Spark将列转换为存储在字符串中的sql类型 [英] Spark cast column to sql type stored in string

问题描述

简单的请求是我需要帮助将一列添加到数据框中，但是，该列必须为空，其类型来自 ...spark.sql.types，并且必须从字符串中定义类型.

>

我可能可以用 ifs 或 case 来做到这一点，但我正在寻找更优雅的东西.不需要为 org.apache.spark.sql.types 中的每种类型编写案例的东西

如果我这样做:

df = df.withColumn("col_name", lit(null).cast(org.apache.spark.sql.types.StringType))

它按预期工作，但我将类型存储为字符串，

var the_type = "StringType"

或var the_type = "org.apache.spark.sql.types.StringType"

我无法通过从字符串定义类型来使其工作.

对于那些感兴趣的人，这里有一些更多的细节:我有一个包含元组(col_name，col_type)作为字符串的集合，我需要添加具有正确类型的列，以便将来在 2 个数据帧之间建立联合.

我目前有这个:

for (i <- set_of_col_type_tuples) yield {val tip = Class.forName("org.apache.spark.sql.types."+i._2)df = df.withColumn(i._1, lit(null).cast(the_type))df }

如果我使用

val the_type = Class.forName("org.apache.spark.sql.types."+i._2)

我明白

错误:重载的方法值转换为替代:(to: String)org.apache.spark.sql.Column <and>(to: org.apache.spark.sql.types.DataType)org.apache.spark.sql.Column 不能应用到 (Class[?0])

如果我使用

val the_type = Class.forName("org.apache.spark.sql.types."+i._2).getName()

这是一个字符串，所以我得到:

org.apache.spark.sql.catalyst.parser.ParseException: 不匹配的输入."期待 {<EOF>, '('}(line 1, pos 3)== SQL == org.apache.spark.sql.types.StringType---^^^

所以，为了清楚起见，该集合包含这样的元组 ("col1","IntegerType"), ("col2","StringType") 而不是 ("col1","int"), ("col2","字符串").简单的强制转换 (i._2) 不起作用.

谢谢.

解决方案

你可以使用重载方法 cast，它有一个 String 作为参数:

val stringType : String = ...column.cast(stringType)

<块引用>

def cast(to: String): 列

使用规范字符串将列转换为不同的数据类型类型的表示.

您还可以扫描所有数据类型:

val types = classOf[DataTypes].getDeclaredFields().filter(f => java.lang.reflect.Modifier.isStatic(f.getModifiers())).map(f => f.get(new DataTypes()).asInstanceOf[DataType])

现在的类型是 Array[DataType].你可以把它翻译成地图:

val typeMap = types.map(t => (t.getClass.getSimpleName.replace("$", ""), t)).toMap

并在代码中使用:

column.cast(typeMap(yourType))

The simple request is I need help adding a column to a dataframe but, the column has to be empty, its type is from ...spark.sql.types and the type has to be defined from a string.

I can probably do this with ifs or case but I'm looking for something more elegant. Something that does not require writing a case for every type in org.apache.spark.sql.types

If I do this for example:

df = df.withColumn("col_name", lit(null).cast(org.apache.spark.sql.types.StringType))

It works as intended, but I have the type stored as a string,

var the_type = "StringType"

or var the_type = "org.apache.spark.sql.types.StringType"

and I can't get it to work by defining the type from the string.

For those interested here are some more details: I have a set containing tuples (col_name, col_type) both as strings and I need to add columns with the correct types for a future union between 2 dataframes.

I currently have this:

for (i <- set_of_col_type_tuples) yield {
    val tip = Class.forName("org.apache.spark.sql.types."+i._2)
    df = df.withColumn(i._1, lit(null).cast(the_type))
    df }

if I use

val the_type = Class.forName("org.apache.spark.sql.types."+i._2)

I get

error: overloaded method value cast with alternatives:   (to: String)org.apache.spark.sql.Column <and>   (to: org.apache.spark.sql.types.DataType)org.apache.spark.sql.Column  cannot be applied to (Class[?0])

if I use

val the_type = Class.forName("org.apache.spark.sql.types."+i._2).getName()

It's a string so I get:

org.apache.spark.sql.catalyst.parser.ParseException: mismatched input '.' expecting {<EOF>, '('}(line 1, pos 3)
== SQL == org.apache.spark.sql.types.StringType
---^^^

EDIT: So, just to be clear, the set contains tuples like this ("col1","IntegerType"), ("col2","StringType") not ("col1","int"), ("col2","string"). A simple cast(i._2) does not work.

Thank you.

解决方案

You can use overloaded method cast, which has a String as an argument:

val stringType : String = ...
column.cast(stringType)

def cast(to: String): Column

Casts the column to a different data type, using the canonical string representation of the type.

You can also scan for all Data Types:

val types = classOf[DataTypes]
    .getDeclaredFields()
    .filter(f => java.lang.reflect.Modifier.isStatic(f.getModifiers()))
    .map(f => f.get(new DataTypes()).asInstanceOf[DataType])

Now types is Array[DataType]. You can translate it to Map:

val typeMap = types.map(t => (t.getClass.getSimpleName.replace("$", ""), t)).toMap

and use in code:

column.cast(typeMap(yourType))

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