PERF: join empty frame (pandas-dev#46015)

* faster joins when left and/or right is empty

* whatsnew

* cleanup

* add asv for joining with empty frame

* asv

Author: lukemanley

asv_bench/benchmarks/join_merge.py

@@ -158,6 +158,19 @@ def time_left_outer_join_index(self):
         self.left.join(self.right, on="jim")
 
 
+class JoinEmpty:
+    def setup(self):
+        N = 100_000
+        self.df = DataFrame({"A": np.arange(N)})
+        self.df_empty = DataFrame(columns=["B", "C"], dtype="int64")
+
+    def time_inner_join_left_empty(self):
+        self.df_empty.join(self.df, how="inner")
+
+    def time_inner_join_right_empty(self):
+        self.df.join(self.df_empty, how="inner")
+
+
 class JoinNonUnique:
     # outer join of non-unique
     # GH 6329

doc/source/whatsnew/v1.5.0.rst

@@ -256,6 +256,7 @@ Performance improvements
 - Performance improvement in :meth:`.GroupBy.transform` for user-defined functions when only a single group exists (:issue:`44977`)
 - Performance improvement in :meth:`MultiIndex.get_locs` (:issue:`45681`)
 - Performance improvement in :func:`merge` when left and/or right are empty (:issue:`45838`)
+- Performance improvement in :meth:`DataFrame.join` when left and/or right are empty (:issue:`46015`)
 - Performance improvement in :class:`DataFrame` and :class:`Series` constructors for extension dtype scalars (:issue:`45854`)
 -
 

pandas/core/indexes/base.py

@@ -4542,15 +4542,25 @@ def join(
         if level is not None and (self._is_multi or other._is_multi):
             return self._join_level(other, level, how=how)
 
-        if len(other) == 0 and how in ("left", "outer"):
-            join_index = self._view()
-            rindexer = np.repeat(np.intp(-1), len(join_index))
-            return join_index, None, rindexer
-
-        if len(self) == 0 and how in ("right", "outer"):
-            join_index = other._view()
-            lindexer = np.repeat(np.intp(-1), len(join_index))
-            return join_index, lindexer, None
+        if len(other) == 0:
+            if how in ("left", "outer"):
+                join_index = self._view()
+                rindexer = np.broadcast_to(np.intp(-1), len(join_index))
+                return join_index, None, rindexer
+            elif how in ("right", "inner", "cross"):
+                join_index = other._view()
+                lindexer = np.array([])
+                return join_index, lindexer, None
+
+        if len(self) == 0:
+            if how in ("right", "outer"):
+                join_index = other._view()
+                lindexer = np.broadcast_to(np.intp(-1), len(join_index))
+                return join_index, lindexer, None
+            elif how in ("left", "inner", "cross"):
+                join_index = self._view()
+                rindexer = np.array([])
+                return join_index, None, rindexer
 
         if self._join_precedence < other._join_precedence:
             how = {"right": "left", "left": "right"}.get(how, how)

pandas/tests/reshape/merge/test_join.py

@@ -881,3 +881,44 @@ def test_join_multiindex_not_alphabetical_categorical(categories, values):
         }
     ).set_index(["first", "second"])
     tm.assert_frame_equal(result, expected)
+
+
+@pytest.mark.parametrize(
+    "left_empty, how, exp",
+    [
+        (False, "left", "left"),
+        (False, "right", "empty"),
+        (False, "inner", "empty"),
+        (False, "outer", "left"),
+        (False, "cross", "empty"),
+        (True, "left", "empty"),
+        (True, "right", "right"),
+        (True, "inner", "empty"),
+        (True, "outer", "right"),
+        (True, "cross", "empty"),
+    ],
+)
+def test_join_empty(left_empty, how, exp):
+
+    left = DataFrame({"A": [2, 1], "B": [3, 4]}, dtype="int64").set_index("A")
+    right = DataFrame({"A": [1], "C": [5]}, dtype="int64").set_index("A")
+
+    if left_empty:
+        left = left.head(0)
+    else:
+        right = right.head(0)
+
+    result = left.join(right, how=how)
+
+    if exp == "left":
+        expected = DataFrame({"A": [2, 1], "B": [3, 4], "C": [np.nan, np.nan]})
+        expected = expected.set_index("A")
+    elif exp == "right":
+        expected = DataFrame({"B": [np.nan], "A": [1], "C": [5]})
+        expected = expected.set_index("A")
+    elif exp == "empty":
+        expected = DataFrame(index=Index([]), columns=["B", "C"], dtype="int64")
+        if how != "cross":
+            expected = expected.rename_axis("A")
+
+    tm.assert_frame_equal(result, expected)