renaissance-movie-lens_0
[2024-08-02T05:14:40.120Z] Running test renaissance-movie-lens_0 ...
[2024-08-02T05:14:40.120Z] ===============================================
[2024-08-02T05:14:40.120Z] renaissance-movie-lens_0 Start Time: Fri Aug 2 00:14:39 2024 Epoch Time (ms): 1722575679435
[2024-08-02T05:14:40.120Z] variation: NoOptions
[2024-08-02T05:14:40.120Z] JVM_OPTIONS:
[2024-08-02T05:14:40.120Z] { \
[2024-08-02T05:14:40.120Z] echo ""; echo "TEST SETUP:"; \
[2024-08-02T05:14:40.120Z] echo "Nothing to be done for setup."; \
[2024-08-02T05:14:40.120Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17225748014076/renaissance-movie-lens_0"; \
[2024-08-02T05:14:40.120Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17225748014076/renaissance-movie-lens_0"; \
[2024-08-02T05:14:40.120Z] echo ""; echo "TESTING:"; \
[2024-08-02T05:14:40.120Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux_testList_0/jdkbinary/j2sdk-image/jdk8u432-b01/bin/..//bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17225748014076/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-02T05:14:40.121Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17225748014076/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-02T05:14:40.121Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-02T05:14:40.121Z] echo "Nothing to be done for teardown."; \
[2024-08-02T05:14:40.121Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17225748014076/TestTargetResult";
[2024-08-02T05:14:40.121Z]
[2024-08-02T05:14:40.121Z] TEST SETUP:
[2024-08-02T05:14:40.121Z] Nothing to be done for setup.
[2024-08-02T05:14:40.121Z]
[2024-08-02T05:14:40.121Z] TESTING:
[2024-08-02T05:14:42.317Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-02T05:14:45.414Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2024-08-02T05:14:48.503Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-02T05:14:49.190Z] Training: 60056, validation: 20285, test: 19854
[2024-08-02T05:14:49.190Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-02T05:14:49.190Z] GC before operation: completed in 374.193 ms, heap usage 114.169 MB -> 28.921 MB.
[2024-08-02T05:14:55.493Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T05:15:00.608Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T05:15:02.834Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T05:15:06.003Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T05:15:08.243Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T05:15:09.655Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T05:15:11.059Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T05:15:13.388Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T05:15:13.388Z] 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.
[2024-08-02T05:15:13.388Z] The best model improves the baseline by 14.43%.
[2024-08-02T05:15:13.388Z] Movies recommended for you:
[2024-08-02T05:15:13.388Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T05:15:13.388Z] There is no way to check that no silent failure occurred.
[2024-08-02T05:15:13.388Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (24106.700 ms) ======
[2024-08-02T05:15:13.388Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-02T05:15:14.064Z] GC before operation: completed in 364.230 ms, heap usage 96.152 MB -> 46.552 MB.
[2024-08-02T05:15:16.270Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T05:15:19.361Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T05:15:22.445Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T05:15:24.685Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T05:15:26.099Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T05:15:28.308Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T05:15:29.721Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T05:15:31.940Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T05:15:32.616Z] 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.
[2024-08-02T05:15:32.616Z] The best model improves the baseline by 14.43%.
[2024-08-02T05:15:32.616Z] Movies recommended for you:
[2024-08-02T05:15:32.616Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T05:15:32.616Z] There is no way to check that no silent failure occurred.
[2024-08-02T05:15:32.616Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (18613.627 ms) ======
[2024-08-02T05:15:32.616Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-02T05:15:32.616Z] GC before operation: completed in 241.631 ms, heap usage 539.880 MB -> 49.426 MB.
[2024-08-02T05:15:35.664Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T05:15:38.717Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T05:15:40.927Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T05:15:43.977Z] RMSE (validation) = 1.0045407704488025 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T05:15:44.653Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T05:15:46.853Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T05:15:48.261Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T05:15:49.692Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T05:15:49.692Z] 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.
[2024-08-02T05:15:49.692Z] The best model improves the baseline by 14.43%.
[2024-08-02T05:15:49.692Z] Movies recommended for you:
[2024-08-02T05:15:49.692Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T05:15:49.692Z] There is no way to check that no silent failure occurred.
[2024-08-02T05:15:49.692Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17233.155 ms) ======
[2024-08-02T05:15:49.692Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-02T05:15:50.369Z] GC before operation: completed in 252.867 ms, heap usage 419.203 MB -> 48.099 MB.
[2024-08-02T05:15:52.568Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T05:15:54.795Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T05:15:57.893Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T05:16:00.110Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T05:16:01.541Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T05:16:02.964Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T05:16:05.165Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T05:16:06.573Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T05:16:06.573Z] 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.
[2024-08-02T05:16:06.573Z] The best model improves the baseline by 14.43%.
[2024-08-02T05:16:06.573Z] Movies recommended for you:
[2024-08-02T05:16:06.573Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T05:16:06.573Z] There is no way to check that no silent failure occurred.
[2024-08-02T05:16:06.573Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16628.623 ms) ======
[2024-08-02T05:16:06.573Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-02T05:16:07.251Z] GC before operation: completed in 126.643 ms, heap usage 635.673 MB -> 57.074 MB.
[2024-08-02T05:16:09.588Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T05:16:11.779Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T05:16:13.997Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T05:16:17.069Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T05:16:18.509Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T05:16:19.920Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T05:16:21.336Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T05:16:22.757Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T05:16:22.757Z] 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.
[2024-08-02T05:16:22.757Z] The best model improves the baseline by 14.43%.
[2024-08-02T05:16:23.436Z] Movies recommended for you:
[2024-08-02T05:16:23.437Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T05:16:23.437Z] There is no way to check that no silent failure occurred.
[2024-08-02T05:16:23.437Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16131.009 ms) ======
[2024-08-02T05:16:23.437Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-02T05:16:23.437Z] GC before operation: completed in 180.707 ms, heap usage 631.822 MB -> 50.711 MB.
[2024-08-02T05:16:25.650Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T05:16:27.865Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T05:16:30.958Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T05:16:33.186Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T05:16:34.603Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T05:16:36.034Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T05:16:37.444Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T05:16:38.864Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T05:16:38.864Z] 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.
[2024-08-02T05:16:38.865Z] The best model improves the baseline by 14.43%.
[2024-08-02T05:16:39.541Z] Movies recommended for you:
[2024-08-02T05:16:39.541Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T05:16:39.541Z] There is no way to check that no silent failure occurred.
[2024-08-02T05:16:39.541Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15907.722 ms) ======
[2024-08-02T05:16:39.541Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-02T05:16:39.541Z] GC before operation: completed in 118.520 ms, heap usage 451.837 MB -> 46.821 MB.
[2024-08-02T05:16:41.737Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T05:16:43.952Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T05:16:46.149Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T05:16:49.236Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T05:16:50.650Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T05:16:52.051Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T05:16:53.480Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T05:16:54.889Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T05:16:54.889Z] 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.
[2024-08-02T05:16:54.889Z] The best model improves the baseline by 14.43%.
[2024-08-02T05:16:54.889Z] Movies recommended for you:
[2024-08-02T05:16:54.889Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T05:16:54.889Z] There is no way to check that no silent failure occurred.
[2024-08-02T05:16:54.889Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15675.815 ms) ======
[2024-08-02T05:16:54.889Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-02T05:16:54.889Z] GC before operation: completed in 198.932 ms, heap usage 529.802 MB -> 50.628 MB.
[2024-08-02T05:16:57.955Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T05:17:00.150Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T05:17:02.362Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T05:17:04.565Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T05:17:05.978Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T05:17:07.388Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T05:17:09.236Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T05:17:10.675Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T05:17:10.676Z] 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.
[2024-08-02T05:17:10.676Z] The best model improves the baseline by 14.43%.
[2024-08-02T05:17:10.676Z] Movies recommended for you:
[2024-08-02T05:17:10.676Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T05:17:10.676Z] There is no way to check that no silent failure occurred.
[2024-08-02T05:17:10.676Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15703.213 ms) ======
[2024-08-02T05:17:10.676Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-02T05:17:11.351Z] GC before operation: completed in 151.162 ms, heap usage 472.811 MB -> 59.088 MB.
[2024-08-02T05:17:13.557Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T05:17:15.746Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T05:17:17.949Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T05:17:21.017Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T05:17:22.434Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T05:17:23.846Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T05:17:25.265Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T05:17:26.677Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T05:17:26.677Z] 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.
[2024-08-02T05:17:26.677Z] The best model improves the baseline by 14.43%.
[2024-08-02T05:17:26.677Z] Movies recommended for you:
[2024-08-02T05:17:26.677Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T05:17:26.677Z] There is no way to check that no silent failure occurred.
[2024-08-02T05:17:26.677Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15919.910 ms) ======
[2024-08-02T05:17:26.677Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-02T05:17:27.376Z] GC before operation: completed in 154.411 ms, heap usage 266.303 MB -> 57.072 MB.
[2024-08-02T05:17:29.571Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T05:17:31.802Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T05:17:34.023Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T05:17:37.100Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T05:17:38.545Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T05:17:39.960Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T05:17:41.393Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T05:17:42.814Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T05:17:43.499Z] 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.
[2024-08-02T05:17:43.499Z] The best model improves the baseline by 14.43%.
[2024-08-02T05:17:43.499Z] Movies recommended for you:
[2024-08-02T05:17:43.499Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T05:17:43.499Z] There is no way to check that no silent failure occurred.
[2024-08-02T05:17:43.499Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (16377.616 ms) ======
[2024-08-02T05:17:43.499Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-02T05:17:43.499Z] GC before operation: completed in 166.430 ms, heap usage 565.174 MB -> 53.253 MB.
[2024-08-02T05:17:45.714Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T05:17:48.789Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T05:17:51.006Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T05:17:53.213Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T05:17:54.635Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T05:17:56.044Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T05:17:57.453Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T05:17:58.878Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T05:17:58.878Z] 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.
[2024-08-02T05:17:58.878Z] The best model improves the baseline by 14.43%.
[2024-08-02T05:17:59.553Z] Movies recommended for you:
[2024-08-02T05:17:59.553Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T05:17:59.553Z] There is no way to check that no silent failure occurred.
[2024-08-02T05:17:59.553Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15586.092 ms) ======
[2024-08-02T05:17:59.553Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-02T05:17:59.553Z] GC before operation: completed in 168.517 ms, heap usage 539.999 MB -> 52.927 MB.
[2024-08-02T05:18:01.752Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T05:18:04.004Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T05:18:07.129Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T05:18:09.324Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T05:18:10.761Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T05:18:12.179Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T05:18:13.597Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T05:18:15.042Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T05:18:15.042Z] 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.
[2024-08-02T05:18:15.042Z] The best model improves the baseline by 14.43%.
[2024-08-02T05:18:15.042Z] Movies recommended for you:
[2024-08-02T05:18:15.042Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T05:18:15.042Z] There is no way to check that no silent failure occurred.
[2024-08-02T05:18:15.042Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15840.233 ms) ======
[2024-08-02T05:18:15.042Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-02T05:18:15.719Z] GC before operation: completed in 154.774 ms, heap usage 445.206 MB -> 64.639 MB.
[2024-08-02T05:18:17.923Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T05:18:20.130Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T05:18:22.495Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T05:18:24.702Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T05:18:26.107Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T05:18:27.545Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T05:18:28.970Z] RMSE (validation) = 0.9275717388537592 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T05:18:31.160Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T05:18:31.160Z] 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.
[2024-08-02T05:18:31.160Z] The best model improves the baseline by 14.43%.
[2024-08-02T05:18:31.160Z] Movies recommended for you:
[2024-08-02T05:18:31.161Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T05:18:31.161Z] There is no way to check that no silent failure occurred.
[2024-08-02T05:18:31.161Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15681.052 ms) ======
[2024-08-02T05:18:31.161Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-02T05:18:31.161Z] GC before operation: completed in 129.309 ms, heap usage 403.906 MB -> 50.107 MB.
[2024-08-02T05:18:33.378Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T05:18:35.576Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T05:18:38.643Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T05:18:40.833Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T05:18:42.237Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T05:18:43.660Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T05:18:45.069Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T05:18:46.502Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T05:18:46.502Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-08-02T05:18:46.502Z] The best model improves the baseline by 14.43%.
[2024-08-02T05:18:47.181Z] Movies recommended for you:
[2024-08-02T05:18:47.181Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T05:18:47.181Z] There is no way to check that no silent failure occurred.
[2024-08-02T05:18:47.181Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15603.512 ms) ======
[2024-08-02T05:18:47.181Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-02T05:18:47.181Z] GC before operation: completed in 186.010 ms, heap usage 427.600 MB -> 53.984 MB.
[2024-08-02T05:18:49.395Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T05:18:51.610Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T05:18:53.825Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T05:18:56.896Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T05:18:58.310Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T05:18:59.732Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T05:19:01.176Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T05:19:02.579Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T05:19:02.579Z] 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.
[2024-08-02T05:19:02.579Z] The best model improves the baseline by 14.43%.
[2024-08-02T05:19:02.579Z] Movies recommended for you:
[2024-08-02T05:19:02.579Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T05:19:02.579Z] There is no way to check that no silent failure occurred.
[2024-08-02T05:19:02.579Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (15631.019 ms) ======
[2024-08-02T05:19:02.579Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-02T05:19:02.579Z] GC before operation: completed in 151.528 ms, heap usage 616.722 MB -> 51.039 MB.
[2024-08-02T05:19:05.219Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T05:19:07.418Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T05:19:09.628Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T05:19:11.855Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T05:19:13.258Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T05:19:14.689Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T05:19:16.903Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T05:19:18.314Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T05:19:18.314Z] 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.
[2024-08-02T05:19:18.314Z] The best model improves the baseline by 14.43%.
[2024-08-02T05:19:18.314Z] Movies recommended for you:
[2024-08-02T05:19:18.314Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T05:19:18.314Z] There is no way to check that no silent failure occurred.
[2024-08-02T05:19:18.314Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15539.699 ms) ======
[2024-08-02T05:19:18.314Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-02T05:19:18.314Z] GC before operation: completed in 146.195 ms, heap usage 523.122 MB -> 56.124 MB.
[2024-08-02T05:19:20.509Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T05:19:23.580Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T05:19:25.771Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T05:19:27.977Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T05:19:29.397Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T05:19:30.807Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T05:19:32.239Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T05:19:33.648Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T05:19:33.648Z] 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.
[2024-08-02T05:19:33.648Z] The best model improves the baseline by 14.43%.
[2024-08-02T05:19:33.648Z] Movies recommended for you:
[2024-08-02T05:19:33.648Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T05:19:33.648Z] There is no way to check that no silent failure occurred.
[2024-08-02T05:19:33.648Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (15443.494 ms) ======
[2024-08-02T05:19:33.648Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-02T05:19:34.356Z] GC before operation: completed in 185.780 ms, heap usage 515.351 MB -> 55.802 MB.
[2024-08-02T05:19:36.567Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T05:19:38.777Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T05:19:41.001Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T05:19:44.102Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T05:19:45.508Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T05:19:46.195Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T05:19:48.396Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T05:19:49.810Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T05:19:49.810Z] 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.
[2024-08-02T05:19:49.810Z] The best model improves the baseline by 14.43%.
[2024-08-02T05:19:49.810Z] Movies recommended for you:
[2024-08-02T05:19:49.810Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T05:19:49.810Z] There is no way to check that no silent failure occurred.
[2024-08-02T05:19:49.810Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (15761.830 ms) ======
[2024-08-02T05:19:49.810Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-02T05:19:49.810Z] GC before operation: completed in 181.907 ms, heap usage 666.038 MB -> 56.254 MB.
[2024-08-02T05:19:52.875Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T05:19:55.087Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T05:19:57.282Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T05:19:59.489Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T05:20:00.900Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T05:20:02.431Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T05:20:03.841Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T05:20:05.378Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T05:20:05.378Z] 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.
[2024-08-02T05:20:05.378Z] The best model improves the baseline by 14.43%.
[2024-08-02T05:20:05.378Z] Movies recommended for you:
[2024-08-02T05:20:05.378Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T05:20:05.378Z] There is no way to check that no silent failure occurred.
[2024-08-02T05:20:05.378Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (15573.110 ms) ======
[2024-08-02T05:20:05.378Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-02T05:20:06.055Z] GC before operation: completed in 147.664 ms, heap usage 691.004 MB -> 61.200 MB.
[2024-08-02T05:20:08.314Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-02T05:20:10.523Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-02T05:20:12.736Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-02T05:20:14.949Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-02T05:20:16.364Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-02T05:20:17.779Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-02T05:20:19.232Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-02T05:20:20.657Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-02T05:20:21.358Z] 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.
[2024-08-02T05:20:21.358Z] The best model improves the baseline by 14.43%.
[2024-08-02T05:20:21.358Z] Movies recommended for you:
[2024-08-02T05:20:21.358Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-02T05:20:21.358Z] There is no way to check that no silent failure occurred.
[2024-08-02T05:20:21.358Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (15520.009 ms) ======
[2024-08-02T05:20:22.760Z] -----------------------------------
[2024-08-02T05:20:22.760Z] renaissance-movie-lens_0_PASSED
[2024-08-02T05:20:22.760Z] -----------------------------------
[2024-08-02T05:20:22.760Z]
[2024-08-02T05:20:22.760Z] TEST TEARDOWN:
[2024-08-02T05:20:22.760Z] Nothing to be done for teardown.
[2024-08-02T05:20:22.760Z] renaissance-movie-lens_0 Finish Time: Fri Aug 2 00:20:22 2024 Epoch Time (ms): 1722576022027