renaissance-movie-lens_0
[2025-06-29T20:41:32.869Z] Running test renaissance-movie-lens_0 ...
[2025-06-29T20:41:32.869Z] ===============================================
[2025-06-29T20:41:32.869Z] renaissance-movie-lens_0 Start Time: Sun Jun 29 20:41:32 2025 Epoch Time (ms): 1751229692008
[2025-06-29T20:41:32.869Z] variation: NoOptions
[2025-06-29T20:41:32.869Z] JVM_OPTIONS:
[2025-06-29T20:41:32.869Z] { \
[2025-06-29T20:41:32.869Z] echo ""; echo "TEST SETUP:"; \
[2025-06-29T20:41:32.869Z] echo "Nothing to be done for setup."; \
[2025-06-29T20:41:32.869Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux_testList_1/aqa-tests/TKG/../TKG/output_17512284915634/renaissance-movie-lens_0"; \
[2025-06-29T20:41:32.869Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux_testList_1/aqa-tests/TKG/../TKG/output_17512284915634/renaissance-movie-lens_0"; \
[2025-06-29T20:41:32.869Z] echo ""; echo "TESTING:"; \
[2025-06-29T20:41:32.869Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_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_aarch64_linux_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux_testList_1/aqa-tests/TKG/../TKG/output_17512284915634/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-06-29T20:41:32.869Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux_testList_1/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux_testList_1/aqa-tests/TKG/../TKG/output_17512284915634/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-06-29T20:41:32.869Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-06-29T20:41:32.869Z] echo "Nothing to be done for teardown."; \
[2025-06-29T20:41:32.869Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux_testList_1/aqa-tests/TKG/../TKG/output_17512284915634/TestTargetResult";
[2025-06-29T20:41:32.869Z]
[2025-06-29T20:41:32.869Z] TEST SETUP:
[2025-06-29T20:41:32.869Z] Nothing to be done for setup.
[2025-06-29T20:41:32.869Z]
[2025-06-29T20:41:32.869Z] TESTING:
[2025-06-29T20:41:40.574Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-06-29T20:41:50.127Z] 20:41:48.945 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.
[2025-06-29T20:41:52.077Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-06-29T20:41:52.897Z] Training: 60056, validation: 20285, test: 19854
[2025-06-29T20:41:52.897Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-06-29T20:41:52.897Z] GC before operation: completed in 129.836 ms, heap usage 144.492 MB -> 76.067 MB.
[2025-06-29T20:42:02.502Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-29T20:42:06.649Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-29T20:42:10.829Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-29T20:42:14.947Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-29T20:42:16.821Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-29T20:42:19.315Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-29T20:42:21.976Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-29T20:42:24.467Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-29T20:42:24.468Z] 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.
[2025-06-29T20:42:24.468Z] The best model improves the baseline by 14.52%.
[2025-06-29T20:42:24.850Z] Top recommended movies for user id 72:
[2025-06-29T20:42:24.850Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-29T20:42:24.850Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-29T20:42:24.850Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-29T20:42:24.850Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-29T20:42:24.850Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-29T20:42:24.850Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (31805.993 ms) ======
[2025-06-29T20:42:24.850Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-06-29T20:42:24.850Z] GC before operation: completed in 148.824 ms, heap usage 109.032 MB -> 91.437 MB.
[2025-06-29T20:42:29.023Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-29T20:42:32.263Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-29T20:42:36.403Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-29T20:42:39.665Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-29T20:42:41.517Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-29T20:42:44.043Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-29T20:42:45.956Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-29T20:42:48.498Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-29T20:42:48.498Z] 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.
[2025-06-29T20:42:48.498Z] The best model improves the baseline by 14.52%.
[2025-06-29T20:42:48.498Z] Top recommended movies for user id 72:
[2025-06-29T20:42:48.498Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-29T20:42:48.498Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-29T20:42:48.498Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-29T20:42:48.498Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-29T20:42:48.498Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-29T20:42:48.498Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (23730.228 ms) ======
[2025-06-29T20:42:48.498Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-06-29T20:42:48.881Z] GC before operation: completed in 146.207 ms, heap usage 719.635 MB -> 92.638 MB.
[2025-06-29T20:42:52.221Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-29T20:42:55.521Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-29T20:42:58.829Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-29T20:43:02.079Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-29T20:43:03.927Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-29T20:43:05.777Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-29T20:43:07.629Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-29T20:43:09.506Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-29T20:43:09.876Z] 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.
[2025-06-29T20:43:09.876Z] The best model improves the baseline by 14.52%.
[2025-06-29T20:43:10.248Z] Top recommended movies for user id 72:
[2025-06-29T20:43:10.248Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-29T20:43:10.248Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-29T20:43:10.248Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-29T20:43:10.248Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-29T20:43:10.248Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-29T20:43:10.248Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (21432.796 ms) ======
[2025-06-29T20:43:10.248Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-06-29T20:43:10.248Z] GC before operation: completed in 151.331 ms, heap usage 390.093 MB -> 89.569 MB.
[2025-06-29T20:43:13.470Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-29T20:43:16.775Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-29T20:43:20.012Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-29T20:43:23.268Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-29T20:43:25.125Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-29T20:43:26.996Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-29T20:43:29.535Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-29T20:43:31.419Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-29T20:43:31.419Z] 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.
[2025-06-29T20:43:31.419Z] The best model improves the baseline by 14.52%.
[2025-06-29T20:43:31.788Z] Top recommended movies for user id 72:
[2025-06-29T20:43:31.788Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-29T20:43:31.788Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-29T20:43:31.788Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-29T20:43:31.788Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-29T20:43:31.788Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-29T20:43:31.788Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (21339.837 ms) ======
[2025-06-29T20:43:31.788Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-06-29T20:43:31.789Z] GC before operation: completed in 139.981 ms, heap usage 343.694 MB -> 89.891 MB.
[2025-06-29T20:43:35.090Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-29T20:43:38.384Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-29T20:43:41.807Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-29T20:43:45.057Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-29T20:43:46.898Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-29T20:43:48.737Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-29T20:43:51.348Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-29T20:43:52.680Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-29T20:43:53.056Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-06-29T20:43:53.056Z] The best model improves the baseline by 14.52%.
[2025-06-29T20:43:53.425Z] Top recommended movies for user id 72:
[2025-06-29T20:43:53.425Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-29T20:43:53.425Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-29T20:43:53.425Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-29T20:43:53.425Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-29T20:43:53.425Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-29T20:43:53.425Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (21526.542 ms) ======
[2025-06-29T20:43:53.425Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-06-29T20:43:53.425Z] GC before operation: completed in 148.201 ms, heap usage 392.924 MB -> 89.803 MB.
[2025-06-29T20:43:56.638Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-29T20:43:59.989Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-29T20:44:03.267Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-29T20:44:06.519Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-29T20:44:07.847Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-29T20:44:09.907Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-29T20:44:12.454Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-29T20:44:13.727Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-29T20:44:14.108Z] 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.
[2025-06-29T20:44:14.108Z] The best model improves the baseline by 14.52%.
[2025-06-29T20:44:14.492Z] Top recommended movies for user id 72:
[2025-06-29T20:44:14.492Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-29T20:44:14.492Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-29T20:44:14.492Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-29T20:44:14.492Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-29T20:44:14.492Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-29T20:44:14.492Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (20907.444 ms) ======
[2025-06-29T20:44:14.492Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-06-29T20:44:14.492Z] GC before operation: completed in 146.754 ms, heap usage 123.195 MB -> 92.116 MB.
[2025-06-29T20:44:17.772Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-29T20:44:21.057Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-29T20:44:24.306Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-29T20:44:26.824Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-29T20:44:28.682Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-29T20:44:30.529Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-29T20:44:32.389Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-29T20:44:34.237Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-29T20:44:34.650Z] 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.
[2025-06-29T20:44:34.650Z] The best model improves the baseline by 14.52%.
[2025-06-29T20:44:34.650Z] Top recommended movies for user id 72:
[2025-06-29T20:44:34.650Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-29T20:44:34.650Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-29T20:44:34.650Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-29T20:44:34.650Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-29T20:44:34.650Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-29T20:44:34.650Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (20073.215 ms) ======
[2025-06-29T20:44:34.650Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-06-29T20:44:34.650Z] GC before operation: completed in 141.853 ms, heap usage 667.267 MB -> 93.764 MB.
[2025-06-29T20:44:37.916Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-29T20:44:41.166Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-29T20:44:43.686Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-29T20:44:46.911Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-29T20:44:48.770Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-29T20:44:50.687Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-29T20:44:52.530Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-29T20:44:54.395Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-29T20:44:54.395Z] 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.
[2025-06-29T20:44:54.395Z] The best model improves the baseline by 14.52%.
[2025-06-29T20:44:54.765Z] Top recommended movies for user id 72:
[2025-06-29T20:44:54.765Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-29T20:44:54.765Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-29T20:44:54.765Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-29T20:44:54.765Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-29T20:44:54.765Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-29T20:44:54.765Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (19973.121 ms) ======
[2025-06-29T20:44:54.765Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-06-29T20:44:54.765Z] GC before operation: completed in 141.841 ms, heap usage 152.263 MB -> 92.707 MB.
[2025-06-29T20:44:58.008Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-29T20:45:01.397Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-29T20:45:03.966Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-29T20:45:07.197Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-29T20:45:09.088Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-29T20:45:10.945Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-29T20:45:12.818Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-29T20:45:14.693Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-29T20:45:14.693Z] 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.
[2025-06-29T20:45:15.076Z] The best model improves the baseline by 14.52%.
[2025-06-29T20:45:15.077Z] Top recommended movies for user id 72:
[2025-06-29T20:45:15.077Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-29T20:45:15.077Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-29T20:45:15.077Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-29T20:45:15.077Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-29T20:45:15.077Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-29T20:45:15.077Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (20198.463 ms) ======
[2025-06-29T20:45:15.077Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-06-29T20:45:15.446Z] GC before operation: completed in 138.510 ms, heap usage 276.895 MB -> 90.071 MB.
[2025-06-29T20:45:17.937Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-29T20:45:21.165Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-29T20:45:23.704Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-29T20:45:27.046Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-29T20:45:28.439Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-29T20:45:30.376Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-29T20:45:32.229Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-29T20:45:33.553Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-29T20:45:33.977Z] 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.
[2025-06-29T20:45:33.977Z] The best model improves the baseline by 14.52%.
[2025-06-29T20:45:33.977Z] Top recommended movies for user id 72:
[2025-06-29T20:45:33.977Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-29T20:45:33.977Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-29T20:45:33.977Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-29T20:45:33.977Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-29T20:45:33.977Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-29T20:45:33.977Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (18881.691 ms) ======
[2025-06-29T20:45:33.977Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-06-29T20:45:34.357Z] GC before operation: completed in 138.407 ms, heap usage 434.409 MB -> 90.486 MB.
[2025-06-29T20:45:37.628Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-29T20:45:40.148Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-29T20:45:43.418Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-29T20:45:45.905Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-29T20:45:47.766Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-29T20:45:49.614Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-29T20:45:52.207Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-29T20:45:53.570Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-29T20:45:53.947Z] 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.
[2025-06-29T20:45:53.947Z] The best model improves the baseline by 14.52%.
[2025-06-29T20:45:53.947Z] Top recommended movies for user id 72:
[2025-06-29T20:45:53.947Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-29T20:45:53.947Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-29T20:45:53.947Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-29T20:45:53.947Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-29T20:45:53.947Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-29T20:45:53.947Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (19810.970 ms) ======
[2025-06-29T20:45:53.947Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-06-29T20:45:54.346Z] GC before operation: completed in 141.823 ms, heap usage 227.759 MB -> 89.925 MB.
[2025-06-29T20:45:57.637Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-29T20:46:00.159Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-29T20:46:03.396Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-29T20:46:06.688Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-29T20:46:07.993Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-29T20:46:09.821Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-29T20:46:11.673Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-29T20:46:13.523Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-29T20:46:13.894Z] 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.
[2025-06-29T20:46:13.894Z] The best model improves the baseline by 14.52%.
[2025-06-29T20:46:14.267Z] Top recommended movies for user id 72:
[2025-06-29T20:46:14.267Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-29T20:46:14.267Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-29T20:46:14.267Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-29T20:46:14.267Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-29T20:46:14.267Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-29T20:46:14.267Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (19931.260 ms) ======
[2025-06-29T20:46:14.267Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-06-29T20:46:14.267Z] GC before operation: completed in 143.435 ms, heap usage 543.186 MB -> 93.833 MB.
[2025-06-29T20:46:17.544Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-29T20:46:20.836Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-29T20:46:23.353Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-29T20:46:26.658Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-29T20:46:28.513Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-29T20:46:30.433Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-29T20:46:32.332Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-29T20:46:34.196Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-29T20:46:34.197Z] 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.
[2025-06-29T20:46:34.197Z] The best model improves the baseline by 14.52%.
[2025-06-29T20:46:34.576Z] Top recommended movies for user id 72:
[2025-06-29T20:46:34.576Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-29T20:46:34.576Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-29T20:46:34.576Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-29T20:46:34.576Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-29T20:46:34.576Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-29T20:46:34.576Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (20210.270 ms) ======
[2025-06-29T20:46:34.576Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-06-29T20:46:34.576Z] GC before operation: completed in 137.315 ms, heap usage 188.067 MB -> 90.230 MB.
[2025-06-29T20:46:37.818Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-29T20:46:40.335Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-29T20:46:43.578Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-29T20:46:46.224Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-29T20:46:48.058Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-29T20:46:49.910Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-29T20:46:51.780Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-29T20:46:53.686Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-29T20:46:53.686Z] 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.
[2025-06-29T20:46:53.686Z] The best model improves the baseline by 14.52%.
[2025-06-29T20:46:54.069Z] Top recommended movies for user id 72:
[2025-06-29T20:46:54.069Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-29T20:46:54.069Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-29T20:46:54.069Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-29T20:46:54.069Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-29T20:46:54.069Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-29T20:46:54.069Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (19243.684 ms) ======
[2025-06-29T20:46:54.069Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-06-29T20:46:54.069Z] GC before operation: completed in 145.395 ms, heap usage 233.435 MB -> 90.111 MB.
[2025-06-29T20:46:57.368Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-29T20:46:59.875Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-29T20:47:03.125Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-29T20:47:06.361Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-29T20:47:08.248Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-29T20:47:09.558Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-29T20:47:12.232Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-29T20:47:13.531Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-29T20:47:13.947Z] 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.
[2025-06-29T20:47:13.947Z] The best model improves the baseline by 14.52%.
[2025-06-29T20:47:13.947Z] Top recommended movies for user id 72:
[2025-06-29T20:47:13.947Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-29T20:47:13.947Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-29T20:47:13.947Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-29T20:47:13.947Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-29T20:47:13.947Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-29T20:47:13.947Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (20034.188 ms) ======
[2025-06-29T20:47:13.947Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-06-29T20:47:14.327Z] GC before operation: completed in 139.424 ms, heap usage 290.528 MB -> 90.488 MB.
[2025-06-29T20:47:17.597Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-29T20:47:20.107Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-29T20:47:23.350Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-29T20:47:25.872Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-29T20:47:28.379Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-29T20:47:29.674Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-29T20:47:32.238Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-29T20:47:34.109Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-29T20:47:34.109Z] 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.
[2025-06-29T20:47:34.110Z] The best model improves the baseline by 14.52%.
[2025-06-29T20:47:34.480Z] Top recommended movies for user id 72:
[2025-06-29T20:47:34.480Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-29T20:47:34.480Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-29T20:47:34.480Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-29T20:47:34.480Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-29T20:47:34.480Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-29T20:47:34.480Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (20232.824 ms) ======
[2025-06-29T20:47:34.480Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-06-29T20:47:34.480Z] GC before operation: completed in 135.397 ms, heap usage 130.851 MB -> 90.088 MB.
[2025-06-29T20:47:37.826Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-29T20:47:40.325Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-29T20:47:42.837Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-29T20:47:46.098Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-29T20:47:47.442Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-29T20:47:49.319Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-29T20:47:50.610Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-29T20:47:52.456Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-29T20:47:52.456Z] 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.
[2025-06-29T20:47:52.837Z] The best model improves the baseline by 14.52%.
[2025-06-29T20:47:52.837Z] Top recommended movies for user id 72:
[2025-06-29T20:47:52.837Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-29T20:47:52.837Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-29T20:47:52.837Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-29T20:47:52.837Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-29T20:47:52.837Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-29T20:47:52.837Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (18259.063 ms) ======
[2025-06-29T20:47:52.837Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-06-29T20:47:52.837Z] GC before operation: completed in 152.581 ms, heap usage 713.732 MB -> 94.221 MB.
[2025-06-29T20:47:56.085Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-29T20:47:59.318Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-29T20:48:01.810Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-29T20:48:04.373Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-29T20:48:06.336Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-29T20:48:07.668Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-29T20:48:09.557Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-29T20:48:11.427Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-29T20:48:11.835Z] 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.
[2025-06-29T20:48:11.835Z] The best model improves the baseline by 14.52%.
[2025-06-29T20:48:11.835Z] Top recommended movies for user id 72:
[2025-06-29T20:48:11.835Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-29T20:48:11.835Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-29T20:48:11.835Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-29T20:48:11.835Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-29T20:48:11.835Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-29T20:48:11.835Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (18913.148 ms) ======
[2025-06-29T20:48:11.835Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-06-29T20:48:12.225Z] GC before operation: completed in 134.726 ms, heap usage 333.659 MB -> 90.193 MB.
[2025-06-29T20:48:15.503Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-29T20:48:18.030Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-29T20:48:21.312Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-29T20:48:24.575Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-29T20:48:25.886Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-29T20:48:28.396Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-29T20:48:29.716Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-29T20:48:31.587Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-29T20:48:31.975Z] 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.
[2025-06-29T20:48:32.357Z] The best model improves the baseline by 14.52%.
[2025-06-29T20:48:32.357Z] Top recommended movies for user id 72:
[2025-06-29T20:48:32.357Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-29T20:48:32.357Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-29T20:48:32.357Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-29T20:48:32.357Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-29T20:48:32.357Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-29T20:48:32.357Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (20323.337 ms) ======
[2025-06-29T20:48:32.357Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-06-29T20:48:32.357Z] GC before operation: completed in 140.212 ms, heap usage 308.078 MB -> 90.296 MB.
[2025-06-29T20:48:35.600Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-29T20:48:38.857Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-29T20:48:41.396Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-29T20:48:44.650Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-29T20:48:46.568Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-29T20:48:48.436Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-29T20:48:50.368Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-29T20:48:52.225Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-29T20:48:52.225Z] 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.
[2025-06-29T20:48:52.225Z] The best model improves the baseline by 14.52%.
[2025-06-29T20:48:52.597Z] Top recommended movies for user id 72:
[2025-06-29T20:48:52.597Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-29T20:48:52.597Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-29T20:48:52.597Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-29T20:48:52.597Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-29T20:48:52.597Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-29T20:48:52.597Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (19937.249 ms) ======
[2025-06-29T20:48:53.100Z] -----------------------------------
[2025-06-29T20:48:53.100Z] renaissance-movie-lens_0_PASSED
[2025-06-29T20:48:53.100Z] -----------------------------------
[2025-06-29T20:48:53.100Z]
[2025-06-29T20:48:53.100Z] TEST TEARDOWN:
[2025-06-29T20:48:53.100Z] Nothing to be done for teardown.
[2025-06-29T20:48:53.100Z] renaissance-movie-lens_0 Finish Time: Sun Jun 29 20:48:53 2025 Epoch Time (ms): 1751230133002