[2025-02-25T21:58:18.616Z] Running test renaissance-movie-lens_0 ... [2025-02-25T21:58:18.616Z] =============================================== [2025-02-25T21:58:18.616Z] renaissance-movie-lens_0 Start Time: Tue Feb 25 21:58:17 2025 Epoch Time (ms): 1740520697919 [2025-02-25T21:58:18.616Z] variation: NoOptions [2025-02-25T21:58:18.616Z] JVM_OPTIONS: [2025-02-25T21:58:18.616Z] { \ [2025-02-25T21:58:18.616Z] echo ""; echo "TEST SETUP:"; \ [2025-02-25T21:58:18.616Z] echo "Nothing to be done for setup."; \ [2025-02-25T21:58:18.616Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17405197075806/renaissance-movie-lens_0"; \ [2025-02-25T21:58:18.616Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17405197075806/renaissance-movie-lens_0"; \ [2025-02-25T21:58:18.616Z] echo ""; echo "TESTING:"; \ [2025-02-25T21:58:18.616Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/jdkbinary/j2sdk-image/bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17405197075806/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-02-25T21:58:18.616Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17405197075806/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-02-25T21:58:18.616Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-02-25T21:58:18.616Z] echo "Nothing to be done for teardown."; \ [2025-02-25T21:58:18.616Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17405197075806/TestTargetResult"; [2025-02-25T21:58:18.616Z] [2025-02-25T21:58:18.616Z] TEST SETUP: [2025-02-25T21:58:18.616Z] Nothing to be done for setup. [2025-02-25T21:58:18.616Z] [2025-02-25T21:58:18.616Z] TESTING: [2025-02-25T21:58:21.660Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2025-02-25T21:58:25.855Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads. [2025-02-25T21:58:30.061Z] Got 100004 ratings from 671 users on 9066 movies. [2025-02-25T21:58:31.026Z] Training: 60056, validation: 20285, test: 19854 [2025-02-25T21:58:31.026Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-02-25T21:58:31.026Z] GC before operation: completed in 197.807 ms, heap usage 237.671 MB -> 29.356 MB. [2025-02-25T21:58:39.281Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-25T21:58:42.350Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-25T21:58:46.558Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-25T21:58:49.617Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-25T21:58:51.600Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-25T21:58:53.586Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-25T21:58:55.569Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-25T21:58:57.548Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-25T21:58:57.548Z] 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. [2025-02-25T21:58:57.548Z] The best model improves the baseline by 14.43%. [2025-02-25T21:58:58.519Z] Movies recommended for you: [2025-02-25T21:58:58.519Z] WARNING: This benchmark provides no result that can be validated. [2025-02-25T21:58:58.519Z] There is no way to check that no silent failure occurred. [2025-02-25T21:58:58.519Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (27251.669 ms) ====== [2025-02-25T21:58:58.519Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-02-25T21:58:58.519Z] GC before operation: completed in 295.915 ms, heap usage 264.300 MB -> 43.859 MB. [2025-02-25T21:59:01.569Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-25T21:59:04.641Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-25T21:59:07.690Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-25T21:59:09.672Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-25T21:59:11.653Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-25T21:59:13.632Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-25T21:59:15.623Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-25T21:59:18.323Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-25T21:59:18.323Z] 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. [2025-02-25T21:59:18.323Z] The best model improves the baseline by 14.43%. [2025-02-25T21:59:18.323Z] Movies recommended for you: [2025-02-25T21:59:18.323Z] WARNING: This benchmark provides no result that can be validated. [2025-02-25T21:59:18.323Z] There is no way to check that no silent failure occurred. [2025-02-25T21:59:18.323Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (19125.179 ms) ====== [2025-02-25T21:59:18.323Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-02-25T21:59:18.323Z] GC before operation: completed in 248.527 ms, heap usage 90.153 MB -> 48.488 MB. [2025-02-25T21:59:21.401Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-25T21:59:23.389Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-25T21:59:26.440Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-25T21:59:29.492Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-25T21:59:31.469Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-25T21:59:32.435Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-25T21:59:34.424Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-25T21:59:35.390Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-25T21:59:36.374Z] 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. [2025-02-25T21:59:36.374Z] The best model improves the baseline by 14.43%. [2025-02-25T21:59:36.374Z] Movies recommended for you: [2025-02-25T21:59:36.374Z] WARNING: This benchmark provides no result that can be validated. [2025-02-25T21:59:36.374Z] There is no way to check that no silent failure occurred. [2025-02-25T21:59:36.374Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (18185.453 ms) ====== [2025-02-25T21:59:36.374Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-02-25T21:59:36.374Z] GC before operation: completed in 245.750 ms, heap usage 1.153 GB -> 53.277 MB. [2025-02-25T21:59:39.432Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-25T21:59:41.430Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-25T21:59:44.519Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-25T21:59:46.510Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-25T21:59:48.511Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-25T21:59:49.477Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-25T21:59:50.454Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-25T21:59:52.446Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-25T21:59:52.446Z] 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. [2025-02-25T21:59:52.446Z] The best model improves the baseline by 14.43%. [2025-02-25T21:59:52.446Z] Movies recommended for you: [2025-02-25T21:59:52.446Z] WARNING: This benchmark provides no result that can be validated. [2025-02-25T21:59:52.446Z] There is no way to check that no silent failure occurred. [2025-02-25T21:59:52.446Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16536.598 ms) ====== [2025-02-25T21:59:52.446Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-02-25T21:59:53.435Z] GC before operation: completed in 200.937 ms, heap usage 1.126 GB -> 53.559 MB. [2025-02-25T21:59:55.417Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-25T21:59:57.426Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-25T21:59:58.393Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-25T22:00:00.389Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-25T22:00:01.355Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-25T22:00:03.339Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-25T22:00:04.304Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-25T22:00:05.265Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-25T22:00:05.266Z] 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. [2025-02-25T22:00:05.266Z] The best model improves the baseline by 14.43%. [2025-02-25T22:00:05.266Z] Movies recommended for you: [2025-02-25T22:00:05.266Z] WARNING: This benchmark provides no result that can be validated. [2025-02-25T22:00:05.266Z] There is no way to check that no silent failure occurred. [2025-02-25T22:00:05.266Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (12575.631 ms) ====== [2025-02-25T22:00:05.266Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-02-25T22:00:06.229Z] GC before operation: completed in 180.648 ms, heap usage 1.100 GB -> 53.604 MB. [2025-02-25T22:00:07.221Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-25T22:00:09.207Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-25T22:00:11.188Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-25T22:00:13.171Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-25T22:00:14.143Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-25T22:00:16.123Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-25T22:00:17.089Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-25T22:00:18.051Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-25T22:00:18.051Z] 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. [2025-02-25T22:00:18.051Z] The best model improves the baseline by 14.43%. [2025-02-25T22:00:18.051Z] Movies recommended for you: [2025-02-25T22:00:18.051Z] WARNING: This benchmark provides no result that can be validated. [2025-02-25T22:00:18.051Z] There is no way to check that no silent failure occurred. [2025-02-25T22:00:18.051Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (12527.301 ms) ====== [2025-02-25T22:00:18.051Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-02-25T22:00:18.051Z] GC before operation: completed in 158.240 ms, heap usage 1.071 GB -> 53.339 MB. [2025-02-25T22:00:20.031Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-25T22:00:22.717Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-25T22:00:23.685Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-25T22:00:25.661Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-25T22:00:26.630Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-25T22:00:28.602Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-25T22:00:29.564Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-25T22:00:30.527Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-25T22:00:30.527Z] 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. [2025-02-25T22:00:30.527Z] The best model improves the baseline by 14.43%. [2025-02-25T22:00:30.527Z] Movies recommended for you: [2025-02-25T22:00:30.527Z] WARNING: This benchmark provides no result that can be validated. [2025-02-25T22:00:30.527Z] There is no way to check that no silent failure occurred. [2025-02-25T22:00:30.527Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (12211.321 ms) ====== [2025-02-25T22:00:30.527Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-02-25T22:00:30.527Z] GC before operation: completed in 168.638 ms, heap usage 1.144 GB -> 53.875 MB. [2025-02-25T22:00:32.500Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-25T22:00:34.473Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-25T22:00:36.446Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-25T22:00:38.429Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-25T22:00:39.390Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-25T22:00:41.425Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-25T22:00:42.387Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-25T22:00:43.358Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-25T22:00:43.358Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712. [2025-02-25T22:00:43.358Z] The best model improves the baseline by 14.43%. [2025-02-25T22:00:43.358Z] Movies recommended for you: [2025-02-25T22:00:43.358Z] WARNING: This benchmark provides no result that can be validated. [2025-02-25T22:00:43.358Z] There is no way to check that no silent failure occurred. [2025-02-25T22:00:43.359Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (12532.239 ms) ====== [2025-02-25T22:00:43.359Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-02-25T22:00:43.359Z] GC before operation: completed in 156.940 ms, heap usage 1.145 GB -> 56.587 MB. [2025-02-25T22:00:45.332Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-25T22:00:49.404Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-25T22:00:49.404Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-25T22:00:50.366Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-25T22:00:52.366Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-25T22:00:53.327Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-25T22:00:54.289Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-25T22:00:55.250Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-25T22:00:55.250Z] 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. [2025-02-25T22:00:55.250Z] The best model improves the baseline by 14.43%. [2025-02-25T22:00:55.250Z] Movies recommended for you: [2025-02-25T22:00:55.250Z] WARNING: This benchmark provides no result that can be validated. [2025-02-25T22:00:55.250Z] There is no way to check that no silent failure occurred. [2025-02-25T22:00:55.250Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (12001.653 ms) ====== [2025-02-25T22:00:55.250Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-02-25T22:00:55.250Z] GC before operation: completed in 149.144 ms, heap usage 1.149 GB -> 53.895 MB. [2025-02-25T22:00:57.223Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-25T22:00:59.204Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-25T22:01:01.180Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-25T22:01:03.156Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-25T22:01:04.117Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-25T22:01:05.076Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-25T22:01:06.050Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-25T22:01:07.017Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-25T22:01:07.980Z] 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. [2025-02-25T22:01:07.980Z] The best model improves the baseline by 14.43%. [2025-02-25T22:01:07.980Z] Movies recommended for you: [2025-02-25T22:01:07.980Z] WARNING: This benchmark provides no result that can be validated. [2025-02-25T22:01:07.980Z] There is no way to check that no silent failure occurred. [2025-02-25T22:01:07.980Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (11965.772 ms) ====== [2025-02-25T22:01:07.980Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-02-25T22:01:07.981Z] GC before operation: completed in 200.538 ms, heap usage 1.086 GB -> 53.689 MB. [2025-02-25T22:01:09.955Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-25T22:01:11.927Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-25T22:01:12.890Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-25T22:01:14.864Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-25T22:01:15.825Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-25T22:01:17.801Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-25T22:01:18.771Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-25T22:01:19.738Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-25T22:01:19.738Z] 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. [2025-02-25T22:01:19.738Z] The best model improves the baseline by 14.43%. [2025-02-25T22:01:19.738Z] Movies recommended for you: [2025-02-25T22:01:19.738Z] WARNING: This benchmark provides no result that can be validated. [2025-02-25T22:01:19.738Z] There is no way to check that no silent failure occurred. [2025-02-25T22:01:19.738Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (11979.439 ms) ====== [2025-02-25T22:01:19.738Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-02-25T22:01:19.738Z] GC before operation: completed in 164.239 ms, heap usage 1.087 GB -> 53.464 MB. [2025-02-25T22:01:21.715Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-25T22:01:23.687Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-25T22:01:25.662Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-25T22:01:27.350Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-25T22:01:28.311Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-25T22:01:29.273Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-25T22:01:30.235Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-25T22:01:31.202Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-25T22:01:32.165Z] 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. [2025-02-25T22:01:32.166Z] The best model improves the baseline by 14.43%. [2025-02-25T22:01:32.166Z] Movies recommended for you: [2025-02-25T22:01:32.166Z] WARNING: This benchmark provides no result that can be validated. [2025-02-25T22:01:32.166Z] There is no way to check that no silent failure occurred. [2025-02-25T22:01:32.166Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (11867.236 ms) ====== [2025-02-25T22:01:32.166Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-02-25T22:01:32.166Z] GC before operation: completed in 148.724 ms, heap usage 1.097 GB -> 55.923 MB. [2025-02-25T22:01:34.138Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-25T22:01:36.261Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-25T22:01:37.226Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-25T22:01:39.269Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-25T22:01:40.231Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-25T22:01:41.193Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-25T22:01:43.166Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-25T22:01:44.128Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-25T22:01:44.128Z] 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. [2025-02-25T22:01:44.128Z] The best model improves the baseline by 14.43%. [2025-02-25T22:01:44.128Z] Movies recommended for you: [2025-02-25T22:01:44.128Z] WARNING: This benchmark provides no result that can be validated. [2025-02-25T22:01:44.128Z] There is no way to check that no silent failure occurred. [2025-02-25T22:01:44.128Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (12127.220 ms) ====== [2025-02-25T22:01:44.128Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-02-25T22:01:44.128Z] GC before operation: completed in 163.046 ms, heap usage 1.168 GB -> 54.398 MB. [2025-02-25T22:01:46.102Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-25T22:01:48.076Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-25T22:01:50.052Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-25T22:01:52.210Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-25T22:01:53.173Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-25T22:01:54.135Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-25T22:01:55.099Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-25T22:01:56.062Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-25T22:01:56.062Z] 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. [2025-02-25T22:01:56.062Z] The best model improves the baseline by 14.43%. [2025-02-25T22:01:56.062Z] Movies recommended for you: [2025-02-25T22:01:56.062Z] WARNING: This benchmark provides no result that can be validated. [2025-02-25T22:01:56.062Z] There is no way to check that no silent failure occurred. [2025-02-25T22:01:56.062Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (12180.471 ms) ====== [2025-02-25T22:01:56.062Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-02-25T22:01:57.027Z] GC before operation: completed in 151.308 ms, heap usage 1.069 GB -> 53.381 MB. [2025-02-25T22:01:59.003Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-25T22:01:59.963Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-25T22:02:01.937Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-25T22:02:03.915Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-25T22:02:04.879Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-25T22:02:05.841Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-25T22:02:07.819Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-25T22:02:08.782Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-25T22:02:08.782Z] 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. [2025-02-25T22:02:08.782Z] The best model improves the baseline by 14.43%. [2025-02-25T22:02:08.782Z] Movies recommended for you: [2025-02-25T22:02:08.782Z] WARNING: This benchmark provides no result that can be validated. [2025-02-25T22:02:08.782Z] There is no way to check that no silent failure occurred. [2025-02-25T22:02:08.782Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (12089.054 ms) ====== [2025-02-25T22:02:08.782Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-02-25T22:02:08.782Z] GC before operation: completed in 145.428 ms, heap usage 1.030 GB -> 53.579 MB. [2025-02-25T22:02:10.759Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-25T22:02:12.747Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-25T22:02:14.752Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-25T22:02:16.727Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-25T22:02:17.690Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-25T22:02:18.653Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-25T22:02:19.616Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-25T22:02:20.583Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-25T22:02:20.583Z] 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. [2025-02-25T22:02:21.546Z] The best model improves the baseline by 14.43%. [2025-02-25T22:02:21.546Z] Movies recommended for you: [2025-02-25T22:02:21.546Z] WARNING: This benchmark provides no result that can be validated. [2025-02-25T22:02:21.546Z] There is no way to check that no silent failure occurred. [2025-02-25T22:02:21.546Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (12271.200 ms) ====== [2025-02-25T22:02:21.546Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-02-25T22:02:21.546Z] GC before operation: completed in 177.977 ms, heap usage 1.065 GB -> 53.772 MB. [2025-02-25T22:02:23.557Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-25T22:02:25.543Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-25T22:02:26.508Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-25T22:02:28.485Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-25T22:02:30.151Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-25T22:02:31.112Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-25T22:02:32.074Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-25T22:02:34.051Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-25T22:02:34.051Z] 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. [2025-02-25T22:02:34.051Z] The best model improves the baseline by 14.43%. [2025-02-25T22:02:34.051Z] Movies recommended for you: [2025-02-25T22:02:34.051Z] WARNING: This benchmark provides no result that can be validated. [2025-02-25T22:02:34.051Z] There is no way to check that no silent failure occurred. [2025-02-25T22:02:34.051Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (12468.046 ms) ====== [2025-02-25T22:02:34.051Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-02-25T22:02:34.051Z] GC before operation: completed in 180.679 ms, heap usage 1.079 GB -> 53.696 MB. [2025-02-25T22:02:36.061Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-25T22:02:38.038Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-25T22:02:38.998Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-25T22:02:40.971Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-25T22:02:41.931Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-25T22:02:43.910Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-25T22:02:44.881Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-25T22:02:45.843Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-25T22:02:45.843Z] 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. [2025-02-25T22:02:45.843Z] The best model improves the baseline by 14.43%. [2025-02-25T22:02:45.843Z] Movies recommended for you: [2025-02-25T22:02:45.843Z] WARNING: This benchmark provides no result that can be validated. [2025-02-25T22:02:45.843Z] There is no way to check that no silent failure occurred. [2025-02-25T22:02:45.843Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (11971.587 ms) ====== [2025-02-25T22:02:45.843Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-02-25T22:02:45.843Z] GC before operation: completed in 183.581 ms, heap usage 1.090 GB -> 54.577 MB. [2025-02-25T22:02:47.837Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-25T22:02:49.817Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-25T22:02:51.800Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-25T22:02:55.055Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-25T22:02:55.055Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-25T22:02:56.017Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-25T22:02:56.979Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-25T22:02:57.943Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-25T22:02:57.943Z] 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. [2025-02-25T22:02:57.943Z] The best model improves the baseline by 14.43%. [2025-02-25T22:02:57.943Z] Movies recommended for you: [2025-02-25T22:02:57.943Z] WARNING: This benchmark provides no result that can be validated. [2025-02-25T22:02:57.943Z] There is no way to check that no silent failure occurred. [2025-02-25T22:02:57.943Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (11937.103 ms) ====== [2025-02-25T22:02:57.943Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-02-25T22:02:57.943Z] GC before operation: completed in 148.608 ms, heap usage 1.083 GB -> 53.994 MB. [2025-02-25T22:02:59.919Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-25T22:03:01.896Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-25T22:03:03.904Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-25T22:03:05.882Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-25T22:03:06.848Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-25T22:03:07.810Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-25T22:03:08.771Z] RMSE (validation) = 0.9275717388537592 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-25T22:03:09.733Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-25T22:03:09.733Z] 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. [2025-02-25T22:03:09.733Z] The best model improves the baseline by 14.43%. [2025-02-25T22:03:09.733Z] Movies recommended for you: [2025-02-25T22:03:09.733Z] WARNING: This benchmark provides no result that can be validated. [2025-02-25T22:03:09.733Z] There is no way to check that no silent failure occurred. [2025-02-25T22:03:09.733Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (11870.587 ms) ====== [2025-02-25T22:03:11.707Z] ----------------------------------- [2025-02-25T22:03:11.707Z] renaissance-movie-lens_0_PASSED [2025-02-25T22:03:11.707Z] ----------------------------------- [2025-02-25T22:03:11.707Z] [2025-02-25T22:03:11.707Z] TEST TEARDOWN: [2025-02-25T22:03:11.707Z] Nothing to be done for teardown. [2025-02-25T22:03:11.707Z] renaissance-movie-lens_0 Finish Time: Tue Feb 25 22:03:10 2025 Epoch Time (ms): 1740520990812