[2025-05-28T21:14:56.000Z] Running test renaissance-movie-lens_0 ... [2025-05-28T21:14:56.000Z] =============================================== [2025-05-28T21:14:56.000Z] renaissance-movie-lens_0 Start Time: Wed May 28 21:14:55 2025 Epoch Time (ms): 1748466895387 [2025-05-28T21:14:56.000Z] variation: NoOptions [2025-05-28T21:14:56.000Z] JVM_OPTIONS: [2025-05-28T21:14:56.000Z] { \ [2025-05-28T21:14:56.000Z] echo ""; echo "TEST SETUP:"; \ [2025-05-28T21:14:56.000Z] echo "Nothing to be done for setup."; \ [2025-05-28T21:14:56.000Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_174846531254/renaissance-movie-lens_0"; \ [2025-05-28T21:14:56.000Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_174846531254/renaissance-movie-lens_0"; \ [2025-05-28T21:14:56.000Z] echo ""; echo "TESTING:"; \ [2025-05-28T21:14:56.000Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/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 "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_174846531254/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-05-28T21:14:56.000Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_174846531254/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-05-28T21:14:56.000Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-05-28T21:14:56.000Z] echo "Nothing to be done for teardown."; \ [2025-05-28T21:14:56.000Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_174846531254/TestTargetResult"; [2025-05-28T21:14:56.000Z] [2025-05-28T21:14:56.000Z] TEST SETUP: [2025-05-28T21:14:56.000Z] Nothing to be done for setup. [2025-05-28T21:14:56.000Z] [2025-05-28T21:14:56.000Z] TESTING: [2025-05-28T21:15:04.281Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-05-28T21:15:19.514Z] 21:15:17.550 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (2797 KiB). The maximum recommended task size is 1000 KiB. [2025-05-28T21:15:24.139Z] Got 100004 ratings from 671 users on 9066 movies. [2025-05-28T21:15:25.784Z] Training: 60056, validation: 20285, test: 19854 [2025-05-28T21:15:25.784Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-05-28T21:15:25.784Z] GC before operation: completed in 189.554 ms, heap usage 458.586 MB -> 75.818 MB. [2025-05-28T21:15:37.639Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:15:43.985Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:15:49.640Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:15:54.240Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:15:56.741Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:15:59.286Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:16:01.785Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:16:04.248Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:16:04.248Z] 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. [2025-05-28T21:16:05.018Z] The best model improves the baseline by 14.34%. [2025-05-28T21:16:05.018Z] Top recommended movies for user id 72: [2025-05-28T21:16:05.018Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T21:16:05.018Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T21:16:05.018Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T21:16:05.018Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T21:16:05.018Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T21:16:05.018Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (38923.081 ms) ====== [2025-05-28T21:16:05.018Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-05-28T21:16:05.018Z] GC before operation: completed in 246.034 ms, heap usage 604.788 MB -> 92.382 MB. [2025-05-28T21:16:09.513Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:16:13.969Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:16:17.361Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:16:20.789Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:16:22.396Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:16:25.107Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:16:27.560Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:16:30.061Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:16:30.062Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-05-28T21:16:30.062Z] The best model improves the baseline by 14.34%. [2025-05-28T21:16:30.062Z] Top recommended movies for user id 72: [2025-05-28T21:16:30.062Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T21:16:30.062Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T21:16:30.062Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T21:16:30.062Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T21:16:30.062Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T21:16:30.062Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (25091.887 ms) ====== [2025-05-28T21:16:30.062Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-05-28T21:16:30.894Z] GC before operation: completed in 255.648 ms, heap usage 166.100 MB -> 87.729 MB. [2025-05-28T21:16:34.359Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:16:37.770Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:16:42.285Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:16:45.686Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:16:47.262Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:16:49.754Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:16:51.337Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:16:53.812Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:16:54.586Z] 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. [2025-05-28T21:16:54.586Z] The best model improves the baseline by 14.34%. [2025-05-28T21:16:54.586Z] Top recommended movies for user id 72: [2025-05-28T21:16:54.586Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T21:16:54.586Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T21:16:54.586Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T21:16:54.586Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T21:16:54.586Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T21:16:54.586Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (24008.859 ms) ====== [2025-05-28T21:16:54.586Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-05-28T21:16:54.586Z] GC before operation: completed in 224.600 ms, heap usage 215.730 MB -> 88.455 MB. [2025-05-28T21:16:59.055Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:17:01.522Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:17:05.128Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:17:09.586Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:17:11.177Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:17:12.841Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:17:15.332Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:17:16.913Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:17:17.693Z] 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. [2025-05-28T21:17:17.693Z] The best model improves the baseline by 14.34%. [2025-05-28T21:17:17.693Z] Top recommended movies for user id 72: [2025-05-28T21:17:17.693Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T21:17:17.693Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T21:17:17.693Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T21:17:17.693Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T21:17:17.693Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T21:17:17.693Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (22785.465 ms) ====== [2025-05-28T21:17:17.693Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-05-28T21:17:17.693Z] GC before operation: completed in 215.400 ms, heap usage 404.967 MB -> 89.044 MB. [2025-05-28T21:17:21.112Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:17:24.549Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:17:27.945Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:17:31.353Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:17:32.933Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:17:35.405Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:17:36.981Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:17:38.600Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:17:39.365Z] 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. [2025-05-28T21:17:39.365Z] The best model improves the baseline by 14.34%. [2025-05-28T21:17:39.365Z] Top recommended movies for user id 72: [2025-05-28T21:17:39.365Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T21:17:39.365Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T21:17:39.365Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T21:17:39.365Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T21:17:39.365Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T21:17:39.365Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (21612.978 ms) ====== [2025-05-28T21:17:39.365Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-05-28T21:17:39.365Z] GC before operation: completed in 186.476 ms, heap usage 166.291 MB -> 88.608 MB. [2025-05-28T21:17:43.832Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:17:46.326Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:17:50.260Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:17:53.689Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:17:55.267Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:17:57.732Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:17:59.318Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:18:01.772Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:18:01.772Z] 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. [2025-05-28T21:18:01.772Z] The best model improves the baseline by 14.34%. [2025-05-28T21:18:01.772Z] Top recommended movies for user id 72: [2025-05-28T21:18:01.772Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T21:18:01.772Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T21:18:01.772Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T21:18:01.772Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T21:18:01.772Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T21:18:01.772Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (22220.399 ms) ====== [2025-05-28T21:18:01.772Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-05-28T21:18:01.772Z] GC before operation: completed in 195.960 ms, heap usage 190.607 MB -> 88.971 MB. [2025-05-28T21:18:05.171Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:18:08.568Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:18:12.001Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:18:15.409Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:18:17.012Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:18:19.477Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:18:21.941Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:18:23.525Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:18:23.525Z] 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. [2025-05-28T21:18:23.525Z] The best model improves the baseline by 14.34%. [2025-05-28T21:18:23.525Z] Top recommended movies for user id 72: [2025-05-28T21:18:23.525Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T21:18:23.525Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T21:18:23.525Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T21:18:23.525Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T21:18:23.525Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T21:18:23.525Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (21826.323 ms) ====== [2025-05-28T21:18:23.525Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-05-28T21:18:24.291Z] GC before operation: completed in 167.564 ms, heap usage 216.525 MB -> 88.993 MB. [2025-05-28T21:18:28.199Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:18:30.650Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:18:34.082Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:18:36.664Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:18:39.147Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:18:40.730Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:18:43.191Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:18:44.765Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:18:44.766Z] 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. [2025-05-28T21:18:44.766Z] The best model improves the baseline by 14.34%. [2025-05-28T21:18:44.766Z] Top recommended movies for user id 72: [2025-05-28T21:18:44.766Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T21:18:44.766Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T21:18:44.766Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T21:18:44.766Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T21:18:44.766Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T21:18:44.766Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (21034.959 ms) ====== [2025-05-28T21:18:44.766Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-05-28T21:18:45.528Z] GC before operation: completed in 200.186 ms, heap usage 495.270 MB -> 92.950 MB. [2025-05-28T21:18:48.935Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:18:51.388Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:18:54.830Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:18:58.235Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:18:59.817Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:19:01.396Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:19:02.974Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:19:05.443Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:19:05.443Z] 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. [2025-05-28T21:19:05.443Z] The best model improves the baseline by 14.34%. [2025-05-28T21:19:05.443Z] Top recommended movies for user id 72: [2025-05-28T21:19:05.443Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T21:19:05.443Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T21:19:05.443Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T21:19:05.443Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T21:19:05.443Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T21:19:05.443Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (20398.687 ms) ====== [2025-05-28T21:19:05.443Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-05-28T21:19:06.222Z] GC before operation: completed in 197.075 ms, heap usage 118.006 MB -> 88.972 MB. [2025-05-28T21:19:09.220Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:19:12.634Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:19:15.095Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:19:18.499Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:19:20.078Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:19:21.655Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:19:24.132Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:19:25.714Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:19:25.714Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-05-28T21:19:25.714Z] The best model improves the baseline by 14.34%. [2025-05-28T21:19:25.714Z] Top recommended movies for user id 72: [2025-05-28T21:19:25.714Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T21:19:25.714Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T21:19:25.714Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T21:19:25.714Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T21:19:25.714Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T21:19:25.714Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (20209.520 ms) ====== [2025-05-28T21:19:25.714Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-05-28T21:19:26.486Z] GC before operation: completed in 191.537 ms, heap usage 546.351 MB -> 93.124 MB. [2025-05-28T21:19:29.890Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:19:32.351Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:19:35.759Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:19:39.168Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:19:40.751Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:19:42.339Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:19:43.922Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:19:46.384Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:19:46.384Z] 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. [2025-05-28T21:19:46.384Z] The best model improves the baseline by 14.34%. [2025-05-28T21:19:46.385Z] Top recommended movies for user id 72: [2025-05-28T21:19:46.385Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T21:19:46.385Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T21:19:46.385Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T21:19:46.385Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T21:19:46.385Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T21:19:46.385Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (20162.725 ms) ====== [2025-05-28T21:19:46.385Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-05-28T21:19:46.385Z] GC before operation: completed in 177.793 ms, heap usage 409.357 MB -> 89.496 MB. [2025-05-28T21:19:49.800Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:19:52.511Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:19:55.917Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:19:58.379Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:19:59.960Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:20:02.413Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:20:04.000Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:20:05.585Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:20:06.356Z] 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. [2025-05-28T21:20:06.356Z] The best model improves the baseline by 14.34%. [2025-05-28T21:20:06.356Z] Top recommended movies for user id 72: [2025-05-28T21:20:06.356Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T21:20:06.356Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T21:20:06.356Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T21:20:06.356Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T21:20:06.356Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T21:20:06.356Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (19776.855 ms) ====== [2025-05-28T21:20:06.356Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-05-28T21:20:06.356Z] GC before operation: completed in 187.183 ms, heap usage 354.100 MB -> 89.642 MB. [2025-05-28T21:20:09.767Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:20:13.170Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:20:15.628Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:20:19.036Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:20:20.613Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:20:22.201Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:20:24.666Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:20:26.252Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:20:26.252Z] 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. [2025-05-28T21:20:26.252Z] The best model improves the baseline by 14.34%. [2025-05-28T21:20:27.042Z] Top recommended movies for user id 72: [2025-05-28T21:20:27.042Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T21:20:27.042Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T21:20:27.042Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T21:20:27.042Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T21:20:27.042Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T21:20:27.042Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (20072.949 ms) ====== [2025-05-28T21:20:27.042Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-05-28T21:20:27.042Z] GC before operation: completed in 180.364 ms, heap usage 310.030 MB -> 89.685 MB. [2025-05-28T21:20:29.774Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:20:33.182Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:20:35.636Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:20:39.043Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:20:40.624Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:20:42.205Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:20:44.674Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:20:46.266Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:20:46.267Z] 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. [2025-05-28T21:20:46.267Z] The best model improves the baseline by 14.34%. [2025-05-28T21:20:47.044Z] Top recommended movies for user id 72: [2025-05-28T21:20:47.044Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T21:20:47.044Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T21:20:47.044Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T21:20:47.044Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T21:20:47.044Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T21:20:47.044Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (19886.383 ms) ====== [2025-05-28T21:20:47.044Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-05-28T21:20:47.044Z] GC before operation: completed in 206.002 ms, heap usage 243.364 MB -> 89.300 MB. [2025-05-28T21:20:50.451Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:20:52.911Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:20:56.317Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:20:58.775Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:21:00.357Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:21:01.942Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:21:04.401Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:21:05.982Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:21:05.982Z] 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. [2025-05-28T21:21:05.982Z] The best model improves the baseline by 14.34%. [2025-05-28T21:21:06.749Z] Top recommended movies for user id 72: [2025-05-28T21:21:06.749Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T21:21:06.749Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T21:21:06.749Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T21:21:06.749Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T21:21:06.749Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T21:21:06.749Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (19542.720 ms) ====== [2025-05-28T21:21:06.749Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-05-28T21:21:06.749Z] GC before operation: completed in 172.794 ms, heap usage 203.113 MB -> 89.457 MB. [2025-05-28T21:21:10.686Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:21:13.150Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:21:16.567Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:21:19.021Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:21:20.600Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:21:23.057Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:21:24.656Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:21:26.238Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:21:27.042Z] 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. [2025-05-28T21:21:27.042Z] The best model improves the baseline by 14.34%. [2025-05-28T21:21:27.042Z] Top recommended movies for user id 72: [2025-05-28T21:21:27.042Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T21:21:27.042Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T21:21:27.042Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T21:21:27.042Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T21:21:27.042Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T21:21:27.042Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (20204.420 ms) ====== [2025-05-28T21:21:27.042Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-05-28T21:21:27.042Z] GC before operation: completed in 163.356 ms, heap usage 385.287 MB -> 89.590 MB. [2025-05-28T21:21:30.454Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:21:32.912Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:21:36.315Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:21:38.764Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:21:40.434Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:21:42.892Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:21:44.476Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:21:46.055Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:21:46.830Z] 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. [2025-05-28T21:21:46.830Z] The best model improves the baseline by 14.34%. [2025-05-28T21:21:46.830Z] Top recommended movies for user id 72: [2025-05-28T21:21:46.830Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T21:21:46.830Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T21:21:46.830Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T21:21:46.830Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T21:21:46.830Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T21:21:46.830Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (19745.107 ms) ====== [2025-05-28T21:21:46.830Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-05-28T21:21:46.830Z] GC before operation: completed in 169.436 ms, heap usage 217.292 MB -> 89.358 MB. [2025-05-28T21:21:50.240Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:21:53.222Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:21:55.691Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:21:59.105Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:22:00.690Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:22:02.270Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:22:03.848Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:22:05.433Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:22:06.214Z] 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. [2025-05-28T21:22:06.214Z] The best model improves the baseline by 14.34%. [2025-05-28T21:22:06.214Z] Top recommended movies for user id 72: [2025-05-28T21:22:06.214Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T21:22:06.214Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T21:22:06.214Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T21:22:06.214Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T21:22:06.214Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T21:22:06.214Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (19208.563 ms) ====== [2025-05-28T21:22:06.214Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-05-28T21:22:06.214Z] GC before operation: completed in 164.530 ms, heap usage 204.435 MB -> 89.218 MB. [2025-05-28T21:22:09.634Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:22:12.088Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:22:15.502Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:22:17.953Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:22:20.408Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:22:21.991Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:22:23.567Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:22:25.148Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:22:25.915Z] 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. [2025-05-28T21:22:25.915Z] The best model improves the baseline by 14.34%. [2025-05-28T21:22:25.915Z] Top recommended movies for user id 72: [2025-05-28T21:22:25.915Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T21:22:25.915Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T21:22:25.915Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T21:22:25.915Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T21:22:25.915Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T21:22:25.915Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (19634.197 ms) ====== [2025-05-28T21:22:25.915Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-05-28T21:22:25.915Z] GC before operation: completed in 183.899 ms, heap usage 112.357 MB -> 90.980 MB. [2025-05-28T21:22:29.324Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T21:22:32.295Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T21:22:35.709Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T21:22:38.169Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T21:22:39.783Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T21:22:41.364Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T21:22:42.943Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T21:22:44.518Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T21:22:45.284Z] 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. [2025-05-28T21:22:45.284Z] The best model improves the baseline by 14.34%. [2025-05-28T21:22:45.284Z] Top recommended movies for user id 72: [2025-05-28T21:22:45.284Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T21:22:45.284Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T21:22:45.284Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T21:22:45.284Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T21:22:45.284Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T21:22:45.284Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (19117.128 ms) ====== [2025-05-28T21:22:46.863Z] ----------------------------------- [2025-05-28T21:22:46.863Z] renaissance-movie-lens_0_PASSED [2025-05-28T21:22:46.863Z] ----------------------------------- [2025-05-28T21:22:46.863Z] [2025-05-28T21:22:46.863Z] TEST TEARDOWN: [2025-05-28T21:22:46.863Z] Nothing to be done for teardown. [2025-05-28T21:22:46.863Z] renaissance-movie-lens_0 Finish Time: Wed May 28 21:22:46 2025 Epoch Time (ms): 1748467366156