renaissance-movie-lens_0
[2024-08-01T21:29:16.288Z] Running test renaissance-movie-lens_0 ...
[2024-08-01T21:29:16.288Z] ===============================================
[2024-08-01T21:29:16.288Z] renaissance-movie-lens_0 Start Time: Thu Aug 1 21:29:15 2024 Epoch Time (ms): 1722547755769
[2024-08-01T21:29:16.288Z] variation: NoOptions
[2024-08-01T21:29:16.288Z] JVM_OPTIONS:
[2024-08-01T21:29:16.288Z] { \
[2024-08-01T21:29:16.288Z] echo ""; echo "TEST SETUP:"; \
[2024-08-01T21:29:16.288Z] echo "Nothing to be done for setup."; \
[2024-08-01T21:29:16.288Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17225466482966/renaissance-movie-lens_0"; \
[2024-08-01T21:29:16.288Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17225466482966/renaissance-movie-lens_0"; \
[2024-08-01T21:29:16.289Z] echo ""; echo "TESTING:"; \
[2024-08-01T21:29:16.289Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix_testList_0/jdkbinary/j2sdk-image/bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17225466482966/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-01T21:29:16.289Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17225466482966/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-01T21:29:16.289Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-01T21:29:16.289Z] echo "Nothing to be done for teardown."; \
[2024-08-01T21:29:16.289Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17225466482966/TestTargetResult";
[2024-08-01T21:29:16.289Z]
[2024-08-01T21:29:16.289Z] TEST SETUP:
[2024-08-01T21:29:16.289Z] Nothing to be done for setup.
[2024-08-01T21:29:16.289Z]
[2024-08-01T21:29:16.289Z] TESTING:
[2024-08-01T21:29:21.872Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-01T21:29:25.270Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 24) threads.
[2024-08-01T21:29:32.122Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-01T21:29:32.122Z] Training: 60056, validation: 20285, test: 19854
[2024-08-01T21:29:32.122Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-01T21:29:32.122Z] GC before operation: completed in 259.470 ms, heap usage 86.456 MB -> 26.125 MB.
[2024-08-01T21:29:41.970Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T21:29:46.435Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T21:29:52.109Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T21:29:56.572Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T21:29:59.060Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T21:30:01.517Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T21:30:03.976Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T21:30:07.539Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T21:30:07.539Z] 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.
[2024-08-01T21:30:07.539Z] The best model improves the baseline by 14.43%.
[2024-08-01T21:30:07.539Z] Movies recommended for you:
[2024-08-01T21:30:07.539Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T21:30:07.539Z] There is no way to check that no silent failure occurred.
[2024-08-01T21:30:07.539Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (35702.001 ms) ======
[2024-08-01T21:30:07.539Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-01T21:30:08.307Z] GC before operation: completed in 318.833 ms, heap usage 304.993 MB -> 42.871 MB.
[2024-08-01T21:30:12.742Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T21:30:17.184Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T21:30:21.650Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T21:30:26.152Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T21:30:28.616Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T21:30:31.076Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T21:30:33.540Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T21:30:36.939Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T21:30:36.939Z] 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.
[2024-08-01T21:30:36.939Z] The best model improves the baseline by 14.43%.
[2024-08-01T21:30:36.939Z] Movies recommended for you:
[2024-08-01T21:30:36.939Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T21:30:36.940Z] There is no way to check that no silent failure occurred.
[2024-08-01T21:30:36.940Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (28884.022 ms) ======
[2024-08-01T21:30:36.940Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-01T21:30:36.940Z] GC before operation: completed in 246.372 ms, heap usage 199.971 MB -> 43.828 MB.
[2024-08-01T21:30:41.384Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T21:30:45.830Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T21:30:50.456Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T21:30:54.897Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T21:30:57.374Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T21:30:59.841Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T21:31:02.299Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T21:31:04.756Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T21:31:05.520Z] 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.
[2024-08-01T21:31:05.520Z] The best model improves the baseline by 14.43%.
[2024-08-01T21:31:05.520Z] Movies recommended for you:
[2024-08-01T21:31:05.520Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T21:31:05.520Z] There is no way to check that no silent failure occurred.
[2024-08-01T21:31:05.520Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (28432.486 ms) ======
[2024-08-01T21:31:05.520Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-01T21:31:05.520Z] GC before operation: completed in 259.053 ms, heap usage 151.460 MB -> 51.593 MB.
[2024-08-01T21:31:10.731Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T21:31:14.110Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T21:31:18.559Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T21:31:23.008Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T21:31:25.481Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T21:31:27.947Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T21:31:30.406Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T21:31:32.867Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T21:31:32.867Z] 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.
[2024-08-01T21:31:32.867Z] The best model improves the baseline by 14.43%.
[2024-08-01T21:31:33.631Z] Movies recommended for you:
[2024-08-01T21:31:33.631Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T21:31:33.631Z] There is no way to check that no silent failure occurred.
[2024-08-01T21:31:33.631Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (27430.733 ms) ======
[2024-08-01T21:31:33.632Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-01T21:31:33.632Z] GC before operation: completed in 257.115 ms, heap usage 424.915 MB -> 69.525 MB.
[2024-08-01T21:31:38.077Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T21:31:42.534Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T21:31:46.987Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T21:31:50.400Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T21:31:52.867Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T21:31:55.327Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T21:31:57.827Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T21:32:00.294Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T21:32:01.062Z] 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.
[2024-08-01T21:32:01.062Z] The best model improves the baseline by 14.43%.
[2024-08-01T21:32:01.062Z] Movies recommended for you:
[2024-08-01T21:32:01.062Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T21:32:01.062Z] There is no way to check that no silent failure occurred.
[2024-08-01T21:32:01.062Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (27464.643 ms) ======
[2024-08-01T21:32:01.062Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-01T21:32:01.062Z] GC before operation: completed in 235.838 ms, heap usage 280.895 MB -> 51.217 MB.
[2024-08-01T21:32:05.503Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T21:32:09.945Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T21:32:14.386Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T21:32:18.845Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T21:32:20.424Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T21:32:22.882Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T21:32:25.344Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T21:32:27.804Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T21:32:28.571Z] 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.
[2024-08-01T21:32:28.571Z] The best model improves the baseline by 14.43%.
[2024-08-01T21:32:28.571Z] Movies recommended for you:
[2024-08-01T21:32:28.571Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T21:32:28.571Z] There is no way to check that no silent failure occurred.
[2024-08-01T21:32:28.571Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (27101.398 ms) ======
[2024-08-01T21:32:28.571Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-01T21:32:28.571Z] GC before operation: completed in 253.150 ms, heap usage 386.347 MB -> 74.451 MB.
[2024-08-01T21:32:33.036Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T21:32:37.997Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T21:32:41.440Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T21:32:45.886Z] RMSE (validation) = 1.0045407704488025 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T21:32:48.349Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T21:32:50.807Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T21:32:53.270Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T21:32:55.795Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T21:32:55.795Z] 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.
[2024-08-01T21:32:55.795Z] The best model improves the baseline by 14.43%.
[2024-08-01T21:32:56.562Z] Movies recommended for you:
[2024-08-01T21:32:56.562Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T21:32:56.562Z] There is no way to check that no silent failure occurred.
[2024-08-01T21:32:56.562Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (27597.833 ms) ======
[2024-08-01T21:32:56.562Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-01T21:32:56.562Z] GC before operation: completed in 208.939 ms, heap usage 158.171 MB -> 46.924 MB.
[2024-08-01T21:33:01.016Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T21:33:05.489Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T21:33:08.912Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T21:33:13.383Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T21:33:15.885Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T21:33:18.344Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T21:33:20.815Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T21:33:23.282Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T21:33:23.282Z] 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.
[2024-08-01T21:33:23.282Z] The best model improves the baseline by 14.43%.
[2024-08-01T21:33:23.282Z] Movies recommended for you:
[2024-08-01T21:33:23.282Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T21:33:23.282Z] There is no way to check that no silent failure occurred.
[2024-08-01T21:33:23.282Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (27139.360 ms) ======
[2024-08-01T21:33:23.282Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-01T21:33:24.049Z] GC before operation: completed in 264.070 ms, heap usage 134.431 MB -> 74.404 MB.
[2024-08-01T21:33:28.500Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T21:33:32.948Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T21:33:37.386Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T21:33:40.823Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T21:33:44.231Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T21:33:45.815Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T21:33:48.324Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T21:33:50.782Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T21:33:51.545Z] 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.
[2024-08-01T21:33:51.545Z] The best model improves the baseline by 14.43%.
[2024-08-01T21:33:51.545Z] Movies recommended for you:
[2024-08-01T21:33:51.545Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T21:33:51.545Z] There is no way to check that no silent failure occurred.
[2024-08-01T21:33:51.545Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (27664.397 ms) ======
[2024-08-01T21:33:51.545Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-01T21:33:51.545Z] GC before operation: completed in 223.376 ms, heap usage 437.267 MB -> 75.044 MB.
[2024-08-01T21:33:55.982Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T21:34:00.429Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T21:34:04.890Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T21:34:09.239Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T21:34:11.714Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T21:34:13.297Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T21:34:16.707Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T21:34:18.297Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T21:34:19.062Z] 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.
[2024-08-01T21:34:19.062Z] The best model improves the baseline by 14.43%.
[2024-08-01T21:34:19.062Z] Movies recommended for you:
[2024-08-01T21:34:19.062Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T21:34:19.062Z] There is no way to check that no silent failure occurred.
[2024-08-01T21:34:19.062Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (27353.148 ms) ======
[2024-08-01T21:34:19.062Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-01T21:34:19.062Z] GC before operation: completed in 321.149 ms, heap usage 422.995 MB -> 74.823 MB.
[2024-08-01T21:34:23.515Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T21:34:27.959Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T21:34:32.404Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T21:34:36.858Z] RMSE (validation) = 1.0045407704488025 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T21:34:39.320Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T21:34:41.781Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T21:34:44.249Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T21:34:46.706Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T21:34:46.706Z] 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.
[2024-08-01T21:34:46.706Z] The best model improves the baseline by 14.43%.
[2024-08-01T21:34:46.706Z] Movies recommended for you:
[2024-08-01T21:34:46.706Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T21:34:46.706Z] There is no way to check that no silent failure occurred.
[2024-08-01T21:34:46.706Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (27343.479 ms) ======
[2024-08-01T21:34:46.706Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-01T21:34:46.706Z] GC before operation: completed in 205.258 ms, heap usage 319.207 MB -> 73.964 MB.
[2024-08-01T21:34:51.160Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T21:34:55.620Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T21:35:00.088Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T21:35:04.550Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T21:35:07.012Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T21:35:09.481Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T21:35:11.942Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T21:35:14.414Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T21:35:14.414Z] 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.
[2024-08-01T21:35:14.414Z] The best model improves the baseline by 14.43%.
[2024-08-01T21:35:14.414Z] Movies recommended for you:
[2024-08-01T21:35:14.414Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T21:35:14.414Z] There is no way to check that no silent failure occurred.
[2024-08-01T21:35:14.414Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (27670.283 ms) ======
[2024-08-01T21:35:14.414Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-01T21:35:15.180Z] GC before operation: completed in 235.501 ms, heap usage 448.610 MB -> 74.888 MB.
[2024-08-01T21:35:19.630Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T21:35:23.046Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T21:35:27.508Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T21:35:31.977Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T21:35:34.448Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T21:35:36.952Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T21:35:39.611Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T21:35:42.086Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T21:35:42.086Z] 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.
[2024-08-01T21:35:42.086Z] The best model improves the baseline by 14.43%.
[2024-08-01T21:35:42.849Z] Movies recommended for you:
[2024-08-01T21:35:42.849Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T21:35:42.849Z] There is no way to check that no silent failure occurred.
[2024-08-01T21:35:42.849Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (27625.334 ms) ======
[2024-08-01T21:35:42.849Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-01T21:35:42.849Z] GC before operation: completed in 265.900 ms, heap usage 441.082 MB -> 75.099 MB.
[2024-08-01T21:35:47.301Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T21:35:50.891Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T21:35:55.365Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T21:35:59.799Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T21:36:02.266Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T21:36:04.727Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T21:36:07.190Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T21:36:09.648Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T21:36:09.648Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-08-01T21:36:09.648Z] The best model improves the baseline by 14.43%.
[2024-08-01T21:36:10.430Z] Movies recommended for you:
[2024-08-01T21:36:10.430Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T21:36:10.430Z] There is no way to check that no silent failure occurred.
[2024-08-01T21:36:10.430Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (27415.025 ms) ======
[2024-08-01T21:36:10.430Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-01T21:36:10.430Z] GC before operation: completed in 206.831 ms, heap usage 216.678 MB -> 73.814 MB.
[2024-08-01T21:36:14.870Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T21:36:19.319Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T21:36:23.845Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T21:36:27.256Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T21:36:30.662Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T21:36:32.256Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T21:36:34.718Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T21:36:37.188Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T21:36:37.967Z] 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.
[2024-08-01T21:36:37.967Z] The best model improves the baseline by 14.43%.
[2024-08-01T21:36:37.967Z] Movies recommended for you:
[2024-08-01T21:36:37.967Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T21:36:37.967Z] There is no way to check that no silent failure occurred.
[2024-08-01T21:36:37.967Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (27591.839 ms) ======
[2024-08-01T21:36:37.967Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-01T21:36:37.967Z] GC before operation: completed in 182.508 ms, heap usage 438.780 MB -> 74.889 MB.
[2024-08-01T21:36:42.405Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T21:36:46.884Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T21:36:51.326Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T21:36:55.763Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T21:36:57.343Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T21:36:59.804Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T21:37:02.299Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T21:37:04.764Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T21:37:05.878Z] 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.
[2024-08-01T21:37:05.878Z] The best model improves the baseline by 14.43%.
[2024-08-01T21:37:05.878Z] Movies recommended for you:
[2024-08-01T21:37:05.878Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T21:37:05.878Z] There is no way to check that no silent failure occurred.
[2024-08-01T21:37:05.878Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (27286.242 ms) ======
[2024-08-01T21:37:05.878Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-01T21:37:05.878Z] GC before operation: completed in 215.748 ms, heap usage 449.674 MB -> 74.659 MB.
[2024-08-01T21:37:10.326Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T21:37:14.859Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T21:37:19.302Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T21:37:22.719Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T21:37:25.189Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T21:37:28.614Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T21:37:31.075Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T21:37:33.550Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T21:37:33.550Z] 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.
[2024-08-01T21:37:33.550Z] The best model improves the baseline by 14.43%.
[2024-08-01T21:37:33.550Z] Movies recommended for you:
[2024-08-01T21:37:33.551Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T21:37:33.551Z] There is no way to check that no silent failure occurred.
[2024-08-01T21:37:33.551Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (28102.087 ms) ======
[2024-08-01T21:37:33.551Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-01T21:37:34.322Z] GC before operation: completed in 184.125 ms, heap usage 294.020 MB -> 54.938 MB.
[2024-08-01T21:37:38.776Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T21:37:42.187Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T21:37:46.645Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T21:37:51.091Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T21:37:53.558Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T21:37:56.019Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T21:37:58.486Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T21:38:00.949Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T21:38:01.714Z] 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.
[2024-08-01T21:38:01.714Z] The best model improves the baseline by 14.43%.
[2024-08-01T21:38:01.714Z] Movies recommended for you:
[2024-08-01T21:38:01.714Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T21:38:01.714Z] There is no way to check that no silent failure occurred.
[2024-08-01T21:38:01.714Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (27587.825 ms) ======
[2024-08-01T21:38:01.714Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-01T21:38:01.714Z] GC before operation: completed in 199.250 ms, heap usage 375.296 MB -> 74.743 MB.
[2024-08-01T21:38:06.182Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T21:38:10.798Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T21:38:15.264Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T21:38:19.758Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T21:38:21.340Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T21:38:24.767Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T21:38:27.764Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T21:38:29.387Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T21:38:29.387Z] 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.
[2024-08-01T21:38:29.387Z] The best model improves the baseline by 14.43%.
[2024-08-01T21:38:29.387Z] Movies recommended for you:
[2024-08-01T21:38:29.387Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T21:38:29.387Z] There is no way to check that no silent failure occurred.
[2024-08-01T21:38:29.387Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (27955.800 ms) ======
[2024-08-01T21:38:29.387Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-01T21:38:30.155Z] GC before operation: completed in 233.345 ms, heap usage 321.677 MB -> 75.061 MB.
[2024-08-01T21:38:34.612Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T21:38:39.065Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T21:38:43.538Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T21:38:46.955Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T21:38:49.428Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T21:38:51.893Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T21:38:54.362Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T21:38:57.781Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T21:38:57.781Z] 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.
[2024-08-01T21:38:57.781Z] The best model improves the baseline by 14.43%.
[2024-08-01T21:38:57.781Z] Movies recommended for you:
[2024-08-01T21:38:57.781Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T21:38:57.781Z] There is no way to check that no silent failure occurred.
[2024-08-01T21:38:57.781Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (27775.834 ms) ======
[2024-08-01T21:38:59.375Z] -----------------------------------
[2024-08-01T21:38:59.375Z] renaissance-movie-lens_0_PASSED
[2024-08-01T21:38:59.375Z] -----------------------------------
[2024-08-01T21:38:59.375Z]
[2024-08-01T21:38:59.375Z] TEST TEARDOWN:
[2024-08-01T21:38:59.375Z] Nothing to be done for teardown.
[2024-08-01T21:38:59.375Z] renaissance-movie-lens_0 Finish Time: Thu Aug 1 21:38:59 2024 Epoch Time (ms): 1722548339246