[2024-08-01T01:21:54.827Z] Running test renaissance-movie-lens_0 ... [2024-08-01T01:21:54.827Z] =============================================== [2024-08-01T01:21:54.827Z] renaissance-movie-lens_0 Start Time: Wed Jul 31 20:21:54 2024 Epoch Time (ms): 1722475314046 [2024-08-01T01:21:54.827Z] variation: NoOptions [2024-08-01T01:21:54.827Z] JVM_OPTIONS: [2024-08-01T01:21:54.827Z] { \ [2024-08-01T01:21:54.827Z] echo ""; echo "TEST SETUP:"; \ [2024-08-01T01:21:54.827Z] echo "Nothing to be done for setup."; \ [2024-08-01T01:21:54.827Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17224746751898/renaissance-movie-lens_0"; \ [2024-08-01T01:21:54.827Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17224746751898/renaissance-movie-lens_0"; \ [2024-08-01T01:21:54.827Z] echo ""; echo "TESTING:"; \ [2024-08-01T01:21:54.827Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux_testList_0/jdkbinary/j2sdk-image/jdk-17.0.13+1/bin/..//bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17224746751898/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-08-01T01:21:54.827Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17224746751898/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-01T01:21:54.827Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-01T01:21:54.827Z] echo "Nothing to be done for teardown."; \ [2024-08-01T01:21:54.827Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux_testList_0/aqa-tests/TKG/../TKG/output_17224746751898/TestTargetResult"; [2024-08-01T01:21:54.827Z] [2024-08-01T01:21:54.827Z] TEST SETUP: [2024-08-01T01:21:54.827Z] Nothing to be done for setup. [2024-08-01T01:21:54.827Z] [2024-08-01T01:21:54.827Z] TESTING: [2024-08-01T01:21:57.040Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-01T01:21:59.275Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads. [2024-08-01T01:22:02.425Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-01T01:22:02.425Z] Training: 60056, validation: 20285, test: 19854 [2024-08-01T01:22:02.425Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-01T01:22:02.425Z] GC before operation: completed in 69.447 ms, heap usage 74.691 MB -> 37.734 MB. [2024-08-01T01:22:10.069Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T01:22:14.150Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T01:22:17.257Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T01:22:19.496Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T01:22:21.717Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T01:22:23.141Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T01:22:25.365Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T01:22:28.151Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T01:22:28.151Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-01T01:22:28.151Z] The best model improves the baseline by 14.43%. [2024-08-01T01:22:28.151Z] Movies recommended for you: [2024-08-01T01:22:28.151Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T01:22:28.151Z] There is no way to check that no silent failure occurred. [2024-08-01T01:22:28.151Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (25391.713 ms) ====== [2024-08-01T01:22:28.151Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-01T01:22:28.151Z] GC before operation: completed in 61.010 ms, heap usage 517.084 MB -> 58.200 MB. [2024-08-01T01:22:31.233Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T01:22:34.351Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T01:22:36.564Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T01:22:39.676Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T01:22:41.108Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T01:22:42.571Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T01:22:43.989Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T01:22:46.213Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T01:22:46.213Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-01T01:22:46.213Z] The best model improves the baseline by 14.43%. [2024-08-01T01:22:46.213Z] Movies recommended for you: [2024-08-01T01:22:46.213Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T01:22:46.213Z] There is no way to check that no silent failure occurred. [2024-08-01T01:22:46.213Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (18194.206 ms) ====== [2024-08-01T01:22:46.213Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-01T01:22:46.213Z] GC before operation: completed in 69.895 ms, heap usage 491.460 MB -> 54.940 MB. [2024-08-01T01:22:49.291Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T01:22:52.379Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T01:22:55.473Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T01:22:57.708Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T01:22:59.142Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T01:23:00.579Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T01:23:01.998Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T01:23:03.434Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T01:23:04.115Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-01T01:23:04.115Z] The best model improves the baseline by 14.43%. [2024-08-01T01:23:04.115Z] Movies recommended for you: [2024-08-01T01:23:04.115Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T01:23:04.115Z] There is no way to check that no silent failure occurred. [2024-08-01T01:23:04.115Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17691.645 ms) ====== [2024-08-01T01:23:04.115Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-01T01:23:04.115Z] GC before operation: completed in 56.730 ms, heap usage 171.252 MB -> 51.960 MB. [2024-08-01T01:23:06.342Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T01:23:09.449Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T01:23:11.701Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T01:23:13.935Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T01:23:15.384Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T01:23:16.806Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T01:23:18.250Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T01:23:19.672Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T01:23:19.672Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-01T01:23:19.672Z] The best model improves the baseline by 14.43%. [2024-08-01T01:23:19.672Z] Movies recommended for you: [2024-08-01T01:23:19.673Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T01:23:19.673Z] There is no way to check that no silent failure occurred. [2024-08-01T01:23:19.673Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (15777.080 ms) ====== [2024-08-01T01:23:19.673Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-01T01:23:19.673Z] GC before operation: completed in 77.590 ms, heap usage 214.708 MB -> 52.302 MB. [2024-08-01T01:23:22.780Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T01:23:25.009Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T01:23:27.230Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T01:23:29.909Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T01:23:31.350Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T01:23:32.057Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T01:23:34.287Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T01:23:34.974Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T01:23:35.663Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-01T01:23:35.663Z] The best model improves the baseline by 14.43%. [2024-08-01T01:23:35.663Z] Movies recommended for you: [2024-08-01T01:23:35.663Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T01:23:35.663Z] There is no way to check that no silent failure occurred. [2024-08-01T01:23:35.663Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15765.707 ms) ====== [2024-08-01T01:23:35.663Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-01T01:23:35.663Z] GC before operation: completed in 60.349 ms, heap usage 215.100 MB -> 55.650 MB. [2024-08-01T01:23:38.748Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T01:23:40.961Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T01:23:43.202Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T01:23:45.422Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T01:23:46.840Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T01:23:48.260Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T01:23:49.759Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T01:23:51.219Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T01:23:51.219Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-01T01:23:51.219Z] The best model improves the baseline by 14.43%. [2024-08-01T01:23:51.219Z] Movies recommended for you: [2024-08-01T01:23:51.219Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T01:23:51.219Z] There is no way to check that no silent failure occurred. [2024-08-01T01:23:51.219Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15559.588 ms) ====== [2024-08-01T01:23:51.219Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-01T01:23:51.219Z] GC before operation: completed in 83.433 ms, heap usage 214.279 MB -> 52.408 MB. [2024-08-01T01:23:54.319Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T01:23:56.563Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T01:23:58.801Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T01:24:01.038Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T01:24:01.722Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T01:24:03.133Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T01:24:04.569Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T01:24:05.997Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T01:24:05.997Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-01T01:24:06.679Z] The best model improves the baseline by 14.43%. [2024-08-01T01:24:06.679Z] Movies recommended for you: [2024-08-01T01:24:06.679Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T01:24:06.679Z] There is no way to check that no silent failure occurred. [2024-08-01T01:24:06.679Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15111.126 ms) ====== [2024-08-01T01:24:06.679Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-01T01:24:06.679Z] GC before operation: completed in 65.437 ms, heap usage 601.050 MB -> 56.016 MB. [2024-08-01T01:24:08.896Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T01:24:11.123Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T01:24:13.362Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T01:24:15.593Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T01:24:17.000Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T01:24:18.409Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T01:24:19.818Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T01:24:21.234Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T01:24:21.911Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-01T01:24:21.911Z] The best model improves the baseline by 14.43%. [2024-08-01T01:24:21.911Z] Movies recommended for you: [2024-08-01T01:24:21.911Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T01:24:21.911Z] There is no way to check that no silent failure occurred. [2024-08-01T01:24:21.911Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15214.245 ms) ====== [2024-08-01T01:24:21.911Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-01T01:24:21.911Z] GC before operation: completed in 61.663 ms, heap usage 426.862 MB -> 53.060 MB. [2024-08-01T01:24:24.119Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T01:24:26.341Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T01:24:29.109Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T01:24:31.357Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T01:24:32.802Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T01:24:33.486Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T01:24:34.915Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T01:24:36.352Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T01:24:37.025Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-01T01:24:37.025Z] The best model improves the baseline by 14.43%. [2024-08-01T01:24:37.025Z] Movies recommended for you: [2024-08-01T01:24:37.025Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T01:24:37.025Z] There is no way to check that no silent failure occurred. [2024-08-01T01:24:37.025Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15106.544 ms) ====== [2024-08-01T01:24:37.025Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-01T01:24:37.025Z] GC before operation: completed in 89.204 ms, heap usage 289.326 MB -> 52.712 MB. [2024-08-01T01:24:39.244Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T01:24:42.338Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T01:24:44.531Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T01:24:46.713Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T01:24:48.127Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T01:24:49.528Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T01:24:50.937Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T01:24:52.347Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T01:24:52.347Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-01T01:24:52.347Z] The best model improves the baseline by 14.43%. [2024-08-01T01:24:52.347Z] Movies recommended for you: [2024-08-01T01:24:52.347Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T01:24:52.347Z] There is no way to check that no silent failure occurred. [2024-08-01T01:24:52.347Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15392.142 ms) ====== [2024-08-01T01:24:52.347Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-01T01:24:52.347Z] GC before operation: completed in 75.152 ms, heap usage 182.081 MB -> 52.772 MB. [2024-08-01T01:24:55.403Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T01:24:57.601Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T01:24:59.887Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T01:25:02.069Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T01:25:03.482Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T01:25:04.906Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T01:25:06.314Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T01:25:07.769Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T01:25:07.769Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-01T01:25:07.769Z] The best model improves the baseline by 14.43%. [2024-08-01T01:25:08.442Z] Movies recommended for you: [2024-08-01T01:25:08.442Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T01:25:08.442Z] There is no way to check that no silent failure occurred. [2024-08-01T01:25:08.442Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15701.210 ms) ====== [2024-08-01T01:25:08.442Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-01T01:25:08.442Z] GC before operation: completed in 63.196 ms, heap usage 354.990 MB -> 52.553 MB. [2024-08-01T01:25:10.639Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T01:25:12.844Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T01:25:15.044Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T01:25:17.263Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T01:25:18.667Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T01:25:20.074Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T01:25:22.266Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T01:25:22.954Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T01:25:23.636Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-01T01:25:23.636Z] The best model improves the baseline by 14.43%. [2024-08-01T01:25:23.636Z] Movies recommended for you: [2024-08-01T01:25:23.636Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T01:25:23.637Z] There is no way to check that no silent failure occurred. [2024-08-01T01:25:23.637Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15354.489 ms) ====== [2024-08-01T01:25:23.637Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-01T01:25:23.637Z] GC before operation: completed in 82.900 ms, heap usage 548.827 MB -> 56.236 MB. [2024-08-01T01:25:26.701Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T01:25:29.352Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T01:25:30.763Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T01:25:32.963Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T01:25:34.373Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T01:25:35.798Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T01:25:37.213Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T01:25:39.406Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T01:25:39.406Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-01T01:25:39.406Z] The best model improves the baseline by 14.43%. [2024-08-01T01:25:39.406Z] Movies recommended for you: [2024-08-01T01:25:39.406Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T01:25:39.406Z] There is no way to check that no silent failure occurred. [2024-08-01T01:25:39.406Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15870.977 ms) ====== [2024-08-01T01:25:39.406Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-01T01:25:39.406Z] GC before operation: completed in 58.699 ms, heap usage 505.877 MB -> 56.315 MB. [2024-08-01T01:25:42.463Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T01:25:44.650Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T01:25:46.862Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T01:25:49.079Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T01:25:49.859Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T01:25:51.274Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T01:25:52.681Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T01:25:54.102Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T01:25:54.102Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-01T01:25:54.102Z] The best model improves the baseline by 14.43%. [2024-08-01T01:25:54.776Z] Movies recommended for you: [2024-08-01T01:25:54.776Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T01:25:54.776Z] There is no way to check that no silent failure occurred. [2024-08-01T01:25:54.776Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14868.377 ms) ====== [2024-08-01T01:25:54.776Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-01T01:25:54.776Z] GC before operation: completed in 87.202 ms, heap usage 402.188 MB -> 52.844 MB. [2024-08-01T01:25:56.986Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T01:25:59.191Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T01:26:01.382Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T01:26:03.589Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T01:26:05.044Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T01:26:06.462Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T01:26:07.863Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T01:26:09.274Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T01:26:09.274Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-01T01:26:09.965Z] The best model improves the baseline by 14.43%. [2024-08-01T01:26:09.965Z] Movies recommended for you: [2024-08-01T01:26:09.965Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T01:26:09.965Z] There is no way to check that no silent failure occurred. [2024-08-01T01:26:09.965Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (15197.518 ms) ====== [2024-08-01T01:26:09.965Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-01T01:26:09.965Z] GC before operation: completed in 81.087 ms, heap usage 342.789 MB -> 52.959 MB. [2024-08-01T01:26:12.164Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T01:26:14.375Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T01:26:16.567Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T01:26:18.891Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T01:26:20.314Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T01:26:21.735Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T01:26:23.151Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T01:26:24.573Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T01:26:25.253Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-01T01:26:25.253Z] The best model improves the baseline by 14.43%. [2024-08-01T01:26:25.253Z] Movies recommended for you: [2024-08-01T01:26:25.253Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T01:26:25.254Z] There is no way to check that no silent failure occurred. [2024-08-01T01:26:25.254Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15293.141 ms) ====== [2024-08-01T01:26:25.254Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-01T01:26:25.254Z] GC before operation: completed in 86.519 ms, heap usage 379.533 MB -> 53.157 MB. [2024-08-01T01:26:27.444Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T01:26:29.874Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T01:26:32.123Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T01:26:34.321Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T01:26:35.730Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T01:26:37.132Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T01:26:38.540Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T01:26:39.957Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T01:26:39.958Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-01T01:26:39.958Z] The best model improves the baseline by 14.43%. [2024-08-01T01:26:39.958Z] Movies recommended for you: [2024-08-01T01:26:39.958Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T01:26:39.958Z] There is no way to check that no silent failure occurred. [2024-08-01T01:26:39.958Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14882.524 ms) ====== [2024-08-01T01:26:39.958Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-01T01:26:39.958Z] GC before operation: completed in 63.194 ms, heap usage 308.910 MB -> 52.812 MB. [2024-08-01T01:26:43.035Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T01:26:45.281Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T01:26:47.499Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T01:26:49.751Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T01:26:50.425Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T01:26:51.830Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T01:26:53.229Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T01:26:54.639Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T01:26:55.324Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-01T01:26:55.324Z] The best model improves the baseline by 14.43%. [2024-08-01T01:26:55.324Z] Movies recommended for you: [2024-08-01T01:26:55.324Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T01:26:55.324Z] There is no way to check that no silent failure occurred. [2024-08-01T01:26:55.324Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (15019.585 ms) ====== [2024-08-01T01:26:55.324Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-01T01:26:55.324Z] GC before operation: completed in 82.072 ms, heap usage 287.353 MB -> 52.891 MB. [2024-08-01T01:26:57.531Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T01:27:00.603Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T01:27:02.049Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T01:27:04.251Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T01:27:05.665Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T01:27:07.076Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T01:27:08.512Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T01:27:09.940Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T01:27:09.940Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-01T01:27:09.940Z] The best model improves the baseline by 14.43%. [2024-08-01T01:27:10.620Z] Movies recommended for you: [2024-08-01T01:27:10.621Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T01:27:10.621Z] There is no way to check that no silent failure occurred. [2024-08-01T01:27:10.621Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (15027.582 ms) ====== [2024-08-01T01:27:10.621Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-01T01:27:10.621Z] GC before operation: completed in 82.846 ms, heap usage 235.844 MB -> 53.004 MB. [2024-08-01T01:27:12.824Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T01:27:15.025Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T01:27:17.235Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T01:27:19.439Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T01:27:20.875Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T01:27:22.280Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T01:27:23.688Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T01:27:25.111Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T01:27:25.111Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2024-08-01T01:27:25.111Z] The best model improves the baseline by 14.43%. [2024-08-01T01:27:25.111Z] Movies recommended for you: [2024-08-01T01:27:25.111Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T01:27:25.111Z] There is no way to check that no silent failure occurred. [2024-08-01T01:27:25.111Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (15003.116 ms) ====== [2024-08-01T01:27:26.511Z] ----------------------------------- [2024-08-01T01:27:26.511Z] renaissance-movie-lens_0_PASSED [2024-08-01T01:27:26.511Z] ----------------------------------- [2024-08-01T01:27:26.511Z] [2024-08-01T01:27:26.511Z] TEST TEARDOWN: [2024-08-01T01:27:26.511Z] Nothing to be done for teardown. [2024-08-01T01:27:26.511Z] renaissance-movie-lens_0 Finish Time: Wed Jul 31 20:27:26 2024 Epoch Time (ms): 1722475646163