如何将新的Struct列添加到DataFrame

Question

我目前正在尝试从MongoDB中提取数据库,并使用Spark将其提取到ElasticSearch中geo_points.

Mongo数据库具有纬度和经度值,但ElasticSearch要求将它们转换为geo_point类型.

Spark中是否有一种方法可以将列lat和lon列复制到一个array或struct哪个新列？

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Answer 1

我假设您从某种扁平模式开始,如下所示:

root
 |-- lat: double (nullable = false)
 |-- long: double (nullable = false)
 |-- key: string (nullable = false)

首先让我们创建示例数据:

import org.apache.spark.sql.Row
import org.apache.spark.sql.functions.{col, udf}
import org.apache.spark.sql.types._

val rdd = sc.parallelize(
    Row(52.23, 21.01, "Warsaw") :: Row(42.30, 9.15, "Corte") :: Nil)

val schema = StructType(
    StructField("lat", DoubleType, false) ::
    StructField("long", DoubleType, false) ::
    StructField("key", StringType, false) ::Nil)

val df = sqlContext.createDataFrame(rdd, schema)

一种简单的方法是使用udf和case类:

case class Location(lat: Double, long: Double)
val makeLocation = udf((lat: Double, long: Double) => Location(lat, long))

val dfRes = df.
   withColumn("location", makeLocation(col("lat"), col("long"))).
   drop("lat").
   drop("long")

dfRes.printSchema

我们得到了

root
 |-- key: string (nullable = false)
 |-- location: struct (nullable = true)
 |    |-- lat: double (nullable = false)
 |    |-- long: double (nullable = false)

一种困难的方法是转换数据并在之后应用模式:

val rddRes = df.
    map{case Row(lat, long, key) => Row(key, Row(lat, long))}

val schemaRes = StructType(
    StructField("key", StringType, false) ::
    StructField("location", StructType(
        StructField("lat", DoubleType, false) ::
        StructField("long", DoubleType, false) :: Nil
    ), true) :: Nil 
)

sqlContext.createDataFrame(rddRes, schemaRes).show

我们得到了预期的输出

+------+-------------+
|   key|     location|
+------+-------------+
|Warsaw|[52.23,21.01]|
| Corte|  [42.3,9.15]|
+------+-------------+

从头开始创建嵌套模式可能很乏味,所以如果可以,我会推荐第一种方法.如果您需要更复杂的结构,它可以很容易地扩展:

case class Pin(location: Location)
val makePin = udf((lat: Double, long: Double) => Pin(Location(lat, long))

df.
    withColumn("pin", makePin(col("lat"), col("long"))).
    drop("lat").
    drop("long").
    printSchema

我们得到预期的输出:

root
 |-- key: string (nullable = false)
 |-- pin: struct (nullable = true)
 |    |-- location: struct (nullable = true)
 |    |    |-- lat: double (nullable = false)
 |    |    |-- long: double (nullable = false)

遗憾的是,您无法控制nullable字段,因此如果对您的项目很重要,则必须指定模式.

最后你可以使用struct1.4中介绍的功能:

import org.apache.spark.sql.functions.struct

df.select($"key", struct($"lat", $"long").alias("location"))

Answer 2

尝试这个：

import org.apache.spark.sql.functions._

df.registerTempTable("dt")

dfres = sql("select struct(lat,lon) as colName from dt")