[2025-02-13T21:59:30.566Z] Running test renaissance-movie-lens_0 ... [2025-02-13T21:59:30.566Z] =============================================== [2025-02-13T21:59:30.566Z] renaissance-movie-lens_0 Start Time: Thu Feb 13 21:59:29 2025 Epoch Time (ms): 1739483969829 [2025-02-13T21:59:30.566Z] variation: NoOptions [2025-02-13T21:59:30.566Z] JVM_OPTIONS: [2025-02-13T21:59:30.566Z] { \ [2025-02-13T21:59:30.566Z] echo ""; echo "TEST SETUP:"; \ [2025-02-13T21:59:30.566Z] echo "Nothing to be done for setup."; \ [2025-02-13T21:59:30.566Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17394828226395/renaissance-movie-lens_0"; \ [2025-02-13T21:59:30.566Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17394828226395/renaissance-movie-lens_0"; \ [2025-02-13T21:59:30.566Z] echo ""; echo "TESTING:"; \ [2025-02-13T21:59:30.566Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/jdkbinary/j2sdk-image/bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17394828226395/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-02-13T21:59:30.566Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17394828226395/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-02-13T21:59:30.566Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-02-13T21:59:30.566Z] echo "Nothing to be done for teardown."; \ [2025-02-13T21:59:30.566Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17394828226395/TestTargetResult"; [2025-02-13T21:59:30.566Z] [2025-02-13T21:59:30.566Z] TEST SETUP: [2025-02-13T21:59:30.566Z] Nothing to be done for setup. [2025-02-13T21:59:30.566Z] [2025-02-13T21:59:30.566Z] TESTING: [2025-02-13T21:59:36.246Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2025-02-13T21:59:39.719Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 24) threads. [2025-02-13T21:59:45.407Z] Got 100004 ratings from 671 users on 9066 movies. [2025-02-13T21:59:46.188Z] Training: 60056, validation: 20285, test: 19854 [2025-02-13T21:59:46.188Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-02-13T21:59:46.188Z] GC before operation: completed in 192.910 ms, heap usage 229.340 MB -> 26.612 MB. [2025-02-13T21:59:56.194Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:00:00.725Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:00:06.528Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:00:11.049Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:00:13.550Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:00:16.052Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:00:18.569Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:00:21.073Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:00:21.852Z] 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. [2025-02-13T22:00:21.853Z] The best model improves the baseline by 14.43%. [2025-02-13T22:00:21.853Z] Movies recommended for you: [2025-02-13T22:00:21.853Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:00:21.853Z] There is no way to check that no silent failure occurred. [2025-02-13T22:00:21.853Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (35729.431 ms) ====== [2025-02-13T22:00:21.853Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-02-13T22:00:22.632Z] GC before operation: completed in 300.406 ms, heap usage 165.645 MB -> 48.846 MB. [2025-02-13T22:00:27.336Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:00:31.859Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:00:36.380Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:00:40.903Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:00:42.528Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:00:45.031Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:00:47.726Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:00:50.233Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:00:51.014Z] 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. [2025-02-13T22:00:51.014Z] The best model improves the baseline by 14.43%. [2025-02-13T22:00:51.014Z] Movies recommended for you: [2025-02-13T22:00:51.014Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:00:51.014Z] There is no way to check that no silent failure occurred. [2025-02-13T22:00:51.014Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (28643.675 ms) ====== [2025-02-13T22:00:51.014Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-02-13T22:00:51.014Z] GC before operation: completed in 231.609 ms, heap usage 244.195 MB -> 43.670 MB. [2025-02-13T22:00:55.529Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:01:00.046Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:01:04.587Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:01:09.108Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:01:10.718Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:01:13.219Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:01:15.722Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:01:18.245Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:01:19.026Z] 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. [2025-02-13T22:01:19.026Z] The best model improves the baseline by 14.43%. [2025-02-13T22:01:19.026Z] Movies recommended for you: [2025-02-13T22:01:19.026Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:01:19.026Z] There is no way to check that no silent failure occurred. [2025-02-13T22:01:19.026Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (27663.476 ms) ====== [2025-02-13T22:01:19.026Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-02-13T22:01:19.026Z] GC before operation: completed in 260.320 ms, heap usage 174.091 MB -> 42.501 MB. [2025-02-13T22:01:23.547Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:01:28.062Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:01:32.585Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:01:36.053Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:01:38.558Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:01:41.069Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:01:43.993Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:01:46.517Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:01:46.517Z] 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. [2025-02-13T22:01:46.517Z] The best model improves the baseline by 14.43%. [2025-02-13T22:01:46.517Z] Movies recommended for you: [2025-02-13T22:01:46.517Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:01:46.517Z] There is no way to check that no silent failure occurred. [2025-02-13T22:01:46.517Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (27452.921 ms) ====== [2025-02-13T22:01:46.517Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-02-13T22:01:46.517Z] GC before operation: completed in 260.305 ms, heap usage 210.531 MB -> 44.986 MB. [2025-02-13T22:01:51.035Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:01:55.566Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:02:00.082Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:02:04.598Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:02:06.208Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:02:08.717Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:02:11.273Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:02:13.782Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:02:13.782Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2025-02-13T22:02:13.782Z] The best model improves the baseline by 14.43%. [2025-02-13T22:02:14.568Z] Movies recommended for you: [2025-02-13T22:02:14.568Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:02:14.568Z] There is no way to check that no silent failure occurred. [2025-02-13T22:02:14.568Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (27405.852 ms) ====== [2025-02-13T22:02:14.568Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-02-13T22:02:14.568Z] GC before operation: completed in 250.244 ms, heap usage 86.392 MB -> 63.119 MB. [2025-02-13T22:02:19.079Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:02:23.613Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:02:28.152Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:02:31.621Z] RMSE (validation) = 1.0045407704488025 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:02:34.127Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:02:36.633Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:02:39.140Z] RMSE (validation) = 0.9275717388537592 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:02:41.651Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:02:42.433Z] 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. [2025-02-13T22:02:42.433Z] The best model improves the baseline by 14.43%. [2025-02-13T22:02:42.433Z] Movies recommended for you: [2025-02-13T22:02:42.433Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:02:42.433Z] There is no way to check that no silent failure occurred. [2025-02-13T22:02:42.433Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (27931.534 ms) ====== [2025-02-13T22:02:42.433Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-02-13T22:02:42.433Z] GC before operation: completed in 206.522 ms, heap usage 326.031 MB -> 54.680 MB. [2025-02-13T22:02:46.947Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:02:51.677Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:02:55.167Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:02:59.694Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:03:02.202Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:03:04.704Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:03:07.205Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:03:09.713Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:03:09.713Z] 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. [2025-02-13T22:03:09.713Z] The best model improves the baseline by 14.43%. [2025-02-13T22:03:09.713Z] Movies recommended for you: [2025-02-13T22:03:09.713Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:03:09.713Z] There is no way to check that no silent failure occurred. [2025-02-13T22:03:09.713Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (27373.634 ms) ====== [2025-02-13T22:03:09.713Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-02-13T22:03:10.498Z] GC before operation: completed in 259.952 ms, heap usage 421.608 MB -> 62.749 MB. [2025-02-13T22:03:15.022Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:03:18.488Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:03:23.019Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:03:27.549Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:03:30.062Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:03:31.685Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:03:35.157Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:03:36.770Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:03:37.551Z] 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. [2025-02-13T22:03:37.551Z] The best model improves the baseline by 14.43%. [2025-02-13T22:03:37.551Z] Movies recommended for you: [2025-02-13T22:03:37.551Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:03:37.551Z] There is no way to check that no silent failure occurred. [2025-02-13T22:03:37.551Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (27300.485 ms) ====== [2025-02-13T22:03:37.551Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-02-13T22:03:37.551Z] GC before operation: completed in 219.350 ms, heap usage 324.810 MB -> 74.518 MB. [2025-02-13T22:03:42.072Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:03:46.596Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:03:51.139Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:03:54.611Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:03:57.297Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:03:59.812Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:04:02.321Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:04:04.837Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:04:04.837Z] 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. [2025-02-13T22:04:04.837Z] The best model improves the baseline by 14.43%. [2025-02-13T22:04:05.619Z] Movies recommended for you: [2025-02-13T22:04:05.619Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:04:05.619Z] There is no way to check that no silent failure occurred. [2025-02-13T22:04:05.619Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (27557.953 ms) ====== [2025-02-13T22:04:05.619Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-02-13T22:04:05.619Z] GC before operation: completed in 217.700 ms, heap usage 347.821 MB -> 51.256 MB. [2025-02-13T22:04:10.145Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:04:14.660Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:04:19.195Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:04:22.665Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:04:25.170Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:04:27.676Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:04:30.188Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:04:32.696Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:04:32.696Z] 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. [2025-02-13T22:04:32.696Z] The best model improves the baseline by 14.43%. [2025-02-13T22:04:33.477Z] Movies recommended for you: [2025-02-13T22:04:33.477Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:04:33.477Z] There is no way to check that no silent failure occurred. [2025-02-13T22:04:33.477Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (27611.555 ms) ====== [2025-02-13T22:04:33.477Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-02-13T22:04:33.477Z] GC before operation: completed in 276.889 ms, heap usage 329.090 MB -> 74.683 MB. [2025-02-13T22:04:37.997Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:04:42.547Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:04:47.078Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:04:50.554Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:04:53.061Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:04:55.562Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:04:59.028Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:05:00.659Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:05:01.446Z] 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. [2025-02-13T22:05:01.446Z] The best model improves the baseline by 14.43%. [2025-02-13T22:05:01.446Z] Movies recommended for you: [2025-02-13T22:05:01.446Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:05:01.446Z] There is no way to check that no silent failure occurred. [2025-02-13T22:05:01.446Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (28132.337 ms) ====== [2025-02-13T22:05:01.446Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-02-13T22:05:01.446Z] GC before operation: completed in 219.197 ms, heap usage 214.785 MB -> 50.713 MB. [2025-02-13T22:05:05.985Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:05:10.506Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:05:15.027Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:05:19.560Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:05:22.079Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:05:24.760Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:05:26.387Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:05:28.892Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:05:29.672Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2025-02-13T22:05:29.672Z] The best model improves the baseline by 14.43%. [2025-02-13T22:05:29.672Z] Movies recommended for you: [2025-02-13T22:05:29.672Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:05:29.673Z] There is no way to check that no silent failure occurred. [2025-02-13T22:05:29.673Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (27774.294 ms) ====== [2025-02-13T22:05:29.673Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-02-13T22:05:29.673Z] GC before operation: completed in 207.314 ms, heap usage 402.614 MB -> 74.447 MB. [2025-02-13T22:05:34.200Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:05:38.744Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:05:43.265Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:05:47.790Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:05:49.403Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:05:51.920Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:05:54.433Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:05:56.935Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:05:57.716Z] 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. [2025-02-13T22:05:57.716Z] The best model improves the baseline by 14.43%. [2025-02-13T22:05:57.716Z] Movies recommended for you: [2025-02-13T22:05:57.716Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:05:57.716Z] There is no way to check that no silent failure occurred. [2025-02-13T22:05:57.716Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (27813.928 ms) ====== [2025-02-13T22:05:57.716Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-02-13T22:05:57.716Z] GC before operation: completed in 209.251 ms, heap usage 438.522 MB -> 74.639 MB. [2025-02-13T22:06:02.239Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:06:06.805Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:06:11.330Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:06:15.866Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:06:17.484Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:06:19.988Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:06:23.465Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:06:26.000Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:06:26.000Z] 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. [2025-02-13T22:06:26.000Z] The best model improves the baseline by 14.43%. [2025-02-13T22:06:26.000Z] Movies recommended for you: [2025-02-13T22:06:26.000Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:06:26.000Z] There is no way to check that no silent failure occurred. [2025-02-13T22:06:26.000Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (28381.189 ms) ====== [2025-02-13T22:06:26.000Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-02-13T22:06:26.784Z] GC before operation: completed in 258.469 ms, heap usage 225.546 MB -> 51.040 MB. [2025-02-13T22:06:30.250Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:06:34.778Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:06:39.300Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:06:43.839Z] RMSE (validation) = 1.0045407704488025 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:06:46.350Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:06:48.855Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:06:51.381Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:06:53.890Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:06:53.890Z] 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. [2025-02-13T22:06:53.890Z] The best model improves the baseline by 14.43%. [2025-02-13T22:06:53.890Z] Movies recommended for you: [2025-02-13T22:06:53.890Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:06:53.890Z] There is no way to check that no silent failure occurred. [2025-02-13T22:06:53.890Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (27609.164 ms) ====== [2025-02-13T22:06:53.890Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-02-13T22:06:53.890Z] GC before operation: completed in 237.042 ms, heap usage 406.645 MB -> 74.931 MB. [2025-02-13T22:06:58.413Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:07:02.950Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:07:07.476Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:07:12.126Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:07:14.629Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:07:17.140Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:07:19.657Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:07:22.166Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:07:22.166Z] 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. [2025-02-13T22:07:22.166Z] The best model improves the baseline by 14.43%. [2025-02-13T22:07:22.166Z] Movies recommended for you: [2025-02-13T22:07:22.166Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:07:22.166Z] There is no way to check that no silent failure occurred. [2025-02-13T22:07:22.166Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (28017.888 ms) ====== [2025-02-13T22:07:22.166Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-02-13T22:07:22.166Z] GC before operation: completed in 227.803 ms, heap usage 411.554 MB -> 74.665 MB. [2025-02-13T22:07:26.702Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:07:31.228Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:07:35.754Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:07:40.280Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:07:42.810Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:07:45.334Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:07:47.838Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:07:50.355Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:07:50.355Z] 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. [2025-02-13T22:07:50.355Z] The best model improves the baseline by 14.43%. [2025-02-13T22:07:51.140Z] Movies recommended for you: [2025-02-13T22:07:51.140Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:07:51.140Z] There is no way to check that no silent failure occurred. [2025-02-13T22:07:51.140Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (28247.529 ms) ====== [2025-02-13T22:07:51.140Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-02-13T22:07:51.140Z] GC before operation: completed in 215.583 ms, heap usage 286.205 MB -> 51.459 MB. [2025-02-13T22:07:55.682Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:08:00.201Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:08:04.728Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:08:08.400Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:08:10.910Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:08:13.422Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:08:15.927Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:08:18.446Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:08:19.233Z] 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. [2025-02-13T22:08:19.233Z] The best model improves the baseline by 14.43%. [2025-02-13T22:08:19.233Z] Movies recommended for you: [2025-02-13T22:08:19.233Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:08:19.233Z] There is no way to check that no silent failure occurred. [2025-02-13T22:08:19.233Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (28228.348 ms) ====== [2025-02-13T22:08:19.233Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-02-13T22:08:19.233Z] GC before operation: completed in 297.499 ms, heap usage 328.176 MB -> 74.220 MB. [2025-02-13T22:08:23.769Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:08:28.285Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:08:32.805Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:08:37.324Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:08:39.827Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:08:42.355Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:08:45.834Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:08:48.383Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:08:48.383Z] 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. [2025-02-13T22:08:48.383Z] The best model improves the baseline by 14.43%. [2025-02-13T22:08:48.383Z] Movies recommended for you: [2025-02-13T22:08:48.383Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:08:48.383Z] There is no way to check that no silent failure occurred. [2025-02-13T22:08:48.383Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (28847.475 ms) ====== [2025-02-13T22:08:48.383Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-02-13T22:08:48.383Z] GC before operation: completed in 246.103 ms, heap usage 353.043 MB -> 74.595 MB. [2025-02-13T22:08:52.910Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-02-13T22:08:57.435Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-02-13T22:09:01.964Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-02-13T22:09:06.484Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-02-13T22:09:09.008Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-02-13T22:09:11.521Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-02-13T22:09:14.386Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-02-13T22:09:16.903Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-02-13T22:09:16.903Z] 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. [2025-02-13T22:09:16.903Z] The best model improves the baseline by 14.43%. [2025-02-13T22:09:17.682Z] Movies recommended for you: [2025-02-13T22:09:17.683Z] WARNING: This benchmark provides no result that can be validated. [2025-02-13T22:09:17.683Z] There is no way to check that no silent failure occurred. [2025-02-13T22:09:17.683Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (28699.535 ms) ====== [2025-02-13T22:09:19.294Z] ----------------------------------- [2025-02-13T22:09:19.294Z] renaissance-movie-lens_0_PASSED [2025-02-13T22:09:19.294Z] ----------------------------------- [2025-02-13T22:09:19.294Z] [2025-02-13T22:09:19.294Z] TEST TEARDOWN: [2025-02-13T22:09:19.294Z] Nothing to be done for teardown. [2025-02-13T22:09:19.294Z] renaissance-movie-lens_0 Finish Time: Thu Feb 13 22:09:18 2025 Epoch Time (ms): 1739484558806