21:36:42.469Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-24T21:37:01.761Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-24T21:37:12.121Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-24T21:37:24.222Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-24T21:37:36.953Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-24T21:37:46.957Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-24T21:37:49.464Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-24T21:37:49.464Z] The best model improves the baseline by 14.52%.
[2024-11-24T21:37:50.238Z] Movies recommended for you:
[2024-11-24T21:37:50.238Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-24T21:37:50.238Z] There is no way to check that no silent failure occurred.
[2024-11-24T21:37:50.238Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (128356.578 ms) ======
[2024-11-24T21:37:50.238Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-24T21:37:50.238Z] GC before operation: completed in 542.402 ms, heap usage 181.667 MB -> 48.464 MB.
[2024-11-24T21:38:06.604Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-24T21:38:22.986Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-24T21:38:42.051Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-24T21:38:58.961Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-24T21:39:10.925Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-24T21:39:21.143Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-24T21:39:31.412Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-24T21:39:39.951Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-24T21:39:41.621Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-24T21:39:41.621Z] The best model improves the baseline by 14.52%.
[2024-11-24T21:39:41.621Z] Movies recommended for you:
[2024-11-24T21:39:41.621Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-24T21:39:41.621Z] There is no way to check that no silent failure occurred.
[2024-11-24T21:39:41.621Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (111231.051 ms) ======
[2024-11-24T21:39:41.621Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-24T21:39:42.404Z] GC before operation: completed in 477.386 ms, heap usage 398.178 MB -> 51.044 MB.
[2024-11-24T21:39:58.908Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-24T21:40:15.471Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-24T21:40:31.757Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-24T21:40:45.672Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-24T21:40:55.783Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-24T21:41:04.380Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-24T21:41:12.826Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-24T21:41:23.723Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-24T21:41:25.508Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-11-24T21:41:25.508Z] The best model improves the baseline by 14.52%.
[2024-11-24T21:41:26.347Z] Movies recommended for you:
[2024-11-24T21:41:26.347Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-24T21:41:26.347Z] There is no way to check that no silent failure occurred.
[2024-11-24T21:41:26.347Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (104096.524 ms) ======
[2024-11-24T21:41:29.061Z] -----------------------------------
[2024-11-24T21:41:29.061Z] renaissance-movie-lens_0_PASSED
[2024-11-24T21:41:29.061Z] -----------------------------------
[2024-11-24T21:41:29.061Z]
[2024-11-24T21:41:29.061Z] TEST TEARDOWN:
[2024-11-24T21:41:29.061Z] Nothing to be done for teardown.
[2024-11-24T21:41:29.061Z] renaissance-movie-lens_0 Finish Time: Sun Nov 24 21:41:28 2024 Epoch Time (ms): 1732484488856