在 DISTINCT ON 之后应用过滤器

最后有一个脚本将完全创建模式并用示例数据填充它。

架构

考虑这两个表：

多边形表：

CREATE TABLE my_polygon (
    my_polygon_id SERIAL PRIMARY KEY,
    common_id INTEGER NOT NULL,
    value1 NUMERIC NOT NULL,
    value2 NUMERIC NOT NULL,
    value3 NUMERIC NOT NULL,
    geom GEOMETRY(Polygon) NOT NULL
)
;

CREATE INDEX ON my_polygon (common_id);
CREATE INDEX ON my_polygon USING GIST (common_id, geom);

多边形内包含的点表：

CREATE TABLE my_point (
    my_point_id SERIAL PRIMARY KEY,
    common_id INTEGER NOT NULL,
    pointvalue NUMERIC NOT NULL,
    geom GEOMETRY(Point) NOT NULL
);

CREATE INDEX ON my_point (common_id);
CREATE INDEX ON my_point USING GIST (common_id, geom);

我使用几何的事实与这里的问题并不严格相关。但是，我认为这使我尝试做的事情的动机更加清晰。

问题查询

问题是多边形之间有非常微小的、微不足道的重叠。（尝试清理它们确实不是一种选择。重叠来自生成它们时的某种浮点错误，尽可能接近。）但是有些点可能落在这些微小的重叠内，当我JOIN他们时会产生两行基于遏制。但实际上，每个点应该只与一个多边形相关联。当一个确实属于其中两个时，它最终与哪一个关联并不重要，因此可以让查询只选择一个，如下所示：

SELECT DISTINCT ON (my_point.my_point_id)
    my_polygon.*,
    my_point.my_point_id,
    my_point.pointvalue,
    my_point.geom AS pointgeom
FROM my_polygon
JOIN my_point ON my_point.common_id = my_polygon.common_id AND ST_Contains(my_polygon.geom, my_point.geom)
WHERE my_polygon.common_id = 1
ORDER BY my_point.my_point_id, my_polygon.my_polygon_id

和上面的查询一样，我通常想SELECT基于common_id. 此查询执行良好。它的查询计划如下所示：

但是，这是我在许多不同查询中需要的逻辑，所以我想把它放在一个视图中。结果是，就查询规划器而言，查询看起来像这样：

SELECT *
FROM (
    SELECT DISTINCT ON (my_point.my_point_id)
        my_polygon.*,
        my_point.my_point_id,
        my_point.pointvalue,
        my_point.geom AS pointgeom
    FROM my_polygon
    JOIN my_point ON my_point.common_id = my_polygon.common_id AND ST_Contains(my_polygon.geom, my_point.geom)
    ORDER BY my_point.my_point_id, my_polygon.my_polygon_id
) point_with_polygon
WHERE common_id = 1

结果是现在 PostgreSQL在执行common_id 之后进行过滤DISTINCT ON，这意味着它必须对JOIN两个表的整体进行过滤。这是它的查询计划：

如何允许 PostgreSQL 将过滤器下推到查询的早期部分，并且仍然将一般查询放在视图中？

我现在卡在 PG 9.3 上，但升级到 9.5 可能是一种选择。

架构和示例数据脚本

需要 PostGIS。（这就是为什么没有 SQL Fiddle 的原因。）

CREATE EXTENSION IF NOT EXISTS postgis;
CREATE EXTENSION IF NOT EXISTS btree_gist;

-- DROP FUNCTION ST_GeneratePoints(geometry, numeric);
DO $doblock$
BEGIN
    IF NOT EXISTS(SELECT * FROM pg_proc WHERE UPPER(proname) = UPPER('ST_GeneratePoints')) THEN
        -- Create naive ST_GeneratePoints if version of PostGIS is not new enough
        CREATE FUNCTION ST_GeneratePoints(g geometry, npoints numeric)
            RETURNS geometry
            VOLATILE
            RETURNS NULL ON NULL INPUT
            LANGUAGE plpgsql
            AS $$
            DECLARE
                num_to_generate INTEGER := npoints::INTEGER;
                adjustment CONSTANT FLOAT := 0.00000000001;
                x_min FLOAT := ST_XMin(g) + adjustment;
                x_max FLOAT := ST_XMax(g) - adjustment;
                y_min FLOAT := ST_YMin(g) + adjustment;
                y_max FLOAT := ST_YMax(g) - adjustment;
                temp_result GEOMETRY[];
                result_array GEOMETRY[] := ARRAY[]::GEOMETRY[];
            BEGIN
                IF ST_IsEmpty(g) THEN
                    RAISE EXCEPTION 'Cannot generate points inside an empty geometry';
                END IF;

                IF ST_Dimension(g) < 2 THEN
                    RAISE EXCEPTION 'Only polygons supported';
                END IF;

                -- Reduce number of loops to reduce slow array_cat calls
                WHILE num_to_generate > 0 LOOP
                    SELECT ARRAY_AGG(contained.point) INTO temp_result
                    FROM (
                        SELECT point
                        FROM (
                            SELECT ST_MakePoint(
                                x_min + random() * (x_max - x_min),
                                y_min + random() * (y_max - y_min)
                            ) point
                            -- Generate extras to reduce number of loops
                            --
                            -- Each point has a probability of  ST_Area(g) / ST_Area(ST_Envelope(g))  to fall within the polygon.
                            -- So on average, we expect ST_Area(g) / ST_Area(ST_Envelope(g)) of the points generated to fall within.
                            -- Generating  ST_Area(ST_Envelope(g)) / ST_Area(g) * num_to_generate  points means that on average, we'll
                            -- get
                            --
                            --     ST_Area(g) / ST_Area(ST_Envelope(g)) * ST_Area(ST_Envelope(g)) / ST_Area(g) * num_to_generate
                            --      = num_to_generate
                            --
                            -- points within the polygon. (Notice the numerators and denominators cancel out.) This means we'll 
                            -- only run one loop about half the time without generating an excessive number of points.
                            --
                            -- Generate at least 20 to avoid a lot of loops for small numbers, though.
                            FROM generate_series(1, GREATEST(20, CEIL(ST_Area(ST_Envelope(g)) / ST_Area(g) * num_to_generate)::INTEGER))
                        ) candidate
                        WHERE ST_Contains(g, candidate.point)
                        -- Filter out extras if we have too many matches
                        LIMIT num_to_generate
                    ) contained
                    ;
                    IF ARRAY_LENGTH(temp_result, 1) > 0 THEN
                        result_array := array_cat(result_array, temp_result);
                        num_to_generate := npoints - COALESCE(ARRAY_LENGTH(result_array, 1), 0);
                    END IF;
                END LOOP;
                RETURN (SELECT ST_Union(point) FROM UNNEST(result_array) result (point));
            END;
            $$;
        RAISE NOTICE 'Created ST_GeneratePoints';
    ELSE
        RAISE NOTICE 'ST_GeneratePoints exists';
    END IF;
END
$doblock$
;

DROP TABLE IF EXISTS my_polygon;

CREATE TABLE my_polygon (
    my_polygon_id SERIAL PRIMARY KEY,
    common_id INTEGER NOT NULL,
    value1 NUMERIC NOT NULL,
    value2 NUMERIC NOT NULL,
    value3 NUMERIC NOT NULL,
    geom GEOMETRY(Polygon) NOT NULL
)
;

CREATE INDEX ON my_polygon (common_id);
CREATE INDEX ON my_polygon USING GIST (common_id, geom);


WITH common AS (
    SELECT
        common_id,
        random() * 5000 AS common_x_translate,
        random() * 5000 AS common_y_translate
    FROM (
        SELECT TRUNC(random() * 1000) + 1 AS common_id
        FROM generate_series(1, 100)
        UNION 
        SELECT 1
    ) a
),
geom_set_with_small_overlaps AS (
    SELECT
        ST_MakeEnvelope(
            x.translate, 
            y.translate, 
            x.translate + 1.1, 
            y.translate + 1.1
        ) AS geom
    FROM
        generate_series(0, 9) x (translate),
        generate_series(0, 9) y (translate)
)
INSERT INTO my_polygon (common_id, value1, value2, value3, geom)
SELECT
    common_id,
    random() * 100,
    random() * 100,
    random() * 100,
    ST_Translate(geom, common_x_translate, common_y_translate)
FROM common, geom_set_with_small_overlaps
;

DROP TABLE IF EXISTS my_point;

CREATE TABLE my_point (
    my_point_id SERIAL PRIMARY KEY,
    common_id INTEGER NOT NULL,
    pointvalue NUMERIC NOT NULL,
    geom GEOMETRY(Point) NOT NULL
);

INSERT INTO my_point (common_id, pointvalue, geom)
SELECT
    common_id,
    random() * 100,
    (ST_Dump(ST_GeneratePoints(extent, FLOOR(5000 + random() * 15000)::NUMERIC))).geom
FROM (
    SELECT
        common_id,
        -- Small negative buffer prevents lying on the outer edge
        ST_Buffer(ST_Extent(geom), - 0.0001) AS extent
    FROM my_polygon
    GROUP BY common_id
) common
UNION ALL
SELECT
    common_id,
    random() * 100,
    (ST_Dump(ST_GeneratePoints(intersection, TRUNC(random() * 5)::NUMERIC))).geom
FROM (
    SELECT
        p1.common_id,
        p1.my_polygon_id AS id1,
        p2.my_polygon_id AS id2,
        ST_Intersection(p1.geom, p2.geom) AS intersection
    FROM my_polygon p1
    JOIN my_polygon p2 ON (
        p1.my_polygon_id < p2.my_polygon_id AND
        p1.common_id = p2.common_id AND
        ST_Intersects(p1.geom, p2.geom)
    )
) a
;

CREATE INDEX ON my_point (common_id);
CREATE INDEX ON my_point USING GIST (common_id, geom);

你可能想VACUUM ANALYZE在那之后。

以文本形式查询计划

WHERE子句内（表现良好）：

Unique  (cost=1195.74..1207.74 rows=2400 width=216)
  ->  Sort  (cost=1195.74..1201.74 rows=2400 width=216)
        Sort Key: my_point.my_point_id, my_polygon.my_polygon_id
        ->  Nested Loop  (cost=5.34..1060.99 rows=2400 width=216)
              ->  Bitmap Heap Scan on my_polygon  (cost=4.93..191.74 rows=100 width=164)
                    Recheck Cond: (common_id = 1)
                    ->  Bitmap Index Scan on my_polygon_common_id_geom_idx  (cost=0.00..4.90 rows=100 width=0)
                          Index Cond: (common_id = 1)
              ->  Index Scan using my_point_common_id_geom_idx on my_point  (cost=0.41..8.68 rows=1 width=52)
                    Index Cond: ((common_id = 1) AND (my_polygon.geom && geom))
                    Filter: _st_contains(my_polygon.geom, geom)

WHERE子句外（表现不佳）：

Subquery Scan on a  (cost=209447.85..215842.18 rows=1827 width=212)
  Filter: (a.common_id = 1)
  ->  Unique  (cost=209447.85..211274.80 rows=365390 width=212)
        ->  Sort  (cost=209447.85..210361.33 rows=365390 width=212)
              Sort Key: my_point.my_point_id, my_polygon.my_polygon_id
              ->  Nested Loop  (cost=0.41..63285.00 rows=365390 width=212)
                    ->  Seq Scan on my_polygon  (cost=0.00..338.00 rows=9800 width=164)
                    ->  Index Scan using my_point_common_id_geom_idx on my_point  (cost=0.41..6.41 rows=1 width=52)
                          Index Cond: ((common_id = my_polygon.common_id) AND (my_polygon.geom && geom))
                          Filter: _st_contains(my_polygon.geom, geom)