renaissance-movie-lens_0
[2025-12-04T02:59:03.425Z] Running test renaissance-movie-lens_0 ...
[2025-12-04T02:59:03.425Z] ===============================================
[2025-12-04T02:59:03.425Z] renaissance-movie-lens_0 Start Time: Thu Dec 4 02:59:02 2025 Epoch Time (ms): 1764817142582
[2025-12-04T02:59:03.425Z] variation: NoOptions
[2025-12-04T02:59:03.425Z] JVM_OPTIONS:
[2025-12-04T02:59:03.425Z] { \
[2025-12-04T02:59:03.425Z] echo ""; echo "TEST SETUP:"; \
[2025-12-04T02:59:03.425Z] echo "Nothing to be done for setup."; \
[2025-12-04T02:59:03.425Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17648118864591/renaissance-movie-lens_0"; \
[2025-12-04T02:59:03.425Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17648118864591/renaissance-movie-lens_0"; \
[2025-12-04T02:59:03.425Z] echo ""; echo "TESTING:"; \
[2025-12-04T02:59:03.425Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17648118864591/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-12-04T02:59:03.425Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17648118864591/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-12-04T02:59:03.425Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-12-04T02:59:03.425Z] echo "Nothing to be done for teardown."; \
[2025-12-04T02:59:03.425Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17648118864591/TestTargetResult";
[2025-12-04T02:59:03.425Z]
[2025-12-04T02:59:03.425Z] TEST SETUP:
[2025-12-04T02:59:03.425Z] Nothing to be done for setup.
[2025-12-04T02:59:03.425Z]
[2025-12-04T02:59:03.425Z] TESTING:
[2025-12-04T02:59:26.394Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-12-04T02:59:59.769Z] 02:59:57.534 WARN [dispatcher-event-loop-3] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-12-04T03:00:08.751Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-12-04T03:00:11.022Z] Training: 60056, validation: 20285, test: 19854
[2025-12-04T03:00:11.022Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-12-04T03:00:11.362Z] GC before operation: completed in 630.853 ms, heap usage 381.341 MB -> 76.499 MB.
[2025-12-04T03:00:39.398Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T03:00:55.403Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T03:01:11.251Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T03:01:24.380Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T03:01:33.262Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T03:01:40.505Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T03:01:47.780Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T03:01:55.021Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T03:01:56.288Z] 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.
[2025-12-04T03:01:56.614Z] The best model improves the baseline by 14.52%.
[2025-12-04T03:01:57.746Z] Top recommended movies for user id 72:
[2025-12-04T03:01:57.746Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T03:01:57.746Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T03:01:57.746Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T03:01:57.746Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T03:01:57.746Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T03:01:57.746Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (106578.283 ms) ======
[2025-12-04T03:01:57.746Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-12-04T03:01:58.909Z] GC before operation: completed in 889.199 ms, heap usage 128.842 MB -> 87.159 MB.
[2025-12-04T03:02:11.988Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T03:02:22.756Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T03:02:33.516Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T03:02:44.308Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T03:02:50.295Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T03:02:56.177Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T03:03:03.404Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T03:03:08.118Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T03:03:09.252Z] 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.
[2025-12-04T03:03:09.252Z] The best model improves the baseline by 14.52%.
[2025-12-04T03:03:10.399Z] Top recommended movies for user id 72:
[2025-12-04T03:03:10.399Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T03:03:10.399Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T03:03:10.399Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T03:03:10.399Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T03:03:10.399Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T03:03:10.399Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (71471.940 ms) ======
[2025-12-04T03:03:10.399Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-12-04T03:03:11.122Z] GC before operation: completed in 930.862 ms, heap usage 246.078 MB -> 89.384 MB.
[2025-12-04T03:03:22.078Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T03:03:30.928Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T03:03:41.705Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T03:03:50.537Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T03:03:56.477Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T03:04:02.344Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T03:04:09.583Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T03:04:15.441Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T03:04:16.137Z] 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.
[2025-12-04T03:04:16.462Z] The best model improves the baseline by 14.52%.
[2025-12-04T03:04:17.159Z] Top recommended movies for user id 72:
[2025-12-04T03:04:17.159Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T03:04:17.159Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T03:04:17.159Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T03:04:17.159Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T03:04:17.159Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T03:04:17.159Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (65999.247 ms) ======
[2025-12-04T03:04:17.159Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-12-04T03:04:18.320Z] GC before operation: completed in 968.652 ms, heap usage 96.161 MB -> 89.998 MB.
[2025-12-04T03:04:29.078Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T03:04:38.034Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T03:04:48.879Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T03:04:57.729Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T03:05:04.975Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T03:05:10.998Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T03:05:16.925Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T03:05:22.894Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T03:05:24.055Z] 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.
[2025-12-04T03:05:24.055Z] The best model improves the baseline by 14.52%.
[2025-12-04T03:05:24.777Z] Top recommended movies for user id 72:
[2025-12-04T03:05:24.777Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T03:05:24.777Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T03:05:24.777Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T03:05:24.777Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T03:05:24.777Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T03:05:24.777Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (66535.525 ms) ======
[2025-12-04T03:05:24.777Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-12-04T03:05:25.496Z] GC before operation: completed in 933.231 ms, heap usage 388.315 MB -> 90.536 MB.
[2025-12-04T03:05:36.292Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T03:05:45.195Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T03:05:54.354Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T03:06:05.121Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T03:06:09.829Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T03:06:15.742Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T03:06:23.046Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T03:06:28.911Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T03:06:29.278Z] 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.
[2025-12-04T03:06:29.601Z] The best model improves the baseline by 14.52%.
[2025-12-04T03:06:30.308Z] Top recommended movies for user id 72:
[2025-12-04T03:06:30.308Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T03:06:30.308Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T03:06:30.308Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T03:06:30.308Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T03:06:30.308Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T03:06:30.308Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (64591.008 ms) ======
[2025-12-04T03:06:30.308Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-12-04T03:06:31.451Z] GC before operation: completed in 1011.662 ms, heap usage 595.366 MB -> 93.917 MB.
[2025-12-04T03:06:42.209Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T03:06:51.061Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T03:06:59.902Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T03:07:07.115Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T03:07:12.992Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T03:07:17.708Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T03:07:23.590Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T03:07:28.313Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T03:07:29.442Z] 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.
[2025-12-04T03:07:29.442Z] The best model improves the baseline by 14.52%.
[2025-12-04T03:07:30.141Z] Top recommended movies for user id 72:
[2025-12-04T03:07:30.141Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T03:07:30.141Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T03:07:30.141Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T03:07:30.141Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T03:07:30.141Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T03:07:30.141Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (58863.621 ms) ======
[2025-12-04T03:07:30.141Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-12-04T03:07:31.293Z] GC before operation: completed in 1008.338 ms, heap usage 526.015 MB -> 90.971 MB.
[2025-12-04T03:07:40.130Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T03:07:50.923Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T03:07:58.144Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T03:08:07.061Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T03:08:10.811Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T03:08:15.535Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T03:08:21.482Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T03:08:26.193Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T03:08:26.520Z] 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.
[2025-12-04T03:08:26.844Z] The best model improves the baseline by 14.52%.
[2025-12-04T03:08:27.544Z] Top recommended movies for user id 72:
[2025-12-04T03:08:27.544Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T03:08:27.544Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T03:08:27.544Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T03:08:27.544Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T03:08:27.544Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T03:08:27.544Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (56431.466 ms) ======
[2025-12-04T03:08:27.544Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-12-04T03:08:28.687Z] GC before operation: completed in 993.690 ms, heap usage 188.435 MB -> 90.629 MB.
[2025-12-04T03:08:37.563Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T03:08:46.394Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T03:08:53.621Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T03:09:02.503Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T03:09:07.213Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T03:09:11.964Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T03:09:16.683Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T03:09:22.584Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T03:09:22.908Z] 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.
[2025-12-04T03:09:22.908Z] The best model improves the baseline by 14.52%.
[2025-12-04T03:09:23.618Z] Top recommended movies for user id 72:
[2025-12-04T03:09:23.618Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T03:09:23.618Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T03:09:23.618Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T03:09:23.618Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T03:09:23.618Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T03:09:23.618Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (54987.574 ms) ======
[2025-12-04T03:09:23.618Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-12-04T03:09:24.773Z] GC before operation: completed in 1031.450 ms, heap usage 502.732 MB -> 91.236 MB.
[2025-12-04T03:09:33.801Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T03:09:41.034Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T03:09:49.901Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T03:09:57.226Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T03:10:02.138Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T03:10:07.450Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T03:10:13.415Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T03:10:18.118Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T03:10:18.118Z] 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.
[2025-12-04T03:10:18.444Z] The best model improves the baseline by 14.52%.
[2025-12-04T03:10:19.144Z] Top recommended movies for user id 72:
[2025-12-04T03:10:19.144Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T03:10:19.144Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T03:10:19.144Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T03:10:19.144Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T03:10:19.144Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T03:10:19.144Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (54739.557 ms) ======
[2025-12-04T03:10:19.144Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-12-04T03:10:20.324Z] GC before operation: completed in 990.455 ms, heap usage 134.143 MB -> 90.529 MB.
[2025-12-04T03:10:29.178Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T03:10:38.364Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T03:10:45.734Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T03:10:54.579Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T03:10:58.332Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T03:11:04.192Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T03:11:09.240Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T03:11:13.966Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T03:11:14.291Z] 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.
[2025-12-04T03:11:14.615Z] The best model improves the baseline by 14.52%.
[2025-12-04T03:11:14.940Z] Top recommended movies for user id 72:
[2025-12-04T03:11:14.940Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T03:11:14.940Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T03:11:14.941Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T03:11:14.941Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T03:11:14.941Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T03:11:14.941Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (54818.626 ms) ======
[2025-12-04T03:11:14.941Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-12-04T03:11:16.085Z] GC before operation: completed in 1037.580 ms, heap usage 811.109 MB -> 94.894 MB.
[2025-12-04T03:11:24.926Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T03:11:32.218Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T03:11:41.210Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T03:11:48.564Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T03:11:53.274Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T03:11:59.180Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T03:12:03.916Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T03:12:08.629Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T03:12:09.325Z] 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.
[2025-12-04T03:12:09.325Z] The best model improves the baseline by 14.52%.
[2025-12-04T03:12:10.106Z] Top recommended movies for user id 72:
[2025-12-04T03:12:10.106Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T03:12:10.106Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T03:12:10.106Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T03:12:10.106Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T03:12:10.106Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T03:12:10.106Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (53964.477 ms) ======
[2025-12-04T03:12:10.106Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-12-04T03:12:11.266Z] GC before operation: completed in 1006.499 ms, heap usage 559.602 MB -> 91.124 MB.
[2025-12-04T03:12:20.167Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T03:12:27.440Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T03:12:36.290Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T03:12:45.120Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T03:12:49.833Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T03:12:55.694Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T03:13:00.407Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T03:13:06.278Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T03:13:06.977Z] 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.
[2025-12-04T03:13:07.395Z] The best model improves the baseline by 14.52%.
[2025-12-04T03:13:07.784Z] Top recommended movies for user id 72:
[2025-12-04T03:13:07.785Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T03:13:07.785Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T03:13:07.785Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T03:13:07.785Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T03:13:07.785Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T03:13:07.785Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (56761.137 ms) ======
[2025-12-04T03:13:07.785Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-12-04T03:13:08.953Z] GC before operation: completed in 986.486 ms, heap usage 430.642 MB -> 91.035 MB.
[2025-12-04T03:13:18.032Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T03:13:26.903Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T03:13:35.744Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T03:13:42.958Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T03:13:48.998Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T03:13:54.857Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T03:14:00.713Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T03:14:06.608Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T03:14:06.939Z] 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.
[2025-12-04T03:14:06.939Z] The best model improves the baseline by 14.52%.
[2025-12-04T03:14:07.729Z] Top recommended movies for user id 72:
[2025-12-04T03:14:07.729Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T03:14:07.729Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T03:14:07.729Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T03:14:07.729Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T03:14:07.729Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T03:14:07.729Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (58805.404 ms) ======
[2025-12-04T03:14:07.729Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-12-04T03:14:08.454Z] GC before operation: completed in 974.862 ms, heap usage 390.264 MB -> 91.184 MB.
[2025-12-04T03:14:19.217Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T03:14:26.561Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T03:14:37.325Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T03:14:44.570Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T03:14:50.432Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T03:14:56.303Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T03:15:01.031Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T03:15:05.857Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T03:15:07.022Z] 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.
[2025-12-04T03:15:07.022Z] The best model improves the baseline by 14.52%.
[2025-12-04T03:15:07.734Z] Top recommended movies for user id 72:
[2025-12-04T03:15:07.734Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T03:15:07.734Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T03:15:07.734Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T03:15:07.734Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T03:15:07.734Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T03:15:07.734Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (58928.456 ms) ======
[2025-12-04T03:15:07.734Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-12-04T03:15:08.457Z] GC before operation: completed in 1010.858 ms, heap usage 718.719 MB -> 94.631 MB.
[2025-12-04T03:15:17.316Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T03:15:26.189Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T03:15:33.429Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T03:15:40.664Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T03:15:45.580Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T03:15:50.300Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T03:15:56.178Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T03:15:59.952Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T03:16:01.085Z] 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.
[2025-12-04T03:16:01.085Z] The best model improves the baseline by 14.52%.
[2025-12-04T03:16:01.787Z] Top recommended movies for user id 72:
[2025-12-04T03:16:01.787Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T03:16:01.787Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T03:16:01.787Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T03:16:01.787Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T03:16:01.787Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T03:16:01.787Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (53226.679 ms) ======
[2025-12-04T03:16:01.787Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-12-04T03:16:02.937Z] GC before operation: completed in 1047.815 ms, heap usage 1.004 GB -> 95.853 MB.
[2025-12-04T03:16:11.787Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T03:16:21.145Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T03:16:28.732Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T03:16:35.964Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T03:16:41.867Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T03:16:47.757Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T03:16:52.478Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T03:16:58.346Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T03:16:58.780Z] 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.
[2025-12-04T03:16:58.780Z] The best model improves the baseline by 14.52%.
[2025-12-04T03:16:59.506Z] Top recommended movies for user id 72:
[2025-12-04T03:16:59.506Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T03:16:59.506Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T03:16:59.506Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T03:16:59.506Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T03:16:59.506Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T03:16:59.506Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (56608.924 ms) ======
[2025-12-04T03:16:59.506Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-12-04T03:17:00.651Z] GC before operation: completed in 1018.516 ms, heap usage 443.641 MB -> 91.060 MB.
[2025-12-04T03:17:09.874Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T03:17:18.722Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T03:17:27.558Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T03:17:34.786Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T03:17:40.663Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T03:17:45.367Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T03:17:51.224Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T03:17:57.096Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T03:17:57.419Z] 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.
[2025-12-04T03:17:57.419Z] The best model improves the baseline by 14.52%.
[2025-12-04T03:17:58.133Z] Top recommended movies for user id 72:
[2025-12-04T03:17:58.133Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T03:17:58.133Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T03:17:58.133Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T03:17:58.133Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T03:17:58.133Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T03:17:58.133Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (57563.303 ms) ======
[2025-12-04T03:17:58.133Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-12-04T03:17:58.853Z] GC before operation: completed in 981.889 ms, heap usage 438.389 MB -> 91.156 MB.
[2025-12-04T03:18:09.641Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T03:18:16.878Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T03:18:25.834Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T03:18:34.693Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T03:18:39.564Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T03:18:46.964Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T03:18:50.977Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T03:18:55.185Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T03:18:55.185Z] 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.
[2025-12-04T03:18:55.185Z] The best model improves the baseline by 14.52%.
[2025-12-04T03:18:55.883Z] Top recommended movies for user id 72:
[2025-12-04T03:18:55.883Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T03:18:55.883Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T03:18:55.883Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T03:18:55.883Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T03:18:55.883Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T03:18:55.883Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (56934.819 ms) ======
[2025-12-04T03:18:55.883Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-12-04T03:18:57.047Z] GC before operation: completed in 977.511 ms, heap usage 118.348 MB -> 90.662 MB.
[2025-12-04T03:19:05.898Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T03:19:15.462Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T03:19:21.219Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T03:19:30.057Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T03:19:34.770Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T03:19:39.477Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T03:19:44.186Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T03:19:50.050Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T03:19:50.375Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-04T03:19:50.375Z] The best model improves the baseline by 14.52%.
[2025-12-04T03:19:51.071Z] Top recommended movies for user id 72:
[2025-12-04T03:19:51.071Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T03:19:51.071Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T03:19:51.071Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T03:19:51.071Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T03:19:51.071Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T03:19:51.071Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (54147.997 ms) ======
[2025-12-04T03:19:51.071Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-12-04T03:19:52.309Z] GC before operation: completed in 1002.219 ms, heap usage 273.141 MB -> 90.980 MB.
[2025-12-04T03:20:01.166Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-04T03:20:08.461Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-04T03:20:17.439Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-04T03:20:24.664Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-04T03:20:29.371Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-04T03:20:34.206Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-04T03:20:38.930Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-04T03:20:43.647Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-04T03:20:43.972Z] 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.
[2025-12-04T03:20:44.306Z] The best model improves the baseline by 14.52%.
[2025-12-04T03:20:45.005Z] Top recommended movies for user id 72:
[2025-12-04T03:20:45.005Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-04T03:20:45.005Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-04T03:20:45.005Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-04T03:20:45.005Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-04T03:20:45.005Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-04T03:20:45.005Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (52776.161 ms) ======
[2025-12-04T03:20:48.760Z] -----------------------------------
[2025-12-04T03:20:48.760Z] renaissance-movie-lens_0_PASSED
[2025-12-04T03:20:48.760Z] -----------------------------------
[2025-12-04T03:20:48.760Z]
[2025-12-04T03:20:48.760Z] TEST TEARDOWN:
[2025-12-04T03:20:48.760Z] Nothing to be done for teardown.
[2025-12-04T03:20:48.760Z] renaissance-movie-lens_0 Finish Time: Thu Dec 4 03:20:48 2025 Epoch Time (ms): 1764818448181