renaissance-movie-lens_0
[2025-12-04T10:56:41.109Z] Running test renaissance-movie-lens_0 ...
[2025-12-04T10:56:41.109Z] ===============================================
[2025-12-04T10:56:41.109Z] renaissance-movie-lens_0 Start Time: Thu Dec 4 02:56:38 2025 Epoch Time (ms): 1764845798955
[2025-12-04T10:56:41.109Z] variation: NoOptions
[2025-12-04T10:56:41.109Z] JVM_OPTIONS:
[2025-12-04T10:56:41.109Z] { \
[2025-12-04T10:56:41.109Z] echo ""; echo "TEST SETUP:"; \
[2025-12-04T10:56:41.109Z] echo "Nothing to be done for setup."; \
[2025-12-04T10:56:41.109Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17648435653745/renaissance-movie-lens_0"; \
[2025-12-04T10:56:41.109Z] cd "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17648435653745/renaissance-movie-lens_0"; \
[2025-12-04T10:56:41.109Z] echo ""; echo "TESTING:"; \
[2025-12-04T10:56:41.109Z] "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/jdkbinary/j2sdk-image/Contents/Home/bin/..//bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17648435653745/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-12-04T10:56:41.109Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17648435653745/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-12-04T10:56:41.109Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-12-04T10:56:41.109Z] echo "Nothing to be done for teardown."; \
[2025-12-04T10:56:41.109Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1/aqa-tests/TKG/../TKG/output_17648435653745/TestTargetResult";
[2025-12-04T10:56:41.109Z]
[2025-12-04T10:56:41.109Z] TEST SETUP:
[2025-12-04T10:56:41.109Z] Nothing to be done for setup.
[2025-12-04T10:56:41.109Z]
[2025-12-04T10:56:41.109Z] TESTING:
[2025-12-04T10:56:59.028Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-12-04T10:57:20.432Z] 02:57:16.709 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-12-04T10:57:24.591Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-12-04T10:57:26.627Z] Training: 60056, validation: 20285, test: 19854
[2025-12-04T10:57:26.627Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-12-04T10:57:27.041Z] GC before operation: completed in 435.093 ms, heap usage 335.000 MB -> 74.626 MB.
[2025-12-04T10:58:03.752Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T10:58:19.613Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T10:58:32.383Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T10:58:47.999Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T10:58:51.897Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T10:58:59.717Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T10:59:07.134Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T10:59:13.033Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T10:59:13.498Z] 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.
[2025-12-04T10:59:14.165Z] The best model improves the baseline by 14.52%.
[2025-12-04T10:59:15.070Z] Top recommended movies for user id 72:
[2025-12-04T10:59:15.070Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T10:59:15.070Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T10:59:15.070Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T10:59:15.070Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T10:59:15.070Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T10:59:15.070Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (108127.665 ms) ======
[2025-12-04T10:59:15.070Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-12-04T10:59:15.541Z] GC before operation: completed in 224.416 ms, heap usage 1.084 GB -> 95.453 MB.
[2025-12-04T10:59:30.467Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T10:59:39.032Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T10:59:51.394Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T11:00:02.335Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T11:00:05.470Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T11:00:10.034Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T11:00:16.077Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T11:00:18.820Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T11:00:19.227Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-04T11:00:19.227Z] The best model improves the baseline by 14.52%.
[2025-12-04T11:00:19.227Z] Top recommended movies for user id 72:
[2025-12-04T11:00:19.227Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T11:00:19.227Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T11:00:19.227Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T11:00:19.227Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T11:00:19.227Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T11:00:19.227Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (63939.687 ms) ======
[2025-12-04T11:00:19.227Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-12-04T11:00:19.227Z] GC before operation: completed in 137.412 ms, heap usage 858.526 MB -> 93.005 MB.
[2025-12-04T11:00:27.597Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T11:00:35.839Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T11:00:44.148Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T11:00:51.050Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T11:00:56.900Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T11:01:02.760Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T11:01:07.346Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T11:01:10.826Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T11:01:11.834Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-04T11:01:11.834Z] The best model improves the baseline by 14.52%.
[2025-12-04T11:01:12.219Z] Top recommended movies for user id 72:
[2025-12-04T11:01:12.219Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T11:01:12.219Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T11:01:12.219Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T11:01:12.219Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T11:01:12.219Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T11:01:12.219Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (52676.574 ms) ======
[2025-12-04T11:01:12.219Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-12-04T11:01:12.219Z] GC before operation: completed in 134.126 ms, heap usage 241.689 MB -> 88.170 MB.
[2025-12-04T11:01:21.911Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T11:01:29.994Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T11:01:36.607Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T11:01:44.718Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T11:01:48.124Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T11:01:54.824Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T11:02:02.375Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T11:02:11.253Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T11:02:11.253Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-04T11:02:11.253Z] The best model improves the baseline by 14.52%.
[2025-12-04T11:02:11.803Z] Top recommended movies for user id 72:
[2025-12-04T11:02:11.803Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T11:02:11.803Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T11:02:11.803Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T11:02:11.803Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T11:02:11.803Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T11:02:11.803Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (59751.426 ms) ======
[2025-12-04T11:02:11.803Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-12-04T11:02:12.249Z] GC before operation: completed in 282.527 ms, heap usage 214.804 MB -> 93.086 MB.
[2025-12-04T11:02:24.544Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T11:02:36.280Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T11:02:48.530Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T11:02:56.704Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T11:03:05.423Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T11:03:12.388Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T11:03:19.461Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T11:03:26.746Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T11:03:26.746Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-04T11:03:27.265Z] The best model improves the baseline by 14.52%.
[2025-12-04T11:03:27.683Z] Top recommended movies for user id 72:
[2025-12-04T11:03:27.684Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T11:03:27.684Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T11:03:27.684Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T11:03:27.684Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T11:03:27.684Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T11:03:27.684Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (75402.871 ms) ======
[2025-12-04T11:03:27.684Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-12-04T11:03:27.684Z] GC before operation: completed in 233.326 ms, heap usage 317.993 MB -> 88.541 MB.
[2025-12-04T11:03:45.190Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T11:04:00.301Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T11:04:13.646Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T11:04:26.263Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T11:04:30.879Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T11:04:36.529Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T11:04:41.898Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T11:04:46.331Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T11:04:46.785Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-04T11:04:46.785Z] The best model improves the baseline by 14.52%.
[2025-12-04T11:04:47.249Z] Top recommended movies for user id 72:
[2025-12-04T11:04:47.249Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T11:04:47.249Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T11:04:47.249Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T11:04:47.249Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T11:04:47.249Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T11:04:47.249Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (79269.878 ms) ======
[2025-12-04T11:04:47.249Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-12-04T11:04:48.268Z] GC before operation: completed in 1023.387 ms, heap usage 871.007 MB -> 93.346 MB.
[2025-12-04T11:04:59.959Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T11:05:12.503Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T11:05:22.807Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T11:05:32.653Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T11:05:36.399Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T11:05:42.115Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T11:05:46.540Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T11:05:51.428Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T11:05:51.428Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-04T11:05:51.429Z] The best model improves the baseline by 14.52%.
[2025-12-04T11:05:51.883Z] Top recommended movies for user id 72:
[2025-12-04T11:05:51.883Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T11:05:51.883Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T11:05:51.883Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T11:05:51.883Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T11:05:51.883Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T11:05:51.883Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (63607.561 ms) ======
[2025-12-04T11:05:51.883Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-12-04T11:05:51.883Z] GC before operation: completed in 99.534 ms, heap usage 922.919 MB -> 93.477 MB.
[2025-12-04T11:05:59.959Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T11:06:12.125Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T11:06:24.958Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T11:06:30.671Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T11:06:36.175Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T11:06:38.830Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T11:06:41.558Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T11:06:45.116Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T11:06:45.492Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-04T11:06:45.492Z] The best model improves the baseline by 14.52%.
[2025-12-04T11:06:45.962Z] Top recommended movies for user id 72:
[2025-12-04T11:06:45.962Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T11:06:45.962Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T11:06:45.962Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T11:06:45.962Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T11:06:45.962Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T11:06:45.962Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (54140.451 ms) ======
[2025-12-04T11:06:45.962Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-12-04T11:06:46.901Z] GC before operation: completed in 726.093 ms, heap usage 201.171 MB -> 91.836 MB.
[2025-12-04T11:06:57.079Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T11:07:12.925Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T11:07:27.757Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T11:07:40.397Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T11:07:45.893Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T11:07:52.863Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T11:07:57.766Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T11:08:01.222Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T11:08:01.222Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-04T11:08:01.222Z] The best model improves the baseline by 14.52%.
[2025-12-04T11:08:01.603Z] Top recommended movies for user id 72:
[2025-12-04T11:08:01.603Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T11:08:01.603Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T11:08:01.603Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T11:08:01.603Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T11:08:01.603Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T11:08:01.603Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (74814.368 ms) ======
[2025-12-04T11:08:01.603Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-12-04T11:08:01.603Z] GC before operation: completed in 217.726 ms, heap usage 1.067 GB -> 94.236 MB.
[2025-12-04T11:08:10.131Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T11:08:15.861Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T11:08:22.688Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T11:08:31.201Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T11:08:34.654Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T11:08:41.887Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T11:08:50.484Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T11:08:57.326Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T11:08:57.326Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-04T11:08:57.326Z] The best model improves the baseline by 14.52%.
[2025-12-04T11:08:58.402Z] Top recommended movies for user id 72:
[2025-12-04T11:08:58.402Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T11:08:58.402Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T11:08:58.402Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T11:08:58.402Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T11:08:58.402Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T11:08:58.402Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (56524.774 ms) ======
[2025-12-04T11:08:58.402Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-12-04T11:08:58.402Z] GC before operation: completed in 263.118 ms, heap usage 217.774 MB -> 89.132 MB.
[2025-12-04T11:09:10.847Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T11:09:25.773Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T11:09:38.200Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T11:09:51.161Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T11:09:58.026Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T11:10:03.778Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T11:10:07.728Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T11:10:16.113Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T11:10:16.982Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-04T11:10:16.982Z] The best model improves the baseline by 14.52%.
[2025-12-04T11:10:18.016Z] Top recommended movies for user id 72:
[2025-12-04T11:10:18.016Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T11:10:18.016Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T11:10:18.016Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T11:10:18.016Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T11:10:18.016Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T11:10:18.016Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (78774.418 ms) ======
[2025-12-04T11:10:18.016Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-12-04T11:10:18.016Z] GC before operation: completed in 245.417 ms, heap usage 942.418 MB -> 93.789 MB.
[2025-12-04T11:10:39.265Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T11:10:51.485Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T11:11:03.748Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T11:11:16.514Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T11:11:24.354Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T11:11:32.462Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T11:11:42.310Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T11:11:51.949Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T11:11:51.949Z] 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.
[2025-12-04T11:11:51.949Z] The best model improves the baseline by 14.52%.
[2025-12-04T11:11:53.212Z] Top recommended movies for user id 72:
[2025-12-04T11:11:53.212Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T11:11:53.212Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T11:11:53.212Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T11:11:53.212Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T11:11:53.212Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T11:11:53.212Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (95670.960 ms) ======
[2025-12-04T11:11:53.212Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-12-04T11:11:53.606Z] GC before operation: completed in 308.308 ms, heap usage 220.800 MB -> 89.214 MB.
[2025-12-04T11:12:08.202Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T11:12:23.460Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T11:12:35.678Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T11:12:47.561Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T11:12:55.048Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T11:13:05.545Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T11:13:14.193Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T11:13:19.255Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T11:13:19.691Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-04T11:13:19.691Z] The best model improves the baseline by 14.52%.
[2025-12-04T11:13:20.234Z] Top recommended movies for user id 72:
[2025-12-04T11:13:20.234Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T11:13:20.234Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T11:13:20.234Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T11:13:20.234Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T11:13:20.234Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T11:13:20.234Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (86471.010 ms) ======
[2025-12-04T11:13:20.234Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-12-04T11:13:20.851Z] GC before operation: completed in 739.191 ms, heap usage 1.758 GB -> 95.783 MB.
[2025-12-04T11:13:35.846Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T11:13:46.580Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T11:13:57.054Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T11:14:05.141Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T11:14:09.367Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T11:14:13.863Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T11:14:18.668Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T11:14:25.745Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T11:14:26.239Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-04T11:14:26.239Z] The best model improves the baseline by 14.52%.
[2025-12-04T11:14:26.721Z] Top recommended movies for user id 72:
[2025-12-04T11:14:26.721Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T11:14:26.721Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T11:14:26.721Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T11:14:26.721Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T11:14:26.721Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T11:14:26.721Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (65766.349 ms) ======
[2025-12-04T11:14:26.721Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-12-04T11:14:26.721Z] GC before operation: completed in 202.140 ms, heap usage 771.581 MB -> 93.139 MB.
[2025-12-04T11:14:41.929Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T11:14:56.886Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T11:15:05.496Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T11:15:17.810Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T11:15:25.156Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T11:15:30.964Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T11:15:38.141Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T11:15:46.960Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T11:15:46.960Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-04T11:15:47.352Z] The best model improves the baseline by 14.52%.
[2025-12-04T11:15:47.768Z] Top recommended movies for user id 72:
[2025-12-04T11:15:47.768Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T11:15:47.768Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T11:15:47.768Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T11:15:47.768Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T11:15:47.768Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T11:15:47.768Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (80877.978 ms) ======
[2025-12-04T11:15:47.768Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-12-04T11:15:47.768Z] GC before operation: completed in 202.348 ms, heap usage 1.024 GB -> 94.553 MB.
[2025-12-04T11:16:02.808Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T11:16:20.307Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T11:16:29.277Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T11:16:48.926Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T11:16:51.919Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T11:16:59.390Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T11:17:05.304Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T11:17:11.071Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T11:17:14.169Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-04T11:17:14.169Z] The best model improves the baseline by 14.52%.
[2025-12-04T11:17:14.721Z] Top recommended movies for user id 72:
[2025-12-04T11:17:14.721Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T11:17:14.721Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T11:17:14.721Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T11:17:14.721Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T11:17:14.721Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T11:17:14.721Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (87057.984 ms) ======
[2025-12-04T11:17:14.721Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-12-04T11:17:15.987Z] GC before operation: completed in 602.822 ms, heap usage 508.639 MB -> 93.185 MB.
[2025-12-04T11:17:30.333Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T11:17:45.465Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T11:17:57.930Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T11:18:09.189Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T11:18:17.753Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T11:18:24.788Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T11:18:29.674Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T11:18:36.794Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T11:18:37.404Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-04T11:18:37.404Z] The best model improves the baseline by 14.52%.
[2025-12-04T11:18:38.009Z] Top recommended movies for user id 72:
[2025-12-04T11:18:38.009Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T11:18:38.009Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T11:18:38.009Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T11:18:38.009Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T11:18:38.009Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T11:18:38.009Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (82553.148 ms) ======
[2025-12-04T11:18:38.009Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-12-04T11:18:38.454Z] GC before operation: completed in 421.138 ms, heap usage 1.129 GB -> 96.639 MB.
[2025-12-04T11:18:53.041Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T11:19:05.496Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T11:19:18.067Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T11:19:30.587Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T11:19:37.784Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T11:19:44.848Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T11:19:51.740Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T11:20:00.689Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T11:20:01.184Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-04T11:20:01.184Z] The best model improves the baseline by 14.52%.
[2025-12-04T11:20:02.260Z] Top recommended movies for user id 72:
[2025-12-04T11:20:02.260Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T11:20:02.260Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T11:20:02.260Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T11:20:02.260Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T11:20:02.260Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T11:20:02.260Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (83458.543 ms) ======
[2025-12-04T11:20:02.260Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-12-04T11:20:02.260Z] GC before operation: completed in 262.628 ms, heap usage 210.354 MB -> 89.161 MB.
[2025-12-04T11:20:20.049Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T11:20:28.711Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T11:20:41.001Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T11:20:49.262Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T11:20:55.971Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T11:20:59.621Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T11:21:04.024Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T11:21:09.751Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T11:21:09.751Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-04T11:21:09.751Z] The best model improves the baseline by 14.52%.
[2025-12-04T11:21:10.136Z] Top recommended movies for user id 72:
[2025-12-04T11:21:10.136Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T11:21:10.136Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T11:21:10.136Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T11:21:10.136Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T11:21:10.136Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T11:21:10.136Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (67877.557 ms) ======
[2025-12-04T11:21:10.136Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-12-04T11:21:10.136Z] GC before operation: completed in 226.649 ms, heap usage 110.744 MB -> 95.220 MB.
[2025-12-04T11:21:22.228Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T11:21:28.969Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T11:21:39.142Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T11:21:49.339Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T11:21:54.858Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T11:22:02.273Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T11:22:08.620Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T11:22:17.258Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T11:22:18.683Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-04T11:22:18.683Z] The best model improves the baseline by 14.52%.
[2025-12-04T11:22:19.140Z] Top recommended movies for user id 72:
[2025-12-04T11:22:19.140Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T11:22:19.140Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T11:22:19.140Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T11:22:19.140Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T11:22:19.140Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T11:22:19.140Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (68718.292 ms) ======
[2025-12-04T11:22:23.487Z] -----------------------------------
[2025-12-04T11:22:23.487Z] renaissance-movie-lens_0_PASSED
[2025-12-04T11:22:23.487Z] -----------------------------------
[2025-12-04T11:22:23.487Z]
[2025-12-04T11:22:23.487Z] TEST TEARDOWN:
[2025-12-04T11:22:23.487Z] Nothing to be done for teardown.
[2025-12-04T11:22:23.487Z] renaissance-movie-lens_0 Finish Time: Thu Dec 4 03:22:22 2025 Epoch Time (ms): 1764847342496