Merge pull request #10698 from rouault/ogr_sqlite_median_mode

SQLite SQL dialect: add MEDIAN, PERCENTILE, PERCENTILE_CONT and MODE ordered-set aggregate functions

autotest/ogr/ogr_sqlite.py

@@ -4149,6 +4149,123 @@ def test_ogr_sqlite_stddev():
         assert f.GetField(1) == pytest.approx(0.5**0.5, rel=1e-15)
 
 
+@pytest.mark.parametrize(
+    "input_values,expected_res",
+    [
+        ([], None),
+        ([1], 1),
+        ([2.5, None, 1], 1.75),
+        ([3, 2.2, 1], 2.2),
+        ([1, "invalid"], None),
+    ],
+)
+def test_ogr_sqlite_median(input_values, expected_res):
+    """Test MEDIAN"""
+
+    ds = ogr.Open(":memory:", update=1)
+    ds.ExecuteSQL("CREATE TABLE test(v)")
+    for v in input_values:
+        ds.ExecuteSQL(
+            "INSERT INTO test VALUES (%s)"
+            % (
+                "NULL"
+                if v is None
+                else ("'" + v + "'")
+                if isinstance(v, str)
+                else str(v)
+            )
+        )
+    if expected_res is None and input_values:
+        with pytest.raises(Exception), gdaltest.error_handler():
+            with ds.ExecuteSQL("SELECT MEDIAN(v) FROM test"):
+                pass
+    else:
+        with ds.ExecuteSQL("SELECT MEDIAN(v) FROM test") as sql_lyr:
+            f = sql_lyr.GetNextFeature()
+            assert f.GetField(0) == pytest.approx(expected_res)
+        with ds.ExecuteSQL("SELECT PERCENTILE(v, 50) FROM test") as sql_lyr:
+            f = sql_lyr.GetNextFeature()
+            assert f.GetField(0) == pytest.approx(expected_res)
+        with ds.ExecuteSQL("SELECT PERCENTILE_CONT(v, 0.5) FROM test") as sql_lyr:
+            f = sql_lyr.GetNextFeature()
+            assert f.GetField(0) == pytest.approx(expected_res)
+
+
+def test_ogr_sqlite_percentile():
+    """Test PERCENTILE"""
+
+    ds = ogr.Open(":memory:", update=1)
+    ds.ExecuteSQL("CREATE TABLE test(v)")
+    ds.ExecuteSQL("INSERT INTO test VALUES (5),(6),(4),(7),(3),(8),(2),(9),(1),(10)")
+
+    with pytest.raises(Exception), gdaltest.error_handler():
+        with ds.ExecuteSQL("SELECT PERCENTILE(v, 'invalid') FROM test"):
+            pass
+    with pytest.raises(Exception), gdaltest.error_handler():
+        with ds.ExecuteSQL("SELECT PERCENTILE(v, -0.1) FROM test"):
+            pass
+    with pytest.raises(Exception), gdaltest.error_handler():
+        with ds.ExecuteSQL("SELECT PERCENTILE(v, 100.1) FROM test"):
+            pass
+    with pytest.raises(Exception), gdaltest.error_handler():
+        with ds.ExecuteSQL("SELECT PERCENTILE(v, v) FROM test"):
+            pass
+
+
+def test_ogr_sqlite_percentile_cont():
+    """Test PERCENTILE_CONT"""
+
+    ds = ogr.Open(":memory:", update=1)
+    ds.ExecuteSQL("CREATE TABLE test(v)")
+    ds.ExecuteSQL("INSERT INTO test VALUES (5),(6),(4),(7),(3),(8),(2),(9),(1),(10)")
+
+    with pytest.raises(Exception), gdaltest.error_handler():
+        with ds.ExecuteSQL("SELECT PERCENTILE_CONT(v, 'invalid') FROM test"):
+            pass
+    with pytest.raises(Exception), gdaltest.error_handler():
+        with ds.ExecuteSQL("SELECT PERCENTILE_CONT(v, -0.1) FROM test"):
+            pass
+    with pytest.raises(Exception), gdaltest.error_handler():
+        with ds.ExecuteSQL("SELECT PERCENTILE_CONT(v, 1.1) FROM test"):
+            pass
+
+
+@pytest.mark.parametrize(
+    "input_values,expected_res",
+    [
+        ([], None),
+        ([1, 2, None, 3, 2], 2),
+        (["foo", "bar", "baz", "bar"], "bar"),
+        ([1, "foo", 2, "foo", "bar"], "foo"),
+        ([1, "foo", 2, "foo", 1], "foo"),
+    ],
+)
+def test_ogr_sqlite_mode(input_values, expected_res):
+    """Test MODE"""
+
+    ds = ogr.Open(":memory:", update=1)
+    ds.ExecuteSQL("CREATE TABLE test(v)")
+    for v in input_values:
+        ds.ExecuteSQL(
+            "INSERT INTO test VALUES (%s)"
+            % (
+                "NULL"
+                if v is None
+                else ("'" + v + "'")
+                if isinstance(v, str)
+                else str(v)
+            )
+        )
+    if expected_res is None and input_values:
+        with pytest.raises(Exception), gdaltest.error_handler():
+            with ds.ExecuteSQL("SELECT MODE(v) FROM test"):
+                pass
+    else:
+        with ds.ExecuteSQL("SELECT MODE(v) FROM test") as sql_lyr:
+            f = sql_lyr.GetNextFeature()
+            assert f.GetField(0) == expected_res
+
+
 def test_ogr_sqlite_run_deferred_actions_before_start_transaction():
 
     ds = ogr.Open(":memory:", update=1)

doc/source/user/sql_sqlite_dialect.rst

@@ -208,8 +208,18 @@ Statistics functions
 In addition to standard COUNT(), SUM(), AVG(), MIN(), MAX(), the following
 aggregate functions are available:
 
-- STDDEV_POP: (GDAL >= 3.10) numerical population standard deviation.
-- STDDEV_SAMP: (GDAL >= 3.10) numerical `sample standard deviation <https://en.wikipedia.org/wiki/Standard_deviation#Sample_standard_deviation>`__
+- ``STDDEV_POP(numeric_value)``: (GDAL >= 3.10) numerical population standard deviation.
+- ``STDDEV_SAMP(numeric_value)``: (GDAL >= 3.10) numerical `sample standard deviation <https://en.wikipedia.org/wiki/Standard_deviation#Sample_standard_deviation>`__
+
+Ordered-set aggregate functions
++++++++++++++++++++++++++++++++
+
+The following aggregate functions are available. Note that they require to allocate an amount of memory proportional to the number of selected rows (for ``MEDIAN``, ``PERCENTILE`` and ``PERCENTILE_CONT``) or to the number of values (for ``MODE``).
+
+- ``MEDIAN(numeric_value)``: (GDAL >= 3.10) (continuous) median (equivalent to ``PERCENTILE(numeric_value, 50)``). NULL values are ignored.
+- ``PERCENTILE(numeric_value, percentage)``: (GDAL >= 3.10) (continuous) percentile, with percentage between 0 and 100 (equivalent to ``PERCENTILE_CONT(numeric_value, percentage / 100)``). NULL values are ignored.
+- ``PERCENTILE_CONT(numeric_value, fraction)``: (GDAL >= 3.10) (continuous) percentile, with fraction between 0 and 1. NULL values are ignored.
+- ``MODE(value)``: (GDAL >= 3.10): mode, i.e. most frequent input value (strings and numeric values are supported), arbitrarily choosing the first one if there are multiple equally-frequent results. NULL values are ignored.
 
 Spatialite SQL functions
 ++++++++++++++++++++++++