renaissance-movie-lens_0
[2025-11-13T02:02:22.380Z] Running test renaissance-movie-lens_0 ...
[2025-11-13T02:02:22.380Z] ===============================================
[2025-11-13T02:02:22.380Z] renaissance-movie-lens_0 Start Time: Thu Nov 13 02:02:19 2025 Epoch Time (ms): 1762999339809
[2025-11-13T02:02:22.380Z] variation: NoOptions
[2025-11-13T02:02:22.380Z] JVM_OPTIONS:
[2025-11-13T02:02:22.380Z] { \
[2025-11-13T02:02:22.380Z] echo ""; echo "TEST SETUP:"; \
[2025-11-13T02:02:22.380Z] echo "Nothing to be done for setup."; \
[2025-11-13T02:02:22.380Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17629947283868/renaissance-movie-lens_0"; \
[2025-11-13T02:02:22.380Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17629947283868/renaissance-movie-lens_0"; \
[2025-11-13T02:02:22.380Z] echo ""; echo "TESTING:"; \
[2025-11-13T02:02:22.380Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17629947283868/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-11-13T02:02:22.380Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17629947283868/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-11-13T02:02:22.380Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-11-13T02:02:22.380Z] echo "Nothing to be done for teardown."; \
[2025-11-13T02:02:22.380Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17629947283868/TestTargetResult";
[2025-11-13T02:02:22.380Z]
[2025-11-13T02:02:22.380Z] TEST SETUP:
[2025-11-13T02:02:22.380Z] Nothing to be done for setup.
[2025-11-13T02:02:22.380Z]
[2025-11-13T02:02:22.380Z] TESTING:
[2025-11-13T02:02:45.368Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-11-13T02:03:18.857Z] 02:03:14.469 WARN [dispatcher-event-loop-3] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-11-13T02:03:26.087Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-11-13T02:03:27.748Z] Training: 60056, validation: 20285, test: 19854
[2025-11-13T02:03:27.748Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-11-13T02:03:28.081Z] GC before operation: completed in 572.729 ms, heap usage 698.994 MB -> 76.429 MB.
[2025-11-13T02:03:55.778Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T02:04:11.622Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T02:04:27.552Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T02:04:38.454Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T02:04:45.711Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T02:04:52.968Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T02:05:00.397Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T02:05:07.671Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T02:05:08.371Z] 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.
[2025-11-13T02:05:08.697Z] The best model improves the baseline by 14.52%.
[2025-11-13T02:05:09.844Z] Top recommended movies for user id 72:
[2025-11-13T02:05:09.844Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T02:05:09.844Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T02:05:09.844Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T02:05:09.844Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T02:05:09.844Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T02:05:09.844Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (101860.499 ms) ======
[2025-11-13T02:05:09.844Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-11-13T02:05:10.990Z] GC before operation: completed in 1086.352 ms, heap usage 181.303 MB -> 88.069 MB.
[2025-11-13T02:05:24.092Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T02:05:34.873Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T02:05:43.884Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T02:05:54.677Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T02:06:00.543Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T02:06:06.416Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T02:06:12.297Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T02:06:18.163Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T02:06:18.944Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-13T02:06:19.303Z] The best model improves the baseline by 14.52%.
[2025-11-13T02:06:20.000Z] Top recommended movies for user id 72:
[2025-11-13T02:06:20.000Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T02:06:20.000Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T02:06:20.000Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T02:06:20.000Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T02:06:20.000Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T02:06:20.000Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (68940.389 ms) ======
[2025-11-13T02:06:20.000Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-11-13T02:06:21.192Z] GC before operation: completed in 1012.461 ms, heap usage 768.594 MB -> 92.851 MB.
[2025-11-13T02:06:31.982Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T02:06:42.749Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T02:06:51.597Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T02:07:00.557Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T02:07:06.419Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T02:07:12.304Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T02:07:17.028Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T02:07:22.900Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T02:07:24.036Z] 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.
[2025-11-13T02:07:24.036Z] The best model improves the baseline by 14.52%.
[2025-11-13T02:07:24.736Z] Top recommended movies for user id 72:
[2025-11-13T02:07:24.736Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T02:07:24.737Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T02:07:24.737Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T02:07:24.737Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T02:07:24.737Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T02:07:24.737Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (63752.316 ms) ======
[2025-11-13T02:07:24.737Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-11-13T02:07:25.888Z] GC before operation: completed in 880.337 ms, heap usage 285.304 MB -> 89.694 MB.
[2025-11-13T02:07:34.759Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T02:07:45.538Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T02:07:52.765Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T02:08:01.619Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T02:08:07.500Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T02:08:13.566Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T02:08:19.443Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T02:08:24.163Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T02:08:25.298Z] 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.
[2025-11-13T02:08:25.298Z] The best model improves the baseline by 14.52%.
[2025-11-13T02:08:25.996Z] Top recommended movies for user id 72:
[2025-11-13T02:08:25.996Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T02:08:25.996Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T02:08:25.996Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T02:08:25.996Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T02:08:25.996Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T02:08:25.996Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (60442.976 ms) ======
[2025-11-13T02:08:25.996Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-11-13T02:08:27.164Z] GC before operation: completed in 865.149 ms, heap usage 265.100 MB -> 89.944 MB.
[2025-11-13T02:08:36.011Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T02:08:46.794Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T02:08:55.744Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T02:09:04.594Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T02:09:10.491Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T02:09:15.212Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T02:09:21.086Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T02:09:26.949Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T02:09:26.949Z] 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.
[2025-11-13T02:09:27.378Z] The best model improves the baseline by 14.52%.
[2025-11-13T02:09:27.951Z] Top recommended movies for user id 72:
[2025-11-13T02:09:27.951Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T02:09:27.951Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T02:09:27.951Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T02:09:27.951Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T02:09:27.951Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T02:09:27.951Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (61020.742 ms) ======
[2025-11-13T02:09:27.951Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-11-13T02:09:29.088Z] GC before operation: completed in 935.053 ms, heap usage 181.594 MB -> 89.866 MB.
[2025-11-13T02:09:39.849Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T02:09:47.106Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T02:09:57.889Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T02:10:05.122Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T02:10:11.060Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T02:10:15.830Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T02:10:20.546Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T02:10:25.273Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T02:10:25.972Z] 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.
[2025-11-13T02:10:26.297Z] The best model improves the baseline by 14.52%.
[2025-11-13T02:10:26.995Z] Top recommended movies for user id 72:
[2025-11-13T02:10:26.995Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T02:10:26.995Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T02:10:26.995Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T02:10:26.995Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T02:10:26.995Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T02:10:26.995Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (58019.923 ms) ======
[2025-11-13T02:10:26.995Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-11-13T02:10:27.717Z] GC before operation: completed in 737.461 ms, heap usage 855.989 MB -> 94.514 MB.
[2025-11-13T02:10:36.562Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T02:10:45.608Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T02:10:52.837Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T02:11:01.693Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T02:11:06.420Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T02:11:11.149Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T02:11:17.088Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T02:11:21.809Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T02:11:22.136Z] 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.
[2025-11-13T02:11:22.136Z] The best model improves the baseline by 14.52%.
[2025-11-13T02:11:23.292Z] Top recommended movies for user id 72:
[2025-11-13T02:11:23.292Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T02:11:23.292Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T02:11:23.292Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T02:11:23.292Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T02:11:23.292Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T02:11:23.292Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (55336.214 ms) ======
[2025-11-13T02:11:23.292Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-11-13T02:11:23.623Z] GC before operation: completed in 692.770 ms, heap usage 243.577 MB -> 90.255 MB.
[2025-11-13T02:11:32.467Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T02:11:41.317Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T02:11:50.163Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T02:11:59.042Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T02:12:03.769Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T02:12:09.635Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T02:12:14.383Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T02:12:20.265Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T02:12:20.592Z] 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.
[2025-11-13T02:12:20.917Z] The best model improves the baseline by 14.52%.
[2025-11-13T02:12:21.251Z] Top recommended movies for user id 72:
[2025-11-13T02:12:21.251Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T02:12:21.251Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T02:12:21.251Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T02:12:21.251Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T02:12:21.251Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T02:12:21.251Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (57696.522 ms) ======
[2025-11-13T02:12:21.251Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-11-13T02:12:21.969Z] GC before operation: completed in 624.711 ms, heap usage 440.675 MB -> 90.700 MB.
[2025-11-13T02:12:30.837Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T02:12:39.732Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T02:12:48.598Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T02:12:57.460Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T02:13:03.330Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T02:13:09.297Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T02:13:14.024Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T02:13:19.906Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T02:13:20.231Z] 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.
[2025-11-13T02:13:20.556Z] The best model improves the baseline by 14.52%.
[2025-11-13T02:13:21.690Z] Top recommended movies for user id 72:
[2025-11-13T02:13:21.690Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T02:13:21.690Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T02:13:21.690Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T02:13:21.690Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T02:13:21.690Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T02:13:21.690Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (59622.822 ms) ======
[2025-11-13T02:13:21.690Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-11-13T02:13:22.404Z] GC before operation: completed in 727.003 ms, heap usage 246.979 MB -> 90.421 MB.
[2025-11-13T02:13:31.273Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T02:13:40.129Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T02:13:51.137Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T02:13:58.361Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T02:14:04.239Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T02:14:08.970Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T02:14:14.842Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T02:14:19.566Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T02:14:20.745Z] 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.
[2025-11-13T02:14:21.068Z] The best model improves the baseline by 14.52%.
[2025-11-13T02:14:21.772Z] Top recommended movies for user id 72:
[2025-11-13T02:14:21.772Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T02:14:21.772Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T02:14:21.772Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T02:14:21.772Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T02:14:21.772Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T02:14:21.772Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (59216.865 ms) ======
[2025-11-13T02:14:21.772Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-11-13T02:14:22.103Z] GC before operation: completed in 643.056 ms, heap usage 385.375 MB -> 90.780 MB.
[2025-11-13T02:14:30.972Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T02:14:39.828Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T02:14:48.685Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T02:14:57.554Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T02:15:02.325Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T02:15:07.047Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T02:15:12.919Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T02:15:17.642Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T02:15:17.969Z] 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.
[2025-11-13T02:15:18.297Z] The best model improves the baseline by 14.52%.
[2025-11-13T02:15:19.041Z] Top recommended movies for user id 72:
[2025-11-13T02:15:19.041Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T02:15:19.041Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T02:15:19.041Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T02:15:19.041Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T02:15:19.041Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T02:15:19.041Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (56601.926 ms) ======
[2025-11-13T02:15:19.041Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-11-13T02:15:19.748Z] GC before operation: completed in 699.889 ms, heap usage 513.418 MB -> 90.655 MB.
[2025-11-13T02:15:28.619Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T02:15:35.973Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T02:15:44.847Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T02:15:52.071Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T02:15:56.789Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T02:16:01.512Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T02:16:07.488Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T02:16:12.211Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T02:16:12.534Z] 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.
[2025-11-13T02:16:12.534Z] The best model improves the baseline by 14.52%.
[2025-11-13T02:16:13.234Z] Top recommended movies for user id 72:
[2025-11-13T02:16:13.234Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T02:16:13.234Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T02:16:13.234Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T02:16:13.234Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T02:16:13.234Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T02:16:13.234Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (53747.562 ms) ======
[2025-11-13T02:16:13.234Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-11-13T02:16:13.938Z] GC before operation: completed in 666.071 ms, heap usage 202.522 MB -> 90.410 MB.
[2025-11-13T02:16:22.814Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T02:16:31.667Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T02:16:38.894Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T02:16:46.156Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T02:16:52.035Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T02:16:57.908Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T02:17:02.628Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T02:17:07.353Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T02:17:08.052Z] 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.
[2025-11-13T02:17:08.052Z] The best model improves the baseline by 14.52%.
[2025-11-13T02:17:08.754Z] Top recommended movies for user id 72:
[2025-11-13T02:17:08.754Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T02:17:08.754Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T02:17:08.754Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T02:17:08.754Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T02:17:08.754Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T02:17:08.754Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (54833.289 ms) ======
[2025-11-13T02:17:08.754Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-11-13T02:17:09.473Z] GC before operation: completed in 676.016 ms, heap usage 862.076 MB -> 94.862 MB.
[2025-11-13T02:17:18.378Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T02:17:25.612Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T02:17:34.501Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T02:17:41.779Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T02:17:46.550Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T02:17:51.273Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T02:17:57.179Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T02:18:01.904Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T02:18:02.228Z] 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.
[2025-11-13T02:18:02.228Z] The best model improves the baseline by 14.52%.
[2025-11-13T02:18:02.924Z] Top recommended movies for user id 72:
[2025-11-13T02:18:02.924Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T02:18:02.924Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T02:18:02.924Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T02:18:02.924Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T02:18:02.924Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T02:18:02.924Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (53554.165 ms) ======
[2025-11-13T02:18:02.924Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-11-13T02:18:03.663Z] GC before operation: completed in 684.301 ms, heap usage 572.585 MB -> 94.073 MB.
[2025-11-13T02:18:12.505Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T02:18:21.346Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T02:18:28.619Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T02:18:37.499Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T02:18:43.366Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T02:18:48.438Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T02:18:53.159Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T02:18:59.032Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T02:18:59.731Z] 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.
[2025-11-13T02:18:59.731Z] The best model improves the baseline by 14.52%.
[2025-11-13T02:19:00.451Z] Top recommended movies for user id 72:
[2025-11-13T02:19:00.451Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T02:19:00.451Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T02:19:00.451Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T02:19:00.451Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T02:19:00.451Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T02:19:00.451Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (56603.439 ms) ======
[2025-11-13T02:19:00.451Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-11-13T02:19:01.156Z] GC before operation: completed in 653.275 ms, heap usage 418.640 MB -> 90.926 MB.
[2025-11-13T02:19:10.022Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T02:19:18.933Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T02:19:27.769Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T02:19:36.765Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T02:19:41.480Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T02:19:46.197Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T02:19:53.441Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T02:19:57.660Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T02:19:58.885Z] 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.
[2025-11-13T02:19:58.885Z] The best model improves the baseline by 14.52%.
[2025-11-13T02:19:59.602Z] Top recommended movies for user id 72:
[2025-11-13T02:19:59.602Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T02:19:59.602Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T02:19:59.602Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T02:19:59.602Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T02:19:59.602Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T02:19:59.602Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (58480.156 ms) ======
[2025-11-13T02:19:59.602Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-11-13T02:20:00.305Z] GC before operation: completed in 665.351 ms, heap usage 106.446 MB -> 90.552 MB.
[2025-11-13T02:20:09.279Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T02:20:18.220Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T02:20:27.142Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T02:20:34.416Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T02:20:40.488Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T02:20:45.219Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T02:20:51.201Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T02:20:55.937Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T02:20:57.079Z] 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.
[2025-11-13T02:20:57.079Z] The best model improves the baseline by 14.52%.
[2025-11-13T02:20:57.786Z] Top recommended movies for user id 72:
[2025-11-13T02:20:57.786Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T02:20:57.786Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T02:20:57.786Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T02:20:57.786Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T02:20:57.786Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T02:20:57.786Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (57600.406 ms) ======
[2025-11-13T02:20:57.786Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-11-13T02:20:58.504Z] GC before operation: completed in 641.757 ms, heap usage 379.866 MB -> 90.906 MB.
[2025-11-13T02:21:07.526Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T02:21:16.437Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T02:21:23.659Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T02:21:31.133Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T02:21:37.018Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T02:21:41.872Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T02:21:46.679Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T02:21:51.390Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T02:21:52.149Z] 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.
[2025-11-13T02:21:52.149Z] The best model improves the baseline by 14.52%.
[2025-11-13T02:21:52.855Z] Top recommended movies for user id 72:
[2025-11-13T02:21:52.855Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T02:21:52.855Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T02:21:52.855Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T02:21:52.855Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T02:21:52.855Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T02:21:52.855Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (54376.622 ms) ======
[2025-11-13T02:21:52.855Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-11-13T02:21:53.560Z] GC before operation: completed in 714.150 ms, heap usage 822.493 MB -> 94.488 MB.
[2025-11-13T02:22:02.725Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T02:22:11.576Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T02:22:18.936Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T02:22:27.803Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T02:22:31.565Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T02:22:36.297Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T02:22:42.165Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T02:22:47.176Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T02:22:47.176Z] 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.
[2025-11-13T02:22:47.501Z] The best model improves the baseline by 14.52%.
[2025-11-13T02:22:48.218Z] Top recommended movies for user id 72:
[2025-11-13T02:22:48.218Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T02:22:48.218Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T02:22:48.218Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T02:22:48.218Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T02:22:48.218Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T02:22:48.218Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (54644.293 ms) ======
[2025-11-13T02:22:48.218Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-11-13T02:22:48.933Z] GC before operation: completed in 709.849 ms, heap usage 849.765 MB -> 94.746 MB.
[2025-11-13T02:22:57.786Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T02:23:05.032Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T02:23:13.886Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T02:23:21.178Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T02:23:25.899Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T02:23:30.646Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T02:23:36.517Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T02:23:41.237Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T02:23:41.563Z] 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.
[2025-11-13T02:23:41.891Z] The best model improves the baseline by 14.52%.
[2025-11-13T02:23:42.596Z] Top recommended movies for user id 72:
[2025-11-13T02:23:42.596Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T02:23:42.596Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T02:23:42.596Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T02:23:42.596Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T02:23:42.596Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T02:23:42.596Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (53616.456 ms) ======
[2025-11-13T02:23:46.513Z] -----------------------------------
[2025-11-13T02:23:46.513Z] renaissance-movie-lens_0_PASSED
[2025-11-13T02:23:46.513Z] -----------------------------------
[2025-11-13T02:23:46.513Z]
[2025-11-13T02:23:46.513Z] TEST TEARDOWN:
[2025-11-13T02:23:46.513Z] Nothing to be done for teardown.
[2025-11-13T02:23:46.513Z] renaissance-movie-lens_0 Finish Time: Thu Nov 13 02:23:46 2025 Epoch Time (ms): 1763000626416