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Raster writer

Note

Sedona writers are available in Scala, Java and Python and have the same APIs.

Write Raster DataFrame to raster files

To write a Sedona Raster DataFrame to raster files, you need to (1) first convert the Raster DataFrame to a binary DataFrame using RS_AsXXX functions and (2) then write the binary DataFrame to raster files using Sedona's built-in raster data source.

Write raster DataFrame to a binary DataFrame

You can use the following RS output functions (RS_AsXXX) to convert a Raster DataFrame to a binary DataFrame. Generally the output format of a raster can be different from the original input format. For example, you can use RS_FromGeoTiff to create rasters and save them using RS_AsArcInfoAsciiGrid.

RS_AsArcGrid

Introduction: Returns a binary DataFrame from a Raster DataFrame. Each raster object in the resulting DataFrame is an ArcGrid image in binary format. ArcGrid only takes 1 source band. If your raster has multiple bands, you need to specify which band you want to use as the source.

Possible values for sourceBand: any non-negative value (>=0). If not given, it will use Band 0.

Format:

RS_AsArcGrid(raster: Raster)

RS_AsArcGrid(raster: Raster, sourceBand: Integer)

Since: v1.4.1

Spark SQL Example:

SELECT RS_AsArcGrid(raster) FROM my_raster_table

Spark SQL Example:

SELECT RS_AsArcGrid(raster, 1) FROM my_raster_table

Output:

+--------------------+
|             arcgrid|
+--------------------+
|[4D 4D 00 2A 00 0...|
+--------------------+

Output schema:

root
 |-- arcgrid: binary (nullable = true)

RS_AsGeoTiff

Introduction: Returns a binary DataFrame from a Raster DataFrame. Each raster object in the resulting DataFrame is a GeoTiff image in binary format.

Possible values for compressionType: None, PackBits, Deflate, Huffman, LZW and JPEG

Possible values for imageQuality: any decimal number between 0 and 1. 0 means the lowest quality and 1 means the highest quality.

Format:

RS_AsGeoTiff(raster: Raster)

RS_AsGeoTiff(raster: Raster, compressionType: String, imageQuality: Double)

Since: v1.4.1

Spark SQL Example:

SELECT RS_AsGeoTiff(raster) FROM my_raster_table

Spark SQL Example:

SELECT RS_AsGeoTiff(raster, 'LZW', '0.75') FROM my_raster_table

Output:

+--------------------+
|             geotiff|
+--------------------+
|[4D 4D 00 2A 00 0...|
+--------------------+

Output schema:

root
 |-- geotiff: binary (nullable = true)

RS_AsPNG

Introduction: Returns a PNG byte array, that can be written to raster files as PNGs using the sedona function. This function can only accept pixel data type of unsigned integer. PNG can accept 1 or 3 bands of data from the raster, refer to RS_Band for more details.

Note

Raster having UNSIGNED_8BITS pixel data type will have range of 0 - 255, whereas rasters having UNSIGNED_16BITS pixel data type will have range of 0 - 65535. If provided pixel value is greater than either 255 for UNSIGNED_8BITS or 65535 for UNSIGNED_16BITS, then the extra bit will be truncated.

Note

Raster that have float or double values will result in an empty byte array. PNG only accepts Integer values, if you want to write your raster to an image file, please refer to RS_AsGeoTiff.

Format: RS_AsPNG(raster: Raster)

Since: v1.5.0

Spark SQL Example:

SELECT RS_AsPNG(raster) FROM Rasters

Output:

[-119, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73...]

Spark SQL Example:

SELECT RS_AsPNG(RS_Band(raster, Array(3, 1, 2)))

Output:

[-103, 78, 94, -26, 61, -16, -91, -103, -65, -116...]

Write a binary DataFrame to raster files

Introduction: You can write a Sedona binary DataFrame to external storage using Sedona's built-in raster data source. Note that: raster data source does not support reading rasters. Please use Spark built-in binaryFile and Sedona RS constructors together to read rasters.

Since: v1.4.1

Available options:

  • rasterField:
    • Default value: the binary type column in the DataFrame. If the input DataFrame has several binary columns, please specify which column you want to use.
    • Allowed values: the name of the to-be-saved binary type column
  • fileExtension
    • Default value: .tiff
    • Allowed values: any string values such as .png, .jpeg, .asc
  • pathField
    • No default value. If you use this option, then the column specified in this option must exist in the DataFrame schema. If this option is not used, each produced raster image will have a random UUID file name.
    • Allowed values: any column name that indicates the paths of each raster file

The schema of the Raster dataframe to be written can be one of the following two schemas:

root
 |-- rs_asgeotiff(raster): binary (nullable = true)

or

root
 |-- rs_asgeotiff(raster): binary (nullable = true)
 |-- path: string (nullable = true)

Spark SQL example 1:

sparkSession.write.format("raster").mode(SaveMode.Overwrite).save("my_raster_file")

Spark SQL example 2:

sparkSession.write.format("raster").option("rasterField", "raster").option("pathField", "path").option("fileExtension", ".tiff").mode(SaveMode.Overwrite).save("my_raster_file")

The produced file structure will look like this:

my_raster_file
- part-00000-6c7af016-c371-4564-886d-1690f3b27ca8-c000
    - test1.tiff
    - .test1.tiff.crc
- part-00001-6c7af016-c371-4564-886d-1690f3b27ca8-c000
    - test2.tiff
    - .test2.tiff.crc
- part-00002-6c7af016-c371-4564-886d-1690f3b27ca8-c000
    - test3.tiff
    - .test3.tiff.crc
- _SUCCESS

To read it back to Sedona Raster DataFrame, you can use the following command (note the * in the path):

sparkSession.read.format("binaryFile").load("my_raster_file/*")

Then you can create Raster type in Sedona like this RS_FromGeoTiff(content) (if the written data was in GeoTiff format).

The newly created DataFrame can be written to disk again but must be under a different name such as my_raster_file_modified

Write Geometry to Raster dataframe

RS_AsRaster

Introduction: Converts a Geometry to a Raster dataset. Defaults to using 1.0 for cell value and null for noDataValue if not provided. Supports all geometry types. The pixelType argument defines data type of the output raster. This can be one of the following, D (double), F (float), I (integer), S (short), US (unsigned short) or B (byte). The useGeomeryExtent argument defines the extent of the resultant raster. When set to true, it corresponds to the extent of geom, and when set to false, it corresponds to the extent of raster. Default value is true if not set. Format:

RS_AsRaster(geom: Geometry, raster: Raster, pixelType: String, value: Double, noDataValue: Double, useGeometryExtent: Boolean)
RS_AsRaster(geom: Geometry, raster: Raster, pixelType: String, value: Double, noDataValue: Double)
RS_AsRaster(geom: Geometry, raster: Raster, pixelType: String, value: Double)
RS_AsRaster(geom: Geometry, raster: Raster, pixelType: String)

Since: v1.5.0

Note

The function doesn't support rasters that have any one of the following properties:

ScaleX < 0
ScaleY > 0
SkewX != 0
SkewY != 0
If a raster is provided with anyone of these properties then IllegalArgumentException is thrown.

Spark SQL Example:

SELECT RS_AsRaster(
        ST_GeomFromWKT('POLYGON((15 15, 18 20, 15 24, 24 25, 15 15))'),
        RS_MakeEmptyRaster(2, 255, 255, 3, -215, 2, -2, 0, 0, 4326),
        'D', 255.0, 0d
    )

Output:

GridCoverage2D["g...

Spark SQL Example:

SELECT RS_AsRaster(
        ST_GeomFromWKT('POLYGON((15 15, 18 20, 15 24, 24 25, 15 15))'),
        RS_MakeEmptyRaster(2, 255, 255, 3, -215, 2, -2, 0, 0, 4326),
        'D'
    )

Output:

GridCoverage2D["g...
SELECT RS_AsRaster(
        ST_GeomFromWKT('POLYGON((15 15, 18 20, 15 24, 24 25, 15 15))'),
        RS_MakeEmptyRaster(2, 255, 255, 3, 215, 2, -2, 0, 0, 0),
       'D',255, 0d, false
)

Output:

GridCoverage2D["g...

Last update: January 9, 2024 10:26:13