为什么 Spark 会因 "value rdf is not a member of org.apache.spark.sql.SparkSession" 而失败?

Why does Spark fail with "value rdf is not a member of org.apache.spark.sql.SparkSession"?

我正在尝试使用 SANSA-RDF 将 turtle RDF 文件读入 Spark 并创建图表。执行以下代码时出现错误。我错过了什么?

    import org.apache.jena.query.QueryFactory
    import org.apache.jena.riot.Lang
    import org.apache.spark.sql.SparkSession
    import net.sansa_stack.rdf.spark.io.rdf._
    import net.sansa_stack.rdf.spark.io._
    import scala.io.Source

    object SparkExecutor {
      private var ss:SparkSession = null

      def ConfigureSpark(): Unit ={

        ss = SparkSession.builder
          .master("local[*]")
          .config("spark.driver.cores", 1)
          .appName("LAM")
          .getOrCreate()

      }

      def createGraph(): Unit ={
        val filename = "xyz.ttl"
        print("Loading graph from file"+ filename)
        val lang = Lang.TTL
        val triples = ss.rdf(lang)(filename)
        val graph = LoadGraph(triples)    
      }
    }

我正在使用

从主函数调用 SparkExecutor
    object main {
      def main(args: Array[String]): Unit = {
        SparkExecutor.ConfigureSpark()
        val RDFGraph = SparkExecutor.createGraph()
      }
    }

这会导致以下错误

    Error: value rdf is not a member of org.apache.spark.sql.SparkSession
val triples = ss.rdf(lang)

好吧,如果你在

中看到 SANSA-RDF 源代码,那么这里有一个隐式转换
sansa-rdf-spark/src/main/scala/net/sansa_stack/rdf/spark/io/package.scala:159

rdf(lang) 不是spark session的方法,而是implicit class RDFReader的方法,所以需要import有隐式定义的包。请尝试添加

import net.sansa_stack.rdf.spark.io._

让我们知道结果。