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net.sansa_stack.ml.spark.featureExtraction

FeatureExtractingSparqlGenerator

object FeatureExtractingSparqlGenerator

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  8. def createDataframesToTraverse(df: DataFrame): (DataFrame, DataFrame)

    creates dataframe for traversing over join

    creates dataframe for traversing over join

    df

    dataframe representing entire graph

    returns

    dataframes for traversing up (which is same as df and down which is up flipped and added the traverse direction column)

  9. def createSeedFetchingSparql(seedVarName: String, seedWhereClause: String, sortedByLinks: Boolean): String

    create on string level the seed fetching query

    create on string level the seed fetching query

    seedVarName

    projection var name for seed element

    seedWhereClause

    where clause how seed can be fetched

    sortedByLinks

    boolean value if seeds should be ordered by outgoing links in desc order or fifo seeds

    returns

    string representing the seed fetching sparql query

  10. def createSparql(ds: Dataset[Triple], seedVarName: String, seedWhereClause: String, maxUp: Int, maxDown: Int, numberSeeds: Int = 0, ratioNumberSeeds: Double = 1.0, numberRandomWalks: Int = 0, sortedByLinks: Boolean = false, featuresInOptionalBlocks: Boolean = true): (String, List[String])

    this function creates the sparql and a list of corresponding porjection variables

    this function creates the sparql and a list of corresponding porjection variables

    the function operates on dataframe level and first fetches the seeds then seeds are cutoff to the desired number or ration to be considered from seeds we traverse up in the graph traverse down create for each traversed path a query line take unique query lines create sparql query

    ds

    dataset of triple of true columns of type string representing triples s p o

    seedVarName

    how the seeds should be named and with beginning question mark as needed for projection variable

    seedWhereClause

    a string representing the where part of a sparql query specifying how to reach seeds

    maxUp

    integer for limiting number of traversal up steps

    maxDown

    integer for limiting traverse down steps

    numberSeeds

    number of seeds to consider

    ratioNumberSeeds

    number of seeds specified by ratio

    returns

    string of resulting sparql and list of string for each projection variable which later can be used for dataframe column naming

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  16. def main(args: Array[String]): Unit

    the main function call the entire process

    the main function call the entire process

    all configuration have to be done in a config file. this allows easier interaction as soon as a standalone jar has been created.

    args

    path to the typesafe conf file

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  20. def rowToQuery(row: Row, seedVarName: String, featuresInOptionalBlocks: Boolean): (String, String)

    creates a string corresponding to an OPTIONAL block for where part in resulting sparql

    creates a string corresponding to an OPTIONAL block for where part in resulting sparql

    row

    row from dataframe created by traversing all paths

    seedVarName

    name of seed projection var

    returns

    string representing OPTIONAL block

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  23. def traverse(paths: DataFrame, traverseDf: DataFrame, iterationLimit: Int, traverseDirection: String, numberRandomWalks: Int = 0): DataFrame

    traverses a tree by joining dataframes of current paths and traversable hops

    traverses a tree by joining dataframes of current paths and traversable hops

    paths

    current paths initially started at seeds

    traverseDf

    the dataframe giving traversal opportunities

    iterationLimit

    how deep to traverse or how often join should be performed max

    traverseDirection

    direction whether up or down

    returns

    the traversed dataframe with current paths after traverse up, and paths ending with literals after traverse down

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