答复: 答复: How can I get the column data based on specific column name and then stored these data in array or list ?

[zml张明磊 <mi...@Ctrip.com>]

Yes. It’s a good method . But UDF ? What is UDF ?  U……………..D……………F ?  OK, I can learn from it.

Thanks,
Minglei.

发件人: Jeff Zhang [mailto:zjffdu@gmail.com]
发送时间: 2015年12月25日 16:00
收件人: zml张明磊
抄送: dev@spark.apache.org
主题: Re: 答复: How can I get the column data based on specific column name and then stored these data in array or list ?

You can use udf to convert one column for array type. Here's one sample


val conf = new SparkConf().setMaster("local[4]").setAppName("test")
val sc = new SparkContext(conf)
val sqlContext = new SQLContext(sc)
import sqlContext.implicits._
import sqlContext._
sqlContext.udf.register("f", (a:String) => Array(a,a))
val df1 = Seq(
  (1, "jeff", 12),
  (2, "andy", 34),
  (3, "pony", 23),
  (4, "jeff", 14)
).toDF("id", "name", "age")

val df2=df1.withColumn("name", expr("f(name)"))
df2.printSchema()
df2.show()

On Fri, Dec 25, 2015 at 3:44 PM, zml张明磊 <mi...@ctrip.com>> wrote:
Thanks, Jeff. It’s not choose some columns of a Row. It’s just choose all data in a column and convert it to an Array. Do you understand my mean ?

In Chinese
我是想基于这个列名把这一列中的所有数据都选出来，然后放到数组里面去。


发件人: Jeff Zhang [mailto:zjffdu@gmail.com<ma...@gmail.com>]
发送时间: 2015年12月25日 15:39
收件人: zml张明磊
抄送: dev@spark.apache.org<ma...@spark.apache.org>
主题: Re: How can I get the column data based on specific column name and then stored these data in array or list ?

Not sure what you mean. Do you want to choose some columns of a Row and convert it to an Arrray ?

On Fri, Dec 25, 2015 at 3:35 PM, zml张明磊 <mi...@ctrip.com>> wrote:

Hi,

       I am a new to Scala and Spark and trying to find relative API in DataFrame to solve my problem as title described. However, I just only find this API DataFrame.col(colName : String) : Column which returns an object of Column. Not the content. If only DataFrame support such API which like Column.toArray : Type is enough for me. But now, it doesn’t. How can I do can achieve this function ?

Thanks,
Minglei.



--
Best Regards

Jeff Zhang



--
Best Regards

Jeff Zhang