[2025-12-24T23:55:21.608Z] Running test renaissance-movie-lens_0 ... [2025-12-24T23:55:21.609Z] =============================================== [2025-12-24T23:55:21.609Z] renaissance-movie-lens_0 Start Time: Wed Dec 24 23:55:21 2025 Epoch Time (ms): 1766620521467 [2025-12-24T23:55:21.609Z] variation: NoOptions [2025-12-24T23:55:21.967Z] JVM_OPTIONS: [2025-12-24T23:55:21.967Z] { \ [2025-12-24T23:55:21.967Z] echo ""; echo "TEST SETUP:"; \ [2025-12-24T23:55:21.967Z] echo "Nothing to be done for setup."; \ [2025-12-24T23:55:21.967Z] mkdir -p "C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17666184974796\\renaissance-movie-lens_0"; \ [2025-12-24T23:55:21.967Z] cd "C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17666184974796\\renaissance-movie-lens_0"; \ [2025-12-24T23:55:21.967Z] echo ""; echo "TESTING:"; \ [2025-12-24T23:55:21.967Z] "c:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/jdkbinary/j2sdk-image\\bin\\java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17666184974796\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2025-12-24T23:55:21.967Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17666184974796\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-24T23:55:21.967Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-24T23:55:21.967Z] echo "Nothing to be done for teardown."; \ [2025-12-24T23:55:21.967Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17666184974796\\TestTargetResult"; [2025-12-24T23:55:21.967Z] [2025-12-24T23:55:21.967Z] TEST SETUP: [2025-12-24T23:55:21.967Z] Nothing to be done for setup. [2025-12-24T23:55:21.967Z] [2025-12-24T23:55:21.967Z] TESTING: [2025-12-24T23:55:35.395Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-12-24T23:55:44.097Z] 23:55:42.748 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. [2025-12-24T23:55:47.429Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-24T23:55:47.978Z] Training: 60056, validation: 20285, test: 19854 [2025-12-24T23:55:47.978Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-24T23:55:47.978Z] GC before operation: completed in 133.521 ms, heap usage 249.716 MB -> 76.297 MB. [2025-12-24T23:56:00.146Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-24T23:56:06.425Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-24T23:56:13.320Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-24T23:56:20.667Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-24T23:56:24.667Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-24T23:56:28.181Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-24T23:56:32.185Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-24T23:56:35.569Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-24T23:56:36.384Z] 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. [2025-12-24T23:56:36.384Z] The best model improves the baseline by 14.34%. [2025-12-24T23:56:36.384Z] Top recommended movies for user id 72: [2025-12-24T23:56:36.384Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-24T23:56:36.384Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-24T23:56:36.384Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-24T23:56:36.384Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-24T23:56:36.384Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-24T23:56:36.384Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (48070.646 ms) ====== [2025-12-24T23:56:36.384Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-24T23:56:36.756Z] GC before operation: completed in 164.292 ms, heap usage 291.946 MB -> 86.296 MB. [2025-12-24T23:56:43.042Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-24T23:56:47.975Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-24T23:56:54.080Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-24T23:56:59.416Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-24T23:57:02.562Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-24T23:57:06.631Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-24T23:57:10.072Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-24T23:57:13.216Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-24T23:57:13.699Z] 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. [2025-12-24T23:57:13.699Z] The best model improves the baseline by 14.34%. [2025-12-24T23:57:13.699Z] Top recommended movies for user id 72: [2025-12-24T23:57:13.699Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-24T23:57:13.699Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-24T23:57:13.699Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-24T23:57:13.699Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-24T23:57:13.699Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-24T23:57:13.699Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (37549.353 ms) ====== [2025-12-24T23:57:13.699Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-24T23:57:14.091Z] GC before operation: completed in 181.199 ms, heap usage 295.544 MB -> 88.202 MB. [2025-12-24T23:57:20.378Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-24T23:57:25.536Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-24T23:57:31.955Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-24T23:57:36.925Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-24T23:57:40.568Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-24T23:57:43.818Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-24T23:57:47.197Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-24T23:57:50.321Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-24T23:57:50.776Z] 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. [2025-12-24T23:57:50.776Z] The best model improves the baseline by 14.34%. [2025-12-24T23:57:50.776Z] Top recommended movies for user id 72: [2025-12-24T23:57:50.776Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-24T23:57:50.776Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-24T23:57:50.776Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-24T23:57:50.776Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-24T23:57:50.776Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-24T23:57:50.776Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (36908.100 ms) ====== [2025-12-24T23:57:50.776Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-24T23:57:51.152Z] GC before operation: completed in 192.571 ms, heap usage 295.068 MB -> 88.786 MB. [2025-12-24T23:57:57.619Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-24T23:58:02.568Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-24T23:58:08.849Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-24T23:58:13.878Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-24T23:58:17.071Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-24T23:58:19.422Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-24T23:58:22.613Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-24T23:58:25.688Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-24T23:58:26.050Z] 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. [2025-12-24T23:58:26.050Z] The best model improves the baseline by 14.34%. [2025-12-24T23:58:26.589Z] Top recommended movies for user id 72: [2025-12-24T23:58:26.589Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-24T23:58:26.589Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-24T23:58:26.589Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-24T23:58:26.589Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-24T23:58:26.589Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-24T23:58:26.589Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (35294.676 ms) ====== [2025-12-24T23:58:26.589Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-24T23:58:26.589Z] GC before operation: completed in 173.459 ms, heap usage 226.443 MB -> 89.088 MB. [2025-12-24T23:58:32.758Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-24T23:58:37.659Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-24T23:58:42.587Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-24T23:58:47.450Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-24T23:58:49.808Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-24T23:58:52.863Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-24T23:58:55.975Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-24T23:58:59.064Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-24T23:58:59.064Z] 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. [2025-12-24T23:58:59.064Z] The best model improves the baseline by 14.34%. [2025-12-24T23:58:59.574Z] Top recommended movies for user id 72: [2025-12-24T23:58:59.574Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-24T23:58:59.574Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-24T23:58:59.574Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-24T23:58:59.574Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-24T23:58:59.574Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-24T23:58:59.574Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (32833.349 ms) ====== [2025-12-24T23:58:59.574Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-24T23:58:59.574Z] GC before operation: completed in 180.404 ms, heap usage 172.265 MB -> 91.094 MB. [2025-12-24T23:59:05.646Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-24T23:59:10.712Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-24T23:59:15.597Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-24T23:59:20.499Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-24T23:59:22.859Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-24T23:59:25.377Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-24T23:59:28.434Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-24T23:59:31.480Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-24T23:59:31.480Z] 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. [2025-12-24T23:59:31.480Z] The best model improves the baseline by 14.34%. [2025-12-24T23:59:32.101Z] Top recommended movies for user id 72: [2025-12-24T23:59:32.101Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-24T23:59:32.101Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-24T23:59:32.101Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-24T23:59:32.101Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-24T23:59:32.101Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-24T23:59:32.101Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (32356.644 ms) ====== [2025-12-24T23:59:32.101Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-24T23:59:32.463Z] GC before operation: completed in 193.569 ms, heap usage 173.294 MB -> 89.335 MB. [2025-12-24T23:59:37.354Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-24T23:59:42.249Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-24T23:59:47.260Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-24T23:59:52.296Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-24T23:59:55.560Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-24T23:59:58.620Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:00:01.685Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:00:04.782Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:00:04.782Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-25T00:00:04.782Z] The best model improves the baseline by 14.34%. [2025-12-25T00:00:05.356Z] Top recommended movies for user id 72: [2025-12-25T00:00:05.356Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-25T00:00:05.356Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-25T00:00:05.356Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-25T00:00:05.356Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-25T00:00:05.356Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-25T00:00:05.356Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (33071.406 ms) ====== [2025-12-25T00:00:05.356Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-25T00:00:05.356Z] GC before operation: completed in 184.368 ms, heap usage 147.922 MB -> 89.191 MB. [2025-12-25T00:00:11.460Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:00:16.472Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:00:21.387Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:00:27.715Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:00:30.042Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:00:33.200Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:00:37.262Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:00:40.431Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:00:40.787Z] 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. [2025-12-25T00:00:41.443Z] The best model improves the baseline by 14.34%. [2025-12-25T00:00:41.443Z] Top recommended movies for user id 72: [2025-12-25T00:00:41.443Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-25T00:00:41.443Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-25T00:00:41.443Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-25T00:00:41.443Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-25T00:00:41.443Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-25T00:00:41.443Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (35873.523 ms) ====== [2025-12-25T00:00:41.443Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-25T00:00:41.795Z] GC before operation: completed in 180.309 ms, heap usage 220.584 MB -> 89.502 MB. [2025-12-25T00:00:46.682Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:00:53.142Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:00:58.098Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:01:04.372Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:01:06.787Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:01:10.248Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:01:13.563Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:01:16.808Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:01:17.206Z] 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. [2025-12-25T00:01:17.206Z] The best model improves the baseline by 14.34%. [2025-12-25T00:01:17.644Z] Top recommended movies for user id 72: [2025-12-25T00:01:17.644Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-25T00:01:17.644Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-25T00:01:17.644Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-25T00:01:17.644Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-25T00:01:17.644Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-25T00:01:17.644Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (36119.964 ms) ====== [2025-12-25T00:01:17.644Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-25T00:01:17.644Z] GC before operation: completed in 117.995 ms, heap usage 292.665 MB -> 89.473 MB. [2025-12-25T00:01:24.291Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:01:29.528Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:01:34.441Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:01:39.670Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:01:42.915Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:01:46.077Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:01:49.455Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:01:52.622Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:01:52.622Z] 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. [2025-12-25T00:01:52.622Z] The best model improves the baseline by 14.34%. [2025-12-25T00:01:53.041Z] Top recommended movies for user id 72: [2025-12-25T00:01:53.041Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-25T00:01:53.041Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-25T00:01:53.041Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-25T00:01:53.041Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-25T00:01:53.041Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-25T00:01:53.041Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (35258.895 ms) ====== [2025-12-25T00:01:53.041Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-25T00:01:53.041Z] GC before operation: completed in 121.472 ms, heap usage 292.141 MB -> 89.622 MB. [2025-12-25T00:01:59.300Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:02:04.218Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:02:09.446Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:02:15.551Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:02:17.380Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:02:20.581Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:02:23.637Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:02:25.997Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:02:26.386Z] 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. [2025-12-25T00:02:26.386Z] The best model improves the baseline by 14.34%. [2025-12-25T00:02:26.912Z] Top recommended movies for user id 72: [2025-12-25T00:02:26.912Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-25T00:02:26.912Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-25T00:02:26.912Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-25T00:02:26.912Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-25T00:02:26.912Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-25T00:02:26.912Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (33700.183 ms) ====== [2025-12-25T00:02:26.912Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-25T00:02:26.912Z] GC before operation: completed in 127.011 ms, heap usage 680.790 MB -> 93.378 MB. [2025-12-25T00:02:31.864Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:02:36.761Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:02:41.835Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:02:46.756Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:02:50.063Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:02:53.993Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:02:57.212Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:03:00.406Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:03:00.406Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-25T00:03:00.406Z] The best model improves the baseline by 14.34%. [2025-12-25T00:03:00.808Z] Top recommended movies for user id 72: [2025-12-25T00:03:00.808Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-25T00:03:00.808Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-25T00:03:00.808Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-25T00:03:00.808Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-25T00:03:00.808Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-25T00:03:00.808Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (33819.957 ms) ====== [2025-12-25T00:03:00.808Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-25T00:03:00.808Z] GC before operation: completed in 120.426 ms, heap usage 290.525 MB -> 89.618 MB. [2025-12-25T00:03:05.845Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:03:12.412Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:03:17.314Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:03:22.509Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:03:25.602Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:03:29.211Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:03:32.562Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:03:35.749Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:03:35.749Z] 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. [2025-12-25T00:03:35.749Z] The best model improves the baseline by 14.34%. [2025-12-25T00:03:36.175Z] Top recommended movies for user id 72: [2025-12-25T00:03:36.175Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-25T00:03:36.175Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-25T00:03:36.175Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-25T00:03:36.175Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-25T00:03:36.175Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-25T00:03:36.175Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (35236.860 ms) ====== [2025-12-25T00:03:36.175Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-25T00:03:36.175Z] GC before operation: completed in 120.649 ms, heap usage 291.394 MB -> 89.711 MB. [2025-12-25T00:03:42.640Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:03:47.941Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:03:53.123Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:03:58.032Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:04:01.263Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:04:04.414Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:04:07.518Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:04:10.811Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:04:11.458Z] 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. [2025-12-25T00:04:11.458Z] The best model improves the baseline by 14.34%. [2025-12-25T00:04:11.458Z] Top recommended movies for user id 72: [2025-12-25T00:04:11.458Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-25T00:04:11.458Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-25T00:04:11.458Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-25T00:04:11.458Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-25T00:04:11.458Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-25T00:04:11.458Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (35118.684 ms) ====== [2025-12-25T00:04:11.458Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-25T00:04:11.827Z] GC before operation: completed in 140.188 ms, heap usage 289.858 MB -> 89.573 MB. [2025-12-25T00:04:18.024Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:04:22.920Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:04:28.116Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:04:33.098Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:04:36.210Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:04:40.093Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:04:43.275Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:04:46.446Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:04:46.446Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-25T00:04:46.446Z] The best model improves the baseline by 14.34%. [2025-12-25T00:04:46.853Z] Top recommended movies for user id 72: [2025-12-25T00:04:46.853Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-25T00:04:46.853Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-25T00:04:46.853Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-25T00:04:46.853Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-25T00:04:46.853Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-25T00:04:46.853Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (35268.310 ms) ====== [2025-12-25T00:04:46.853Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-25T00:04:46.853Z] GC before operation: completed in 122.209 ms, heap usage 293.999 MB -> 89.744 MB. [2025-12-25T00:04:53.114Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:04:58.013Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:05:02.943Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:05:07.892Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:05:10.281Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:05:12.615Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:05:15.739Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:05:18.811Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:05:18.811Z] 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. [2025-12-25T00:05:18.811Z] The best model improves the baseline by 14.34%. [2025-12-25T00:05:19.401Z] Top recommended movies for user id 72: [2025-12-25T00:05:19.402Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-25T00:05:19.402Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-25T00:05:19.402Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-25T00:05:19.402Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-25T00:05:19.402Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-25T00:05:19.402Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (32407.047 ms) ====== [2025-12-25T00:05:19.402Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-25T00:05:19.402Z] GC before operation: completed in 122.563 ms, heap usage 171.691 MB -> 89.472 MB. [2025-12-25T00:05:24.433Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:05:29.329Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:05:34.237Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:05:39.147Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:05:42.219Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:05:44.576Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:05:47.604Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:05:49.961Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:05:50.865Z] 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. [2025-12-25T00:05:50.865Z] The best model improves the baseline by 14.34%. [2025-12-25T00:05:50.865Z] Top recommended movies for user id 72: [2025-12-25T00:05:50.865Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-25T00:05:50.865Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-25T00:05:50.865Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-25T00:05:50.865Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-25T00:05:50.865Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-25T00:05:50.865Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (31401.252 ms) ====== [2025-12-25T00:05:50.865Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-25T00:05:51.207Z] GC before operation: completed in 126.112 ms, heap usage 365.829 MB -> 89.929 MB. [2025-12-25T00:05:56.151Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:06:01.041Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:06:05.940Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:06:10.836Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:06:13.206Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:06:15.586Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:06:18.656Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:06:21.712Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:06:21.712Z] 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. [2025-12-25T00:06:21.712Z] The best model improves the baseline by 14.34%. [2025-12-25T00:06:27.766Z] Top recommended movies for user id 72: [2025-12-25T00:06:27.766Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-25T00:06:27.766Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-25T00:06:27.766Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-25T00:06:27.766Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-25T00:06:27.766Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-25T00:06:27.766Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (31077.618 ms) ====== [2025-12-25T00:06:27.766Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-25T00:06:27.766Z] GC before operation: completed in 5715.485 ms, heap usage 238.225 MB -> 89.502 MB. [2025-12-25T00:06:32.647Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:06:37.531Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:06:42.453Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:06:47.331Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:06:49.671Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:06:52.714Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:06:55.805Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:06:58.132Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:06:59.155Z] 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. [2025-12-25T00:06:59.155Z] The best model improves the baseline by 14.34%. [2025-12-25T00:06:59.155Z] Top recommended movies for user id 72: [2025-12-25T00:06:59.155Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-25T00:06:59.155Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-25T00:06:59.155Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-25T00:06:59.155Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-25T00:06:59.155Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-25T00:06:59.155Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (31352.739 ms) ====== [2025-12-25T00:06:59.155Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-25T00:06:59.155Z] GC before operation: completed in 122.869 ms, heap usage 171.221 MB -> 89.505 MB. [2025-12-25T00:07:04.039Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-25T00:07:08.908Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-25T00:07:14.928Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-25T00:07:18.892Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-25T00:07:21.961Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-25T00:07:25.029Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-25T00:07:27.375Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-25T00:07:30.447Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-25T00:07:30.804Z] 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. [2025-12-25T00:07:30.804Z] The best model improves the baseline by 14.34%. [2025-12-25T00:07:31.158Z] Top recommended movies for user id 72: [2025-12-25T00:07:31.159Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-25T00:07:31.159Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-25T00:07:31.159Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-25T00:07:31.159Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-25T00:07:31.159Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-25T00:07:31.159Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (32026.460 ms) ====== [2025-12-25T00:07:31.512Z] ----------------------------------- [2025-12-25T00:07:31.512Z] renaissance-movie-lens_0_PASSED [2025-12-25T00:07:31.512Z] ----------------------------------- [2025-12-25T00:07:31.856Z] [2025-12-25T00:07:31.856Z] TEST TEARDOWN: [2025-12-25T00:07:31.856Z] Nothing to be done for teardown. [2025-12-25T00:07:32.194Z] renaissance-movie-lens_0 Finish Time: Thu Dec 25 00:07:31 2025 Epoch Time (ms): 1766621251897