renaissance-movie-lens_0
[2026-02-27T09:31:05.381Z] Running test renaissance-movie-lens_0 ...
[2026-02-27T09:31:05.381Z] ===============================================
[2026-02-27T09:31:05.381Z] renaissance-movie-lens_0 Start Time: Fri Feb 27 09:31:05 2026 Epoch Time (ms): 1772184665158
[2026-02-27T09:31:05.381Z] variation: NoOptions
[2026-02-27T09:31:05.381Z] JVM_OPTIONS:
[2026-02-27T09:31:05.381Z] { \
[2026-02-27T09:31:05.381Z] echo ""; echo "TEST SETUP:"; \
[2026-02-27T09:31:05.381Z] echo "Nothing to be done for setup."; \
[2026-02-27T09:31:05.381Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_rerun/aqa-tests/TKG/../TKG/output_17721840542737/renaissance-movie-lens_0"; \
[2026-02-27T09:31:05.381Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_rerun/aqa-tests/TKG/../TKG/output_17721840542737/renaissance-movie-lens_0"; \
[2026-02-27T09:31:05.381Z] echo ""; echo "TESTING:"; \
[2026-02-27T09:31:05.381Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_rerun/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_rerun/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_rerun/aqa-tests/TKG/../TKG/output_17721840542737/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2026-02-27T09:31:05.381Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_rerun/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_rerun/aqa-tests/TKG/../TKG/output_17721840542737/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2026-02-27T09:31:05.381Z] echo ""; echo "TEST TEARDOWN:"; \
[2026-02-27T09:31:05.381Z] echo "Nothing to be done for teardown."; \
[2026-02-27T09:31:05.381Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_rerun/aqa-tests/TKG/../TKG/output_17721840542737/TestTargetResult";
[2026-02-27T09:31:05.381Z]
[2026-02-27T09:31:05.381Z] TEST SETUP:
[2026-02-27T09:31:05.381Z] Nothing to be done for setup.
[2026-02-27T09:31:05.381Z]
[2026-02-27T09:31:05.381Z] TESTING:
[2026-02-27T09:31:28.528Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2026-02-27T09:32:08.486Z] 09:32:01.995 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.
[2026-02-27T09:32:15.704Z] Got 100004 ratings from 671 users on 9066 movies.
[2026-02-27T09:32:17.935Z] Training: 60056, validation: 20285, test: 19854
[2026-02-27T09:32:17.935Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2026-02-27T09:32:18.654Z] GC before operation: completed in 532.888 ms, heap usage 342.515 MB -> 76.897 MB.
[2026-02-27T09:32:51.945Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-27T09:33:07.774Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-27T09:33:20.852Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-27T09:33:33.926Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-27T09:33:39.813Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-27T09:33:47.072Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-27T09:33:54.326Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-27T09:34:01.579Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-27T09:34:01.579Z] 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.
[2026-02-27T09:34:02.284Z] The best model improves the baseline by 14.52%.
[2026-02-27T09:34:03.430Z] Top recommended movies for user id 72:
[2026-02-27T09:34:03.430Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-27T09:34:03.430Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-27T09:34:03.430Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-27T09:34:03.430Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-27T09:34:03.430Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-27T09:34:03.430Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (104768.994 ms) ======
[2026-02-27T09:34:03.430Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2026-02-27T09:34:04.146Z] GC before operation: completed in 890.899 ms, heap usage 261.181 MB -> 89.728 MB.
[2026-02-27T09:34:17.253Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-27T09:34:26.390Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-27T09:34:37.477Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-27T09:34:48.261Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-27T09:34:53.001Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-27T09:34:58.953Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-27T09:35:06.208Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-27T09:35:12.080Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-27T09:35:12.777Z] 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.
[2026-02-27T09:35:12.777Z] The best model improves the baseline by 14.52%.
[2026-02-27T09:35:13.931Z] Top recommended movies for user id 72:
[2026-02-27T09:35:13.931Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-27T09:35:13.931Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-27T09:35:13.931Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-27T09:35:13.931Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-27T09:35:13.931Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-27T09:35:13.931Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (69393.916 ms) ======
[2026-02-27T09:35:13.931Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2026-02-27T09:35:14.654Z] GC before operation: completed in 924.958 ms, heap usage 776.574 MB -> 93.549 MB.
[2026-02-27T09:35:25.424Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-27T09:35:34.283Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-27T09:35:45.062Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-27T09:35:53.902Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-27T09:35:58.646Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-27T09:36:04.520Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-27T09:36:10.383Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-27T09:36:16.260Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-27T09:36:16.960Z] 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.
[2026-02-27T09:36:16.960Z] The best model improves the baseline by 14.52%.
[2026-02-27T09:36:18.113Z] Top recommended movies for user id 72:
[2026-02-27T09:36:18.113Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-27T09:36:18.113Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-27T09:36:18.113Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-27T09:36:18.113Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-27T09:36:18.113Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-27T09:36:18.113Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (63304.115 ms) ======
[2026-02-27T09:36:18.113Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2026-02-27T09:36:18.841Z] GC before operation: completed in 906.092 ms, heap usage 215.915 MB -> 90.374 MB.
[2026-02-27T09:36:29.631Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-27T09:36:38.479Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-27T09:36:47.656Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-27T09:36:56.595Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-27T09:37:02.491Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-27T09:37:08.367Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-27T09:37:13.108Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-27T09:37:18.966Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-27T09:37:19.294Z] 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.
[2026-02-27T09:37:19.294Z] The best model improves the baseline by 14.52%.
[2026-02-27T09:37:20.428Z] Top recommended movies for user id 72:
[2026-02-27T09:37:20.428Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-27T09:37:20.428Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-27T09:37:20.428Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-27T09:37:20.428Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-27T09:37:20.428Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-27T09:37:20.428Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (61471.673 ms) ======
[2026-02-27T09:37:20.428Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2026-02-27T09:37:21.147Z] GC before operation: completed in 954.027 ms, heap usage 559.187 MB -> 91.065 MB.
[2026-02-27T09:37:31.971Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-27T09:37:40.881Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-27T09:37:52.396Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-27T09:37:58.266Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-27T09:38:04.133Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-27T09:38:10.023Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-27T09:38:15.891Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-27T09:38:21.778Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-27T09:38:22.913Z] 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.
[2026-02-27T09:38:22.913Z] The best model improves the baseline by 14.52%.
[2026-02-27T09:38:23.613Z] Top recommended movies for user id 72:
[2026-02-27T09:38:23.613Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-27T09:38:23.613Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-27T09:38:23.613Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-27T09:38:23.613Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-27T09:38:23.613Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-27T09:38:23.613Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (62459.916 ms) ======
[2026-02-27T09:38:23.613Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2026-02-27T09:38:24.787Z] GC before operation: completed in 958.042 ms, heap usage 905.934 MB -> 97.353 MB.
[2026-02-27T09:38:37.891Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-27T09:38:46.739Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-27T09:38:57.519Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-27T09:39:05.014Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-27T09:39:10.895Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-27T09:39:16.757Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-27T09:39:21.484Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-27T09:39:27.397Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-27T09:39:27.723Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2026-02-27T09:39:28.048Z] The best model improves the baseline by 14.52%.
[2026-02-27T09:39:28.764Z] Top recommended movies for user id 72:
[2026-02-27T09:39:28.764Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-27T09:39:28.764Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-27T09:39:28.764Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-27T09:39:28.765Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-27T09:39:28.765Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-27T09:39:28.765Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (63962.403 ms) ======
[2026-02-27T09:39:28.765Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2026-02-27T09:39:29.502Z] GC before operation: completed in 957.458 ms, heap usage 279.710 MB -> 95.399 MB.
[2026-02-27T09:39:38.361Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-27T09:39:47.250Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-27T09:39:55.136Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-27T09:40:03.992Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-27T09:40:08.743Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-27T09:40:14.648Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-27T09:40:19.382Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-27T09:40:24.456Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-27T09:40:26.911Z] 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.
[2026-02-27T09:40:26.911Z] The best model improves the baseline by 14.52%.
[2026-02-27T09:40:26.911Z] Top recommended movies for user id 72:
[2026-02-27T09:40:26.911Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-27T09:40:26.911Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-27T09:40:26.911Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-27T09:40:26.911Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-27T09:40:26.911Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-27T09:40:26.911Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (56770.833 ms) ======
[2026-02-27T09:40:26.911Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2026-02-27T09:40:29.394Z] GC before operation: completed in 967.880 ms, heap usage 218.473 MB -> 90.816 MB.
[2026-02-27T09:40:36.470Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-27T09:40:46.829Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-27T09:40:52.826Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-27T09:41:01.743Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-27T09:41:06.465Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-27T09:41:11.179Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-27T09:41:16.049Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-27T09:41:21.967Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-27T09:41:21.967Z] 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.
[2026-02-27T09:41:22.425Z] The best model improves the baseline by 14.52%.
[2026-02-27T09:41:23.401Z] Top recommended movies for user id 72:
[2026-02-27T09:41:23.401Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-27T09:41:23.401Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-27T09:41:23.401Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-27T09:41:23.401Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-27T09:41:23.401Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-27T09:41:23.401Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (55684.204 ms) ======
[2026-02-27T09:41:23.401Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2026-02-27T09:41:24.046Z] GC before operation: completed in 972.398 ms, heap usage 866.207 MB -> 95.455 MB.
[2026-02-27T09:41:32.976Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-27T09:41:41.843Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-27T09:41:49.132Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-27T09:41:58.219Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-27T09:42:04.090Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-27T09:42:08.812Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-27T09:42:14.693Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-27T09:42:20.563Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-27T09:42:21.264Z] 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.
[2026-02-27T09:42:21.264Z] The best model improves the baseline by 14.52%.
[2026-02-27T09:42:22.414Z] Top recommended movies for user id 72:
[2026-02-27T09:42:22.414Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-27T09:42:22.414Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-27T09:42:22.414Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-27T09:42:22.414Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-27T09:42:22.414Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-27T09:42:22.414Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (58210.619 ms) ======
[2026-02-27T09:42:22.415Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2026-02-27T09:42:23.147Z] GC before operation: completed in 930.373 ms, heap usage 141.122 MB -> 94.026 MB.
[2026-02-27T09:42:33.924Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-27T09:42:44.757Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-27T09:42:53.620Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-27T09:43:02.480Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-27T09:43:08.361Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-27T09:43:13.096Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-27T09:43:18.972Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-27T09:43:23.699Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-27T09:43:24.833Z] 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.
[2026-02-27T09:43:24.833Z] The best model improves the baseline by 14.52%.
[2026-02-27T09:43:25.534Z] Top recommended movies for user id 72:
[2026-02-27T09:43:25.534Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-27T09:43:25.534Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-27T09:43:25.534Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-27T09:43:25.534Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-27T09:43:25.534Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-27T09:43:25.534Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (62360.692 ms) ======
[2026-02-27T09:43:25.534Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2026-02-27T09:43:26.693Z] GC before operation: completed in 956.210 ms, heap usage 717.049 MB -> 95.107 MB.
[2026-02-27T09:43:37.812Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-27T09:43:48.588Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-27T09:43:59.399Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-27T09:44:08.240Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-27T09:44:14.102Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-27T09:44:19.972Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-27T09:44:25.879Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-27T09:44:30.616Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-27T09:44:31.746Z] 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.
[2026-02-27T09:44:31.746Z] The best model improves the baseline by 14.52%.
[2026-02-27T09:44:32.442Z] Top recommended movies for user id 72:
[2026-02-27T09:44:32.442Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-27T09:44:32.442Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-27T09:44:32.442Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-27T09:44:32.442Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-27T09:44:32.442Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-27T09:44:32.442Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (66005.862 ms) ======
[2026-02-27T09:44:32.442Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2026-02-27T09:44:33.612Z] GC before operation: completed in 946.095 ms, heap usage 477.075 MB -> 92.443 MB.
[2026-02-27T09:44:44.388Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-27T09:44:55.199Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-27T09:45:04.127Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-27T09:45:11.345Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-27T09:45:17.209Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-27T09:45:21.923Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-27T09:45:26.653Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-27T09:45:32.535Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-27T09:45:32.535Z] 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.
[2026-02-27T09:45:32.926Z] The best model improves the baseline by 14.52%.
[2026-02-27T09:45:33.626Z] Top recommended movies for user id 72:
[2026-02-27T09:45:33.626Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-27T09:45:33.626Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-27T09:45:33.626Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-27T09:45:33.626Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-27T09:45:33.626Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-27T09:45:33.626Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (60166.124 ms) ======
[2026-02-27T09:45:33.626Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2026-02-27T09:45:34.780Z] GC before operation: completed in 997.624 ms, heap usage 877.050 MB -> 98.893 MB.
[2026-02-27T09:45:43.998Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-27T09:45:52.878Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-27T09:46:01.760Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-27T09:46:08.994Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-27T09:46:13.713Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-27T09:46:19.599Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-27T09:46:24.323Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-27T09:46:29.048Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-27T09:46:29.747Z] 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.
[2026-02-27T09:46:29.747Z] The best model improves the baseline by 14.52%.
[2026-02-27T09:46:30.448Z] Top recommended movies for user id 72:
[2026-02-27T09:46:30.448Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-27T09:46:30.448Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-27T09:46:30.448Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-27T09:46:30.448Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-27T09:46:30.448Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-27T09:46:30.448Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (55992.939 ms) ======
[2026-02-27T09:46:30.448Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2026-02-27T09:46:31.604Z] GC before operation: completed in 1021.553 ms, heap usage 1.109 GB -> 96.382 MB.
[2026-02-27T09:46:42.389Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-27T09:46:49.622Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-27T09:46:58.487Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-27T09:47:05.722Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-27T09:47:10.440Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-27T09:47:15.151Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-27T09:47:21.035Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-27T09:47:25.768Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-27T09:47:26.093Z] 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.
[2026-02-27T09:47:26.093Z] The best model improves the baseline by 14.52%.
[2026-02-27T09:47:26.805Z] Top recommended movies for user id 72:
[2026-02-27T09:47:26.805Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-27T09:47:26.805Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-27T09:47:26.805Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-27T09:47:26.805Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-27T09:47:26.805Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-27T09:47:26.805Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (55362.164 ms) ======
[2026-02-27T09:47:26.805Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2026-02-27T09:47:27.984Z] GC before operation: completed in 968.807 ms, heap usage 842.955 MB -> 95.160 MB.
[2026-02-27T09:47:36.860Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-27T09:47:45.730Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-27T09:47:53.203Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-27T09:48:00.743Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-27T09:48:05.478Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-27T09:48:11.352Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-27T09:48:16.083Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-27T09:48:20.809Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-27T09:48:21.515Z] 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.
[2026-02-27T09:48:21.515Z] The best model improves the baseline by 14.52%.
[2026-02-27T09:48:22.215Z] Top recommended movies for user id 72:
[2026-02-27T09:48:22.215Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-27T09:48:22.215Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-27T09:48:22.215Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-27T09:48:22.215Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-27T09:48:22.215Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-27T09:48:22.215Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (54413.427 ms) ======
[2026-02-27T09:48:22.215Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2026-02-27T09:48:23.397Z] GC before operation: completed in 989.311 ms, heap usage 185.880 MB -> 91.202 MB.
[2026-02-27T09:48:32.272Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-27T09:48:41.131Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-27T09:48:48.371Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-27T09:48:55.611Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-27T09:49:01.515Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-27T09:49:06.248Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-27T09:49:10.998Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-27T09:49:15.727Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-27T09:49:16.430Z] 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.
[2026-02-27T09:49:16.757Z] The best model improves the baseline by 14.52%.
[2026-02-27T09:49:17.464Z] Top recommended movies for user id 72:
[2026-02-27T09:49:17.464Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-27T09:49:17.464Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-27T09:49:17.464Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-27T09:49:17.464Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-27T09:49:17.464Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-27T09:49:17.464Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (54185.872 ms) ======
[2026-02-27T09:49:17.464Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2026-02-27T09:49:18.642Z] GC before operation: completed in 965.372 ms, heap usage 203.867 MB -> 91.069 MB.
[2026-02-27T09:49:27.505Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-27T09:49:34.898Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-27T09:49:45.135Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-27T09:49:51.138Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-27T09:49:55.923Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-27T09:50:00.653Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-27T09:50:06.528Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-27T09:50:11.260Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-27T09:50:11.958Z] 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.
[2026-02-27T09:50:11.958Z] The best model improves the baseline by 14.52%.
[2026-02-27T09:50:12.657Z] Top recommended movies for user id 72:
[2026-02-27T09:50:12.657Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-27T09:50:12.657Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-27T09:50:12.657Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-27T09:50:12.657Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-27T09:50:12.657Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-27T09:50:12.657Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (54177.951 ms) ======
[2026-02-27T09:50:12.657Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2026-02-27T09:50:13.829Z] GC before operation: completed in 996.123 ms, heap usage 650.990 MB -> 95.031 MB.
[2026-02-27T09:50:22.676Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-27T09:50:29.897Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-27T09:50:38.745Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-27T09:50:45.981Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-27T09:50:50.708Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-27T09:50:55.670Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-27T09:51:00.415Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-27T09:51:05.159Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-27T09:51:06.297Z] 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.
[2026-02-27T09:51:06.297Z] The best model improves the baseline by 14.52%.
[2026-02-27T09:51:07.009Z] Top recommended movies for user id 72:
[2026-02-27T09:51:07.009Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-27T09:51:07.009Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-27T09:51:07.009Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-27T09:51:07.009Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-27T09:51:07.009Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-27T09:51:07.010Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (53539.800 ms) ======
[2026-02-27T09:51:07.010Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2026-02-27T09:51:08.168Z] GC before operation: completed in 997.979 ms, heap usage 257.162 MB -> 91.031 MB.
[2026-02-27T09:51:17.036Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-27T09:51:25.890Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-27T09:51:33.162Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-27T09:51:42.020Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-27T09:51:46.751Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-27T09:51:51.619Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-27T09:51:56.384Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-27T09:52:02.259Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-27T09:52:02.259Z] 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.
[2026-02-27T09:52:02.585Z] The best model improves the baseline by 14.52%.
[2026-02-27T09:52:03.294Z] Top recommended movies for user id 72:
[2026-02-27T09:52:03.294Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-27T09:52:03.294Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-27T09:52:03.294Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-27T09:52:03.294Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-27T09:52:03.294Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-27T09:52:03.294Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (54991.777 ms) ======
[2026-02-27T09:52:03.294Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2026-02-27T09:52:04.016Z] GC before operation: completed in 987.236 ms, heap usage 510.345 MB -> 91.586 MB.
[2026-02-27T09:52:12.866Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-27T09:52:20.105Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-27T09:52:28.971Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-27T09:52:36.208Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-27T09:52:40.937Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-27T09:52:46.097Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-27T09:52:50.834Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-27T09:52:55.559Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-27T09:52:56.698Z] 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.
[2026-02-27T09:52:56.698Z] The best model improves the baseline by 14.52%.
[2026-02-27T09:52:57.397Z] Top recommended movies for user id 72:
[2026-02-27T09:52:57.397Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-27T09:52:57.397Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-27T09:52:57.397Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-27T09:52:57.397Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-27T09:52:57.397Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-27T09:52:57.397Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (53417.370 ms) ======
[2026-02-27T09:53:02.133Z] -----------------------------------
[2026-02-27T09:53:02.133Z] renaissance-movie-lens_0_PASSED
[2026-02-27T09:53:02.133Z] -----------------------------------
[2026-02-27T09:53:02.133Z]
[2026-02-27T09:53:02.133Z] TEST TEARDOWN:
[2026-02-27T09:53:02.133Z] Nothing to be done for teardown.
[2026-02-27T09:53:02.133Z] renaissance-movie-lens_0 Finish Time: Fri Feb 27 09:53:01 2026 Epoch Time (ms): 1772185981230