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Filter out partially aggregated clusters

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Fixes #889
This commit is contained in:
Javier Goizueta
2018-07-15 22:26:37 +02:00
parent 31feb58e1f
commit 716f983e71
1 changed files with 43 additions and 28 deletions
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lib/cartodb/models/aggregation/aggregation-query.js
+43 -28
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@@ -248,28 +248,58 @@ const gridResolution = ctx => {
return `GREATEST(${256/ctx.res}*CDB_XYZ_Resolution(CDB_ZoomFromScale(!scale_denominator!)), ${minimumResolution})::double precision`;
};
// Each aggregation cell is defined by the cell coordinates Floor(x/res), Floor(y/res),
// i.e. they include the West and South borders but not the East and North ones.
// So, to avoid picking points that don't belong to cells in the tile, given the tile
// limits Xmin, Ymin, Xmax, Ymax (bbox), we should select points that satisfy
// Xmin <= x < Xmax and Ymin <= y < Ymax (with x, y from the_geom_webmercator)
// On the other hand we can efficiently filter spatially (relying on spatial indexing)
// with `the_geom_webmercator && bbox` which is equivalent to
// Xmin <= x <= Xmax and Ymin <= y <= Ymax
// So, in order to be both efficient and accurate we will need to use both
// conditions for spatial filtering.
const spatialFilter = `
(_cdb_query.the_geom_webmercator && _cdb_params.bbox) AND
ST_X(_cdb_query.the_geom_webmercator) >= _cdb_params.xmin AND ST_X(_cdb_query.the_geom_webmercator) < _cdb_params.xmax AND
ST_Y(_cdb_query.the_geom_webmercator) >= _cdb_params.ymin AND ST_Y(_cdb_query.the_geom_webmercator) < _cdb_params.ymax
`;
// Notes:
// * We need to filter spatially using !bbox! to make the queries efficient because
// the filter added by Mapnik (wrapping the query)
// is only applied after the aggregation.
// * This queries are used for rendering and the_geom is omitted in the results for better performance
// * If the MVT extent or tile buffer was 0 or a multiple of the resolution we could use directly
// the bbox for them, but in general we need to find the nearest cell limits inside the bbox.
const sqlParams = (ctx) => `
_cdb_res AS (
SELECT
${gridResolution(ctx)} AS res,
!bbox! AS bbox
),
_cdb_params AS (
SELECT
res,
bbox,
CEIL(ST_XMIN(bbox)/res)*res AS xmin,
FLOOR(ST_XMAX(bbox)/res)*res AS xmax,
CEIL(ST_YMIN(bbox)/res)*res AS ymin,
FLOOR(ST_YMAX(bbox)/res)*res AS ymax
FROM _cdb_res
)
`;
// The special default aggregation includes all the columns of a sample row per grid cell and
// the count (_cdb_feature_count) of the aggregated rows.
const defaultAggregationQueryTemplate = ctx => `
WITH
_cdb_params AS (
SELECT
${gridResolution(ctx)} AS res,
!bbox! AS bbox
),
WITH ${sqlParams(ctx)},
_cdb_clusters AS (
SELECT
MIN(cartodb_id) AS cartodb_id
${dimensionDefs(ctx)}
${aggregateColumnDefs(ctx)}
FROM (${ctx.sourceQuery}) _cdb_query, _cdb_params
WHERE _cdb_query.the_geom_webmercator && _cdb_params.bbox
WHERE ${spatialFilter}
GROUP BY
Floor(ST_X(_cdb_query.the_geom_webmercator)/_cdb_params.res),
Floor(ST_Y(_cdb_query.the_geom_webmercator)/_cdb_params.res)
@@ -284,12 +314,7 @@ const defaultAggregationQueryTemplate = ctx => `
const aggregationQueryTemplates = {
'centroid': ctx => `
WITH
_cdb_params AS (
SELECT
${gridResolution(ctx)} AS res,
!bbox! AS bbox
)
WITH ${sqlParams(ctx)}
SELECT
MIN(_cdb_query.cartodb_id) AS cartodb_id,
ST_SetSRID(
@@ -301,7 +326,7 @@ const aggregationQueryTemplates = {
${dimensionDefs(ctx)}
${aggregateColumnDefs(ctx)}
FROM (${ctx.sourceQuery}) _cdb_query, _cdb_params
WHERE _cdb_query.the_geom_webmercator && _cdb_params.bbox
WHERE ${spatialFilter}
GROUP BY
Floor(ST_X(_cdb_query.the_geom_webmercator)/_cdb_params.res),
Floor(ST_Y(_cdb_query.the_geom_webmercator)/_cdb_params.res)
@@ -310,12 +335,7 @@ const aggregationQueryTemplates = {
`,
'point-grid': ctx => `
WITH
_cdb_params AS (
SELECT
${gridResolution(ctx)} AS res,
!bbox! AS bbox
),
WITH ${sqlParams(ctx)},
_cdb_clusters AS (
SELECT
MIN(_cdb_query.cartodb_id) AS cartodb_id,
@@ -324,7 +344,7 @@ const aggregationQueryTemplates = {
${dimensionDefs(ctx)}
${aggregateColumnDefs(ctx)}
FROM (${ctx.sourceQuery}) _cdb_query, _cdb_params
WHERE the_geom_webmercator && _cdb_params.bbox
WHERE ${spatialFilter}
GROUP BY _cdb_gx, _cdb_gy ${dimensionNames(ctx)}
${havingClause(ctx)}
)
@@ -337,19 +357,14 @@ const aggregationQueryTemplates = {
`,
'point-sample': ctx => `
WITH
_cdb_params AS (
SELECT
${gridResolution(ctx)} AS res,
!bbox! AS bbox
),
WITH ${sqlParams(ctx)},
_cdb_clusters AS (
SELECT
MIN(cartodb_id) AS cartodb_id
${dimensionDefs(ctx)}
${aggregateColumnDefs(ctx)}
FROM (${ctx.sourceQuery}) _cdb_query, _cdb_params
WHERE _cdb_query.the_geom_webmercator && _cdb_params.bbox
WHERE ${spatialFilter}
GROUP BY
Floor(ST_X(_cdb_query.the_geom_webmercator)/_cdb_params.res),
Floor(ST_Y(_cdb_query.the_geom_webmercator)/_cdb_params.res)