spark typed 源码
spark typed 代码
文件路径：/sql/core/src/main/scala/org/apache/spark/sql/expressions/scalalang/typed.scala
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.spark.sql.expressions.scalalang
import org.apache.spark.sql._
import org.apache.spark.sql.execution.aggregate._
/**
* Type-safe functions available for `Dataset` operations in Scala.
*
* Java users should use [[org.apache.spark.sql.expressions.javalang.typed]].
*
* @since 2.0.0
*/
@deprecated("please use untyped builtin aggregate functions.", "3.0.0")
// scalastyle:off
object typed {
// scalastyle:on
// Note: whenever we update this file, we should update the corresponding Java version too.
// The reason we have separate files for Java and Scala is because in the Scala version, we can
// use tighter types (primitive types) for return types, whereas in the Java version we can only
// use boxed primitive types.
// For example, avg in the Scala version returns Scala primitive Double, whose bytecode
// signature is just a java.lang.Object; avg in the Java version returns java.lang.Double.
// TODO: This is pretty hacky. Maybe we should have an object for implicit encoders.
private val implicits = new SQLImplicits {
override protected def _sqlContext: SQLContext = null
}
/**
* Average aggregate function.
*
* @since 2.0.0
*/
def avg[IN](f: IN => Double): TypedColumn[IN, Double] = new TypedAverage(f).toColumn
/**
* Count aggregate function.
*
* @since 2.0.0
*/
def count[IN](f: IN => Any): TypedColumn[IN, Long] = new TypedCount(f).toColumn
/**
* Sum aggregate function for floating point (double) type.
*
* @since 2.0.0
*/
def sum[IN](f: IN => Double): TypedColumn[IN, Double] = new TypedSumDouble[IN](f).toColumn
/**
* Sum aggregate function for integral (long, i.e. 64 bit integer) type.
*
* @since 2.0.0
*/
def sumLong[IN](f: IN => Long): TypedColumn[IN, Long] = new TypedSumLong[IN](f).toColumn
}
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