renaissance-movie-lens_0
[2025-12-17T18:56:20.129Z] Running test renaissance-movie-lens_0 ...
[2025-12-17T18:56:20.130Z] ===============================================
[2025-12-17T18:56:20.130Z] renaissance-movie-lens_0 Start Time: Wed Dec 17 10:56:19 2025 Epoch Time (ms): 1765997779776
[2025-12-17T18:56:20.130Z] variation: NoOptions
[2025-12-17T18:56:20.130Z] JVM_OPTIONS:
[2025-12-17T18:56:20.130Z] { \
[2025-12-17T18:56:20.130Z] echo ""; echo "TEST SETUP:"; \
[2025-12-17T18:56:20.130Z] echo "Nothing to be done for setup."; \
[2025-12-17T18:56:20.130Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_176599424512/renaissance-movie-lens_0"; \
[2025-12-17T18:56:20.130Z] cd "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_176599424512/renaissance-movie-lens_0"; \
[2025-12-17T18:56:20.130Z] echo ""; echo "TESTING:"; \
[2025-12-17T18:56:20.130Z] "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_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_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_176599424512/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-12-17T18:56:20.130Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_176599424512/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-12-17T18:56:20.130Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-12-17T18:56:20.130Z] echo "Nothing to be done for teardown."; \
[2025-12-17T18:56:20.130Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_176599424512/TestTargetResult";
[2025-12-17T18:56:20.130Z]
[2025-12-17T18:56:20.130Z] TEST SETUP:
[2025-12-17T18:56:20.130Z] Nothing to be done for setup.
[2025-12-17T18:56:20.130Z]
[2025-12-17T18:56:20.130Z] TESTING:
[2025-12-17T18:56:21.552Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called
[2025-12-17T18:56:21.552Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/output_176599424512/renaissance-movie-lens_0/launcher-105620-550861763202617002/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar)
[2025-12-17T18:56:21.552Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$
[2025-12-17T18:56:21.552Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release
[2025-12-17T18:56:29.708Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-12-17T18:56:41.934Z] 10:56:41.517 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-12-17T18:56:45.798Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-12-17T18:56:46.805Z] Training: 60056, validation: 20285, test: 19854
[2025-12-17T18:56:46.805Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-12-17T18:56:46.805Z] GC before operation: completed in 213.549 ms, heap usage 464.273 MB -> 74.839 MB.
[2025-12-17T18:57:01.784Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-17T18:57:10.385Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-17T18:57:20.754Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-17T18:57:29.467Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-17T18:57:33.141Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-17T18:57:38.813Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-17T18:57:43.498Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-17T18:57:48.075Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-17T18:57:48.540Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-17T18:57:48.985Z] The best model improves the baseline by 14.52%.
[2025-12-17T18:57:49.434Z] Top recommended movies for user id 72:
[2025-12-17T18:57:49.434Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-17T18:57:49.434Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-17T18:57:49.434Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-17T18:57:49.434Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-17T18:57:49.434Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-17T18:57:49.434Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (62439.593 ms) ======
[2025-12-17T18:57:49.434Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-12-17T18:57:49.434Z] GC before operation: completed in 218.647 ms, heap usage 251.993 MB -> 92.517 MB.
[2025-12-17T18:58:01.495Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-17T18:58:10.017Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-17T18:58:18.257Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-17T18:58:26.728Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-17T18:58:31.441Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-17T18:58:36.010Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-17T18:58:39.613Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-17T18:58:44.151Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-17T18:58:45.605Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-17T18:58:45.605Z] The best model improves the baseline by 14.52%.
[2025-12-17T18:58:45.605Z] Top recommended movies for user id 72:
[2025-12-17T18:58:45.605Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-17T18:58:45.605Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-17T18:58:45.605Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-17T18:58:45.605Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-17T18:58:45.605Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-17T18:58:45.605Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (56214.607 ms) ======
[2025-12-17T18:58:45.605Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-12-17T18:58:46.027Z] GC before operation: completed in 147.370 ms, heap usage 1.714 GB -> 93.953 MB.
[2025-12-17T18:58:54.408Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-17T18:59:01.047Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-17T18:59:07.718Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-17T18:59:13.339Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-17T18:59:17.845Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-17T18:59:20.662Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-17T18:59:26.446Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-17T18:59:30.912Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-17T18:59:30.912Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-17T18:59:30.912Z] The best model improves the baseline by 14.52%.
[2025-12-17T18:59:31.354Z] Top recommended movies for user id 72:
[2025-12-17T18:59:31.354Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-17T18:59:31.354Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-17T18:59:31.354Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-17T18:59:31.354Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-17T18:59:31.354Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-17T18:59:31.354Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (45445.230 ms) ======
[2025-12-17T18:59:31.354Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-12-17T18:59:31.354Z] GC before operation: completed in 146.793 ms, heap usage 268.080 MB -> 88.773 MB.
[2025-12-17T18:59:40.015Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-17T18:59:48.088Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-17T18:59:56.282Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-17T19:00:03.120Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-17T19:00:08.601Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-17T19:00:14.134Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-17T19:00:17.673Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-17T19:00:22.160Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-17T19:00:22.160Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-17T19:00:22.160Z] The best model improves the baseline by 14.52%.
[2025-12-17T19:00:22.686Z] Top recommended movies for user id 72:
[2025-12-17T19:00:22.686Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-17T19:00:22.686Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-17T19:00:22.686Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-17T19:00:22.686Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-17T19:00:22.686Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-17T19:00:22.686Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (50946.192 ms) ======
[2025-12-17T19:00:22.686Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-12-17T19:00:22.686Z] GC before operation: completed in 163.097 ms, heap usage 191.170 MB -> 88.734 MB.
[2025-12-17T19:00:31.150Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-17T19:00:39.370Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-17T19:00:47.614Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-17T19:00:54.474Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-17T19:00:58.853Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-17T19:01:03.395Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-17T19:01:08.079Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-17T19:01:11.325Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-17T19:01:11.768Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-17T19:01:11.768Z] The best model improves the baseline by 14.52%.
[2025-12-17T19:01:11.768Z] Top recommended movies for user id 72:
[2025-12-17T19:01:11.768Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-17T19:01:11.768Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-17T19:01:11.768Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-17T19:01:11.768Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-17T19:01:11.768Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-17T19:01:11.769Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (49336.231 ms) ======
[2025-12-17T19:01:11.769Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-12-17T19:01:12.154Z] GC before operation: completed in 158.029 ms, heap usage 147.673 MB -> 88.411 MB.
[2025-12-17T19:01:22.093Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-17T19:01:29.041Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-17T19:01:35.794Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-17T19:01:43.909Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-17T19:01:49.648Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-17T19:01:52.516Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-17T19:01:56.972Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-17T19:02:01.658Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-17T19:02:02.727Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-17T19:02:02.727Z] The best model improves the baseline by 14.52%.
[2025-12-17T19:02:03.114Z] Top recommended movies for user id 72:
[2025-12-17T19:02:03.114Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-17T19:02:03.114Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-17T19:02:03.114Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-17T19:02:03.114Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-17T19:02:03.114Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-17T19:02:03.114Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (51079.776 ms) ======
[2025-12-17T19:02:03.114Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-12-17T19:02:03.114Z] GC before operation: completed in 166.589 ms, heap usage 346.029 MB -> 89.288 MB.
[2025-12-17T19:02:13.112Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-17T19:02:21.560Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-17T19:02:36.946Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-17T19:02:41.281Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-17T19:02:45.642Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-17T19:02:51.316Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-17T19:02:56.105Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-17T19:03:01.796Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-17T19:03:02.280Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-17T19:03:02.710Z] The best model improves the baseline by 14.52%.
[2025-12-17T19:03:02.710Z] Top recommended movies for user id 72:
[2025-12-17T19:03:02.710Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-17T19:03:02.710Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-17T19:03:02.710Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-17T19:03:02.710Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-17T19:03:02.710Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-17T19:03:02.710Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (59583.995 ms) ======
[2025-12-17T19:03:02.710Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-12-17T19:03:03.079Z] GC before operation: completed in 150.490 ms, heap usage 204.484 MB -> 89.022 MB.
[2025-12-17T19:03:13.429Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-17T19:03:23.661Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-17T19:03:31.908Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-17T19:03:41.933Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-17T19:03:46.951Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-17T19:03:53.732Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-17T19:04:00.859Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-17T19:04:05.632Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-17T19:04:06.045Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-17T19:04:06.045Z] The best model improves the baseline by 14.52%.
[2025-12-17T19:04:06.443Z] Top recommended movies for user id 72:
[2025-12-17T19:04:06.443Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-17T19:04:06.443Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-17T19:04:06.443Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-17T19:04:06.443Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-17T19:04:06.443Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-17T19:04:06.443Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (63237.136 ms) ======
[2025-12-17T19:04:06.443Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-12-17T19:04:06.443Z] GC before operation: completed in 159.492 ms, heap usage 123.204 MB -> 89.182 MB.
[2025-12-17T19:04:18.473Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-17T19:04:33.667Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-17T19:04:43.848Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-17T19:04:50.943Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-17T19:04:56.445Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-17T19:05:03.276Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-17T19:05:07.667Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-17T19:05:14.922Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-17T19:05:15.350Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-17T19:05:15.350Z] The best model improves the baseline by 14.52%.
[2025-12-17T19:05:15.350Z] Top recommended movies for user id 72:
[2025-12-17T19:05:15.350Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-17T19:05:15.350Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-17T19:05:15.350Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-17T19:05:15.350Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-17T19:05:15.350Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-17T19:05:15.350Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (68974.287 ms) ======
[2025-12-17T19:05:15.350Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-12-17T19:05:15.350Z] GC before operation: completed in 136.244 ms, heap usage 218.511 MB -> 89.159 MB.
[2025-12-17T19:05:25.154Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-17T19:05:37.234Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-17T19:05:47.177Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-17T19:05:55.406Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-17T19:05:58.108Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-17T19:06:01.636Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-17T19:06:06.135Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-17T19:06:11.794Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-17T19:06:13.951Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-17T19:06:13.951Z] The best model improves the baseline by 14.52%.
[2025-12-17T19:06:14.355Z] Top recommended movies for user id 72:
[2025-12-17T19:06:14.355Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-17T19:06:14.355Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-17T19:06:14.355Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-17T19:06:14.355Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-17T19:06:14.355Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-17T19:06:14.355Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (58771.410 ms) ======
[2025-12-17T19:06:14.355Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-12-17T19:06:14.355Z] GC before operation: completed in 186.532 ms, heap usage 1.135 GB -> 94.803 MB.
[2025-12-17T19:06:22.709Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-17T19:06:32.829Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-17T19:06:41.196Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-17T19:06:47.963Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-17T19:06:53.594Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-17T19:06:58.084Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-17T19:07:02.635Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-17T19:07:08.132Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-17T19:07:08.545Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-17T19:07:08.545Z] The best model improves the baseline by 14.52%.
[2025-12-17T19:07:08.917Z] Top recommended movies for user id 72:
[2025-12-17T19:07:08.917Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-17T19:07:08.917Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-17T19:07:08.917Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-17T19:07:08.917Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-17T19:07:08.917Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-17T19:07:08.917Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (54436.132 ms) ======
[2025-12-17T19:07:08.917Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-12-17T19:07:08.917Z] GC before operation: completed in 174.123 ms, heap usage 929.186 MB -> 93.790 MB.
[2025-12-17T19:07:18.962Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-17T19:07:28.934Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-17T19:07:37.514Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-17T19:07:46.203Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-17T19:07:51.639Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-17T19:07:55.119Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-17T19:07:59.020Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-17T19:08:03.287Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-17T19:08:03.726Z] 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.
[2025-12-17T19:08:03.726Z] The best model improves the baseline by 14.52%.
[2025-12-17T19:08:03.726Z] Top recommended movies for user id 72:
[2025-12-17T19:08:03.726Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-17T19:08:03.726Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-17T19:08:03.726Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-17T19:08:03.726Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-17T19:08:03.726Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-17T19:08:03.726Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (54662.376 ms) ======
[2025-12-17T19:08:03.726Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-12-17T19:08:04.486Z] GC before operation: completed in 177.751 ms, heap usage 459.508 MB -> 89.715 MB.
[2025-12-17T19:08:11.486Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-17T19:08:21.278Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-17T19:08:29.544Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-17T19:08:36.357Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-17T19:08:41.051Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-17T19:08:46.539Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-17T19:08:51.017Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-17T19:08:56.639Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-17T19:08:56.639Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-17T19:08:56.639Z] The best model improves the baseline by 14.52%.
[2025-12-17T19:08:57.048Z] Top recommended movies for user id 72:
[2025-12-17T19:08:57.048Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-17T19:08:57.048Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-17T19:08:57.048Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-17T19:08:57.048Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-17T19:08:57.048Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-17T19:08:57.048Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (53140.422 ms) ======
[2025-12-17T19:08:57.048Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-12-17T19:08:57.475Z] GC before operation: completed in 229.937 ms, heap usage 386.011 MB -> 89.468 MB.
[2025-12-17T19:09:07.451Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-17T19:09:26.098Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-17T19:09:31.499Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-17T19:09:38.240Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-17T19:09:45.229Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-17T19:09:48.791Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-17T19:09:55.730Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-17T19:10:00.279Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-17T19:10:00.279Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-17T19:10:00.279Z] The best model improves the baseline by 14.52%.
[2025-12-17T19:10:00.279Z] Top recommended movies for user id 72:
[2025-12-17T19:10:00.279Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-17T19:10:00.279Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-17T19:10:00.279Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-17T19:10:00.279Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-17T19:10:00.279Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-17T19:10:00.279Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (62904.273 ms) ======
[2025-12-17T19:10:00.279Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-12-17T19:10:00.279Z] GC before operation: completed in 211.825 ms, heap usage 818.113 MB -> 93.231 MB.
[2025-12-17T19:10:10.447Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-17T19:10:18.904Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-17T19:10:27.088Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-17T19:10:39.334Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-17T19:10:44.059Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-17T19:10:49.597Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-17T19:10:54.096Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-17T19:10:59.792Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-17T19:11:01.511Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-17T19:11:01.511Z] The best model improves the baseline by 14.52%.
[2025-12-17T19:11:01.922Z] Top recommended movies for user id 72:
[2025-12-17T19:11:01.922Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-17T19:11:01.922Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-17T19:11:01.922Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-17T19:11:01.922Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-17T19:11:01.922Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-17T19:11:01.922Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (61446.430 ms) ======
[2025-12-17T19:11:01.922Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-12-17T19:11:01.922Z] GC before operation: completed in 108.324 ms, heap usage 327.897 MB -> 89.684 MB.
[2025-12-17T19:11:10.388Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-17T19:11:18.648Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-17T19:11:26.918Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-17T19:11:35.208Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-17T19:11:40.754Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-17T19:11:46.194Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-17T19:11:50.673Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-17T19:11:56.349Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-17T19:11:57.257Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-17T19:11:57.257Z] The best model improves the baseline by 14.52%.
[2025-12-17T19:11:57.654Z] Top recommended movies for user id 72:
[2025-12-17T19:11:57.654Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-17T19:11:57.654Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-17T19:11:57.655Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-17T19:11:57.655Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-17T19:11:57.655Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-17T19:11:57.655Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (55633.686 ms) ======
[2025-12-17T19:11:57.655Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-12-17T19:11:57.655Z] GC before operation: completed in 196.687 ms, heap usage 267.056 MB -> 89.214 MB.
[2025-12-17T19:12:07.603Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-17T19:12:16.005Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-17T19:12:24.219Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-17T19:12:31.084Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-17T19:12:36.706Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-17T19:12:43.605Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-17T19:12:49.235Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-17T19:12:54.863Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-17T19:12:56.017Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-17T19:12:56.017Z] The best model improves the baseline by 14.52%.
[2025-12-17T19:12:57.011Z] Top recommended movies for user id 72:
[2025-12-17T19:12:57.011Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-17T19:12:57.011Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-17T19:12:57.011Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-17T19:12:57.011Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-17T19:12:57.011Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-17T19:12:57.011Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (58965.108 ms) ======
[2025-12-17T19:12:57.011Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-12-17T19:12:57.011Z] GC before operation: completed in 120.437 ms, heap usage 266.512 MB -> 89.430 MB.
[2025-12-17T19:13:04.279Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-17T19:13:14.237Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-17T19:13:22.848Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-17T19:13:31.262Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-17T19:13:34.017Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-17T19:13:39.666Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-17T19:13:45.148Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-17T19:13:48.648Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-17T19:13:49.659Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-17T19:13:49.659Z] The best model improves the baseline by 14.52%.
[2025-12-17T19:13:50.061Z] Top recommended movies for user id 72:
[2025-12-17T19:13:50.061Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-17T19:13:50.061Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-17T19:13:50.061Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-17T19:13:50.061Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-17T19:13:50.061Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-17T19:13:50.061Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (53028.823 ms) ======
[2025-12-17T19:13:50.061Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-12-17T19:13:50.450Z] GC before operation: completed in 200.236 ms, heap usage 968.323 MB -> 93.918 MB.
[2025-12-17T19:13:58.732Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-17T19:14:08.819Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-17T19:14:17.370Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-17T19:14:23.985Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-17T19:14:25.832Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-17T19:14:30.125Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-17T19:14:35.669Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-17T19:14:41.407Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-17T19:14:41.407Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-17T19:14:41.407Z] The best model improves the baseline by 14.52%.
[2025-12-17T19:14:41.407Z] Top recommended movies for user id 72:
[2025-12-17T19:14:41.407Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-17T19:14:41.407Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-17T19:14:41.407Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-17T19:14:41.407Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-17T19:14:41.407Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-17T19:14:41.407Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (51036.227 ms) ======
[2025-12-17T19:14:41.407Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-12-17T19:14:41.935Z] GC before operation: completed in 551.101 ms, heap usage 817.717 MB -> 93.536 MB.
[2025-12-17T19:14:51.837Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-17T19:15:00.111Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-17T19:15:08.470Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-17T19:15:18.446Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-17T19:15:23.051Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-17T19:15:27.514Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-17T19:15:33.156Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-17T19:15:36.796Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-17T19:15:37.220Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-17T19:15:37.220Z] The best model improves the baseline by 14.52%.
[2025-12-17T19:15:37.220Z] Top recommended movies for user id 72:
[2025-12-17T19:15:37.220Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-17T19:15:37.220Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-17T19:15:37.220Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-17T19:15:37.220Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-17T19:15:37.220Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-17T19:15:37.220Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (55458.894 ms) ======
[2025-12-17T19:15:39.228Z] -----------------------------------
[2025-12-17T19:15:39.228Z] renaissance-movie-lens_0_PASSED
[2025-12-17T19:15:39.228Z] -----------------------------------
[2025-12-17T19:15:39.606Z]
[2025-12-17T19:15:39.606Z] TEST TEARDOWN:
[2025-12-17T19:15:39.606Z] Nothing to be done for teardown.
[2025-12-17T19:15:39.606Z] renaissance-movie-lens_0 Finish Time: Wed Dec 17 11:15:39 2025 Epoch Time (ms): 1765998939321