org.apache.spark.sql.catalyst.expressions.aggregate.Complete Scala Examples

The following examples show how to use org.apache.spark.sql.catalyst.expressions.aggregate.Complete. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example.
Example 1
Source File: Aggregator.scala    From drizzle-spark   with Apache License 2.0 5 votes vote down vote up 
package org.apache.spark.sql.expressions

import org.apache.spark.annotation.{Experimental, InterfaceStability}
import org.apache.spark.sql.{Dataset, Encoder, TypedColumn}
import org.apache.spark.sql.catalyst.encoders.encoderFor
import org.apache.spark.sql.catalyst.expressions.aggregate.{AggregateExpression, Complete}
import org.apache.spark.sql.execution.aggregate.TypedAggregateExpression


  def toColumn: TypedColumn[IN, OUT] = {
    implicit val bEncoder = bufferEncoder
    implicit val cEncoder = outputEncoder

    val expr =
      AggregateExpression(
        TypedAggregateExpression(this),
        Complete,
        isDistinct = false)

    new TypedColumn[IN, OUT](expr, encoderFor[OUT])
  }
}
Example 2
Source File: Aggregator.scala    From XSQL   with Apache License 2.0 5 votes vote down vote up 
package org.apache.spark.sql.expressions

import org.apache.spark.annotation.{Experimental, InterfaceStability}
import org.apache.spark.sql.{Dataset, Encoder, TypedColumn}
import org.apache.spark.sql.catalyst.encoders.encoderFor
import org.apache.spark.sql.catalyst.expressions.aggregate.{AggregateExpression, Complete}
import org.apache.spark.sql.execution.aggregate.TypedAggregateExpression


  def toColumn: TypedColumn[IN, OUT] = {
    implicit val bEncoder = bufferEncoder
    implicit val cEncoder = outputEncoder

    val expr =
      AggregateExpression(
        TypedAggregateExpression(this),
        Complete,
        isDistinct = false)

    new TypedColumn[IN, OUT](expr, encoderFor[OUT])
  }
}
Example 3
Source File: ResolveCountDistinctStarSuite.scala    From HANAVora-Extensions   with Apache License 2.0 5 votes vote down vote up 
package org.apache.spark.sql.catalyst.analysis

import org.apache.spark.sql.SQLContext
import org.apache.spark.sql.catalyst.expressions.{Alias, AttributeReference}
import org.apache.spark.sql.catalyst.plans.logical.Aggregate
import org.apache.spark.sql.execution.datasources.LogicalRelation
import org.apache.spark.sql.sources.BaseRelation
import org.apache.spark.sql.types.{IntegerType, StringType, StructField, StructType}
import org.scalatest.FunSuite
import org.scalatest.Inside._
import org.scalatest.mock.MockitoSugar
import org.apache.spark.sql.catalyst.dsl.plans.DslLogicalPlan
import org.apache.spark.sql.catalyst.expressions.aggregate.{AggregateExpression, Complete, Count}

import scala.collection.mutable.ArrayBuffer

class ResolveCountDistinctStarSuite extends FunSuite with MockitoSugar {
  val persons = new LogicalRelation(new BaseRelation {
    override def sqlContext: SQLContext = mock[SQLContext]
    override def schema: StructType = StructType(Seq(
      StructField("age", IntegerType),
      StructField("name", StringType)
    ))
  })

  test("Count distinct star is resolved correctly") {
    val projection = persons.select(UnresolvedAlias(
      AggregateExpression(Count(UnresolvedStar(None) :: Nil), Complete, true)))
    val stillNotCompletelyResolvedAggregate = SimpleAnalyzer.execute(projection)
    val resolvedAggregate = ResolveCountDistinctStar(SimpleAnalyzer)
                              .apply(stillNotCompletelyResolvedAggregate)
    inside(resolvedAggregate) {
      case Aggregate(Nil,
      ArrayBuffer(Alias(AggregateExpression(Count(expressions), Complete, true), _)), _) =>
        assert(expressions.collect {
          case a:AttributeReference => a.name
        }.toSet == Set("name", "age"))
    }
    assert(resolvedAggregate.resolved)
  }
}
Example 4
Source File: Aggregator.scala    From sparkoscope   with Apache License 2.0 5 votes vote down vote up 
package org.apache.spark.sql.expressions

import org.apache.spark.annotation.{Experimental, InterfaceStability}
import org.apache.spark.sql.{Dataset, Encoder, TypedColumn}
import org.apache.spark.sql.catalyst.encoders.encoderFor
import org.apache.spark.sql.catalyst.expressions.aggregate.{AggregateExpression, Complete}
import org.apache.spark.sql.execution.aggregate.TypedAggregateExpression


  def toColumn: TypedColumn[IN, OUT] = {
    implicit val bEncoder = bufferEncoder
    implicit val cEncoder = outputEncoder

    val expr =
      AggregateExpression(
        TypedAggregateExpression(this),
        Complete,
        isDistinct = false)

    new TypedColumn[IN, OUT](expr, encoderFor[OUT])
  }
}
Example 5
Source File: Aggregator.scala    From multi-tenancy-spark   with Apache License 2.0 5 votes vote down vote up 
package org.apache.spark.sql.expressions

import org.apache.spark.annotation.{Experimental, InterfaceStability}
import org.apache.spark.sql.{Dataset, Encoder, TypedColumn}
import org.apache.spark.sql.catalyst.encoders.encoderFor
import org.apache.spark.sql.catalyst.expressions.aggregate.{AggregateExpression, Complete}
import org.apache.spark.sql.execution.aggregate.TypedAggregateExpression


  def toColumn: TypedColumn[IN, OUT] = {
    implicit val bEncoder = bufferEncoder
    implicit val cEncoder = outputEncoder

    val expr =
      AggregateExpression(
        TypedAggregateExpression(this),
        Complete,
        isDistinct = false)

    new TypedColumn[IN, OUT](expr, encoderFor[OUT])
  }
}
Example 6
Source File: Aggregator.scala    From Spark-2.3.1   with Apache License 2.0 5 votes vote down vote up 
package org.apache.spark.sql.expressions

import org.apache.spark.annotation.{Experimental, InterfaceStability}
import org.apache.spark.sql.{Dataset, Encoder, TypedColumn}
import org.apache.spark.sql.catalyst.encoders.encoderFor
import org.apache.spark.sql.catalyst.expressions.aggregate.{AggregateExpression, Complete}
import org.apache.spark.sql.execution.aggregate.TypedAggregateExpression


  def toColumn: TypedColumn[IN, OUT] = {
    implicit val bEncoder = bufferEncoder
    implicit val cEncoder = outputEncoder

    val expr =
      AggregateExpression(
        TypedAggregateExpression(this),
        Complete,
        isDistinct = false)

    new TypedColumn[IN, OUT](expr, encoderFor[OUT])
  }
}
Example 7
Source File: Aggregator.scala    From BigDatalog   with Apache License 2.0 5 votes vote down vote up 
package org.apache.spark.sql.expressions

import org.apache.spark.sql.catalyst.encoders.encoderFor
import org.apache.spark.sql.catalyst.expressions.aggregate.{AggregateExpression, Complete}
import org.apache.spark.sql.execution.aggregate.TypedAggregateExpression
import org.apache.spark.sql.{DataFrame, Dataset, Encoder, TypedColumn}


  def toColumn(
      implicit bEncoder: Encoder[B],
      cEncoder: Encoder[O]): TypedColumn[I, O] = {
    val expr =
      new AggregateExpression(
        TypedAggregateExpression(this),
        Complete,
        false)

    new TypedColumn[I, O](expr, encoderFor[O])
  }
}