[2025-12-18T01:31:38.569Z] Running test renaissance-movie-lens_0 ... [2025-12-18T01:31:38.569Z] =============================================== [2025-12-18T01:31:38.569Z] renaissance-movie-lens_0 Start Time: Wed Dec 17 17:31:37 2025 Epoch Time (ms): 1766021497342 [2025-12-18T01:31:38.569Z] variation: NoOptions [2025-12-18T01:31:38.569Z] JVM_OPTIONS: [2025-12-18T01:31:38.569Z] { \ [2025-12-18T01:31:38.569Z] echo ""; echo "TEST SETUP:"; \ [2025-12-18T01:31:38.569Z] echo "Nothing to be done for setup."; \ [2025-12-18T01:31:38.569Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17660192194901/renaissance-movie-lens_0"; \ [2025-12-18T01:31:38.569Z] cd "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17660192194901/renaissance-movie-lens_0"; \ [2025-12-18T01:31:38.569Z] echo ""; echo "TESTING:"; \ [2025-12-18T01:31:38.569Z] "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/jdkbinary/j2sdk-image/Contents/Home/bin/..//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 "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17660192194901/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-18T01:31:38.569Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17660192194901/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-18T01:31:38.569Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-18T01:31:38.569Z] echo "Nothing to be done for teardown."; \ [2025-12-18T01:31:38.569Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17660192194901/TestTargetResult"; [2025-12-18T01:31:39.028Z] [2025-12-18T01:31:39.028Z] TEST SETUP: [2025-12-18T01:31:39.028Z] Nothing to be done for setup. [2025-12-18T01:31:39.028Z] [2025-12-18T01:31:39.028Z] TESTING: [2025-12-18T01:31:56.427Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-12-18T01:32:14.489Z] 17:32:12.516 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-12-18T01:32:20.998Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-18T01:32:22.041Z] Training: 60056, validation: 20285, test: 19854 [2025-12-18T01:32:22.041Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-18T01:32:22.490Z] GC before operation: completed in 268.629 ms, heap usage 450.574 MB -> 75.368 MB. [2025-12-18T01:32:48.598Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-18T01:33:06.703Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-18T01:33:22.629Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-18T01:33:36.073Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-18T01:33:42.456Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-18T01:33:49.899Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-18T01:33:55.725Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-18T01:34:03.280Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-18T01:34:03.280Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-18T01:34:03.714Z] The best model improves the baseline by 14.52%. [2025-12-18T01:34:04.182Z] Top recommended movies for user id 72: [2025-12-18T01:34:04.182Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-18T01:34:04.182Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-18T01:34:04.182Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-18T01:34:04.182Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-18T01:34:04.182Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-18T01:34:04.182Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (101886.659 ms) ====== [2025-12-18T01:34:04.182Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-18T01:34:04.731Z] GC before operation: completed in 475.021 ms, heap usage 704.543 MB -> 92.167 MB. [2025-12-18T01:34:19.858Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-18T01:34:34.609Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-18T01:34:45.290Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-18T01:34:52.913Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-18T01:35:00.216Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-18T01:35:03.549Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-18T01:35:08.428Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-18T01:35:13.242Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-18T01:35:13.242Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-18T01:35:13.242Z] The best model improves the baseline by 14.52%. [2025-12-18T01:35:13.815Z] Top recommended movies for user id 72: [2025-12-18T01:35:13.815Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-18T01:35:13.815Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-18T01:35:13.815Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-18T01:35:13.815Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-18T01:35:13.815Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-18T01:35:13.815Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (68880.604 ms) ====== [2025-12-18T01:35:13.815Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-18T01:35:14.228Z] GC before operation: completed in 600.154 ms, heap usage 377.860 MB -> 88.381 MB. [2025-12-18T01:35:24.647Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-18T01:35:31.986Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-18T01:35:39.549Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-18T01:35:45.520Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-18T01:35:49.152Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-18T01:35:52.848Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-18T01:35:57.577Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-18T01:35:59.528Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-18T01:36:00.040Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-18T01:36:00.536Z] The best model improves the baseline by 14.52%. [2025-12-18T01:36:00.980Z] Top recommended movies for user id 72: [2025-12-18T01:36:00.980Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-18T01:36:00.980Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-18T01:36:00.980Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-18T01:36:00.980Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-18T01:36:00.980Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-18T01:36:00.980Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (46511.315 ms) ====== [2025-12-18T01:36:00.980Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-18T01:36:00.980Z] GC before operation: completed in 221.162 ms, heap usage 844.943 MB -> 92.981 MB. [2025-12-18T01:36:07.912Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-18T01:36:12.714Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-18T01:36:16.417Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-18T01:36:20.935Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-18T01:36:24.446Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-18T01:36:28.138Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-18T01:36:32.867Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-18T01:36:36.539Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-18T01:36:36.539Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-18T01:36:36.539Z] The best model improves the baseline by 14.52%. [2025-12-18T01:36:36.539Z] Top recommended movies for user id 72: [2025-12-18T01:36:36.539Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-18T01:36:36.539Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-18T01:36:36.539Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-18T01:36:36.539Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-18T01:36:36.539Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-18T01:36:36.539Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (35612.332 ms) ====== [2025-12-18T01:36:36.539Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-18T01:36:36.954Z] GC before operation: completed in 95.136 ms, heap usage 347.454 MB -> 89.316 MB. [2025-12-18T01:36:43.732Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-18T01:36:50.673Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-18T01:36:59.422Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-18T01:37:07.999Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-18T01:37:11.060Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-18T01:37:15.688Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-18T01:37:21.467Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-18T01:37:26.045Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-18T01:37:26.942Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-18T01:37:26.942Z] The best model improves the baseline by 14.52%. [2025-12-18T01:37:27.497Z] Top recommended movies for user id 72: [2025-12-18T01:37:27.497Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-18T01:37:27.497Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-18T01:37:27.497Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-18T01:37:27.497Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-18T01:37:27.497Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-18T01:37:27.497Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (50529.089 ms) ====== [2025-12-18T01:37:27.497Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-18T01:37:27.497Z] GC before operation: completed in 304.045 ms, heap usage 992.741 MB -> 94.081 MB. [2025-12-18T01:37:37.887Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-18T01:37:48.256Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-18T01:37:58.319Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-18T01:38:05.369Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-18T01:38:11.172Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-18T01:38:15.663Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-18T01:38:22.493Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-18T01:38:27.057Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-18T01:38:27.570Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-18T01:38:27.570Z] The best model improves the baseline by 14.52%. [2025-12-18T01:38:27.570Z] Top recommended movies for user id 72: [2025-12-18T01:38:27.570Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-18T01:38:27.570Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-18T01:38:27.570Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-18T01:38:27.570Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-18T01:38:27.570Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-18T01:38:27.570Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (60105.540 ms) ====== [2025-12-18T01:38:27.570Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-18T01:38:28.043Z] GC before operation: completed in 174.487 ms, heap usage 207.184 MB -> 89.477 MB. [2025-12-18T01:38:38.031Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-18T01:38:45.049Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-18T01:38:50.610Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-18T01:38:54.788Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-18T01:38:58.225Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-18T01:39:00.985Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-18T01:39:04.364Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-18T01:39:08.953Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-18T01:39:09.879Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-18T01:39:09.879Z] The best model improves the baseline by 14.52%. [2025-12-18T01:39:09.879Z] Top recommended movies for user id 72: [2025-12-18T01:39:09.879Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-18T01:39:09.879Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-18T01:39:09.879Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-18T01:39:09.879Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-18T01:39:09.879Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-18T01:39:09.879Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (42024.172 ms) ====== [2025-12-18T01:39:09.879Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-18T01:39:09.879Z] GC before operation: completed in 154.943 ms, heap usage 451.230 MB -> 89.701 MB. [2025-12-18T01:39:20.005Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-18T01:39:24.569Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-18T01:39:30.073Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-18T01:39:33.441Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-18T01:39:35.296Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-18T01:39:36.542Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-18T01:39:38.356Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-18T01:39:39.683Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-18T01:39:39.683Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-18T01:39:39.683Z] The best model improves the baseline by 14.52%. [2025-12-18T01:39:39.683Z] Top recommended movies for user id 72: [2025-12-18T01:39:39.683Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-18T01:39:39.683Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-18T01:39:39.683Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-18T01:39:39.683Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-18T01:39:39.683Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-18T01:39:39.683Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (29709.564 ms) ====== [2025-12-18T01:39:39.683Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-18T01:39:39.683Z] GC before operation: completed in 70.228 ms, heap usage 233.196 MB -> 89.628 MB. [2025-12-18T01:39:43.916Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-18T01:39:46.394Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-18T01:39:48.894Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-18T01:39:52.259Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-18T01:39:55.789Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-18T01:39:57.637Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-18T01:39:59.534Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-18T01:40:04.247Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-18T01:40:04.247Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-18T01:40:04.615Z] The best model improves the baseline by 14.52%. [2025-12-18T01:40:05.001Z] Top recommended movies for user id 72: [2025-12-18T01:40:05.001Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-18T01:40:05.001Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-18T01:40:05.001Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-18T01:40:05.001Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-18T01:40:05.001Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-18T01:40:05.001Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (25069.462 ms) ====== [2025-12-18T01:40:05.001Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-18T01:40:05.001Z] GC before operation: completed in 139.128 ms, heap usage 150.343 MB -> 92.809 MB. [2025-12-18T01:40:11.776Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-18T01:40:16.056Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-18T01:40:21.385Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-18T01:40:26.830Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-18T01:40:29.529Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-18T01:40:32.339Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-18T01:40:34.229Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-18T01:40:36.063Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-18T01:40:36.453Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-18T01:40:36.453Z] The best model improves the baseline by 14.52%. [2025-12-18T01:40:36.453Z] Top recommended movies for user id 72: [2025-12-18T01:40:36.453Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-18T01:40:36.453Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-18T01:40:36.453Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-18T01:40:36.453Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-18T01:40:36.453Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-18T01:40:36.453Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (31460.933 ms) ====== [2025-12-18T01:40:36.453Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-18T01:40:36.453Z] GC before operation: completed in 69.125 ms, heap usage 850.359 MB -> 93.940 MB. [2025-12-18T01:40:38.875Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-18T01:40:40.695Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-18T01:40:43.104Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-18T01:40:45.534Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-18T01:40:46.819Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-18T01:40:47.596Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-18T01:40:48.899Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-18T01:40:50.199Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-18T01:40:50.572Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-18T01:40:50.572Z] The best model improves the baseline by 14.52%. [2025-12-18T01:40:50.572Z] Top recommended movies for user id 72: [2025-12-18T01:40:50.572Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-18T01:40:50.572Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-18T01:40:50.572Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-18T01:40:50.572Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-18T01:40:50.572Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-18T01:40:50.572Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14027.730 ms) ====== [2025-12-18T01:40:50.572Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-18T01:40:50.572Z] GC before operation: completed in 59.847 ms, heap usage 342.917 MB -> 89.569 MB. [2025-12-18T01:40:52.367Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-18T01:40:54.828Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-18T01:40:56.679Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-18T01:40:59.260Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-18T01:41:00.532Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-18T01:41:01.851Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-18T01:41:03.109Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-18T01:41:04.879Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-18T01:41:04.879Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-18T01:41:04.879Z] The best model improves the baseline by 14.52%. [2025-12-18T01:41:05.272Z] Top recommended movies for user id 72: [2025-12-18T01:41:05.272Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-18T01:41:05.272Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-18T01:41:05.272Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-18T01:41:05.272Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-18T01:41:05.272Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-18T01:41:05.272Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14440.920 ms) ====== [2025-12-18T01:41:05.272Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-18T01:41:05.272Z] GC before operation: completed in 102.081 ms, heap usage 347.458 MB -> 89.878 MB. [2025-12-18T01:41:10.488Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-18T01:41:13.834Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-18T01:41:17.241Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-18T01:41:20.586Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-18T01:41:23.205Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-18T01:41:25.000Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-18T01:41:26.841Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-18T01:41:28.708Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-18T01:41:28.708Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-18T01:41:28.708Z] The best model improves the baseline by 14.52%. [2025-12-18T01:41:28.708Z] Top recommended movies for user id 72: [2025-12-18T01:41:28.708Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-18T01:41:28.708Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-18T01:41:28.708Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-18T01:41:28.708Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-18T01:41:28.708Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-18T01:41:28.708Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (23520.840 ms) ====== [2025-12-18T01:41:28.708Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-18T01:41:28.708Z] GC before operation: completed in 62.140 ms, heap usage 460.724 MB -> 90.047 MB. [2025-12-18T01:41:31.877Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-18T01:41:35.067Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-18T01:41:38.385Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-18T01:41:41.597Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-18T01:41:43.469Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-18T01:41:45.348Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-18T01:41:48.013Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-18T01:41:49.854Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-18T01:41:50.220Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-18T01:41:50.220Z] The best model improves the baseline by 14.52%. [2025-12-18T01:41:50.220Z] Top recommended movies for user id 72: [2025-12-18T01:41:50.220Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-18T01:41:50.220Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-18T01:41:50.220Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-18T01:41:50.220Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-18T01:41:50.220Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-18T01:41:50.220Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (21449.135 ms) ====== [2025-12-18T01:41:50.220Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-18T01:41:50.220Z] GC before operation: completed in 62.345 ms, heap usage 332.212 MB -> 89.867 MB. [2025-12-18T01:41:53.520Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-18T01:41:56.695Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-18T01:42:00.902Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-18T01:42:02.762Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-18T01:42:04.087Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-18T01:42:05.955Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-18T01:42:07.917Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-18T01:42:09.758Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-18T01:42:09.758Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-18T01:42:09.758Z] The best model improves the baseline by 14.52%. [2025-12-18T01:42:10.145Z] Top recommended movies for user id 72: [2025-12-18T01:42:10.145Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-18T01:42:10.145Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-18T01:42:10.145Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-18T01:42:10.145Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-18T01:42:10.145Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-18T01:42:10.145Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (19845.157 ms) ====== [2025-12-18T01:42:10.145Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-18T01:42:10.145Z] GC before operation: completed in 70.597 ms, heap usage 592.526 MB -> 93.723 MB. [2025-12-18T01:42:13.314Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-18T01:42:16.566Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-18T01:42:19.901Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-18T01:42:25.544Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-18T01:42:29.836Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-18T01:42:34.292Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-18T01:42:37.046Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-18T01:42:40.451Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-18T01:42:40.870Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-18T01:42:40.870Z] The best model improves the baseline by 14.52%. [2025-12-18T01:42:40.870Z] Top recommended movies for user id 72: [2025-12-18T01:42:40.870Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-18T01:42:40.870Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-18T01:42:40.870Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-18T01:42:40.870Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-18T01:42:40.870Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-18T01:42:40.870Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (30761.154 ms) ====== [2025-12-18T01:42:40.870Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-18T01:42:41.277Z] GC before operation: completed in 107.972 ms, heap usage 679.054 MB -> 93.387 MB. [2025-12-18T01:42:46.770Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-18T01:42:51.112Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-18T01:42:59.451Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-18T01:43:06.408Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-18T01:43:08.342Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-18T01:43:11.987Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-18T01:43:17.805Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-18T01:43:21.286Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-18T01:43:21.286Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-18T01:43:21.286Z] The best model improves the baseline by 14.52%. [2025-12-18T01:43:21.286Z] Top recommended movies for user id 72: [2025-12-18T01:43:21.286Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-18T01:43:21.286Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-18T01:43:21.286Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-18T01:43:21.286Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-18T01:43:21.286Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-18T01:43:21.286Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (40271.565 ms) ====== [2025-12-18T01:43:21.286Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-18T01:43:21.667Z] GC before operation: completed in 141.373 ms, heap usage 130.290 MB -> 91.569 MB. [2025-12-18T01:43:28.236Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-18T01:43:30.032Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-18T01:43:31.820Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-18T01:43:33.663Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-18T01:43:34.970Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-18T01:43:36.266Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-18T01:43:37.537Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-18T01:43:38.759Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-18T01:43:38.759Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-18T01:43:38.759Z] The best model improves the baseline by 14.52%. [2025-12-18T01:43:38.759Z] Top recommended movies for user id 72: [2025-12-18T01:43:38.759Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-18T01:43:38.759Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-18T01:43:38.759Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-18T01:43:38.759Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-18T01:43:38.759Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-18T01:43:38.759Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (17318.133 ms) ====== [2025-12-18T01:43:38.759Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-18T01:43:38.759Z] GC before operation: completed in 66.862 ms, heap usage 844.452 MB -> 93.858 MB. [2025-12-18T01:43:40.580Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-18T01:43:44.874Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-18T01:43:47.455Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-18T01:43:50.743Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-18T01:43:52.011Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-18T01:43:53.266Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-18T01:43:54.509Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-18T01:43:56.353Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-18T01:43:56.353Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-18T01:43:56.353Z] The best model improves the baseline by 14.52%. [2025-12-18T01:43:56.719Z] Top recommended movies for user id 72: [2025-12-18T01:43:56.719Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-18T01:43:56.719Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-18T01:43:56.719Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-18T01:43:56.719Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-18T01:43:56.719Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-18T01:43:56.719Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (17745.103 ms) ====== [2025-12-18T01:43:56.719Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-18T01:43:56.719Z] GC before operation: completed in 75.394 ms, heap usage 852.636 MB -> 93.939 MB. [2025-12-18T01:44:00.924Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-18T01:44:05.331Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-18T01:44:07.804Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-18T01:44:10.238Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-18T01:44:11.491Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-18T01:44:13.321Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-18T01:44:14.613Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-18T01:44:16.417Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-18T01:44:16.417Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-18T01:44:16.417Z] The best model improves the baseline by 14.52%. [2025-12-18T01:44:16.417Z] Top recommended movies for user id 72: [2025-12-18T01:44:16.417Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-18T01:44:16.417Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-18T01:44:16.417Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-18T01:44:16.417Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-18T01:44:16.417Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-18T01:44:16.417Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (19792.996 ms) ====== [2025-12-18T01:44:17.214Z] ----------------------------------- [2025-12-18T01:44:17.214Z] renaissance-movie-lens_0_PASSED [2025-12-18T01:44:17.214Z] ----------------------------------- [2025-12-18T01:44:17.214Z] [2025-12-18T01:44:17.214Z] TEST TEARDOWN: [2025-12-18T01:44:17.214Z] Nothing to be done for teardown. [2025-12-18T01:44:17.214Z] renaissance-movie-lens_0 Finish Time: Wed Dec 17 17:44:17 2025 Epoch Time (ms): 1766022257032