renaissance-movie-lens_0
[2024-08-02T02:21:08.689Z] Running test renaissance-movie-lens_0 ...
[2024-08-02T02:21:08.689Z] ===============================================
[2024-08-02T02:21:08.689Z] renaissance-movie-lens_0 Start Time: Fri Aug 2 02:21:08 2024 Epoch Time (ms): 1722565268505
[2024-08-02T02:21:08.689Z] variation: NoOptions
[2024-08-02T02:21:08.689Z] JVM_OPTIONS:
[2024-08-02T02:21:08.689Z] { \
[2024-08-02T02:21:08.689Z] echo ""; echo "TEST SETUP:"; \
[2024-08-02T02:21:08.689Z] echo "Nothing to be done for setup."; \
[2024-08-02T02:21:08.689Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17225640756604/renaissance-movie-lens_0"; \
[2024-08-02T02:21:08.689Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17225640756604/renaissance-movie-lens_0"; \
[2024-08-02T02:21:08.689Z] echo ""; echo "TESTING:"; \
[2024-08-02T02:21:08.689Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux_testList_0/jdkbinary/j2sdk-image/bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17225640756604/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-02T02:21:08.689Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17225640756604/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-02T02:21:08.689Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-02T02:21:08.689Z] echo "Nothing to be done for teardown."; \
[2024-08-02T02:21:08.689Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17225640756604/TestTargetResult";
[2024-08-02T02:21:08.689Z]
[2024-08-02T02:21:08.689Z] TEST SETUP:
[2024-08-02T02:21:08.689Z] Nothing to be done for setup.
[2024-08-02T02:21:08.689Z]
[2024-08-02T02:21:08.689Z] TESTING:
[2024-08-02T02:21:12.793Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-02T02:21:16.887Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2024-08-02T02:21:23.673Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-02T02:21:23.673Z] Training: 60056, validation: 20285, test: 19854
[2024-08-02T02:21:23.673Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-02T02:21:23.673Z] GC before operation: completed in 259.019 ms, heap usage 240.303 MB -> 29.341 MB.
[2024-08-02T02:21:33.314Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T02:21:38.637Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T02:21:43.982Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T02:21:48.094Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T02:21:51.077Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T02:21:53.013Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T02:21:56.004Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T02:21:57.944Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T02:21:58.885Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-08-02T02:21:58.885Z] The best model improves the baseline by 14.43%.
[2024-08-02T02:21:58.885Z] Movies recommended for you:
[2024-08-02T02:21:58.885Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T02:21:58.885Z] There is no way to check that no silent failure occurred.
[2024-08-02T02:21:58.885Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (35292.135 ms) ======
[2024-08-02T02:21:58.885Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-02T02:21:59.828Z] GC before operation: completed in 354.164 ms, heap usage 515.490 MB -> 44.281 MB.
[2024-08-02T02:22:02.814Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T02:22:06.927Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T02:22:11.042Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T02:22:14.036Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T02:22:17.026Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T02:22:18.963Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T02:22:21.981Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T02:22:23.917Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T02:22:25.563Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-08-02T02:22:25.564Z] The best model improves the baseline by 14.43%.
[2024-08-02T02:22:25.564Z] Movies recommended for you:
[2024-08-02T02:22:25.564Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T02:22:25.564Z] There is no way to check that no silent failure occurred.
[2024-08-02T02:22:25.564Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (25434.306 ms) ======
[2024-08-02T02:22:25.564Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-02T02:22:25.564Z] GC before operation: completed in 329.084 ms, heap usage 1005.442 MB -> 51.043 MB.
[2024-08-02T02:22:28.562Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T02:22:32.681Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T02:22:36.828Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T02:22:39.806Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T02:22:41.741Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T02:22:43.676Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T02:22:45.611Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T02:22:47.547Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T02:22:48.491Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-08-02T02:22:48.491Z] The best model improves the baseline by 14.43%.
[2024-08-02T02:22:48.491Z] Movies recommended for you:
[2024-08-02T02:22:48.491Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T02:22:48.491Z] There is no way to check that no silent failure occurred.
[2024-08-02T02:22:48.491Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (23303.426 ms) ======
[2024-08-02T02:22:48.491Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-02T02:22:48.491Z] GC before operation: completed in 271.708 ms, heap usage 831.133 MB -> 50.760 MB.
[2024-08-02T02:22:52.611Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T02:22:55.596Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T02:22:58.587Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T02:23:01.573Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T02:23:03.504Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T02:23:06.487Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T02:23:08.494Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T02:23:10.426Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T02:23:10.426Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-08-02T02:23:10.426Z] The best model improves the baseline by 14.43%.
[2024-08-02T02:23:11.365Z] Movies recommended for you:
[2024-08-02T02:23:11.365Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T02:23:11.365Z] There is no way to check that no silent failure occurred.
[2024-08-02T02:23:11.365Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (22298.111 ms) ======
[2024-08-02T02:23:11.365Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-02T02:23:11.365Z] GC before operation: completed in 260.274 ms, heap usage 675.274 MB -> 50.508 MB.
[2024-08-02T02:23:14.348Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T02:23:18.483Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T02:23:21.508Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T02:23:24.491Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T02:23:26.430Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T02:23:28.363Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T02:23:31.374Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T02:23:33.306Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T02:23:33.306Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-08-02T02:23:33.306Z] The best model improves the baseline by 14.43%.
[2024-08-02T02:23:33.306Z] Movies recommended for you:
[2024-08-02T02:23:33.306Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T02:23:33.306Z] There is no way to check that no silent failure occurred.
[2024-08-02T02:23:33.306Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (22285.683 ms) ======
[2024-08-02T02:23:33.306Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-02T02:23:34.256Z] GC before operation: completed in 265.812 ms, heap usage 728.715 MB -> 50.881 MB.
[2024-08-02T02:23:37.246Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T02:23:40.230Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T02:23:44.351Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T02:23:47.328Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T02:23:49.258Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T02:23:51.185Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T02:23:53.119Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T02:23:55.050Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T02:23:55.992Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-08-02T02:23:55.992Z] The best model improves the baseline by 14.43%.
[2024-08-02T02:23:55.992Z] Movies recommended for you:
[2024-08-02T02:23:55.992Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T02:23:55.992Z] There is no way to check that no silent failure occurred.
[2024-08-02T02:23:55.992Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (21865.389 ms) ======
[2024-08-02T02:23:55.992Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-02T02:23:55.992Z] GC before operation: completed in 245.212 ms, heap usage 770.405 MB -> 50.830 MB.
[2024-08-02T02:23:58.975Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T02:24:02.314Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T02:24:05.326Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T02:24:09.455Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T02:24:11.430Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T02:24:13.377Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T02:24:15.312Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T02:24:17.247Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T02:24:17.247Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-08-02T02:24:18.188Z] The best model improves the baseline by 14.43%.
[2024-08-02T02:24:18.188Z] Movies recommended for you:
[2024-08-02T02:24:18.188Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T02:24:18.188Z] There is no way to check that no silent failure occurred.
[2024-08-02T02:24:18.188Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (21920.986 ms) ======
[2024-08-02T02:24:18.188Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-02T02:24:18.188Z] GC before operation: completed in 245.403 ms, heap usage 707.133 MB -> 50.653 MB.
[2024-08-02T02:24:21.170Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T02:24:24.152Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T02:24:28.257Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T02:24:31.237Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T02:24:33.166Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T02:24:35.097Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T02:24:37.028Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T02:24:38.989Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T02:24:39.932Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-08-02T02:24:39.932Z] The best model improves the baseline by 14.43%.
[2024-08-02T02:24:39.932Z] Movies recommended for you:
[2024-08-02T02:24:39.932Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T02:24:39.932Z] There is no way to check that no silent failure occurred.
[2024-08-02T02:24:39.932Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (21670.679 ms) ======
[2024-08-02T02:24:39.932Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-02T02:24:39.932Z] GC before operation: completed in 234.516 ms, heap usage 729.534 MB -> 51.166 MB.
[2024-08-02T02:24:42.913Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T02:24:45.908Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T02:24:50.010Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T02:24:52.990Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T02:24:54.919Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T02:24:56.848Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T02:24:58.780Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T02:25:01.769Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T02:25:01.770Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-08-02T02:25:01.770Z] The best model improves the baseline by 14.43%.
[2024-08-02T02:25:01.770Z] Movies recommended for you:
[2024-08-02T02:25:01.770Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T02:25:01.770Z] There is no way to check that no silent failure occurred.
[2024-08-02T02:25:01.770Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (21854.685 ms) ======
[2024-08-02T02:25:01.770Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-02T02:25:01.770Z] GC before operation: completed in 239.724 ms, heap usage 664.402 MB -> 50.743 MB.
[2024-08-02T02:25:05.870Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T02:25:08.853Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T02:25:11.833Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T02:25:14.812Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T02:25:16.740Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T02:25:18.671Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T02:25:21.655Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T02:25:23.584Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T02:25:23.584Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-08-02T02:25:23.584Z] The best model improves the baseline by 14.43%.
[2024-08-02T02:25:23.584Z] Movies recommended for you:
[2024-08-02T02:25:23.584Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T02:25:23.584Z] There is no way to check that no silent failure occurred.
[2024-08-02T02:25:23.584Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (21671.836 ms) ======
[2024-08-02T02:25:23.584Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-02T02:25:24.525Z] GC before operation: completed in 269.984 ms, heap usage 733.315 MB -> 51.159 MB.
[2024-08-02T02:25:27.506Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T02:25:30.486Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T02:25:34.173Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T02:25:37.157Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T02:25:39.088Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T02:25:41.017Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T02:25:42.947Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T02:25:44.877Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T02:25:44.877Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-08-02T02:25:44.877Z] The best model improves the baseline by 14.43%.
[2024-08-02T02:25:45.819Z] Movies recommended for you:
[2024-08-02T02:25:45.819Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T02:25:45.819Z] There is no way to check that no silent failure occurred.
[2024-08-02T02:25:45.819Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (21257.375 ms) ======
[2024-08-02T02:25:45.819Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-02T02:25:45.819Z] GC before operation: completed in 242.905 ms, heap usage 747.368 MB -> 50.847 MB.
[2024-08-02T02:25:48.798Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T02:25:51.778Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T02:25:54.760Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T02:25:57.740Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T02:25:59.670Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T02:26:02.654Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T02:26:04.583Z] RMSE (validation) = 0.9275717388537592 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T02:26:06.514Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T02:26:06.514Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-08-02T02:26:06.514Z] The best model improves the baseline by 14.43%.
[2024-08-02T02:26:06.514Z] Movies recommended for you:
[2024-08-02T02:26:06.514Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T02:26:06.514Z] There is no way to check that no silent failure occurred.
[2024-08-02T02:26:06.514Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (21278.570 ms) ======
[2024-08-02T02:26:06.514Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-02T02:26:07.454Z] GC before operation: completed in 216.806 ms, heap usage 725.605 MB -> 50.889 MB.
[2024-08-02T02:26:10.526Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T02:26:13.508Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T02:26:16.497Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T02:26:19.480Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T02:26:21.592Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T02:26:23.524Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T02:26:27.562Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T02:26:27.562Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T02:26:28.502Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-08-02T02:26:28.503Z] The best model improves the baseline by 14.43%.
[2024-08-02T02:26:28.503Z] Movies recommended for you:
[2024-08-02T02:26:28.503Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T02:26:28.503Z] There is no way to check that no silent failure occurred.
[2024-08-02T02:26:28.503Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (21577.519 ms) ======
[2024-08-02T02:26:28.503Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-02T02:26:28.503Z] GC before operation: completed in 217.980 ms, heap usage 799.310 MB -> 51.364 MB.
[2024-08-02T02:26:32.613Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T02:26:35.596Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T02:26:38.583Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T02:26:41.567Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T02:26:43.506Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T02:26:45.439Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T02:26:47.378Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T02:26:49.312Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T02:26:50.255Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-08-02T02:26:50.255Z] The best model improves the baseline by 14.43%.
[2024-08-02T02:26:50.255Z] Movies recommended for you:
[2024-08-02T02:26:50.255Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T02:26:50.255Z] There is no way to check that no silent failure occurred.
[2024-08-02T02:26:50.255Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (21265.825 ms) ======
[2024-08-02T02:26:50.255Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-02T02:26:50.255Z] GC before operation: completed in 213.113 ms, heap usage 663.408 MB -> 50.770 MB.
[2024-08-02T02:26:53.239Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T02:26:56.223Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T02:27:00.358Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T02:27:03.340Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T02:27:05.274Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T02:27:07.206Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T02:27:09.167Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T02:27:11.500Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T02:27:11.500Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-08-02T02:27:11.500Z] The best model improves the baseline by 14.43%.
[2024-08-02T02:27:11.500Z] Movies recommended for you:
[2024-08-02T02:27:11.500Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T02:27:11.500Z] There is no way to check that no silent failure occurred.
[2024-08-02T02:27:11.500Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (21091.382 ms) ======
[2024-08-02T02:27:11.500Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-02T02:27:11.500Z] GC before operation: completed in 241.801 ms, heap usage 714.867 MB -> 51.037 MB.
[2024-08-02T02:27:14.482Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T02:27:17.551Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T02:27:21.664Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T02:27:24.652Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T02:27:26.589Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T02:27:28.521Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T02:27:30.456Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T02:27:32.388Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T02:27:32.388Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-08-02T02:27:33.330Z] The best model improves the baseline by 14.43%.
[2024-08-02T02:27:33.330Z] Movies recommended for you:
[2024-08-02T02:27:33.330Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T02:27:33.330Z] There is no way to check that no silent failure occurred.
[2024-08-02T02:27:33.330Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (21349.694 ms) ======
[2024-08-02T02:27:33.330Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-02T02:27:33.330Z] GC before operation: completed in 221.769 ms, heap usage 748.377 MB -> 51.293 MB.
[2024-08-02T02:27:36.313Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T02:27:39.297Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T02:27:42.281Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T02:27:45.268Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T02:27:47.203Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T02:27:49.134Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T02:27:51.068Z] RMSE (validation) = 0.9275717388537592 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T02:27:54.054Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T02:27:54.054Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-08-02T02:27:54.054Z] The best model improves the baseline by 14.43%.
[2024-08-02T02:27:54.054Z] Movies recommended for you:
[2024-08-02T02:27:54.054Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T02:27:54.054Z] There is no way to check that no silent failure occurred.
[2024-08-02T02:27:54.054Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (20863.987 ms) ======
[2024-08-02T02:27:54.054Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-02T02:27:54.054Z] GC before operation: completed in 221.634 ms, heap usage 782.971 MB -> 51.188 MB.
[2024-08-02T02:27:57.039Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T02:28:01.154Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T02:28:04.142Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T02:28:07.133Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T02:28:09.166Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T02:28:10.108Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T02:28:12.046Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T02:28:15.036Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T02:28:15.036Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-08-02T02:28:15.036Z] The best model improves the baseline by 14.43%.
[2024-08-02T02:28:15.036Z] Movies recommended for you:
[2024-08-02T02:28:15.036Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T02:28:15.036Z] There is no way to check that no silent failure occurred.
[2024-08-02T02:28:15.036Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (20723.092 ms) ======
[2024-08-02T02:28:15.036Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-02T02:28:15.036Z] GC before operation: completed in 191.052 ms, heap usage 711.963 MB -> 51.028 MB.
[2024-08-02T02:28:18.028Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T02:28:21.009Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T02:28:23.992Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T02:28:26.977Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T02:28:28.918Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T02:28:30.851Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T02:28:32.785Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T02:28:34.719Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T02:28:35.660Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-08-02T02:28:35.660Z] The best model improves the baseline by 14.43%.
[2024-08-02T02:28:35.660Z] Movies recommended for you:
[2024-08-02T02:28:35.660Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T02:28:35.660Z] There is no way to check that no silent failure occurred.
[2024-08-02T02:28:35.660Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (20399.941 ms) ======
[2024-08-02T02:28:35.660Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-02T02:28:35.660Z] GC before operation: completed in 192.579 ms, heap usage 697.685 MB -> 51.258 MB.
[2024-08-02T02:28:38.649Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T02:28:42.335Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T02:28:44.278Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T02:28:47.263Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T02:28:48.205Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T02:28:50.138Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T02:28:51.123Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T02:28:53.060Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T02:28:53.060Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-08-02T02:28:53.060Z] The best model improves the baseline by 14.43%.
[2024-08-02T02:28:53.060Z] Movies recommended for you:
[2024-08-02T02:28:53.060Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T02:28:53.060Z] There is no way to check that no silent failure occurred.
[2024-08-02T02:28:53.060Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (17398.866 ms) ======
[2024-08-02T02:28:54.993Z] -----------------------------------
[2024-08-02T02:28:54.993Z] renaissance-movie-lens_0_PASSED
[2024-08-02T02:28:54.993Z] -----------------------------------
[2024-08-02T02:28:54.993Z]
[2024-08-02T02:28:54.993Z] TEST TEARDOWN:
[2024-08-02T02:28:54.993Z] Nothing to be done for teardown.
[2024-08-02T02:28:54.993Z] renaissance-movie-lens_0 Finish Time: Fri Aug 2 02:28:54 2024 Epoch Time (ms): 1722565734544