CSVLoader

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1. final def !=(arg0: AnyRef): Boolean

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3. final def ##(): Int

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14. def loadGraphFromCSV(file: String, csvLoaderConfig: CsvLoaderConfig = CsvLoaderConfig(), defaultVertex: Option[String] = Option(""), column1: Int = 0, column2: Int = 1, edgeAttributeProvider: (Row) ⇒ Double = defaultEdgeAttribute, partitions: Int = 0)(implicit sc: SparkContext): Graph[String, Double]

    Simple load graph from CSV.

    Simple load graph from CSV. Columns from witch vertices will be created must be numeric identifiers of vertices

    file

    - CSV input file

    csvLoaderConfig

    - Loader config, with default value

    defaultVertex

    - default vertex, has default value

    column1

    - first column to be selected as vertex, default:0

    column2

    - second column to be selected as vertex, default:1

    sc

    - spark contex

    returns

    Graph[String,Double] - loaded graph

15. def loadGraphFromCSV[VD, ED](file: String, graphBuilder: (DataFrame) ⇒ Graph[VD, ED], csvLoaderConfig: CsvLoaderConfig, partitions: Int)(implicit sc: SparkContext): Graph[VD, ED]

    Main method for graph loading from csv, should be used for extension and further development, please use case specific loading methods present in that object

    Main method for graph loading from csv, should be used for extension and further development, please use case specific loading methods present in that object

    VD

    - vertex attribute type

    ED

    - edge attribute type

    file

    - CSV file

    graphBuilder

    - graph builder to handle graph creation from csv file

    csvLoaderConfig

    - csv loader configuration

    sc

    - spark context

    returns

    Graph[VD,ED] - loaded graph

16. def loadGraphFromCSVWitVertexIndexing[VD, ED](file: String, csvLoaderConfig: CsvLoaderConfig = CsvLoaderConfig(), defaultVertex: Option[VD] = Option("").asInstanceOf[Option[VD]], column1: Int = 0, column2: Int = 1, edgeAttributeProvider: (Row) ⇒ ED = defaultEdgeAttribute, partitions: Int = 0)(implicit arg0: ClassTag[VD], arg1: ClassTag[ED], sc: SparkContext): Graph[VD, ED]

    Load graph from given CSV file, indexing vertices toprovide each unique ID.

    Load graph from given CSV file, indexing vertices toprovide each unique ID.

    VD

    - vertex type

    ED

    - edge type

    file

    - input CSV file

    csvLoaderConfig

    - CSV loader config , has default value

    defaultVertex

    - default Vertex value

    column1

    - first column to be selected as vertex, default:0

    column2

    - second column to be selected as vertex, default:1

    edgeAttributeProvider

    - provider for edge attribute, default 1L

    sc

    - spark context

    returns

    Graph[VD,ED] - loaded graph

17. final def ne(arg0: AnyRef): Boolean

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18. final def notify(): Unit

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22. final def wait(): Unit

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24. final def wait(arg0: Long): Unit

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