renaissance-movie-lens_0
[2026-02-26T17:30:29.450Z] Running test renaissance-movie-lens_0 ...
[2026-02-26T17:30:29.450Z] ===============================================
[2026-02-26T17:30:29.786Z] renaissance-movie-lens_0 Start Time: Thu Feb 26 17:30:29 2026 Epoch Time (ms): 1772127029467
[2026-02-26T17:30:29.786Z] variation: NoOptions
[2026-02-26T17:30:29.786Z] JVM_OPTIONS:
[2026-02-26T17:30:29.786Z] { \
[2026-02-26T17:30:29.786Z] echo ""; echo "TEST SETUP:"; \
[2026-02-26T17:30:29.786Z] echo "Nothing to be done for setup."; \
[2026-02-26T17:30:29.786Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17721240453167/renaissance-movie-lens_0"; \
[2026-02-26T17:30:29.786Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17721240453167/renaissance-movie-lens_0"; \
[2026-02-26T17:30:29.786Z] echo ""; echo "TESTING:"; \
[2026-02-26T17:30:29.786Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17721240453167/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2026-02-26T17:30:29.786Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17721240453167/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2026-02-26T17:30:29.786Z] echo ""; echo "TEST TEARDOWN:"; \
[2026-02-26T17:30:29.786Z] echo "Nothing to be done for teardown."; \
[2026-02-26T17:30:29.786Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17721240453167/TestTargetResult";
[2026-02-26T17:30:29.786Z]
[2026-02-26T17:30:29.786Z] TEST SETUP:
[2026-02-26T17:30:29.786Z] Nothing to be done for setup.
[2026-02-26T17:30:29.786Z]
[2026-02-26T17:30:29.786Z] TESTING:
[2026-02-26T17:30:52.873Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2026-02-26T17:31:26.410Z] 17:31:24.597 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2026-02-26T17:31:35.393Z] Got 100004 ratings from 671 users on 9066 movies.
[2026-02-26T17:31:38.369Z] Training: 60056, validation: 20285, test: 19854
[2026-02-26T17:31:38.369Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2026-02-26T17:31:39.079Z] GC before operation: completed in 653.207 ms, heap usage 529.241 MB -> 76.327 MB.
[2026-02-26T17:32:06.911Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-26T17:32:26.157Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-26T17:32:39.483Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-26T17:32:53.066Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-26T17:33:01.984Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-26T17:33:09.350Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-26T17:33:16.646Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-26T17:33:22.661Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-26T17:33:23.375Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2026-02-26T17:33:23.707Z] The best model improves the baseline by 14.52%.
[2026-02-26T17:33:24.938Z] Top recommended movies for user id 72:
[2026-02-26T17:33:24.938Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-26T17:33:24.938Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-26T17:33:24.938Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-26T17:33:24.938Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-26T17:33:24.938Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-26T17:33:24.938Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (105700.167 ms) ======
[2026-02-26T17:33:24.938Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2026-02-26T17:33:25.678Z] GC before operation: completed in 1049.219 ms, heap usage 278.159 MB -> 90.068 MB.
[2026-02-26T17:33:38.807Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-26T17:33:49.737Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-26T17:34:00.560Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-26T17:34:09.555Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-26T17:34:15.470Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-26T17:34:21.429Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-26T17:34:28.727Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-26T17:34:34.635Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-26T17:34:34.967Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2026-02-26T17:34:34.967Z] The best model improves the baseline by 14.52%.
[2026-02-26T17:34:35.674Z] Top recommended movies for user id 72:
[2026-02-26T17:34:35.674Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-26T17:34:35.674Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-26T17:34:35.674Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-26T17:34:35.674Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-26T17:34:35.674Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-26T17:34:35.674Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (70002.240 ms) ======
[2026-02-26T17:34:35.674Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2026-02-26T17:34:36.874Z] GC before operation: completed in 1013.344 ms, heap usage 844.292 MB -> 93.120 MB.
[2026-02-26T17:34:47.733Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-26T17:34:58.571Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-26T17:35:09.443Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-26T17:35:18.485Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-26T17:35:24.400Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-26T17:35:30.359Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-26T17:35:36.275Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-26T17:35:42.181Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-26T17:35:42.891Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2026-02-26T17:35:43.224Z] The best model improves the baseline by 14.52%.
[2026-02-26T17:35:43.933Z] Top recommended movies for user id 72:
[2026-02-26T17:35:43.933Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-26T17:35:43.933Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-26T17:35:43.933Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-26T17:35:43.933Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-26T17:35:43.933Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-26T17:35:43.933Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (67050.440 ms) ======
[2026-02-26T17:35:43.933Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2026-02-26T17:35:44.661Z] GC before operation: completed in 820.167 ms, heap usage 410.227 MB -> 89.925 MB.
[2026-02-26T17:35:55.555Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-26T17:36:04.587Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-26T17:36:13.535Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-26T17:36:22.445Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-26T17:36:29.739Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-26T17:36:35.729Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-26T17:36:40.532Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-26T17:36:46.525Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-26T17:36:47.687Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2026-02-26T17:36:48.017Z] The best model improves the baseline by 14.52%.
[2026-02-26T17:36:48.741Z] Top recommended movies for user id 72:
[2026-02-26T17:36:48.741Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-26T17:36:48.741Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-26T17:36:48.741Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-26T17:36:48.741Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-26T17:36:48.741Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-26T17:36:48.741Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (63886.247 ms) ======
[2026-02-26T17:36:48.741Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2026-02-26T17:36:49.475Z] GC before operation: completed in 807.426 ms, heap usage 442.753 MB -> 90.149 MB.
[2026-02-26T17:37:00.310Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-26T17:37:09.218Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-26T17:37:20.122Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-26T17:37:29.038Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-26T17:37:35.048Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-26T17:37:41.005Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-26T17:37:46.919Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-26T17:37:52.833Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-26T17:37:53.543Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2026-02-26T17:37:53.872Z] The best model improves the baseline by 14.52%.
[2026-02-26T17:37:54.584Z] Top recommended movies for user id 72:
[2026-02-26T17:37:54.584Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-26T17:37:54.584Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-26T17:37:54.584Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-26T17:37:54.584Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-26T17:37:54.584Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-26T17:37:54.584Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (65073.067 ms) ======
[2026-02-26T17:37:54.584Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2026-02-26T17:37:55.301Z] GC before operation: completed in 838.042 ms, heap usage 370.370 MB -> 90.084 MB.
[2026-02-26T17:38:06.128Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-26T17:38:13.414Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-26T17:38:22.506Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-26T17:38:29.783Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-26T17:38:34.547Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-26T17:38:40.468Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-26T17:38:46.380Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-26T17:38:51.140Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-26T17:38:52.320Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2026-02-26T17:38:52.320Z] The best model improves the baseline by 14.52%.
[2026-02-26T17:38:53.028Z] Top recommended movies for user id 72:
[2026-02-26T17:38:53.028Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-26T17:38:53.028Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-26T17:38:53.028Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-26T17:38:53.028Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-26T17:38:53.028Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-26T17:38:53.028Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (57654.535 ms) ======
[2026-02-26T17:38:53.028Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2026-02-26T17:38:53.764Z] GC before operation: completed in 894.140 ms, heap usage 1.002 GB -> 95.048 MB.
[2026-02-26T17:39:02.655Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-26T17:39:11.700Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-26T17:39:20.596Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-26T17:39:27.901Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-26T17:39:32.713Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-26T17:39:37.475Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-26T17:39:43.394Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-26T17:39:48.170Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-26T17:39:48.981Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2026-02-26T17:39:48.981Z] The best model improves the baseline by 14.52%.
[2026-02-26T17:39:49.702Z] Top recommended movies for user id 72:
[2026-02-26T17:39:49.702Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-26T17:39:49.702Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-26T17:39:49.702Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-26T17:39:49.702Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-26T17:39:49.702Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-26T17:39:49.702Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (55695.978 ms) ======
[2026-02-26T17:39:49.702Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2026-02-26T17:39:50.432Z] GC before operation: completed in 901.284 ms, heap usage 731.223 MB -> 94.054 MB.
[2026-02-26T17:39:59.340Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-26T17:40:08.249Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-26T17:40:17.193Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-26T17:40:26.116Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-26T17:40:30.880Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-26T17:40:35.826Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-26T17:40:40.587Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-26T17:40:45.349Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-26T17:40:46.062Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2026-02-26T17:40:46.062Z] The best model improves the baseline by 14.52%.
[2026-02-26T17:40:46.770Z] Top recommended movies for user id 72:
[2026-02-26T17:40:46.770Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-26T17:40:46.770Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-26T17:40:46.770Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-26T17:40:46.770Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-26T17:40:46.770Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-26T17:40:46.770Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (56378.313 ms) ======
[2026-02-26T17:40:46.770Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2026-02-26T17:40:47.937Z] GC before operation: completed in 872.604 ms, heap usage 651.885 MB -> 94.201 MB.
[2026-02-26T17:40:56.864Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-26T17:41:05.802Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-26T17:41:14.787Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-26T17:41:22.215Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-26T17:41:28.116Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-26T17:41:34.069Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-26T17:41:39.995Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-26T17:41:44.756Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-26T17:41:45.900Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2026-02-26T17:41:46.229Z] The best model improves the baseline by 14.52%.
[2026-02-26T17:41:46.936Z] Top recommended movies for user id 72:
[2026-02-26T17:41:46.936Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-26T17:41:46.936Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-26T17:41:46.936Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-26T17:41:46.936Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-26T17:41:46.936Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-26T17:41:46.936Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (59240.324 ms) ======
[2026-02-26T17:41:46.936Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2026-02-26T17:41:47.664Z] GC before operation: completed in 818.694 ms, heap usage 303.286 MB -> 90.345 MB.
[2026-02-26T17:41:57.345Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-26T17:42:06.410Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-26T17:42:15.346Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-26T17:42:22.633Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-26T17:42:27.391Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-26T17:42:33.348Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-26T17:42:39.256Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-26T17:42:44.017Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-26T17:42:44.730Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2026-02-26T17:42:44.730Z] The best model improves the baseline by 14.52%.
[2026-02-26T17:42:45.445Z] Top recommended movies for user id 72:
[2026-02-26T17:42:45.445Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-26T17:42:45.445Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-26T17:42:45.445Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-26T17:42:45.445Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-26T17:42:45.445Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-26T17:42:45.445Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (57682.825 ms) ======
[2026-02-26T17:42:45.445Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2026-02-26T17:42:46.240Z] GC before operation: completed in 850.441 ms, heap usage 415.770 MB -> 90.610 MB.
[2026-02-26T17:42:55.192Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-26T17:43:04.101Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-26T17:43:13.000Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-26T17:43:23.013Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-26T17:43:25.982Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-26T17:43:33.695Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-26T17:43:37.598Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-26T17:43:43.544Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-26T17:43:43.877Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2026-02-26T17:43:43.877Z] The best model improves the baseline by 14.52%.
[2026-02-26T17:43:44.585Z] Top recommended movies for user id 72:
[2026-02-26T17:43:44.585Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-26T17:43:44.585Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-26T17:43:44.585Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-26T17:43:44.585Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-26T17:43:44.585Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-26T17:43:44.585Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (58379.834 ms) ======
[2026-02-26T17:43:44.585Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2026-02-26T17:43:45.745Z] GC before operation: completed in 898.557 ms, heap usage 902.467 MB -> 94.385 MB.
[2026-02-26T17:43:54.515Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-26T17:44:03.406Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-26T17:44:11.562Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-26T17:44:18.828Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-26T17:44:23.298Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-26T17:44:29.252Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-26T17:44:34.006Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-26T17:44:39.403Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-26T17:44:41.622Z] 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.
[2026-02-26T17:44:41.622Z] The best model improves the baseline by 14.52%.
[2026-02-26T17:44:41.622Z] Top recommended movies for user id 72:
[2026-02-26T17:44:41.622Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-26T17:44:41.622Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-26T17:44:41.622Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-26T17:44:41.622Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-26T17:44:41.622Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-26T17:44:41.622Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (54770.641 ms) ======
[2026-02-26T17:44:41.622Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2026-02-26T17:44:41.622Z] GC before operation: completed in 830.447 ms, heap usage 385.395 MB -> 90.583 MB.
[2026-02-26T17:44:56.965Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-26T17:45:02.542Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-26T17:45:06.541Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-26T17:45:13.814Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-26T17:45:19.743Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-26T17:45:24.538Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-26T17:45:29.371Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-26T17:45:35.385Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-26T17:45:35.385Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2026-02-26T17:45:35.716Z] The best model improves the baseline by 14.52%.
[2026-02-26T17:45:36.424Z] Top recommended movies for user id 72:
[2026-02-26T17:45:36.424Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-26T17:45:36.424Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-26T17:45:36.424Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-26T17:45:36.424Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-26T17:45:36.424Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-26T17:45:36.424Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (55168.527 ms) ======
[2026-02-26T17:45:36.424Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2026-02-26T17:45:37.173Z] GC before operation: completed in 888.797 ms, heap usage 1018.778 MB -> 95.508 MB.
[2026-02-26T17:45:46.076Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-26T17:45:54.980Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-26T17:46:03.902Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-26T17:46:11.311Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-26T17:46:16.162Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-26T17:46:20.967Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-26T17:46:25.725Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-26T17:46:30.481Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-26T17:46:31.633Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2026-02-26T17:46:31.633Z] The best model improves the baseline by 14.52%.
[2026-02-26T17:46:32.346Z] Top recommended movies for user id 72:
[2026-02-26T17:46:32.346Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-26T17:46:32.346Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-26T17:46:32.346Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-26T17:46:32.346Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-26T17:46:32.346Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-26T17:46:32.346Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (55136.306 ms) ======
[2026-02-26T17:46:32.346Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2026-02-26T17:46:33.495Z] GC before operation: completed in 882.315 ms, heap usage 257.733 MB -> 90.301 MB.
[2026-02-26T17:46:42.527Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-26T17:46:49.807Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-26T17:46:58.777Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-26T17:47:06.093Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-26T17:47:10.957Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-26T17:47:14.810Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-26T17:47:20.729Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-26T17:47:25.489Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-26T17:47:25.820Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2026-02-26T17:47:25.820Z] The best model improves the baseline by 14.52%.
[2026-02-26T17:47:26.529Z] Top recommended movies for user id 72:
[2026-02-26T17:47:26.529Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-26T17:47:26.529Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-26T17:47:26.529Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-26T17:47:26.529Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-26T17:47:26.529Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-26T17:47:26.529Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (53249.854 ms) ======
[2026-02-26T17:47:26.529Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2026-02-26T17:47:27.259Z] GC before operation: completed in 834.405 ms, heap usage 182.700 MB -> 90.510 MB.
[2026-02-26T17:47:36.169Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-26T17:47:43.589Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-26T17:47:52.529Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-26T17:47:59.827Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-26T17:48:04.827Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-26T17:48:09.595Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-26T17:48:15.516Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-26T17:48:20.283Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-26T17:48:21.000Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2026-02-26T17:48:21.000Z] The best model improves the baseline by 14.52%.
[2026-02-26T17:48:21.723Z] Top recommended movies for user id 72:
[2026-02-26T17:48:21.723Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-26T17:48:21.723Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-26T17:48:21.723Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-26T17:48:21.723Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-26T17:48:21.723Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-26T17:48:21.723Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (54516.463 ms) ======
[2026-02-26T17:48:21.723Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2026-02-26T17:48:22.872Z] GC before operation: completed in 845.336 ms, heap usage 383.810 MB -> 90.623 MB.
[2026-02-26T17:48:31.778Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-26T17:48:40.698Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-26T17:48:49.608Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-26T17:48:57.039Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-26T17:49:02.997Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-26T17:49:08.932Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-26T17:49:13.700Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-26T17:49:19.615Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-26T17:49:19.947Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2026-02-26T17:49:19.947Z] The best model improves the baseline by 14.52%.
[2026-02-26T17:49:20.677Z] Top recommended movies for user id 72:
[2026-02-26T17:49:20.677Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-26T17:49:20.677Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-26T17:49:20.677Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-26T17:49:20.677Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-26T17:49:20.677Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-26T17:49:20.677Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (57824.081 ms) ======
[2026-02-26T17:49:20.677Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2026-02-26T17:49:21.340Z] GC before operation: completed in 838.140 ms, heap usage 379.571 MB -> 90.726 MB.
[2026-02-26T17:49:30.352Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-26T17:49:39.268Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-26T17:49:48.176Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-26T17:49:57.092Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-26T17:50:01.855Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-26T17:50:07.777Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-26T17:50:12.708Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-26T17:50:18.629Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-26T17:50:18.959Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2026-02-26T17:50:18.959Z] The best model improves the baseline by 14.52%.
[2026-02-26T17:50:19.671Z] Top recommended movies for user id 72:
[2026-02-26T17:50:19.671Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-26T17:50:19.671Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-26T17:50:19.671Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-26T17:50:19.671Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-26T17:50:19.671Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-26T17:50:19.671Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (58238.579 ms) ======
[2026-02-26T17:50:19.671Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2026-02-26T17:50:20.394Z] GC before operation: completed in 841.106 ms, heap usage 406.948 MB -> 90.483 MB.
[2026-02-26T17:50:29.310Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-26T17:50:38.217Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-26T17:50:47.125Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-26T17:50:54.511Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-26T17:50:59.298Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-26T17:51:04.065Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-26T17:51:08.833Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-26T17:51:14.753Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-26T17:51:15.087Z] 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.
[2026-02-26T17:51:15.087Z] The best model improves the baseline by 14.52%.
[2026-02-26T17:51:16.253Z] Top recommended movies for user id 72:
[2026-02-26T17:51:16.253Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-26T17:51:16.253Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-26T17:51:16.253Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-26T17:51:16.253Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-26T17:51:16.253Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-26T17:51:16.253Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (55520.437 ms) ======
[2026-02-26T17:51:16.253Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2026-02-26T17:51:16.980Z] GC before operation: completed in 823.219 ms, heap usage 306.435 MB -> 90.591 MB.
[2026-02-26T17:51:26.019Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-26T17:51:34.923Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-26T17:51:43.836Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-26T17:51:51.119Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-26T17:51:57.043Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-26T17:52:01.828Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-26T17:52:07.831Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-26T17:52:12.616Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-26T17:52:12.948Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2026-02-26T17:52:12.948Z] The best model improves the baseline by 14.52%.
[2026-02-26T17:52:13.663Z] Top recommended movies for user id 72:
[2026-02-26T17:52:13.663Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-26T17:52:13.663Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-26T17:52:13.663Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-26T17:52:13.663Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-26T17:52:13.663Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-26T17:52:13.663Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (56844.717 ms) ======
[2026-02-26T17:52:17.451Z] -----------------------------------
[2026-02-26T17:52:17.451Z] renaissance-movie-lens_0_PASSED
[2026-02-26T17:52:17.451Z] -----------------------------------
[2026-02-26T17:52:17.451Z]
[2026-02-26T17:52:17.451Z] TEST TEARDOWN:
[2026-02-26T17:52:17.451Z] Nothing to be done for teardown.
[2026-02-26T17:52:17.451Z] renaissance-movie-lens_0 Finish Time: Thu Feb 26 17:52:16 2026 Epoch Time (ms): 1772128336676