org.elasticsearch.spark.sql.package.scala Maven / Gradle / Ivy
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package org.elasticsearch.spark;
import scala.language.implicitConversions
import org.apache.spark.sql.DataFrame
import org.apache.spark.sql.SQLContext
import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.Dataset
import scala.reflect.ClassTag
package object sql {
implicit def sqlContextFunctions(sc: SQLContext)= new SQLContextFunctions(sc)
class SQLContextFunctions(sc: SQLContext) extends Serializable {
def esDF() = EsSparkSQL.esDF(sc)
def esDF(resource: String) = EsSparkSQL.esDF(sc, resource)
def esDF(resource: String, query: String) = EsSparkSQL.esDF(sc, resource, query)
def esDF(cfg: scala.collection.Map[String, String]) = EsSparkSQL.esDF(sc, cfg)
def esDF(resource: String, cfg: scala.collection.Map[String, String]) = EsSparkSQL.esDF(sc, resource, cfg)
def esDF(resource: String, query: String, cfg: scala.collection.Map[String, String]) = EsSparkSQL.esDF(sc, resource, query, cfg)
}
// the sparkDatasetFunctions already takes care of this
// but older clients might still import it hence why it's still here
implicit def sparkDataFrameFunctions(df: DataFrame) = new SparkDataFrameFunctions(df)
class SparkDataFrameFunctions(df: DataFrame) extends Serializable {
def saveToEs(resource: String): Unit = { EsSparkSQL.saveToEs(df, resource) }
def saveToEs(resource: String, cfg: scala.collection.Map[String, String]): Unit = { EsSparkSQL.saveToEs(df, resource, cfg) }
def saveToEs(cfg: scala.collection.Map[String, String]): Unit = { EsSparkSQL.saveToEs(df, cfg) }
}
implicit def sparkSessionFunctions(ss: SparkSession)= new SparkSessionFunctions(ss)
class SparkSessionFunctions(ss: SparkSession) extends Serializable {
def esDF() = EsSparkSQL.esDF(ss)
def esDF(resource: String) = EsSparkSQL.esDF(ss, resource)
def esDF(resource: String, query: String) = EsSparkSQL.esDF(ss, resource, query)
def esDF(cfg: scala.collection.Map[String, String]) = EsSparkSQL.esDF(ss, cfg)
def esDF(resource: String, cfg: scala.collection.Map[String, String]) = EsSparkSQL.esDF(ss, resource, cfg)
def esDF(resource: String, query: String, cfg: scala.collection.Map[String, String]) = EsSparkSQL.esDF(ss, resource, query, cfg)
}
implicit def sparkDatasetFunctions[T : ClassTag](ds: Dataset[T]) = new SparkDatasetFunctions(ds)
class SparkDatasetFunctions[T : ClassTag](ds: Dataset[T]) extends Serializable {
def saveToEs(resource: String): Unit = { EsSparkSQL.saveToEs(ds, resource) }
def saveToEs(resource: String, cfg: scala.collection.Map[String, String]): Unit = { EsSparkSQL.saveToEs(ds, resource, cfg) }
def saveToEs(cfg: scala.collection.Map[String, String]): Unit = { EsSparkSQL.saveToEs(ds, cfg) }
}
}
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