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cleanup docs
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@ -20,11 +20,11 @@ Similar to the `flat` schema, but also includes a `tile_hash` column that contai
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```sql, ignore
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CREATE TABLE tiles_with_hash (
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zoom_level INTEGER NOT NULL,
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zoom_level INTEGER NOT NULL,
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tile_column INTEGER NOT NULL,
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tile_row INTEGER NOT NULL,
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tile_data BLOB,
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tile_hash TEXT);
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tile_row INTEGER NOT NULL,
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tile_data BLOB,
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tile_hash TEXT);
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CREATE UNIQUE INDEX tiles_with_hash_index on tiles_with_hash (
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zoom_level, tile_column, tile_row);
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@ -39,13 +39,13 @@ Normalized schema is the most efficient when the tileset contains duplicate tile
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```sql, ignore
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CREATE TABLE map (
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zoom_level INTEGER,
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zoom_level INTEGER,
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tile_column INTEGER,
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tile_row INTEGER,
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tile_id TEXT);
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tile_row INTEGER,
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tile_id TEXT);
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CREATE TABLE images (
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tile_id TEXT,
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tile_id TEXT,
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tile_data BLOB);
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CREATE UNIQUE INDEX map_index ON map (
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@ -55,9 +55,9 @@ CREATE UNIQUE INDEX images_id ON images (
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CREATE VIEW tiles AS
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SELECT
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map.zoom_level AS zoom_level,
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map.tile_column AS tile_column,
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map.tile_row AS tile_row,
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map.zoom_level AS zoom_level,
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map.tile_column AS tile_column,
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map.tile_row AS tile_row,
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images.tile_data AS tile_data
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FROM
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map JOIN images
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@ -69,11 +69,11 @@ Optionally, `.mbtiles` files with `normalized` schema can include a `tiles_with_
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```sql, ignore
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CREATE VIEW tiles_with_hash AS
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SELECT
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map.zoom_level AS zoom_level,
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map.tile_column AS tile_column,
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map.tile_row AS tile_row,
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map.zoom_level AS zoom_level,
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map.tile_column AS tile_column,
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map.tile_row AS tile_row,
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images.tile_data AS tile_data,
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images.tile_id AS tile_hash
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images.tile_id AS tile_hash
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FROM
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map JOIN images
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ON map.tile_id = images.tile_id;
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