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c

com.wherobots.VTiles

GenerationConfig

case class GenerationConfig(minZoom: Int = 0, maxZoom: Int = 15, tileResolution: Int = 4096, buffer: Double = 0.1, featureFilter: Option[Column] = None, tileFilter: Option[Column] = None, featureSimplify: Option[Column] = None, maxFeaturesPerTile: Option[Int] = Some(50000), cacheFrequency: Option[Int] = Some(2), persistStorageLevel: StorageLevel = StorageLevel.MEMORY_AND_DISK, maxDatasetSize: Option[Int] = None, partitionCount: Option[Int] = None, repartitionFrequency: Option[Int] = None) extends Product with Serializable

minZoom

the lowest zoom for which to generate tiles

maxZoom

the highest zoom for which to generate tiles

tileResolution

the resolution of the tiles to generate

buffer

the buffer (as a fraction) to apply to the tiles. the margin on a 1000 resolution tile with a buffer of .1 would be 100

featureFilter

a predicate Column for filtering features, optional

tileFilter

a Column for manipulating the array of features within a tile, optional

featureSimplify

a Column for manipulating feature geometries, optional

maxFeaturesPerTile

the maximum number of features to include in each tile, optional

cacheFrequency

the frequency at which to cache the dataset, optional. e.g 2 means every 2nd zoom level. Default is 2

persistStorageLevel

the storage level to persist the dataset at. Default is DISK_ONLY

maxDatasetSize

the maximum size of the dataset from which to generate tiles, optional. if the dataset is larger than this, it will be reduced to this size by randomly sampling features

partitionCount

the number of partitions to use in tile generation. Default is 2x the number of worker cores

repartitionFrequency

the frequency (ie number of zoom levels) at which to repartition the dataset. Default behavior not to repartition a certain zooms. Repartitioning helps when the geometries are large relative to the tiles, for example processing a collection of countries to zoom 16.

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Instance Constructors

  1. new GenerationConfig(minZoom: Int = 0, maxZoom: Int = 15, tileResolution: Int = 4096, buffer: Double = 0.1, featureFilter: Option[Column] = None, tileFilter: Option[Column] = None, featureSimplify: Option[Column] = None, maxFeaturesPerTile: Option[Int] = Some(50000), cacheFrequency: Option[Int] = Some(2), persistStorageLevel: StorageLevel = StorageLevel.MEMORY_AND_DISK, maxDatasetSize: Option[Int] = None, partitionCount: Option[Int] = None, repartitionFrequency: Option[Int] = None)

    minZoom

    the lowest zoom for which to generate tiles

    maxZoom

    the highest zoom for which to generate tiles

    tileResolution

    the resolution of the tiles to generate

    buffer

    the buffer (as a fraction) to apply to the tiles. the margin on a 1000 resolution tile with a buffer of .1 would be 100

    featureFilter

    a predicate Column for filtering features, optional

    tileFilter

    a Column for manipulating the array of features within a tile, optional

    featureSimplify

    a Column for manipulating feature geometries, optional

    maxFeaturesPerTile

    the maximum number of features to include in each tile, optional

    cacheFrequency

    the frequency at which to cache the dataset, optional. e.g 2 means every 2nd zoom level. Default is 2

    persistStorageLevel

    the storage level to persist the dataset at. Default is DISK_ONLY

    maxDatasetSize

    the maximum size of the dataset from which to generate tiles, optional. if the dataset is larger than this, it will be reduced to this size by randomly sampling features

    partitionCount

    the number of partitions to use in tile generation. Default is 2x the number of worker cores

    repartitionFrequency

    the frequency (ie number of zoom levels) at which to repartition the dataset. Default behavior not to repartition a certain zooms. Repartitioning helps when the geometries are large relative to the tiles, for example processing a collection of countries to zoom 16.

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  5. val buffer: Double
  6. val cacheFrequency: Option[Int]
  7. def clone(): AnyRef
    Attributes
    protected[lang]
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    @throws( ... ) @native() @IntrinsicCandidate()
  8. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  9. val featureFilter: Option[Column]
  10. val featureSimplify: Option[Column]
  11. final def getClass(): Class[_]
    Definition Classes
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    Annotations
    @native() @IntrinsicCandidate()
  12. val getFeatureFilter: Column
  13. val getFeatureSimplify: Column
  14. val getPartitionCount: Int
  15. val getTileFilter: Column
  16. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  17. val maxDatasetSize: Option[Int]
  18. val maxFeaturesPerTile: Option[Int]
  19. val maxZoom: Int
  20. val minZoom: Int
  21. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  22. final def notify(): Unit
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    @native() @IntrinsicCandidate()
  23. final def notifyAll(): Unit
    Definition Classes
    AnyRef
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    @native() @IntrinsicCandidate()
  24. val partitionCount: Option[Int]
  25. val persistStorageLevel: StorageLevel
  26. val repartitionFrequency: Option[Int]
  27. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  28. val tileFilter: Option[Column]
  29. val tileResolution: Int
  30. def validate(): Unit
  31. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
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    @throws( ... )
  32. final def wait(arg0: Long): Unit
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    @throws( ... ) @native()
  33. final def wait(): Unit
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    @throws( ... )
  34. def withSuggestedMaxZoom(df: Dataset[Row]): GenerationConfig

    Sets the maxZoom based on heuristics of the input dataframe

    Sets the maxZoom based on heuristics of the input dataframe

    df

    The dataframe that will be used along with this Config to generate tiles.

    returns

    a new GenerationConfig with the maxZoom set based on heuristics of the input dataframe

  35. def withSuggestedMinZoom(df: Dataset[Row]): GenerationConfig

    Sets the minZoom based on heuristics of the input dataframe

    Sets the minZoom based on heuristics of the input dataframe

    df

    The dataframe that will be used along with this Config to generate tiles.

    returns

    a new GenerationConfig with the minZoom set based on heuristics of the input dataframe

Deprecated Value Members

  1. def finalize(): Unit
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    @throws( classOf[java.lang.Throwable] ) @Deprecated
    Deprecated

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