[2025-11-13T00:08:32.036Z] Running test renaissance-movie-lens_0 ... [2025-11-13T00:08:32.342Z] =============================================== [2025-11-13T00:08:32.342Z] renaissance-movie-lens_0 Start Time: Thu Nov 13 00:08:32 2025 Epoch Time (ms): 1762992512145 [2025-11-13T00:08:32.342Z] variation: NoOptions [2025-11-13T00:08:32.669Z] JVM_OPTIONS: [2025-11-13T00:08:32.669Z] { \ [2025-11-13T00:08:32.670Z] echo ""; echo "TEST SETUP:"; \ [2025-11-13T00:08:32.670Z] echo "Nothing to be done for setup."; \ [2025-11-13T00:08:32.670Z] mkdir -p "C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17629898278816\\renaissance-movie-lens_0"; \ [2025-11-13T00:08:32.670Z] cd "C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17629898278816\\renaissance-movie-lens_0"; \ [2025-11-13T00:08:32.670Z] echo ""; echo "TESTING:"; \ [2025-11-13T00:08:32.670Z] "c:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/jdkbinary/j2sdk-image\\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 "C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17629898278816\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2025-11-13T00:08:32.670Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17629898278816\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-11-13T00:08:32.670Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-11-13T00:08:32.670Z] echo "Nothing to be done for teardown."; \ [2025-11-13T00:08:32.670Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17629898278816\\TestTargetResult"; [2025-11-13T00:08:32.670Z] [2025-11-13T00:08:32.670Z] TEST SETUP: [2025-11-13T00:08:32.670Z] Nothing to be done for setup. [2025-11-13T00:08:32.670Z] [2025-11-13T00:08:32.670Z] TESTING: [2025-11-13T00:08:48.609Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-11-13T00:09:00.463Z] 00:08:59.441 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (2797 KiB). The maximum recommended task size is 1000 KiB. [2025-11-13T00:09:05.538Z] Got 100004 ratings from 671 users on 9066 movies. [2025-11-13T00:09:06.236Z] Training: 60056, validation: 20285, test: 19854 [2025-11-13T00:09:06.236Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-11-13T00:09:06.236Z] GC before operation: completed in 191.275 ms, heap usage 294.234 MB -> 76.079 MB. [2025-11-13T00:09:22.588Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T00:09:32.012Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T00:09:41.159Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T00:09:47.395Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T00:09:52.217Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T00:09:56.019Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T00:10:00.943Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T00:10:04.896Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T00:10:05.723Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-13T00:10:06.814Z] The best model improves the baseline by 14.34%. [2025-11-13T00:10:06.814Z] Top recommended movies for user id 72: [2025-11-13T00:10:06.814Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-13T00:10:06.814Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-13T00:10:06.814Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-13T00:10:06.814Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-13T00:10:06.814Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-13T00:10:06.814Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (59880.013 ms) ====== [2025-11-13T00:10:06.814Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-11-13T00:10:07.134Z] GC before operation: completed in 295.013 ms, heap usage 235.627 MB -> 99.553 MB. [2025-11-13T00:10:14.422Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T00:10:21.707Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T00:10:28.885Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T00:10:35.073Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T00:10:39.808Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T00:10:43.764Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T00:10:48.421Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T00:10:52.234Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T00:10:53.179Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-13T00:10:53.179Z] The best model improves the baseline by 14.34%. [2025-11-13T00:10:53.179Z] Top recommended movies for user id 72: [2025-11-13T00:10:53.179Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-13T00:10:53.179Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-13T00:10:53.179Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-13T00:10:53.179Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-13T00:10:53.179Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-13T00:10:53.179Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (46774.179 ms) ====== [2025-11-13T00:10:53.179Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-11-13T00:10:53.518Z] GC before operation: completed in 281.226 ms, heap usage 184.283 MB -> 88.023 MB. [2025-11-13T00:11:00.772Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T00:11:07.969Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T00:11:15.023Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T00:11:20.877Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T00:11:24.653Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T00:11:29.288Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T00:11:32.969Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T00:11:37.629Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T00:11:37.629Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-13T00:11:37.629Z] The best model improves the baseline by 14.34%. [2025-11-13T00:11:38.429Z] Top recommended movies for user id 72: [2025-11-13T00:11:38.429Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-13T00:11:38.429Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-13T00:11:38.429Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-13T00:11:38.429Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-13T00:11:38.429Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-13T00:11:38.429Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (44610.113 ms) ====== [2025-11-13T00:11:38.429Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-11-13T00:11:38.767Z] GC before operation: completed in 225.778 ms, heap usage 458.830 MB -> 92.321 MB. [2025-11-13T00:11:45.901Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T00:11:51.752Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T00:11:58.889Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T00:12:06.115Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T00:12:09.074Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T00:12:13.679Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T00:12:17.374Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T00:12:21.099Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T00:12:21.918Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-13T00:12:21.918Z] The best model improves the baseline by 14.34%. [2025-11-13T00:12:21.918Z] Top recommended movies for user id 72: [2025-11-13T00:12:21.918Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-13T00:12:21.918Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-13T00:12:21.918Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-13T00:12:21.918Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-13T00:12:21.918Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-13T00:12:21.918Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (43712.254 ms) ====== [2025-11-13T00:12:21.918Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-11-13T00:12:22.282Z] GC before operation: completed in 237.389 ms, heap usage 213.385 MB -> 89.049 MB. [2025-11-13T00:12:29.367Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T00:12:36.577Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T00:12:43.678Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T00:12:49.437Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T00:12:54.052Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T00:12:57.696Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T00:13:02.367Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T00:13:06.149Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T00:13:06.149Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-13T00:13:06.149Z] The best model improves the baseline by 14.34%. [2025-11-13T00:13:06.564Z] Top recommended movies for user id 72: [2025-11-13T00:13:06.564Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-13T00:13:06.564Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-13T00:13:06.564Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-13T00:13:06.564Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-13T00:13:06.564Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-13T00:13:06.564Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (44384.750 ms) ====== [2025-11-13T00:13:06.564Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-11-13T00:13:07.148Z] GC before operation: completed in 210.122 ms, heap usage 184.700 MB -> 88.983 MB. [2025-11-13T00:13:14.313Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T00:13:21.365Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T00:13:27.177Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T00:13:34.279Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T00:13:37.917Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T00:13:41.583Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T00:13:45.298Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T00:13:49.953Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T00:13:49.953Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-13T00:13:49.953Z] The best model improves the baseline by 14.34%. [2025-11-13T00:13:50.574Z] Top recommended movies for user id 72: [2025-11-13T00:13:50.574Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-13T00:13:50.574Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-13T00:13:50.574Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-13T00:13:50.574Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-13T00:13:50.574Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-13T00:13:50.574Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (43487.662 ms) ====== [2025-11-13T00:13:50.574Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-11-13T00:13:50.574Z] GC before operation: completed in 227.368 ms, heap usage 185.214 MB -> 89.304 MB. [2025-11-13T00:13:57.663Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T00:14:04.984Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T00:14:10.907Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T00:14:18.051Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T00:14:21.763Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T00:14:25.452Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T00:14:30.689Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T00:14:34.343Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T00:14:35.110Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-13T00:14:35.110Z] The best model improves the baseline by 14.34%. [2025-11-13T00:14:35.110Z] Top recommended movies for user id 72: [2025-11-13T00:14:35.110Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-13T00:14:35.110Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-13T00:14:35.110Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-13T00:14:35.110Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-13T00:14:35.110Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-13T00:14:35.110Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (44650.871 ms) ====== [2025-11-13T00:14:35.110Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-11-13T00:14:35.701Z] GC before operation: completed in 175.773 ms, heap usage 312.530 MB -> 89.538 MB. [2025-11-13T00:14:42.778Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T00:14:48.508Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T00:14:55.665Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T00:15:02.742Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T00:15:06.570Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T00:15:10.264Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T00:15:13.997Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T00:15:17.835Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T00:15:18.276Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-13T00:15:18.276Z] The best model improves the baseline by 14.34%. [2025-11-13T00:15:18.276Z] Top recommended movies for user id 72: [2025-11-13T00:15:18.276Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-13T00:15:18.276Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-13T00:15:18.276Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-13T00:15:18.276Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-13T00:15:18.276Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-13T00:15:18.276Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (42936.885 ms) ====== [2025-11-13T00:15:18.276Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-11-13T00:15:18.837Z] GC before operation: completed in 219.900 ms, heap usage 247.097 MB -> 89.636 MB. [2025-11-13T00:15:25.987Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T00:15:31.862Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T00:15:37.812Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T00:15:44.920Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T00:15:47.773Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T00:15:52.721Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T00:15:56.435Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T00:16:00.209Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T00:16:00.992Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-13T00:16:00.992Z] The best model improves the baseline by 14.34%. [2025-11-13T00:16:01.473Z] Top recommended movies for user id 72: [2025-11-13T00:16:01.473Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-13T00:16:01.473Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-13T00:16:01.473Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-13T00:16:01.473Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-13T00:16:01.473Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-13T00:16:01.473Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (42702.223 ms) ====== [2025-11-13T00:16:01.473Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-11-13T00:16:01.473Z] GC before operation: completed in 193.190 ms, heap usage 400.998 MB -> 89.782 MB. [2025-11-13T00:16:08.552Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T00:16:14.368Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T00:16:21.656Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T00:16:27.509Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T00:16:31.148Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T00:16:34.897Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T00:16:38.755Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T00:16:42.624Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T00:16:42.957Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-13T00:16:42.957Z] The best model improves the baseline by 14.34%. [2025-11-13T00:16:43.509Z] Top recommended movies for user id 72: [2025-11-13T00:16:43.509Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-13T00:16:43.509Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-13T00:16:43.509Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-13T00:16:43.509Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-13T00:16:43.509Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-13T00:16:43.509Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (41899.230 ms) ====== [2025-11-13T00:16:43.509Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-11-13T00:16:43.509Z] GC before operation: completed in 159.845 ms, heap usage 216.555 MB -> 89.617 MB. [2025-11-13T00:16:50.640Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T00:16:56.463Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T00:17:03.711Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T00:17:10.916Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T00:17:14.355Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T00:17:18.166Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T00:17:23.078Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T00:17:26.049Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T00:17:26.773Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-13T00:17:26.773Z] The best model improves the baseline by 14.34%. [2025-11-13T00:17:27.293Z] Top recommended movies for user id 72: [2025-11-13T00:17:27.293Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-13T00:17:27.293Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-13T00:17:27.293Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-13T00:17:27.293Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-13T00:17:27.293Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-13T00:17:27.293Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (43599.664 ms) ====== [2025-11-13T00:17:27.293Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-11-13T00:17:27.293Z] GC before operation: completed in 162.630 ms, heap usage 441.589 MB -> 89.764 MB. [2025-11-13T00:17:34.456Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T00:17:40.278Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T00:17:47.386Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T00:17:53.156Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T00:17:56.841Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T00:18:00.626Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T00:18:05.332Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T00:18:09.152Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T00:18:09.152Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-13T00:18:09.794Z] The best model improves the baseline by 14.34%. [2025-11-13T00:18:09.794Z] Top recommended movies for user id 72: [2025-11-13T00:18:09.794Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-13T00:18:09.794Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-13T00:18:09.794Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-13T00:18:09.794Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-13T00:18:09.794Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-13T00:18:09.794Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (42341.221 ms) ====== [2025-11-13T00:18:09.794Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-11-13T00:18:10.120Z] GC before operation: completed in 157.049 ms, heap usage 247.195 MB -> 89.644 MB. [2025-11-13T00:18:17.207Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T00:18:22.951Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T00:18:30.023Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T00:18:35.850Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T00:18:39.605Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T00:18:43.782Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T00:18:47.468Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T00:18:51.185Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T00:18:51.569Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-13T00:18:51.921Z] The best model improves the baseline by 14.34%. [2025-11-13T00:18:51.922Z] Top recommended movies for user id 72: [2025-11-13T00:18:51.922Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-13T00:18:51.922Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-13T00:18:51.922Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-13T00:18:51.922Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-13T00:18:51.922Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-13T00:18:51.922Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (42262.441 ms) ====== [2025-11-13T00:18:51.922Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-11-13T00:18:52.576Z] GC before operation: completed in 168.458 ms, heap usage 247.413 MB -> 89.820 MB. [2025-11-13T00:19:00.045Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T00:19:05.811Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T00:19:13.259Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T00:19:19.047Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T00:19:22.731Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T00:19:26.516Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T00:19:30.208Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T00:19:33.871Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T00:19:34.653Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-13T00:19:34.653Z] The best model improves the baseline by 14.34%. [2025-11-13T00:19:34.653Z] Top recommended movies for user id 72: [2025-11-13T00:19:34.653Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-13T00:19:34.653Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-13T00:19:34.653Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-13T00:19:34.653Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-13T00:19:34.653Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-13T00:19:34.653Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (42280.231 ms) ====== [2025-11-13T00:19:34.653Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-11-13T00:19:34.989Z] GC before operation: completed in 164.973 ms, heap usage 220.752 MB -> 89.620 MB. [2025-11-13T00:19:42.149Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T00:19:48.079Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T00:19:53.983Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T00:20:01.105Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T00:20:04.029Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T00:20:07.718Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T00:20:12.352Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T00:20:15.994Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T00:20:15.994Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-13T00:20:15.994Z] The best model improves the baseline by 14.34%. [2025-11-13T00:20:16.645Z] Top recommended movies for user id 72: [2025-11-13T00:20:16.645Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-13T00:20:16.645Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-13T00:20:16.645Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-13T00:20:16.645Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-13T00:20:16.645Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-13T00:20:16.645Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (41772.483 ms) ====== [2025-11-13T00:20:16.645Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-11-13T00:20:16.965Z] GC before operation: completed in 162.999 ms, heap usage 367.520 MB -> 90.028 MB. [2025-11-13T00:20:24.072Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T00:20:29.789Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T00:20:35.541Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T00:20:42.669Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T00:20:45.523Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T00:20:49.433Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T00:20:53.561Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T00:20:57.407Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T00:20:58.370Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-13T00:20:58.370Z] The best model improves the baseline by 14.34%. [2025-11-13T00:20:58.370Z] Top recommended movies for user id 72: [2025-11-13T00:20:58.370Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-13T00:20:58.370Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-13T00:20:58.370Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-13T00:20:58.371Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-13T00:20:58.371Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-13T00:20:58.371Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (41412.496 ms) ====== [2025-11-13T00:20:58.371Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-11-13T00:20:58.742Z] GC before operation: completed in 164.442 ms, heap usage 170.156 MB -> 89.564 MB. [2025-11-13T00:21:04.587Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T00:21:11.699Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T00:21:18.851Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T00:21:24.603Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T00:21:28.346Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T00:21:32.609Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T00:21:36.313Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T00:21:40.146Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T00:21:40.478Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-13T00:21:40.478Z] The best model improves the baseline by 14.34%. [2025-11-13T00:21:41.045Z] Top recommended movies for user id 72: [2025-11-13T00:21:41.045Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-13T00:21:41.045Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-13T00:21:41.045Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-13T00:21:41.045Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-13T00:21:41.045Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-13T00:21:41.045Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (42721.427 ms) ====== [2025-11-13T00:21:41.045Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-11-13T00:21:41.045Z] GC before operation: completed in 158.151 ms, heap usage 315.191 MB -> 89.912 MB. [2025-11-13T00:21:48.195Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T00:21:54.001Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T00:22:01.136Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T00:22:06.906Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T00:22:10.516Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T00:22:15.258Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T00:22:18.953Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T00:22:22.793Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T00:22:22.793Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-13T00:22:22.793Z] The best model improves the baseline by 14.34%. [2025-11-13T00:22:23.347Z] Top recommended movies for user id 72: [2025-11-13T00:22:23.347Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-13T00:22:23.347Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-13T00:22:23.347Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-13T00:22:23.347Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-13T00:22:23.347Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-13T00:22:23.347Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (42148.324 ms) ====== [2025-11-13T00:22:23.347Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-11-13T00:22:23.347Z] GC before operation: completed in 161.995 ms, heap usage 222.346 MB -> 89.556 MB. [2025-11-13T00:22:30.427Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T00:22:36.290Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T00:22:43.390Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T00:22:49.182Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T00:22:52.879Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T00:22:56.521Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T00:23:00.226Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T00:23:03.872Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T00:23:04.226Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-13T00:23:04.226Z] The best model improves the baseline by 14.34%. [2025-11-13T00:23:04.610Z] Top recommended movies for user id 72: [2025-11-13T00:23:04.610Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-13T00:23:04.611Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-13T00:23:04.611Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-13T00:23:04.611Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-13T00:23:04.611Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-13T00:23:04.611Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (41336.351 ms) ====== [2025-11-13T00:23:04.611Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-11-13T00:23:05.157Z] GC before operation: completed in 196.932 ms, heap usage 116.147 MB -> 89.510 MB. [2025-11-13T00:23:12.280Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T00:23:19.367Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T00:23:25.120Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T00:23:30.861Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T00:23:34.522Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T00:23:38.197Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T00:23:41.929Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T00:23:45.628Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T00:23:46.382Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-13T00:23:46.723Z] The best model improves the baseline by 14.34%. [2025-11-13T00:23:47.052Z] Top recommended movies for user id 72: [2025-11-13T00:23:47.052Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-13T00:23:47.052Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-13T00:23:47.052Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-13T00:23:47.052Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-13T00:23:47.052Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-13T00:23:47.052Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (42078.674 ms) ====== [2025-11-13T00:23:47.727Z] ----------------------------------- [2025-11-13T00:23:47.727Z] renaissance-movie-lens_0_PASSED [2025-11-13T00:23:47.727Z] ----------------------------------- [2025-11-13T00:23:48.039Z] [2025-11-13T00:23:48.039Z] TEST TEARDOWN: [2025-11-13T00:23:48.039Z] Nothing to be done for teardown. [2025-11-13T00:23:48.039Z] renaissance-movie-lens_0 Finish Time: Thu Nov 13 00:23:47 2025 Epoch Time (ms): 1762993427972