tiler
ADVANCED
We currently provide procedures to create the following kind of tilesets:
- Spatial index tiles (aggregates spatial indexes into tiles at specific resolutions)
- Geometry-based MVT tiles of two types:
- simple tilesets to visualize features individually
- aggregation tilesets to generate aggregated point visualizations
Visit the Tilesets section to learn more about tileset types and which procedures to use in each case.
CREATE_TILESET(input, output_table, options)
Description
Creates a simple tileset. It differs from
CREATE_SIMPLE_TILESET
in that the procedure performs a previous analysis in order to find automatically the right options for the tileset. It is done by extracting all the properties to be included within the tileset and sampling the data in order to avoid BigQuery limitations. Therefore, only input
and output_table
are mandatory and options
can be set to NULL
.input
:STRING
that can either be a quoted qualified table name (e.g.`project-id.dataset-id.table-name`
) or a full query contained by parentheses (e.g.(SELECT * FROM `project-id.dataset-id.table-name`)
).output_table
: Where the resulting table will be stored. It must be aSTRING
of the form`project-id.dataset-id.table-name`
. Theproject-id
can be omitted (in which case the default one will be used). The dataset must exist and the caller needs to have permissions to create a new table on it. The process will fail if the target table already exists.options
:STRUCT<name STRING, description STRING,legend STRING, zoom_min INT64, zoom_max INT64, geom_column_name STRING, zoom_min_column STRING, zoom_max_column STRING, max_tile_size_kb INT64, tile_feature_order STRING, drop_duplicates BOOL, extra_metadata STRING>|NULL
containing the different options. Valid options are described in the table below.
Option | Description |
---|---|
name | |
description | |
legend | |
zoom_min | Default: 0 for POINTS datasets and 2 for POLYGON/LINESTRING datasets. A NUMBER that defines the minimum zoom level for tiles. Any zoom level under this level won't be generated. |
zoom_max | Default: 12 . A NUMBER that defines the maximum zoom level for tiles. Any zoom level over this level won't be generated. |
geom_column_name | Default: "geom" . A STRING that contains the name of the geography column that will be used. It must be of type GEOGRAPHY . |
zoom_min_column | Default: NULL . It is the column that each row could have to modify its starting zoom. It can be NULL (then zoom_min will be used). It must be a positive number between zoom_min and zoom_max . |
zoom_max_column | Default: NULL . It is the column that each row could have to modify its end zoom level. It can be NULL (then zoom_max will be used). It must be a positive number between zoom_min and zoom_max . |
max_tile_size_kb | Default: 512 . Maximum allowed: 6144 . A NUMBER setting the approximate maximum size for a tile in kilobytes. For every zoom level, a consistent fraction of features will be dropped in every tile to make sure all generated tiles are below this maximum. |
tile_feature_order | Default: NULL . A STRING defining the order in which properties are added to a tile. This expects the SQL ORDER BY keyword definition, such as "aggregated_total DESC" , the "ORDER BY" part isn't necessary. Note that in aggregation tilesets you can only use columns defined as properties, but in simple feature tilesets you can use any source column no matter if it's included in the tile as property or not. This is an expensive operation, so it's recommended to only use it when necessary. If no order is provided, a custom dropping depending on the geometry type is performed. In case of POINT geometries, features are dropped randomly. In case of POLYGON geometries the features are added ordered by their area, while for LINESTRING geometries the criteria is the feature length. |
drop_duplicates | Default: false . A BOOLEAN to drop duplicate features in a tile. This will drop only exact matches (both the geometry and the properties are exactly equal). As this requires sorting the properties, which is expensive, it should only be used when necessary. |
extra_metadata | Default: {}. A JSON object to specify the custom metadata of the tileset. |
tip
Any option left as
NULL
will take its default value. This also applies for geometry type dependant options such as zoom_min
or tile_feature_order
.tip
A
fraction_dropped_per_zoom
property will be included in the TileJSON, containing an estimate of the percentage of the features that have been dropped per zoom level as a result of applying the drop_fraction_as_needed
strategy. Please bear in mind that the exact percentages can be up to 5% higher.warning
It should be taken into account that
CREATE_TILESET
will not be executed for any level that reaches more than 10 millions tiles. This threshold is set in order to avoid some BigQuery limitations. This could occur if the input dataset is very sparse or zoom_max
is quite large.warning
There are some cases where flat-rates is the only option to create a tileset. Some tables containing huge geographies might trigger a
Query exceeded resource limits
error because of the high CPU usage.Examples
carto-un
carto-un-eu
manual
CALL `carto-un`.carto.CREATE_TILESET(
R'''(
SELECT geom, type
FROM `carto-do-public-data.natural_earth.geography_glo_roads_410`
)
''',
R'''`cartobq.maps.natural_earth_roads`''',
NULL
);
CALL `carto-un-eu`.carto.CREATE_TILESET(
R'''(
SELECT geom, type
FROM `carto-do-public-data.natural_earth.geography_glo_roads_410`
)
''',
R'''`cartobq.maps.natural_earth_roads`''',
NULL
);
CALL carto.CREATE_TILESET(
R'''(
SELECT geom, type
FROM `carto-do-public-data.natural_earth.geography_glo_roads_410`
)
''',
R'''`cartobq.maps.natural_earth_roads`''',
NULL
);
If any of the options introduced above are required, the remaining fields should also be provided or set to
NULL
. Here is an example of a valid structure for the options
parameter (the field alias can be ignored):carto-un
carto-un-eu
manual
CALL `carto-un`.carto.CREATE_TILESET(
R'''(
SELECT geom, type
FROM `carto-do-public-data.natural_earth.geography_glo_roads_410`
)
''',
R'''`cartobq.maps.natural_earth_roads`''',
STRUCT(
"Tileset name" AS name,
"Tileset description" AS description,
NULL AS legend,
0 AS zoom_min,
10 AS zoom_max,
"geom" AS geom_column_name,
NULL AS zoom_min_column,
NULL AS zoom_max_column,
1024 AS max_tile_size_kb,
"RAND() DESC" AS tile_feature_order,
true AS drop_duplicates,
R'''
"custom_metadata": {
"version": "1.0.0",
"layer": "layer1"
}
''' AS extra_metadata
)
);
CALL `carto-un-eu`.carto.CREATE_TILESET(
R'''(
SELECT geom, type
FROM `carto-do-public-data.natural_earth.geography_glo_roads_410`
)
''',
R'''`cartobq.maps.natural_earth_roads`''',
STRUCT(
"Tileset name" AS name,
"Tileset description" AS description,
NULL AS legend,
0 AS zoom_min,
10 AS zoom_max,
"geom" AS geom_column_name,
NULL AS zoom_min_column,
NULL AS zoom_max_column,
1024 AS max_tile_size_kb,
"RAND() DESC" AS tile_feature_order,
true AS drop_duplicates,
R'''
"custom_metadata": {
"version": "1.0.0",
"layer": "layer1"
}
''' AS extra_metadata
)
);
CALL carto.CREATE_TILESET(
R'''(
SELECT geom, type
FROM `carto-do-public-data.natural_earth.geography_glo_roads_410`
)
''',
R'''`cartobq.maps.natural_earth_roads`''',
STRUCT(
"Tileset name" AS name,
"Tileset description" AS description,
NULL AS legend,
0 AS zoom_min,
10 AS zoom_max,
"geom" AS geom_column_name,
NULL AS zoom_min_column,
NULL AS zoom_max_column,
1024 AS max_tile_size_kb,
"RAND() DESC" AS tile_feature_order,
true AS drop_duplicates,
R'''
"custom_metadata": {
"version": "1.0.0",
"layer": "layer1"
}
''' AS extra_metadata
)
);
warning
In case of
input
is set as a query, it should be taken into account that CTEs are not allowed. Also, the query should be as simple as possible in order to avoid BigQuery limitations about the complexity of the final query.Additional examples
CREATE_POINT_AGGREGATION_TILESET(input, output_table, options)
Description
Generates a point aggregation tileset.
input
:STRING
that can either be a quoted qualified table name (e.g.project-id.dataset-id.table-name
) or a full query wrapped in parentheses (e.g.(Select * FROM `project-id.dataset-id.table-name`)
).output_table
: Where the resulting table will be stored. It must be aSTRING
of the formproject-id.dataset-id.table-name
. Theproject-id
can be omitted (in which case the default one will be used). The dataset must exist and the caller needs to have permissions to create a new table on it. The process will fail if the target table already exists.options
:STRING
containing a valid JSON with the different options. Valid options are described the table below.
Option | Description |
---|---|
geom_column | Default: "geom" . A STRING that marks the name of the geography column that will be used. It must be of type GEOGRAPHY . |
zoom_min | Default: 0 . A NUMBER that defines the minimum zoom level for tiles. Any zoom level under this level won't be generated. |
zoom_max | Default: 12 . A NUMBER that defines the maximum zoom level for tiles. Any zoom level over this level won't be generated. |
zoom_min_column | Default: NULL . It is the column that each row could have to modify its starting zoom. It can be NULL (then zoom_min will be used). When provided, if its value is greater than zoom_min , it will take precedence and be used as the actual minimum. |
zoom_max_column | Default: NULL . It is the column that each row could have to modify its end zoom level. It can be NULL (then zoom_max will be used). When provided, if its value is lower than zoom_max , it will be taken as the real maximum zoom level. |
target_partitions | Default: 3999 . Max: 3999 . A NUMBER that defines the maximum number of partitions to be used in the target table. The partition system, which uses a column named carto_partition , divides the available partitions first by zoom level and spatial locality to minimize the cost of tile read requests in web maps. Beware that this does not necessarily mean that all the partitions will be used, as a sparse dataset will leave some of these partitions unused. If you are using BigQuery BI Engine consider that it supports a maximum of 500 partitions per table. |
target_tilestats | Default: true . A BOOLEAN to determine whether to include statistics of the properties in the metadata. These statistics are based on mapbox-tilestats and depend on the property type:
For aggregation tilesets, these statistics refer to the cells at the maximum zoom generated. |
tile_extent | Default: 4096 . A NUMBER defining the extent of the tile in integer coordinates as defined by the MVT spec. |
tile_buffer | Default: 0 (disabled). A NUMBER defining the additional buffer added around the tiles in extent units, which is useful to facilitate geometry stitching across tiles in the renderers. In aggregation tilesets, this property is currently not available and always 0 as no geometries go across tile boundaries. |
max_tile_size_kb | Default: 1024 . A NUMBER specifying the approximate maximum size for a tile. |
max_tile_size_strategy | Default: "throw_error" . A STRING that determines what to do when the maximum size of a tile is reached while it is still processing data. There are three options available:
|
max_tile_features | Default: 0 (disabled). A NUMBER that sets the maximum number of features a tile might contain. This limit is applied before max_tile_size_kb , i.e., the tiler will first drop as many features as needed to keep this amount, and then continue with the size limits (if required). To configure in which order features are kept, use in conjunction with tile_feature_order . |
tile_feature_order | Default: "" (disabled). A STRING defining the order in which properties are added to a tile. This expects the SQL ORDER BY keyword definition, such as "aggregated_total DESC", the "ORDER BY" part isn't necessary. Note that in aggregation tilesets you can only use columns defined as properties, but in simple feature tilesets you can use any source column no matter if it's included in the tile as property or not. This is an expensive operation, so it's recommended to only use it when necessary. |
aggregation_type | Default: "quadgrid" . A STRING defining what kind of spatial aggregation is to be used. Currently only quadgrid is supported. |
aggregation_resolution | Default: 6 . A NUMBER that specifies the resolution of the spatial aggregation.
For quadgrid the aggregation for zoom z is done at z + resolution level . For example, with resolution 6 , the z0 tile will be divided into cells that match the z6 tiles, or the cells contained in the z10 tile will be the boundaries of the z16 tiles within them. In other words, each tile is subdivided into 4^resolution cells.
Note that adding more granularity necessarily means heavier tiles which take longer to be transmitted and processed in the final client, and you are more likely to hit the internal memory limits. |
aggregation_placement | Default: "cell-centroid" . A STRING that defines what type of geometry will be used for the cells generated in the aggregation. For a quadgrid aggregation, there are currently four options:
|
metadata | Default: {} . A JSON object to specify the associated metadata of the tileset. Use this to set the name, description and legend to be included in the TileJSON. Other fields will be included in the object extra_metadata. |
properties | Default: {} . A JSON object that defines the properties that will be included associated with each cell feature. Each property is defined by its name, type (Number, Boolean, String, etc.) and formula to be applied to the values of the points that fall under the cell. This formula can be any SQL formula that uses an aggregate function supported by BigQuery and returns the expected type. Note that every property different from Number will be casted to String. |
warning
There are some cases where flat-rates is the only option to create a tileset. Some tables containing huge geographies might trigger a
Query exceeded resource limits
error because of the high CPU usage.Examples
carto-un
carto-un-eu
manual
CALL `carto-un`.carto.CREATE_POINT_AGGREGATION_TILESET(
R'''(
SELECT ST_CENTROID(geometry) as geom
FROM `bigquery-public-data.geo_openstreetmap.planet_features`
WHERE 'building' IN (SELECT key FROM UNNEST(all_tags)) AND geometry IS NOT NULL
)''',
'`your-project.your-dataset.osm_buildings_14_7`',
R'''
{
"zoom_min": 0,
"zoom_max": 14,
"aggregation_resolution": 7,
"aggregation_placement": "cell-centroid",
"properties": {
"aggregated_total": {
"formula": "COUNT(*)",
"type": "Number"
}
}
}
''');
CALL `carto-un-eu`.carto.CREATE_POINT_AGGREGATION_TILESET(
R'''(
SELECT ST_CENTROID(geometry) as geom
FROM `bigquery-public-data.geo_openstreetmap.planet_features`
WHERE 'building' IN (SELECT key FROM UNNEST(all_tags)) AND geometry IS NOT NULL
)''',
'`your-project.your-dataset.osm_buildings_14_7`',
R'''
{
"zoom_min": 0,
"zoom_max": 14,
"aggregation_resolution": 7,
"aggregation_placement": "cell-centroid",
"properties": {
"aggregated_total": {
"formula": "COUNT(*)",
"type": "Number"
}
}
}
''');
CALL carto.CREATE_POINT_AGGREGATION_TILESET(
R'''(
SELECT ST_CENTROID(geometry) as geom
FROM `bigquery-public-data.geo_openstreetmap.planet_features`
WHERE 'building' IN (SELECT key FROM UNNEST(all_tags)) AND geometry IS NOT NULL
)''',
'`your-project.your-dataset.osm_buildings_14_7`',
R'''
{
"zoom_min": 0,
"zoom_max": 14,
"aggregation_resolution": 7,
"aggregation_placement": "cell-centroid",
"properties": {
"aggregated_total": {
"formula": "COUNT(*)",
"type": "Number"
}
}
}
''');
Here is an example of valid
properties
for a Point Aggregation Tileset:carto-un
carto-un-eu
manual
R'''
{
"properties": {
"new_column_name": {
"formula": "COUNT(*)",
"type": "Number"
},
"most_common_ethnicity": {
"formula": "APPROX_TOP_COUNT(ethnicity, 1)[OFFSET(0)].value",
"type": "String"
},
"has_other_ethnicities": {
"formula": "COUNTIF(ethnicity = 'other_race') > 0",
"type": "Boolean"
},
"name": {
"formula": "IF(COUNT(*) <= 1, ANY_VALUE(name), NULL)",
"type": "String"
},
"address": {
"formula": "IF(COUNT(*) <= 1, ANY_VALUE(address), NULL)",
"type": "String"
}
}
}
'''
R'''
{
"properties": {
"new_column_name": {
"formula": "COUNT(*)",
"type": "Number"
},
"most_common_ethnicity": {
"formula": "APPROX_TOP_COUNT(ethnicity, 1)[OFFSET(0)].value",
"type": "String"
},
"has_other_ethnicities": {
"formula": "COUNTIF(ethnicity = 'other_race') > 0",
"type": "Boolean"
},
"name": {
"formula": "IF(COUNT(*) <= 1, ANY_VALUE(name), NULL)",
"type": "String"
},
"address": {
"formula": "IF(COUNT(*) <= 1, ANY_VALUE(address), NULL)",
"type": "String"
}
}
}
'''
R'''
{
"properties": {
"new_column_name": {
"formula": "COUNT(*)",
"type": "Number"
},
"most_common_ethnicity": {
"formula": "APPROX_TOP_COUNT(ethnicity, 1)[OFFSET(0)].value",
"type": "String"
},
"has_other_ethnicities": {
"formula": "COUNTIF(ethnicity = 'other_race') > 0",
"type": "Boolean"
},
"name": {
"formula": "IF(COUNT(*) <= 1, ANY_VALUE(name), NULL)",
"type": "String"
},
"address": {
"formula": "IF(COUNT(*) <= 1, ANY_VALUE(address), NULL)",
"type": "String"
}
}
}
'''
In the example above, for all features we would get a property
"new_column_name"
with the number of points that fall in it, the "most_common_ethnicity"
of those rows and whether there are points whose ethnicity value matches one specific value ("has_other_ethnicities"
). In addition to this, when there is only one point that belongs to this property (and only in that case) we will also get the column values from the source data: "name"
and "address"
.Additional examples
CREATE_SPATIAL_INDEX_TILESET(input, output_table, options)
Description
Creates a tileset that uses a spatial index (H3 and QUADBIN are currently supported), aggregating data from an input table that uses that same spatial index.
Aggregated data is computed for all levels between
resolution_min
and resolution_max
. For each resolution level, all tiles for the area covered by the source table are added, with data aggregated at level resolution + aggregation resolution
.input
:STRING
that can either be a quoted qualified table name (e.g.`project-id.dataset-id.table-name`
) or a full query contained by parentheses (e.g.(SELECT * FROM `project-id.dataset-id.table-name`)
).output_table
: Where the resulting table will be stored. It must be aSTRING
of the form`project-id.dataset-id.table-name`
. Theproject-id
can be omitted (in which case the default one will be used). The dataset must exist and the caller needs to have permissions to create a new table on it. The process will fail if the target table already exists.options
:STRING
containing a valid JSON with the different options. Valid options are described the table below.
Option | Description |
---|---|
resolution_min | Default: 0 . A NUMBER that defines the minimum resolution level for tiles. Any resolution level under this level won't be generated. |
resolution_max | Default: 12 for QUADBIN tilesets, 6 for H3 tilesets. A NUMBER that defines the maximum resolution level for tiles. Any resolution level over this level won't be generated. |
spatial_index_column | A STRING in the format spatial_index_type:column_name , with spatial_index_type being the type of spatial index used in the input table (can be quadbin or h3 ), and column_name being the name of the column in that input table that contains the tile ids. Notice that the spatial index name is case-sensitive. The type of spatial index also defines the type used in the output table, which will be QUADBIN (for spatial index type quadbin ) or H3 (for spatial index type h3 ). |
resolution | A NUMBER defining the resolution of the tiles in the input table. |
aggregation_resolution | Defaults: 6 for QUADBIN tilesets, 4 for H3 tilesets. A NUMBER defining the resolution to use when aggregating data at each resolution level. For a given resolution , data is aggregated at resolution_level + aggregation resolution . |
properties | A JSON object containing the aggregated properties to add to each tile in the output table. It cannot be empty, since at least one property is needed for aggregating the original values |
metadata | Default: {} . A JSON object to specify the associated metadata of the tileset. Use this to set the name, description and legend to be included in the TileJSON. Other fields will be included in the object extra_metadata. |
tip
Any option left as
NULL
will take its default value if available.warning
There are some cases where flat-rates is the only option to create a tileset. Some tables containing huge geographies might trigger a
Query exceeded resource limits
error because of the high CPU usage.Examples
carto-un
carto-un-eu
manual
CALL `carto-un`.carto.CREATE_SPATIAL_INDEX_TILESET(
'YOUR_DATABASE.YOUR_SCHEMA.INPUT_TABLE_QUADBIN_LEVEL14',
'YOUR_DATABASE.YOUR_SCHEMA.OUTPUT_TILESET_QUADBIN_LEVEL14',
R'''{
"spatial_index_column": "quadbin:index",
"resolution": 14,
"resolution_min": 0,
"resolution_max": 8,
"aggregation_resolution": 6,
"properties": {
"population": {
"formula": "SUM(population)",
"type": "Number"
}
}
}'''
);
CALL `carto-un-eu`.carto.CREATE_SPATIAL_INDEX_TILESET(
'YOUR_DATABASE.YOUR_SCHEMA.INPUT_TABLE_QUADBIN_LEVEL14',
'YOUR_DATABASE.YOUR_SCHEMA.OUTPUT_TILESET_QUADBIN_LEVEL14',
R'''{
"spatial_index_column": "quadbin:index",
"resolution": 14,
"resolution_min": 0,
"resolution_max": 8,
"aggregation_resolution": 6,
"properties": {
"population": {
"formula": "SUM(population)",
"type": "Number"
}
}
}'''
);
CALL carto.CREATE_SPATIAL_INDEX_TILESET(
'YOUR_DATABASE.YOUR_SCHEMA.INPUT_TABLE_QUADBIN_LEVEL14',
'YOUR_DATABASE.YOUR_SCHEMA.OUTPUT_TILESET_QUADBIN_LEVEL14',
R'''{
"spatial_index_column": "quadbin:index",
"resolution": 14,
"resolution_min": 0,
"resolution_max": 8,
"aggregation_resolution": 6,
"properties": {
"population": {
"formula": "SUM(population)",
"type": "Number"
}
}
}'''
);
carto-un
carto-un-eu
manual
CALL `carto-un`.carto.CREATE_SPATIAL_INDEX_TILESET(
'(SELECT * FROM YOUR_DATABASE.YOUR_SCHEMA.INPUT_TABLE_H3_LEVEL10)',
'YOUR_DATABASE.YOUR_SCHEMA.OUTPUT_TILESET_H3_LEVEL10',
R'''{
"spatial_index_column": "h3:index",
"resolution": 10,
"resolution_min": 0,
"resolution_max": 6,
"aggregation_resolution": 4,
"properties": {
"population": {
"formula": "SUM(population)",
"type": "Number"
}
}
}'''
);
CALL `carto-un-eu`.carto.CREATE_SPATIAL_INDEX_TILESET(
'(SELECT * FROM YOUR_DATABASE.YOUR_SCHEMA.INPUT_TABLE_H3_LEVEL10)',
'YOUR_DATABASE.YOUR_SCHEMA.OUTPUT_TILESET_H3_LEVEL10',
R'''{
"spatial_index_column": "h3:index",
"resolution": 10,
"resolution_min": 0,
"resolution_max": 6,
"aggregation_resolution": 4,
"properties": {
"population": {
"formula": "SUM(population)",
"type": "Number"
}
}
}'''
);
CALL carto.CREATE_SPATIAL_INDEX_TILESET(
'(SELECT * FROM YOUR_DATABASE.YOUR_SCHEMA.INPUT_TABLE_H3_LEVEL10)',
'YOUR_DATABASE.YOUR_SCHEMA.OUTPUT_TILESET_H3_LEVEL10',
R'''{
"spatial_index_column": "h3:index",
"resolution": 10,
"resolution_min": 0,
"resolution_max": 6,
"aggregation_resolution": 4,
"properties": {
"population": {
"formula": "SUM(population)",
"type": "Number"
}
}
}'''
);
warning
In case of
input
being set as a query, it should be taken into account that CTEs are not allowed. Also, the query should be as simple as possible in order to avoid BigQuery limitations about the complexity of the final query.Additional examples
CREATE_SIMPLE_TILESET(input, output_table, options)
warning
This procedure is the older version of
CREATE_TILESET
and you can achieve exactly the same results with either of these procedures. However, CREATE_TILESET
is capable of finding the right configuration for your input data, whereas this procedure requires you to set them yourself. Please use this procedure only if you need a really specific configuration for your tileset or need to tweak a particular option that it's not available in CREATE_TILESET
.Description
Generates a simple tileset.
input
:STRING
that can either be a quoted qualified table name (e.g.`project-id.dataset-id.table-name`
) or a full query contained by parentheses (e.g.(SELECT * FROM `project-id.dataset-id.table-name`)
).output_table
: Where the resulting table will be stored. It must be aSTRING
of the form`projectI-id.dataset-id.table-name`
. Theproject-id
can be omitted (in which case the default one will be used). The dataset must exist and the caller needs to have permissions to create a new table on it. The process will fail if the target table already exists.options
:STRING
containing a valid JSON with the different options. Valid options are described the table below.
tip
To avoid issues in the process when building the queries that will be executed internally against BigQuery, it is highly recommended to use raw strings when passing long queries in the
input
that might contain special characters.Option | Description |
---|---|
geom_column | Default: "geom" . A STRING that marks the name of the geography column that will be used. It must be of type GEOGRAPHY . |
zoom_min | Default: 0 . A NUMBER that defines the minimum zoom level for tiles. Any zoom level under this level won't be generated. |
zoom_max | Default: 12 . A NUMBER that defines the maximum zoom level for tiles. Any zoom level over this level won't be generated. |
zoom_min_column | Default: NULL . It is the column that each row could have to modify its starting zoom. It can be NULL (then zoom_min will be used). When provided, if its value is greater than zoom_min , it will take precedence and be used as the actual minimum. |
zoom_max_column | Default: NULL . It is the column that each row could have to modify its end zoom level. It can be NULL (then zoom_max will be used). When provided, if its value is lower than zoom_max , it will be taken as the real maximum zoom level. |
target_partitions | Default: 3999 . Max: 3999 . A NUMBER that defines the maximum amount of partitions to be used in the target table. The partition system, which uses a column named carto_partition , divides the available partitions first by zoom level and spatial locality to minimize the cost of tile read requests in web maps. Beware that this does not necessarily mean that all the partitions will be used, as a sparse dataset will leave some of these partitions unused. If you are using BigQuery BI Engine consider that it supports a maximum of 500 partitions per table. |
target_tilestats | Default: true . A BOOLEAN to determine whether to include statistics of the properties in the metadata. These statistics are based on mapbox-tilestats and depend on the property type:
In Simple Tilesets, these statistics are based on the source data. |
tile_extent | Default: 4096 . A NUMBER defining the extent of the tile in integer coordinates as defined by the MVT specification. |
tile_buffer | Default: 16 . A NUMBER defining the additional buffer added around the tiles in extent units, which is useful to facilitate geometry stitching across tiles in the renderers. |
max_tile_size_kb | Default: 1024 . Maximum allowed: 6144 . A NUMBER specifying the approximate maximum size for a tile in kilobytes. |
max_tile_size_strategy | Default: "throw_error" . A STRING that determines what to do when the maximum size of a tile is reached while it is still processing data. There are three options available:
|
max_tile_features | Default: 0 (disabled). A NUMBER that sets the maximum number of features a tile might contain. This limit is applied before max_tile_size_kb , i.e., the tiler will first drop as many features as needed to keep this amount, and then continue with the size limits (if required). To configure in which order features are kept, use in conjunction with tile_feature_order . |
tile_feature_order | Default: "" (disabled). A STRING defining the order in which properties are added to a tile. This expects the SQL ORDER BY keyword definition, such as "aggregated_total DESC" , the "ORDER BY" part isn't necessary. Note that in aggregation tilesets you can only use columns defined as properties, but in simple feature tilesets you can use any source column no matter if it's included in the tile as property or not. This is an expensive operation, so it's recommended to only use it when necessary. |
drop_duplicates | Default: false . A BOOLEAN to drop duplicate features in a tile. This will drop only exact matches (both the geometry and the properties are exactly equal). As this requires sorting the properties, which is expensive, it should only be used when necessary. |
generate_feature_id | |
metadata | Default: {} . A JSON object to specify the associated metadata of the tileset. Use this to set the name, description and legend to be included in the TileJSON. Other fields will be included in the object extra_metadata. |
properties | Default: {} . A JSON object that defines the extra properties that will be included associated to each cell feature. Each property is defined by its name and type (Number, Boolean or String). Check out the examples included below. |
tip
If
drop_fraction_as_needed
is used, a fraction_dropped_per_zoom
property will be included in the TileJSON, containing an estimate of the percentage of the features that have been dropped per zoom level. Please bear in mind that the exact percentages can be up to 5% higher.warning
There are some cases where flat-rates is the only option to create a tileset. Some tables containing huge geographies might trigger a
Query exceeded resource limits
error because of the high CPU usage.Examples
carto-un
carto-un-eu
manual
CALL `carto-un`.carto.CREATE_SIMPLE_TILESET(
R'''(
SELECT geom, type
FROM `carto-do-public-data.natural_earth.geography_glo_roads_410`
) _input
''',
R'''`cartobq.maps.natural_earth_roads`''',
R'''
{
"properties":{
"type": "String"
}
}'''
);
CALL `carto-un-eu`.carto.CREATE_SIMPLE_TILESET(
R'''(
SELECT geom, type
FROM `carto-do-public-data.natural_earth.geography_glo_roads_410`
) _input
''',
R'''`cartobq.maps.natural_earth_roads`''',
R'''
{
"properties":{
"type": "String"
}
}'''
);
CALL carto.CREATE_SIMPLE_TILESET(
R'''(
SELECT geom, type
FROM `carto-do-public-data.natural_earth.geography_glo_roads_410`
) _input
''',
R'''`cartobq.maps.natural_earth_roads`''',
R'''
{
"properties":{
"type": "String"
}
}'''
);
In Simple Tilesets, the
properties
are defined by the source data itself. You only have to write the name of the column (as defined in the source query or table) and its type. It doesn't support any extra transformations or formulae since those can be applied to the source query directly.carto-un
carto-un-eu
manual
R'''
{
"properties": {
"source_column_name": "Number",
"source_column_name_2": "String"
}
}
'''
R'''
{
"properties": {
"source_column_name": "Number",
"source_column_name_2": "String"
}
}
'''
R'''
{
"properties": {
"source_column_name": "Number",
"source_column_name_2": "String"
}
}
'''
Here is an example of a valid JSON for the
options
parameter:carto-un
carto-un-eu
manual
R'''
{
"geom_column": "geom",
"zoom_min": 0,
"zoom_max": 0,
"tile_extent": 4096,
"tile_buffer": 0,
"max_tile_size_kb": 1024,
"max_tile_size_strategy": "return_null",
"max_tile_features": 10000,
"tile_feature_order": "total_pop DESC",
"target_partitions": 4000,
"target_tilestats" : true,
"drop_duplicates": true,
"properties": {
"geoid": "String",
"total_pop": "Number"
}
}
'''
R'''
{
"geom_column": "geom",
"zoom_min": 0,
"zoom_max": 0,
"tile_extent": 4096,
"tile_buffer": 0,
"max_tile_size_kb": 1024,
"max_tile_size_strategy": "return_null",
"max_tile_features": 10000,
"tile_feature_order": "total_pop DESC",
"target_partitions": 4000,
"target_tilestats" : true,
"drop_duplicates": true,
"properties": {
"geoid": "String",
"total_pop": "Number"
}
}
'''
R'''
{
"geom_column": "geom",
"zoom_min": 0,
"zoom_max": 0,
"tile_extent": 4096,
"tile_buffer": 0,
"max_tile_size_kb": 1024,
"max_tile_size_strategy": "return_null",
"max_tile_features": 10000,
"tile_feature_order": "total_pop DESC",
"target_partitions": 4000,
"target_tilestats" : true,
"drop_duplicates": true,
"properties": {
"geoid": "String",
"total_pop": "Number"
}
}
'''
Additional examples
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 960401.

Last modified 23d ago