renaissance-movie-lens_0
[2025-05-08T10:27:34.961Z] Running test renaissance-movie-lens_0 ...
[2025-05-08T10:27:34.961Z] ===============================================
[2025-05-08T10:27:34.961Z] renaissance-movie-lens_0 Start Time: Thu May 8 10:27:33 2025 Epoch Time (ms): 1746700053347
[2025-05-08T10:27:34.961Z] variation: NoOptions
[2025-05-08T10:27:34.961Z] JVM_OPTIONS:
[2025-05-08T10:27:34.961Z] { \
[2025-05-08T10:27:34.961Z] echo ""; echo "TEST SETUP:"; \
[2025-05-08T10:27:34.961Z] echo "Nothing to be done for setup."; \
[2025-05-08T10:27:34.961Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17466919033356/renaissance-movie-lens_0"; \
[2025-05-08T10:27:34.961Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17466919033356/renaissance-movie-lens_0"; \
[2025-05-08T10:27:34.961Z] echo ""; echo "TESTING:"; \
[2025-05-08T10:27:34.961Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17466919033356/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-05-08T10:27:34.961Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17466919033356/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-05-08T10:27:34.961Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-05-08T10:27:34.961Z] echo "Nothing to be done for teardown."; \
[2025-05-08T10:27:34.961Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17466919033356/TestTargetResult";
[2025-05-08T10:27:34.961Z]
[2025-05-08T10:27:34.961Z] TEST SETUP:
[2025-05-08T10:27:34.961Z] Nothing to be done for setup.
[2025-05-08T10:27:34.961Z]
[2025-05-08T10:27:34.961Z] TESTING:
[2025-05-08T10:28:00.973Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-05-08T10:28:42.749Z] 10:28:42.029 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.
[2025-05-08T10:28:56.854Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-05-08T10:28:58.512Z] Training: 60056, validation: 20285, test: 19854
[2025-05-08T10:28:58.512Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-05-08T10:28:59.316Z] GC before operation: completed in 922.987 ms, heap usage 423.611 MB -> 75.667 MB.
[2025-05-08T10:29:46.674Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T10:30:12.827Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T10:30:34.993Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T10:30:54.122Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T10:31:08.005Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T10:31:18.297Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T10:31:30.298Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T10:31:40.234Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T10:31:41.020Z] 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.
[2025-05-08T10:31:41.020Z] The best model improves the baseline by 14.52%.
[2025-05-08T10:31:42.740Z] Top recommended movies for user id 72:
[2025-05-08T10:31:42.740Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T10:31:42.740Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T10:31:42.740Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T10:31:42.740Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T10:31:42.740Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T10:31:42.740Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (163228.007 ms) ======
[2025-05-08T10:31:42.740Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-05-08T10:31:43.536Z] GC before operation: completed in 842.793 ms, heap usage 132.013 MB -> 95.121 MB.
[2025-05-08T10:32:02.752Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T10:32:16.727Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T10:32:33.316Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T10:32:49.753Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T10:32:58.106Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T10:33:06.439Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T10:33:16.362Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T10:33:23.300Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T10:33:24.890Z] 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.
[2025-05-08T10:33:25.666Z] The best model improves the baseline by 14.52%.
[2025-05-08T10:33:26.439Z] Top recommended movies for user id 72:
[2025-05-08T10:33:26.439Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T10:33:26.439Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T10:33:26.439Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T10:33:26.439Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T10:33:26.439Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T10:33:26.439Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (102762.712 ms) ======
[2025-05-08T10:33:26.439Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-05-08T10:33:27.221Z] GC before operation: completed in 707.554 ms, heap usage 255.502 MB -> 90.149 MB.
[2025-05-08T10:33:43.468Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T10:33:57.334Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T10:34:13.634Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T10:34:27.453Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T10:34:35.931Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T10:34:43.263Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T10:34:53.323Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T10:35:01.701Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T10:35:03.323Z] 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.
[2025-05-08T10:35:03.323Z] The best model improves the baseline by 14.52%.
[2025-05-08T10:35:04.116Z] Top recommended movies for user id 72:
[2025-05-08T10:35:04.116Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T10:35:04.116Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T10:35:04.116Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T10:35:04.116Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T10:35:04.116Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T10:35:04.116Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (97127.867 ms) ======
[2025-05-08T10:35:04.116Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-05-08T10:35:04.892Z] GC before operation: completed in 717.014 ms, heap usage 358.771 MB -> 89.175 MB.
[2025-05-08T10:35:21.323Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T10:35:35.148Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T10:35:49.097Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T10:36:02.973Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T10:36:11.301Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T10:36:21.285Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T10:36:31.261Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T10:36:39.839Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T10:36:40.683Z] 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.
[2025-05-08T10:36:40.683Z] The best model improves the baseline by 14.52%.
[2025-05-08T10:36:41.503Z] Top recommended movies for user id 72:
[2025-05-08T10:36:41.503Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T10:36:41.503Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T10:36:41.503Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T10:36:41.503Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T10:36:41.503Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T10:36:41.504Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (96910.855 ms) ======
[2025-05-08T10:36:41.504Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-05-08T10:36:42.291Z] GC before operation: completed in 627.335 ms, heap usage 239.530 MB -> 89.249 MB.
[2025-05-08T10:36:56.905Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T10:37:10.792Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T10:37:24.787Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T10:37:38.900Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T10:37:47.323Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T10:37:55.739Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T10:38:04.457Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T10:38:14.500Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T10:38:14.500Z] 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.
[2025-05-08T10:38:15.291Z] The best model improves the baseline by 14.52%.
[2025-05-08T10:38:16.096Z] Top recommended movies for user id 72:
[2025-05-08T10:38:16.096Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T10:38:16.096Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T10:38:16.096Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T10:38:16.096Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T10:38:16.096Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T10:38:16.096Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (93493.119 ms) ======
[2025-05-08T10:38:16.096Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-05-08T10:38:16.883Z] GC before operation: completed in 557.413 ms, heap usage 199.164 MB -> 89.196 MB.
[2025-05-08T10:38:30.882Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T10:38:44.886Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T10:38:58.774Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T10:39:13.265Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T10:39:21.631Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T10:39:28.617Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T10:39:38.556Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T10:39:45.457Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T10:39:47.061Z] 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.
[2025-05-08T10:39:47.061Z] The best model improves the baseline by 14.52%.
[2025-05-08T10:39:47.848Z] Top recommended movies for user id 72:
[2025-05-08T10:39:47.848Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T10:39:47.848Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T10:39:47.848Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T10:39:47.848Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T10:39:47.848Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T10:39:47.848Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (91225.529 ms) ======
[2025-05-08T10:39:47.848Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-05-08T10:39:48.633Z] GC before operation: completed in 673.777 ms, heap usage 762.864 MB -> 93.576 MB.
[2025-05-08T10:40:02.636Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T10:40:19.035Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T10:40:33.151Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T10:40:44.974Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T10:40:53.382Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T10:41:00.422Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T10:41:07.441Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T10:41:15.136Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T10:41:15.955Z] 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.
[2025-05-08T10:41:15.955Z] The best model improves the baseline by 14.52%.
[2025-05-08T10:41:17.609Z] Top recommended movies for user id 72:
[2025-05-08T10:41:17.609Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T10:41:17.609Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T10:41:17.609Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T10:41:17.609Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T10:41:17.609Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T10:41:17.609Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (88736.803 ms) ======
[2025-05-08T10:41:17.609Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-05-08T10:41:17.609Z] GC before operation: completed in 688.538 ms, heap usage 171.507 MB -> 89.475 MB.
[2025-05-08T10:41:34.013Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T10:41:45.898Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T10:41:59.908Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T10:42:13.935Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T10:42:21.248Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T10:42:28.354Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T10:42:35.586Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T10:42:42.753Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T10:42:43.556Z] 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.
[2025-05-08T10:42:43.556Z] The best model improves the baseline by 14.52%.
[2025-05-08T10:42:44.369Z] Top recommended movies for user id 72:
[2025-05-08T10:42:44.369Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T10:42:44.369Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T10:42:44.369Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T10:42:44.369Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T10:42:44.369Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T10:42:44.369Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (86622.738 ms) ======
[2025-05-08T10:42:44.369Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-05-08T10:42:45.194Z] GC before operation: completed in 451.947 ms, heap usage 606.481 MB -> 93.471 MB.
[2025-05-08T10:42:57.092Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T10:43:10.067Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T10:43:22.527Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T10:43:34.658Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T10:43:41.720Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T10:43:47.577Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T10:43:54.669Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T10:44:01.748Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T10:44:03.382Z] 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.
[2025-05-08T10:44:03.382Z] The best model improves the baseline by 14.52%.
[2025-05-08T10:44:04.182Z] Top recommended movies for user id 72:
[2025-05-08T10:44:04.182Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T10:44:04.182Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T10:44:04.182Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T10:44:04.182Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T10:44:04.182Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T10:44:04.182Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (78898.816 ms) ======
[2025-05-08T10:44:04.182Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-05-08T10:44:04.182Z] GC before operation: completed in 630.439 ms, heap usage 134.394 MB -> 92.848 MB.
[2025-05-08T10:44:20.532Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T10:44:34.843Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T10:44:51.872Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T10:45:06.623Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T10:45:13.659Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T10:45:20.659Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T10:45:30.683Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T10:45:38.004Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T10:45:39.622Z] 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.
[2025-05-08T10:45:39.622Z] The best model improves the baseline by 14.52%.
[2025-05-08T10:45:41.272Z] Top recommended movies for user id 72:
[2025-05-08T10:45:41.272Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T10:45:41.272Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T10:45:41.272Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T10:45:41.272Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T10:45:41.272Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T10:45:41.272Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (96484.842 ms) ======
[2025-05-08T10:45:41.272Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-05-08T10:45:41.272Z] GC before operation: completed in 567.910 ms, heap usage 377.847 MB -> 92.310 MB.
[2025-05-08T10:46:00.533Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T10:46:14.657Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T10:46:31.208Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T10:46:43.825Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T10:47:25.361Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T10:47:25.361Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T10:47:25.361Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T10:47:25.361Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T10:47:25.361Z] 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.
[2025-05-08T10:47:25.361Z] The best model improves the baseline by 14.52%.
[2025-05-08T10:47:25.361Z] Top recommended movies for user id 72:
[2025-05-08T10:47:25.361Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T10:47:25.361Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T10:47:25.361Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T10:47:25.361Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T10:47:25.361Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T10:47:25.361Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (98592.820 ms) ======
[2025-05-08T10:47:25.361Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-05-08T10:47:25.361Z] GC before operation: completed in 667.389 ms, heap usage 210.695 MB -> 93.121 MB.
[2025-05-08T10:47:40.614Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T10:47:52.050Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T10:48:02.476Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T10:48:13.709Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T10:48:22.302Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T10:48:29.442Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T10:48:37.979Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T10:48:45.581Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T10:48:47.272Z] 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.
[2025-05-08T10:48:47.272Z] The best model improves the baseline by 14.52%.
[2025-05-08T10:48:48.123Z] Top recommended movies for user id 72:
[2025-05-08T10:48:48.123Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T10:48:48.123Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T10:48:48.123Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T10:48:48.123Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T10:48:48.123Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T10:48:48.123Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (87568.842 ms) ======
[2025-05-08T10:48:48.123Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-05-08T10:48:48.923Z] GC before operation: completed in 691.964 ms, heap usage 374.572 MB -> 91.649 MB.
[2025-05-08T10:49:05.526Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T10:49:19.609Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T10:49:33.724Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T10:49:45.657Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T10:49:54.207Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T10:50:01.774Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T10:50:10.233Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T10:50:18.690Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T10:50:19.483Z] 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.
[2025-05-08T10:50:19.483Z] The best model improves the baseline by 14.52%.
[2025-05-08T10:50:20.271Z] Top recommended movies for user id 72:
[2025-05-08T10:50:20.271Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T10:50:20.271Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T10:50:20.271Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T10:50:20.271Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T10:50:20.271Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T10:50:20.271Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (91465.794 ms) ======
[2025-05-08T10:50:20.271Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-05-08T10:50:21.084Z] GC before operation: completed in 641.597 ms, heap usage 515.133 MB -> 92.174 MB.
[2025-05-08T10:50:35.241Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T10:50:47.219Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T10:50:59.183Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T10:51:09.901Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T10:51:17.012Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T10:51:24.132Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T10:51:32.788Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T10:51:39.906Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T10:51:40.701Z] 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.
[2025-05-08T10:51:40.701Z] The best model improves the baseline by 14.52%.
[2025-05-08T10:51:41.518Z] Top recommended movies for user id 72:
[2025-05-08T10:51:41.518Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T10:51:41.518Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T10:51:41.518Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T10:51:41.518Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T10:51:41.518Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T10:51:41.518Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (80381.176 ms) ======
[2025-05-08T10:51:41.518Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-05-08T10:51:42.326Z] GC before operation: completed in 608.429 ms, heap usage 478.807 MB -> 94.437 MB.
[2025-05-08T10:51:54.281Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T10:52:06.660Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T10:52:20.587Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T10:52:32.556Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T10:52:38.376Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T10:52:45.348Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T10:52:53.800Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T10:53:00.863Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T10:53:03.087Z] 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.
[2025-05-08T10:53:03.087Z] The best model improves the baseline by 14.52%.
[2025-05-08T10:53:03.891Z] Top recommended movies for user id 72:
[2025-05-08T10:53:03.891Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T10:53:03.891Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T10:53:03.891Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T10:53:03.891Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T10:53:03.891Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T10:53:03.891Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (81424.744 ms) ======
[2025-05-08T10:53:03.891Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-05-08T10:53:04.695Z] GC before operation: completed in 779.614 ms, heap usage 271.012 MB -> 90.471 MB.
[2025-05-08T10:53:18.668Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T10:53:28.751Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T10:53:42.726Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T10:53:52.751Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T10:53:59.707Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T10:54:07.267Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T10:54:14.301Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T10:54:21.346Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T10:54:22.139Z] 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.
[2025-05-08T10:54:22.932Z] The best model improves the baseline by 14.52%.
[2025-05-08T10:54:22.932Z] Top recommended movies for user id 72:
[2025-05-08T10:54:22.932Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T10:54:22.932Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T10:54:22.932Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T10:54:22.932Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T10:54:22.932Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T10:54:22.932Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (78962.435 ms) ======
[2025-05-08T10:54:22.932Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-05-08T10:54:23.718Z] GC before operation: completed in 731.685 ms, heap usage 389.802 MB -> 90.311 MB.
[2025-05-08T10:54:37.695Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T10:54:49.645Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T10:55:01.663Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T10:55:13.482Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T10:55:20.804Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T10:55:27.750Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T10:55:33.407Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T10:55:40.333Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T10:55:41.109Z] 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.
[2025-05-08T10:55:41.109Z] The best model improves the baseline by 14.52%.
[2025-05-08T10:55:41.109Z] Top recommended movies for user id 72:
[2025-05-08T10:55:41.109Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T10:55:41.109Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T10:55:41.109Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T10:55:41.109Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T10:55:41.109Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T10:55:41.109Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (77359.877 ms) ======
[2025-05-08T10:55:41.109Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-05-08T10:55:41.898Z] GC before operation: completed in 697.325 ms, heap usage 616.874 MB -> 90.367 MB.
[2025-05-08T10:55:55.850Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T10:56:07.827Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T10:56:21.883Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T10:56:31.993Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T10:56:38.989Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T10:56:44.709Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T10:56:50.758Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T10:56:56.604Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T10:56:57.404Z] 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.
[2025-05-08T10:56:57.404Z] The best model improves the baseline by 14.52%.
[2025-05-08T10:56:58.203Z] Top recommended movies for user id 72:
[2025-05-08T10:56:58.203Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T10:56:58.203Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T10:56:58.203Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T10:56:58.203Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T10:56:58.203Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T10:56:58.203Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (76297.804 ms) ======
[2025-05-08T10:56:58.203Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-05-08T10:56:59.011Z] GC before operation: completed in 509.994 ms, heap usage 276.905 MB -> 88.810 MB.
[2025-05-08T10:57:10.983Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T10:57:21.031Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T10:57:31.110Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T10:57:40.217Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T10:57:45.968Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T10:57:51.744Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T10:57:57.489Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T10:58:04.472Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T10:58:06.089Z] 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.
[2025-05-08T10:58:06.089Z] The best model improves the baseline by 14.52%.
[2025-05-08T10:58:06.089Z] Top recommended movies for user id 72:
[2025-05-08T10:58:06.089Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T10:58:06.089Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T10:58:06.089Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T10:58:06.089Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T10:58:06.089Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T10:58:06.089Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (67454.884 ms) ======
[2025-05-08T10:58:06.089Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-05-08T10:58:06.911Z] GC before operation: completed in 562.762 ms, heap usage 247.737 MB -> 89.399 MB.
[2025-05-08T10:58:18.921Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T10:58:29.069Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T10:58:41.105Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T10:59:07.548Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T10:59:07.548Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T10:59:07.548Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T10:59:12.984Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T10:59:20.178Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T10:59:20.978Z] 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.
[2025-05-08T10:59:20.978Z] The best model improves the baseline by 14.52%.
[2025-05-08T10:59:21.781Z] Top recommended movies for user id 72:
[2025-05-08T10:59:21.781Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T10:59:21.781Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T10:59:21.781Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T10:59:21.781Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T10:59:21.781Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T10:59:21.781Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (74627.477 ms) ======
[2025-05-08T10:59:23.453Z] -----------------------------------
[2025-05-08T10:59:23.453Z] renaissance-movie-lens_0_PASSED
[2025-05-08T10:59:23.453Z] -----------------------------------
[2025-05-08T10:59:23.453Z]
[2025-05-08T10:59:23.453Z] TEST TEARDOWN:
[2025-05-08T10:59:23.453Z] Nothing to be done for teardown.
[2025-05-08T10:59:23.453Z] renaissance-movie-lens_0 Finish Time: Thu May 8 10:59:23 2025 Epoch Time (ms): 1746701963311