renaissance-movie-lens_0
[2026-02-11T23:26:58.898Z] Running test renaissance-movie-lens_0 ...
[2026-02-11T23:26:58.898Z] ===============================================
[2026-02-11T23:26:58.898Z] renaissance-movie-lens_0 Start Time: Wed Feb 11 18:26:58 2026 Epoch Time (ms): 1770852418357
[2026-02-11T23:26:58.898Z] variation: NoOptions
[2026-02-11T23:26:58.898Z] JVM_OPTIONS:
[2026-02-11T23:26:58.898Z] { \
[2026-02-11T23:26:58.898Z] echo ""; echo "TEST SETUP:"; \
[2026-02-11T23:26:58.898Z] echo "Nothing to be done for setup."; \
[2026-02-11T23:26:58.898Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17708518614257/renaissance-movie-lens_0"; \
[2026-02-11T23:26:58.898Z] cd "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17708518614257/renaissance-movie-lens_0"; \
[2026-02-11T23:26:58.898Z] echo ""; echo "TESTING:"; \
[2026-02-11T23:26:58.898Z] "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/jdkbinary/j2sdk-image/Contents/Home/bin/..//bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17708518614257/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2026-02-11T23:26:58.898Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17708518614257/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2026-02-11T23:26:58.898Z] echo ""; echo "TEST TEARDOWN:"; \
[2026-02-11T23:26:58.898Z] echo "Nothing to be done for teardown."; \
[2026-02-11T23:26:58.898Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17708518614257/TestTargetResult";
[2026-02-11T23:26:58.898Z]
[2026-02-11T23:26:58.898Z] TEST SETUP:
[2026-02-11T23:26:58.898Z] Nothing to be done for setup.
[2026-02-11T23:26:58.898Z]
[2026-02-11T23:26:58.898Z] TESTING:
[2026-02-11T23:27:03.910Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2026-02-11T23:27:07.992Z] 18:27:07.808 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.
[2026-02-11T23:27:09.232Z] Got 100004 ratings from 671 users on 9066 movies.
[2026-02-11T23:27:09.607Z] Training: 60056, validation: 20285, test: 19854
[2026-02-11T23:27:09.607Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2026-02-11T23:27:09.607Z] GC before operation: completed in 81.480 ms, heap usage 209.167 MB -> 75.874 MB.
[2026-02-11T23:27:13.680Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-11T23:27:16.142Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-11T23:27:18.585Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-11T23:27:21.000Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-11T23:27:21.770Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-11T23:27:23.590Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-11T23:27:25.448Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-11T23:27:26.726Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-11T23:27:26.726Z] 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.
[2026-02-11T23:27:26.726Z] The best model improves the baseline by 14.52%.
[2026-02-11T23:27:27.098Z] Top recommended movies for user id 72:
[2026-02-11T23:27:27.098Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-11T23:27:27.098Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-11T23:27:27.098Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-11T23:27:27.098Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-11T23:27:27.098Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-11T23:27:27.098Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (17542.525 ms) ======
[2026-02-11T23:27:27.098Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2026-02-11T23:27:27.098Z] GC before operation: completed in 140.563 ms, heap usage 208.769 MB -> 86.549 MB.
[2026-02-11T23:27:29.513Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-11T23:27:32.705Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-11T23:27:35.158Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-11T23:27:37.571Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-11T23:27:38.350Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-11T23:27:40.137Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-11T23:27:41.374Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-11T23:27:42.646Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-11T23:27:42.646Z] 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.
[2026-02-11T23:27:43.044Z] The best model improves the baseline by 14.52%.
[2026-02-11T23:27:43.045Z] Top recommended movies for user id 72:
[2026-02-11T23:27:43.045Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-11T23:27:43.045Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-11T23:27:43.045Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-11T23:27:43.045Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-11T23:27:43.045Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-11T23:27:43.045Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (15782.221 ms) ======
[2026-02-11T23:27:43.045Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2026-02-11T23:27:43.045Z] GC before operation: completed in 103.987 ms, heap usage 94.900 MB -> 88.770 MB.
[2026-02-11T23:27:45.500Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-11T23:27:47.916Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-11T23:27:50.355Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-11T23:27:52.796Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-11T23:27:54.076Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-11T23:27:55.977Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-11T23:27:57.311Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-11T23:27:58.553Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-11T23:27:58.929Z] 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.
[2026-02-11T23:27:58.929Z] The best model improves the baseline by 14.52%.
[2026-02-11T23:27:59.305Z] Top recommended movies for user id 72:
[2026-02-11T23:27:59.305Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-11T23:27:59.305Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-11T23:27:59.305Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-11T23:27:59.305Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-11T23:27:59.305Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-11T23:27:59.305Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16000.777 ms) ======
[2026-02-11T23:27:59.305Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2026-02-11T23:27:59.305Z] GC before operation: completed in 79.993 ms, heap usage 261.197 MB -> 89.524 MB.
[2026-02-11T23:28:01.789Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-11T23:28:03.638Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-11T23:28:06.151Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-11T23:28:08.546Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-11T23:28:09.813Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-11T23:28:11.052Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-11T23:28:12.334Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-11T23:28:14.180Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-11T23:28:14.181Z] 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.
[2026-02-11T23:28:14.181Z] The best model improves the baseline by 14.52%.
[2026-02-11T23:28:14.557Z] Top recommended movies for user id 72:
[2026-02-11T23:28:14.557Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-11T23:28:14.557Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-11T23:28:14.557Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-11T23:28:14.557Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-11T23:28:14.557Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-11T23:28:14.557Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (15186.139 ms) ======
[2026-02-11T23:28:14.557Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2026-02-11T23:28:14.557Z] GC before operation: completed in 88.168 ms, heap usage 123.088 MB -> 89.599 MB.
[2026-02-11T23:28:16.998Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-11T23:28:19.441Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-11T23:28:21.264Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-11T23:28:23.704Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-11T23:28:25.518Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-11T23:28:27.306Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-11T23:28:28.541Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-11T23:28:29.817Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-11T23:28:30.195Z] 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.
[2026-02-11T23:28:30.195Z] The best model improves the baseline by 14.52%.
[2026-02-11T23:28:30.195Z] Top recommended movies for user id 72:
[2026-02-11T23:28:30.195Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-11T23:28:30.195Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-11T23:28:30.195Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-11T23:28:30.195Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-11T23:28:30.195Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-11T23:28:30.195Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15700.141 ms) ======
[2026-02-11T23:28:30.195Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2026-02-11T23:28:30.195Z] GC before operation: completed in 115.845 ms, heap usage 466.217 MB -> 90.036 MB.
[2026-02-11T23:28:32.617Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-11T23:28:35.033Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-11T23:28:36.819Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-11T23:28:38.663Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-11T23:28:39.912Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-11T23:28:41.140Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-11T23:28:42.376Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-11T23:28:43.623Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-11T23:28:44.021Z] 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.
[2026-02-11T23:28:44.021Z] The best model improves the baseline by 14.52%.
[2026-02-11T23:28:44.021Z] Top recommended movies for user id 72:
[2026-02-11T23:28:44.021Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-11T23:28:44.021Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-11T23:28:44.021Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-11T23:28:44.021Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-11T23:28:44.021Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-11T23:28:44.021Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (13814.547 ms) ======
[2026-02-11T23:28:44.021Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2026-02-11T23:28:44.394Z] GC before operation: completed in 110.777 ms, heap usage 202.598 MB -> 90.052 MB.
[2026-02-11T23:28:46.804Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-11T23:28:48.585Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-11T23:28:50.383Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-11T23:28:52.174Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-11T23:28:53.961Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-11T23:28:55.197Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-11T23:28:56.447Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-11T23:28:57.701Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-11T23:28:58.063Z] 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.
[2026-02-11T23:28:58.063Z] The best model improves the baseline by 14.52%.
[2026-02-11T23:28:58.063Z] Top recommended movies for user id 72:
[2026-02-11T23:28:58.063Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-11T23:28:58.063Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-11T23:28:58.063Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-11T23:28:58.063Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-11T23:28:58.063Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-11T23:28:58.063Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (13795.373 ms) ======
[2026-02-11T23:28:58.063Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2026-02-11T23:28:58.063Z] GC before operation: completed in 78.818 ms, heap usage 375.369 MB -> 90.209 MB.
[2026-02-11T23:28:59.924Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-11T23:29:01.777Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-11T23:29:04.246Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-11T23:29:06.630Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-11T23:29:07.887Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-11T23:29:09.151Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-11T23:29:10.422Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-11T23:29:11.669Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-11T23:29:12.020Z] 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.
[2026-02-11T23:29:12.020Z] The best model improves the baseline by 14.52%.
[2026-02-11T23:29:12.020Z] Top recommended movies for user id 72:
[2026-02-11T23:29:12.020Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-11T23:29:12.020Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-11T23:29:12.020Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-11T23:29:12.020Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-11T23:29:12.020Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-11T23:29:12.020Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (13967.602 ms) ======
[2026-02-11T23:29:12.020Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2026-02-11T23:29:12.020Z] GC before operation: completed in 77.127 ms, heap usage 123.713 MB -> 92.070 MB.
[2026-02-11T23:29:15.187Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-11T23:29:16.983Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-11T23:29:18.771Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-11T23:29:20.543Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-11T23:29:21.786Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-11T23:29:23.064Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-11T23:29:24.891Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-11T23:29:25.706Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-11T23:29:26.073Z] 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.
[2026-02-11T23:29:26.073Z] The best model improves the baseline by 14.52%.
[2026-02-11T23:29:26.073Z] Top recommended movies for user id 72:
[2026-02-11T23:29:26.073Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-11T23:29:26.073Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-11T23:29:26.073Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-11T23:29:26.073Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-11T23:29:26.073Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-11T23:29:26.073Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (13893.992 ms) ======
[2026-02-11T23:29:26.073Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2026-02-11T23:29:26.073Z] GC before operation: completed in 119.299 ms, heap usage 280.876 MB -> 90.137 MB.
[2026-02-11T23:29:28.485Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-11T23:29:30.289Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-11T23:29:32.069Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-11T23:29:33.869Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-11T23:29:34.659Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-11T23:29:35.901Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-11T23:29:37.141Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-11T23:29:37.924Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-11T23:29:38.289Z] 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.
[2026-02-11T23:29:38.289Z] The best model improves the baseline by 14.52%.
[2026-02-11T23:29:38.289Z] Top recommended movies for user id 72:
[2026-02-11T23:29:38.289Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-11T23:29:38.289Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-11T23:29:38.289Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-11T23:29:38.289Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-11T23:29:38.289Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-11T23:29:38.289Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (12253.803 ms) ======
[2026-02-11T23:29:38.289Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2026-02-11T23:29:38.653Z] GC before operation: completed in 147.319 ms, heap usage 358.383 MB -> 90.542 MB.
[2026-02-11T23:29:41.069Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-11T23:29:42.863Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-11T23:29:45.285Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-11T23:29:47.773Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-11T23:29:48.541Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-11T23:29:49.809Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-11T23:29:50.580Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-11T23:29:51.852Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-11T23:29:51.852Z] 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.
[2026-02-11T23:29:51.852Z] The best model improves the baseline by 14.52%.
[2026-02-11T23:29:51.852Z] Top recommended movies for user id 72:
[2026-02-11T23:29:51.852Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-11T23:29:51.852Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-11T23:29:51.852Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-11T23:29:51.852Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-11T23:29:51.852Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-11T23:29:51.852Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (13444.250 ms) ======
[2026-02-11T23:29:51.852Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2026-02-11T23:29:52.213Z] GC before operation: completed in 116.323 ms, heap usage 677.368 MB -> 93.833 MB.
[2026-02-11T23:29:54.656Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-11T23:29:57.100Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-11T23:29:58.973Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-11T23:30:00.774Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-11T23:30:01.578Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-11T23:30:02.845Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-11T23:30:04.671Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-11T23:30:05.904Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-11T23:30:05.904Z] 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.
[2026-02-11T23:30:05.904Z] The best model improves the baseline by 14.52%.
[2026-02-11T23:30:06.279Z] Top recommended movies for user id 72:
[2026-02-11T23:30:06.279Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-11T23:30:06.279Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-11T23:30:06.279Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-11T23:30:06.279Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-11T23:30:06.279Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-11T23:30:06.279Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14025.595 ms) ======
[2026-02-11T23:30:06.279Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2026-02-11T23:30:06.279Z] GC before operation: completed in 120.602 ms, heap usage 438.337 MB -> 90.623 MB.
[2026-02-11T23:30:08.719Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-11T23:30:11.110Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-11T23:30:13.597Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-11T23:30:15.387Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-11T23:30:16.618Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-11T23:30:17.860Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-11T23:30:19.119Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-11T23:30:20.380Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-11T23:30:20.381Z] 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.
[2026-02-11T23:30:20.381Z] The best model improves the baseline by 14.52%.
[2026-02-11T23:30:20.758Z] Top recommended movies for user id 72:
[2026-02-11T23:30:20.758Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-11T23:30:20.758Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-11T23:30:20.758Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-11T23:30:20.758Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-11T23:30:20.758Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-11T23:30:20.758Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (14291.405 ms) ======
[2026-02-11T23:30:20.758Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2026-02-11T23:30:20.758Z] GC before operation: completed in 145.910 ms, heap usage 243.687 MB -> 90.348 MB.
[2026-02-11T23:30:23.234Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-11T23:30:25.688Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-11T23:30:28.113Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-11T23:30:29.901Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-11T23:30:31.137Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-11T23:30:32.367Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-11T23:30:33.648Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-11T23:30:34.905Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-11T23:30:35.271Z] 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.
[2026-02-11T23:30:35.271Z] The best model improves the baseline by 14.52%.
[2026-02-11T23:30:35.652Z] Top recommended movies for user id 72:
[2026-02-11T23:30:35.652Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-11T23:30:35.652Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-11T23:30:35.652Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-11T23:30:35.652Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-11T23:30:35.652Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-11T23:30:35.652Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14801.377 ms) ======
[2026-02-11T23:30:35.652Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2026-02-11T23:30:35.652Z] GC before operation: completed in 151.735 ms, heap usage 490.759 MB -> 90.589 MB.
[2026-02-11T23:30:38.051Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-11T23:30:39.836Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-11T23:30:42.232Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-11T23:30:44.042Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-11T23:30:45.846Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-11T23:30:46.621Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-11T23:30:47.849Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-11T23:30:49.150Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-11T23:30:49.150Z] 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.
[2026-02-11T23:30:49.150Z] The best model improves the baseline by 14.52%.
[2026-02-11T23:30:49.515Z] Top recommended movies for user id 72:
[2026-02-11T23:30:49.515Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-11T23:30:49.515Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-11T23:30:49.515Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-11T23:30:49.515Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-11T23:30:49.515Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-11T23:30:49.515Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (13782.366 ms) ======
[2026-02-11T23:30:49.515Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2026-02-11T23:30:49.515Z] GC before operation: completed in 162.515 ms, heap usage 200.185 MB -> 90.415 MB.
[2026-02-11T23:30:51.963Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-11T23:30:54.403Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-11T23:30:56.861Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-11T23:30:58.777Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-11T23:30:59.543Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-11T23:31:01.375Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-11T23:31:02.163Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-11T23:31:03.432Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-11T23:31:03.827Z] 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.
[2026-02-11T23:31:03.827Z] The best model improves the baseline by 14.52%.
[2026-02-11T23:31:03.827Z] Top recommended movies for user id 72:
[2026-02-11T23:31:03.827Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-11T23:31:03.827Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-11T23:31:03.827Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-11T23:31:03.827Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-11T23:31:03.827Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-11T23:31:03.827Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14184.253 ms) ======
[2026-02-11T23:31:03.827Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2026-02-11T23:31:04.197Z] GC before operation: completed in 217.856 ms, heap usage 533.550 MB -> 93.964 MB.
[2026-02-11T23:31:06.638Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-11T23:31:08.408Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-11T23:31:10.191Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-11T23:31:11.979Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-11T23:31:13.246Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-11T23:31:14.533Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-11T23:31:16.354Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-11T23:31:17.112Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-11T23:31:17.112Z] 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.
[2026-02-11T23:31:17.112Z] The best model improves the baseline by 14.52%.
[2026-02-11T23:31:17.487Z] Top recommended movies for user id 72:
[2026-02-11T23:31:17.487Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-11T23:31:17.487Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-11T23:31:17.487Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-11T23:31:17.487Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-11T23:31:17.487Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-11T23:31:17.487Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (13339.235 ms) ======
[2026-02-11T23:31:17.487Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2026-02-11T23:31:17.487Z] GC before operation: completed in 88.031 ms, heap usage 120.685 MB -> 90.239 MB.
[2026-02-11T23:31:19.285Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-11T23:31:21.726Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-11T23:31:23.552Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-11T23:31:25.977Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-11T23:31:27.237Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-11T23:31:28.468Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-11T23:31:29.702Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-11T23:31:30.938Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-11T23:31:30.938Z] 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.
[2026-02-11T23:31:31.298Z] The best model improves the baseline by 14.52%.
[2026-02-11T23:31:31.298Z] Top recommended movies for user id 72:
[2026-02-11T23:31:31.299Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-11T23:31:31.299Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-11T23:31:31.299Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-11T23:31:31.299Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-11T23:31:31.299Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-11T23:31:31.299Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (13785.903 ms) ======
[2026-02-11T23:31:31.299Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2026-02-11T23:31:31.299Z] GC before operation: completed in 132.942 ms, heap usage 368.764 MB -> 90.417 MB.
[2026-02-11T23:31:33.723Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-11T23:31:36.159Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-11T23:31:38.584Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-11T23:31:39.834Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-11T23:31:41.086Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-11T23:31:41.874Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-11T23:31:43.144Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-11T23:31:44.479Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-11T23:31:44.479Z] 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.
[2026-02-11T23:31:44.849Z] The best model improves the baseline by 14.52%.
[2026-02-11T23:31:44.849Z] Top recommended movies for user id 72:
[2026-02-11T23:31:44.849Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-11T23:31:44.849Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-11T23:31:44.849Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-11T23:31:44.849Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-11T23:31:44.849Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-11T23:31:44.849Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (13407.606 ms) ======
[2026-02-11T23:31:44.849Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2026-02-11T23:31:44.849Z] GC before operation: completed in 128.158 ms, heap usage 489.621 MB -> 90.704 MB.
[2026-02-11T23:31:47.261Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-11T23:31:49.061Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-11T23:31:50.308Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-11T23:31:52.094Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-11T23:31:54.507Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-11T23:31:55.747Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-11T23:31:56.539Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-11T23:31:57.832Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-11T23:31:57.832Z] 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.
[2026-02-11T23:31:57.832Z] The best model improves the baseline by 14.52%.
[2026-02-11T23:31:57.832Z] Top recommended movies for user id 72:
[2026-02-11T23:31:57.832Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-11T23:31:57.832Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-11T23:31:57.832Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-11T23:31:57.832Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-11T23:31:57.832Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-11T23:31:57.832Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (13062.000 ms) ======
[2026-02-11T23:31:58.598Z] -----------------------------------
[2026-02-11T23:31:58.598Z] renaissance-movie-lens_0_PASSED
[2026-02-11T23:31:58.598Z] -----------------------------------
[2026-02-11T23:31:58.598Z]
[2026-02-11T23:31:58.598Z] TEST TEARDOWN:
[2026-02-11T23:31:58.598Z] Nothing to be done for teardown.
[2026-02-11T23:31:58.598Z] renaissance-movie-lens_0 Finish Time: Wed Feb 11 18:31:58 2026 Epoch Time (ms): 1770852718289