Bound the size of the histogram cache. (#9440)

- A new histogram collection with a limit in size.
- Unify histogram building logic between hist, multi-hist, and approx.

python-package/xgboost/testing/data_iter.py

@@ -0,0 +1,34 @@
+"""Tests related to the `DataIter` interface."""
+import numpy as np
+
+import xgboost
+from xgboost import testing as tm
+
+
+def run_mixed_sparsity(device: str) -> None:
+    """Check QDM with mixed batches."""
+    X_0, y_0, _ = tm.make_regression(128, 16, False)
+    if device.startswith("cuda"):
+        X_1, y_1 = tm.make_sparse_regression(256, 16, 0.1, True)
+    else:
+        X_1, y_1 = tm.make_sparse_regression(256, 16, 0.1, False)
+    X_2, y_2 = tm.make_sparse_regression(512, 16, 0.9, True)
+    X = [X_0, X_1, X_2]
+    y = [y_0, y_1, y_2]
+
+    if device.startswith("cuda"):
+        import cupy as cp  # pylint: disable=import-error
+
+        X = [cp.array(batch) for batch in X]
+
+    it = tm.IteratorForTest(X, y, None, None)
+    Xy_0 = xgboost.QuantileDMatrix(it)
+
+    X_1, y_1 = tm.make_sparse_regression(256, 16, 0.1, True)
+    X = [X_0, X_1, X_2]
+    y = [y_0, y_1, y_2]
+    X_arr = np.concatenate(X, axis=0)
+    y_arr = np.concatenate(y, axis=0)
+    Xy_1 = xgboost.QuantileDMatrix(X_arr, y_arr)
+
+    assert tm.predictor_equal(Xy_0, Xy_1)

python-package/xgboost/testing/params.py

@@ -41,6 +41,10 @@ hist_parameter_strategy = strategies.fixed_dictionaries(
     and (cast(int, x["max_depth"]) > 0 or x["grow_policy"] == "lossguide")
 )
 
+hist_cache_strategy = strategies.fixed_dictionaries(
+    {"internal_max_cached_hist_node": strategies.sampled_from([1, 4, 1024, 2**31])}
+)
+
 hist_multi_parameter_strategy = strategies.fixed_dictionaries(
     {
         "max_depth": strategies.integers(1, 11),