[2025-06-19T04:59:48.378Z] Running test renaissance-movie-lens_0 ... [2025-06-19T04:59:48.378Z] =============================================== [2025-06-19T04:59:48.378Z] renaissance-movie-lens_0 Start Time: Thu Jun 19 04:59:48 2025 Epoch Time (ms): 1750309188250 [2025-06-19T04:59:48.378Z] variation: NoOptions [2025-06-19T04:59:48.378Z] JVM_OPTIONS: [2025-06-19T04:59:48.378Z] { \ [2025-06-19T04:59:48.378Z] echo ""; echo "TEST SETUP:"; \ [2025-06-19T04:59:48.378Z] echo "Nothing to be done for setup."; \ [2025-06-19T04:59:48.378Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17503075588361/renaissance-movie-lens_0"; \ [2025-06-19T04:59:48.378Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17503075588361/renaissance-movie-lens_0"; \ [2025-06-19T04:59:48.378Z] echo ""; echo "TESTING:"; \ [2025-06-19T04:59:48.378Z] "/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_17503075588361/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-06-19T04:59:48.378Z] 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_17503075588361/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-06-19T04:59:48.378Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-06-19T04:59:48.378Z] echo "Nothing to be done for teardown."; \ [2025-06-19T04:59:48.378Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17503075588361/TestTargetResult"; [2025-06-19T04:59:48.378Z] [2025-06-19T04:59:48.378Z] TEST SETUP: [2025-06-19T04:59:48.378Z] Nothing to be done for setup. [2025-06-19T04:59:48.378Z] [2025-06-19T04:59:48.378Z] TESTING: [2025-06-19T04:59:58.240Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-06-19T05:00:12.087Z] 05:00:10.288 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. [2025-06-19T05:00:16.687Z] Got 100004 ratings from 671 users on 9066 movies. [2025-06-19T05:00:17.452Z] Training: 60056, validation: 20285, test: 19854 [2025-06-19T05:00:17.452Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-06-19T05:00:17.452Z] GC before operation: completed in 180.329 ms, heap usage 197.193 MB -> 75.636 MB. [2025-06-19T05:00:28.086Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T05:00:33.843Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T05:00:38.320Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T05:00:42.839Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T05:00:45.316Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T05:00:47.815Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T05:00:51.234Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T05:00:53.733Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T05:00:54.499Z] 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. [2025-06-19T05:00:54.499Z] The best model improves the baseline by 14.34%. [2025-06-19T05:00:54.499Z] Top recommended movies for user id 72: [2025-06-19T05:00:54.499Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-19T05:00:54.499Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-19T05:00:54.499Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-19T05:00:54.499Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-19T05:00:54.499Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-19T05:00:54.499Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (37331.720 ms) ====== [2025-06-19T05:00:54.499Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-06-19T05:00:54.499Z] GC before operation: completed in 260.920 ms, heap usage 353.235 MB -> 88.138 MB. [2025-06-19T05:00:58.986Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T05:01:02.415Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T05:01:06.921Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T05:01:09.925Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T05:01:11.544Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T05:01:13.127Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T05:01:15.590Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T05:01:17.187Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T05:01:17.953Z] 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. [2025-06-19T05:01:17.953Z] The best model improves the baseline by 14.34%. [2025-06-19T05:01:17.953Z] Top recommended movies for user id 72: [2025-06-19T05:01:17.953Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-19T05:01:17.953Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-19T05:01:17.953Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-19T05:01:17.953Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-19T05:01:17.953Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-19T05:01:17.953Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (23065.262 ms) ====== [2025-06-19T05:01:17.953Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-06-19T05:01:17.953Z] GC before operation: completed in 237.226 ms, heap usage 396.253 MB -> 88.141 MB. [2025-06-19T05:01:22.398Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T05:01:24.889Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T05:01:29.343Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T05:01:31.821Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T05:01:34.285Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T05:01:35.886Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T05:01:38.348Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T05:01:40.804Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T05:01:40.804Z] 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. [2025-06-19T05:01:40.804Z] The best model improves the baseline by 14.34%. [2025-06-19T05:01:40.804Z] Top recommended movies for user id 72: [2025-06-19T05:01:40.804Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-19T05:01:40.804Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-19T05:01:40.804Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-19T05:01:40.804Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-19T05:01:40.804Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-19T05:01:40.805Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (22836.947 ms) ====== [2025-06-19T05:01:40.805Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-06-19T05:01:41.571Z] GC before operation: completed in 222.505 ms, heap usage 388.199 MB -> 88.750 MB. [2025-06-19T05:01:44.974Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T05:01:48.390Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T05:01:51.794Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T05:01:55.204Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T05:01:57.354Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T05:01:58.941Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T05:02:00.543Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T05:02:02.135Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T05:02:02.916Z] 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. [2025-06-19T05:02:02.916Z] The best model improves the baseline by 14.34%. [2025-06-19T05:02:02.916Z] Top recommended movies for user id 72: [2025-06-19T05:02:02.916Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-19T05:02:02.916Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-19T05:02:02.916Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-19T05:02:02.916Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-19T05:02:02.916Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-19T05:02:02.916Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (21567.916 ms) ====== [2025-06-19T05:02:02.916Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-06-19T05:02:02.916Z] GC before operation: completed in 187.323 ms, heap usage 166.429 MB -> 88.673 MB. [2025-06-19T05:02:06.365Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T05:02:08.822Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T05:02:12.269Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T05:02:14.733Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T05:02:16.319Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T05:02:18.776Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T05:02:20.359Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T05:02:21.944Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T05:02:21.944Z] 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. [2025-06-19T05:02:21.944Z] The best model improves the baseline by 14.34%. [2025-06-19T05:02:22.711Z] Top recommended movies for user id 72: [2025-06-19T05:02:22.711Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-19T05:02:22.711Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-19T05:02:22.711Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-19T05:02:22.711Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-19T05:02:22.711Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-19T05:02:22.711Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (19403.572 ms) ====== [2025-06-19T05:02:22.711Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-06-19T05:02:22.711Z] GC before operation: completed in 159.917 ms, heap usage 383.993 MB -> 89.017 MB. [2025-06-19T05:02:26.125Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T05:02:28.606Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T05:02:31.062Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T05:02:34.467Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T05:02:36.050Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T05:02:37.629Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T05:02:39.471Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T05:02:41.307Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T05:02:41.307Z] 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. [2025-06-19T05:02:41.307Z] The best model improves the baseline by 14.34%. [2025-06-19T05:02:41.307Z] Top recommended movies for user id 72: [2025-06-19T05:02:41.307Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-19T05:02:41.307Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-19T05:02:41.307Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-19T05:02:41.307Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-19T05:02:41.307Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-19T05:02:41.307Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (18834.199 ms) ====== [2025-06-19T05:02:41.307Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-06-19T05:02:41.307Z] GC before operation: completed in 157.100 ms, heap usage 252.321 MB -> 89.110 MB. [2025-06-19T05:02:44.837Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T05:02:47.315Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T05:02:49.784Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T05:02:53.210Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T05:02:54.802Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T05:02:56.384Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T05:02:57.965Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T05:02:59.546Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T05:02:59.546Z] 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. [2025-06-19T05:02:59.546Z] The best model improves the baseline by 14.34%. [2025-06-19T05:02:59.546Z] Top recommended movies for user id 72: [2025-06-19T05:02:59.546Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-19T05:02:59.546Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-19T05:02:59.546Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-19T05:02:59.546Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-19T05:02:59.546Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-19T05:02:59.546Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (18348.637 ms) ====== [2025-06-19T05:02:59.546Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-06-19T05:03:00.311Z] GC before operation: completed in 146.749 ms, heap usage 243.029 MB -> 89.026 MB. [2025-06-19T05:03:02.765Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T05:03:06.170Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T05:03:08.633Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T05:03:11.157Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T05:03:12.738Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T05:03:14.320Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T05:03:15.903Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T05:03:17.486Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T05:03:18.251Z] 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. [2025-06-19T05:03:18.251Z] The best model improves the baseline by 14.34%. [2025-06-19T05:03:18.251Z] Top recommended movies for user id 72: [2025-06-19T05:03:18.251Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-19T05:03:18.251Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-19T05:03:18.251Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-19T05:03:18.251Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-19T05:03:18.251Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-19T05:03:18.251Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (18118.544 ms) ====== [2025-06-19T05:03:18.251Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-06-19T05:03:18.251Z] GC before operation: completed in 145.856 ms, heap usage 303.595 MB -> 89.386 MB. [2025-06-19T05:03:21.664Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T05:03:23.845Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T05:03:26.303Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T05:03:29.708Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T05:03:31.288Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T05:03:32.868Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T05:03:34.450Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T05:03:36.046Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T05:03:36.046Z] 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. [2025-06-19T05:03:36.046Z] The best model improves the baseline by 14.34%. [2025-06-19T05:03:36.046Z] Top recommended movies for user id 72: [2025-06-19T05:03:36.046Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-19T05:03:36.046Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-19T05:03:36.046Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-19T05:03:36.046Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-19T05:03:36.046Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-19T05:03:36.046Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (17908.242 ms) ====== [2025-06-19T05:03:36.046Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-06-19T05:03:36.046Z] GC before operation: completed in 152.037 ms, heap usage 167.360 MB -> 89.024 MB. [2025-06-19T05:03:39.471Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T05:03:41.923Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T05:03:45.322Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T05:03:47.777Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T05:03:49.358Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T05:03:50.943Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T05:03:52.522Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T05:03:54.102Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T05:03:54.102Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-19T05:03:54.102Z] The best model improves the baseline by 14.34%. [2025-06-19T05:03:54.868Z] Top recommended movies for user id 72: [2025-06-19T05:03:54.868Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-19T05:03:54.868Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-19T05:03:54.868Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-19T05:03:54.868Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-19T05:03:54.868Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-19T05:03:54.868Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (18258.561 ms) ====== [2025-06-19T05:03:54.868Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-06-19T05:03:54.868Z] GC before operation: completed in 136.325 ms, heap usage 180.874 MB -> 89.200 MB. [2025-06-19T05:03:57.340Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T05:03:59.791Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T05:04:03.203Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T05:04:05.715Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T05:04:07.000Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T05:04:08.615Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T05:04:10.197Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T05:04:11.786Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T05:04:12.552Z] 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. [2025-06-19T05:04:12.552Z] The best model improves the baseline by 14.34%. [2025-06-19T05:04:12.552Z] Top recommended movies for user id 72: [2025-06-19T05:04:12.552Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-19T05:04:12.552Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-19T05:04:12.552Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-19T05:04:12.552Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-19T05:04:12.552Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-19T05:04:12.552Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (17609.614 ms) ====== [2025-06-19T05:04:12.552Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-06-19T05:04:12.552Z] GC before operation: completed in 153.450 ms, heap usage 355.613 MB -> 89.344 MB. [2025-06-19T05:04:15.005Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T05:04:18.403Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T05:04:20.866Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T05:04:23.346Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T05:04:25.832Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T05:04:27.412Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T05:04:28.991Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T05:04:30.572Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T05:04:30.572Z] 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. [2025-06-19T05:04:30.572Z] The best model improves the baseline by 14.34%. [2025-06-19T05:04:30.572Z] Top recommended movies for user id 72: [2025-06-19T05:04:30.572Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-19T05:04:30.572Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-19T05:04:30.572Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-19T05:04:30.572Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-19T05:04:30.572Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-19T05:04:30.573Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (18279.563 ms) ====== [2025-06-19T05:04:30.573Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-06-19T05:04:31.337Z] GC before operation: completed in 148.479 ms, heap usage 243.026 MB -> 89.335 MB. [2025-06-19T05:04:33.824Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T05:04:36.286Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T05:04:39.690Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T05:04:42.144Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T05:04:43.745Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T05:04:45.326Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T05:04:46.907Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T05:04:48.488Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T05:04:48.488Z] 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. [2025-06-19T05:04:48.488Z] The best model improves the baseline by 14.34%. [2025-06-19T05:04:48.488Z] Top recommended movies for user id 72: [2025-06-19T05:04:48.488Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-19T05:04:48.488Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-19T05:04:48.488Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-19T05:04:48.488Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-19T05:04:48.488Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-19T05:04:48.488Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (17870.497 ms) ====== [2025-06-19T05:04:48.488Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-06-19T05:04:49.252Z] GC before operation: completed in 138.709 ms, heap usage 181.463 MB -> 89.281 MB. [2025-06-19T05:04:52.213Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T05:04:54.676Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T05:04:57.130Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T05:04:59.584Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T05:05:01.165Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T05:05:03.660Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T05:05:05.240Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T05:05:06.822Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T05:05:07.588Z] 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. [2025-06-19T05:05:07.588Z] The best model improves the baseline by 14.34%. [2025-06-19T05:05:07.588Z] Top recommended movies for user id 72: [2025-06-19T05:05:07.588Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-19T05:05:07.588Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-19T05:05:07.588Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-19T05:05:07.588Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-19T05:05:07.588Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-19T05:05:07.588Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (18617.809 ms) ====== [2025-06-19T05:05:07.588Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-06-19T05:05:07.588Z] GC before operation: completed in 153.429 ms, heap usage 352.577 MB -> 89.419 MB. [2025-06-19T05:05:10.996Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T05:05:13.455Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T05:05:15.912Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T05:05:18.371Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T05:05:19.954Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T05:05:21.537Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T05:05:23.994Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T05:05:24.760Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T05:05:25.526Z] 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. [2025-06-19T05:05:25.526Z] The best model improves the baseline by 14.34%. [2025-06-19T05:05:25.526Z] Top recommended movies for user id 72: [2025-06-19T05:05:25.526Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-19T05:05:25.526Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-19T05:05:25.526Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-19T05:05:25.526Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-19T05:05:25.526Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-19T05:05:25.526Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (17856.168 ms) ====== [2025-06-19T05:05:25.526Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-06-19T05:05:25.526Z] GC before operation: completed in 142.318 ms, heap usage 405.081 MB -> 89.795 MB. [2025-06-19T05:05:28.930Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T05:05:31.387Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T05:05:34.351Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T05:05:36.809Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T05:05:38.392Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T05:05:39.984Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T05:05:41.571Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T05:05:43.154Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T05:05:43.154Z] 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. [2025-06-19T05:05:43.154Z] The best model improves the baseline by 14.34%. [2025-06-19T05:05:43.154Z] Top recommended movies for user id 72: [2025-06-19T05:05:43.154Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-19T05:05:43.154Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-19T05:05:43.154Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-19T05:05:43.154Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-19T05:05:43.154Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-19T05:05:43.154Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (17474.194 ms) ====== [2025-06-19T05:05:43.154Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-06-19T05:05:43.154Z] GC before operation: completed in 145.410 ms, heap usage 243.876 MB -> 89.367 MB. [2025-06-19T05:05:46.557Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T05:05:49.964Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T05:05:52.419Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T05:05:55.823Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T05:05:57.406Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T05:05:59.016Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T05:06:00.596Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T05:06:03.056Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T05:06:03.056Z] 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. [2025-06-19T05:06:03.056Z] The best model improves the baseline by 14.34%. [2025-06-19T05:06:03.056Z] Top recommended movies for user id 72: [2025-06-19T05:06:03.056Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-19T05:06:03.056Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-19T05:06:03.056Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-19T05:06:03.056Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-19T05:06:03.056Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-19T05:06:03.056Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (19840.789 ms) ====== [2025-06-19T05:06:03.056Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-06-19T05:06:03.056Z] GC before operation: completed in 146.080 ms, heap usage 167.013 MB -> 89.365 MB. [2025-06-19T05:06:06.461Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T05:06:08.933Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T05:06:11.391Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T05:06:13.851Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T05:06:15.435Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T05:06:18.429Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T05:06:19.196Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T05:06:20.776Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T05:06:20.776Z] 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. [2025-06-19T05:06:20.776Z] The best model improves the baseline by 14.34%. [2025-06-19T05:06:20.776Z] Top recommended movies for user id 72: [2025-06-19T05:06:20.776Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-19T05:06:20.776Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-19T05:06:20.776Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-19T05:06:20.776Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-19T05:06:20.776Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-19T05:06:20.776Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (17726.260 ms) ====== [2025-06-19T05:06:20.776Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-06-19T05:06:21.542Z] GC before operation: completed in 147.162 ms, heap usage 304.406 MB -> 89.375 MB. [2025-06-19T05:06:24.016Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T05:06:26.472Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T05:06:29.906Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T05:06:32.364Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T05:06:33.945Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T05:06:35.528Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T05:06:37.132Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T05:06:38.716Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T05:06:38.716Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-19T05:06:38.716Z] The best model improves the baseline by 14.34%. [2025-06-19T05:06:38.716Z] Top recommended movies for user id 72: [2025-06-19T05:06:38.716Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-19T05:06:38.716Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-19T05:06:38.716Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-19T05:06:38.716Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-19T05:06:38.716Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-19T05:06:38.716Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (17734.071 ms) ====== [2025-06-19T05:06:38.716Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-06-19T05:06:39.483Z] GC before operation: completed in 142.030 ms, heap usage 352.176 MB -> 89.557 MB. [2025-06-19T05:06:41.940Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T05:06:44.408Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T05:06:46.863Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T05:06:49.317Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T05:06:50.915Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T05:06:52.496Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T05:06:54.075Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T05:06:55.657Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T05:06:56.424Z] 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. [2025-06-19T05:06:56.424Z] The best model improves the baseline by 14.34%. [2025-06-19T05:06:56.424Z] Top recommended movies for user id 72: [2025-06-19T05:06:56.424Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-19T05:06:56.424Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-19T05:06:56.424Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-19T05:06:56.424Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-19T05:06:56.424Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-19T05:06:56.424Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (17197.155 ms) ====== [2025-06-19T05:06:57.191Z] ----------------------------------- [2025-06-19T05:06:57.191Z] renaissance-movie-lens_0_PASSED [2025-06-19T05:06:57.191Z] ----------------------------------- [2025-06-19T05:06:57.191Z] [2025-06-19T05:06:57.191Z] TEST TEARDOWN: [2025-06-19T05:06:57.191Z] Nothing to be done for teardown. [2025-06-19T05:06:57.191Z] renaissance-movie-lens_0 Finish Time: Thu Jun 19 05:06:56 2025 Epoch Time (ms): 1750309616965