在读取/加载时将原始JSON保留为Spark DataFrame中的列？

Posted 2021-03-28

在将数据读入Spark DataFrame时，我一直在寻找一种将原始（JSON）数据添加为列的方法。我有一种方法可以通过连接执行此操作，但我希望有一种方法可以在使用Spark 2.2.x +的单个操作中执行此操作。

例如数据：

{"team":"Golden Knights","colors":"gold,red,black","origin":"Las Vegas"}
{"team":"Sharks","origin": "San Jose", "eliminated":"true"}
{"team":"Wild","colors":"red,green,gold","origin":"Minnesota"}

执行时：

val logs = sc.textFile("/Users/vgk/data/tiny.json") // example data file
spark.read.json(logs).show

可以预见，我们得到：

+--------------+----------+--------------------+--------------+
|        colors|eliminated|              origin|          team|
+--------------+----------+--------------------+--------------+
|gold,red,black|      null|           Las Vegas|Golden Knights|
|          null|      true|            San Jose|        Sharks|
|red,green,gold|      null|           Minnesota|          Wild|
|red,white,blue|     false|District of Columbia|      Capitals|
+--------------+----------+--------------------+--------------+

我在初始加载时想要的是上面的内容，但是将原始JSON数据作为附加列。例如（截断的原始值）：

+--------------+-------------------------------+--------------+--------------------+
|        colors|eliminated|              origin|          team|               value|
+--------------+----------+--------------------+--------------+--------------------+
|red,white,blue|     false|District of Columbia|      Capitals|{"colors":"red,wh...|
|gold,red,black|      null|           Las Vegas|Golden Knights|{"colors":"gold,r...|
|          null|      true|            San Jose|        Sharks|{"eliminated":"tr...|
|red,green,gold|      null|           Minnesota|          Wild|{"colors":"red,gr...|
+--------------+----------+--------------------+--------------+--------------------+

一个非理想的解决方案涉及一个联接：

val logs = sc.textFile("/Users/vgk/data/tiny.json")
val df = spark.read.json(logs).withColumn("uniqueID",monotonically_increasing_id)
val rawdf = df.toJSON.withColumn("uniqueID",monotonically_increasing_id)
df.join(rawdf, "uniqueID")

这导致与上面相同的数据帧，但添加和添加uniqueID列。另外，json是从DF渲染的，不一定是“原始”数据。在实践中它们是相同的，但对于我的用例，实际的原始数据是更可取的。

有人知道一个解决方案会将原始JSON数据捕获为加载时的附加列吗？

答案

如果你有一个你收到的数据的模式，那么你可以使用from_json和schema获取所有字段并保持raw字段，因为它是

val logs = spark.sparkContext.textFile(path) // example data file

val schema = StructType(
  StructField("team", StringType, true)::
  StructField("colors", StringType, true)::
  StructField("eliminated", StringType, true)::
  StructField("origin", StringType, true)::Nil
)

logs.toDF("values")
    .withColumn("json", from_json($"values", schema))
    .select("values", "json.*")

    .show(false)

输出：

+------------------------------------------------------------------------+--------------+--------------+----------+---------+
|values                                                                  |team          |colors        |eliminated|origin   |
+------------------------------------------------------------------------+--------------+--------------+----------+---------+
|{"team":"Golden Knights","colors":"gold,red,black","origin":"Las Vegas"}|Golden Knights|gold,red,black|null      |Las Vegas|
|{"team":"Sharks","origin": "San Jose", "eliminated":"true"}             |Sharks        |null          |true      |San Jose |
|{"team":"Wild","colors":"red,green,gold","origin":"Minnesota"}          |Wild          |red,green,gold|null      |Minnesota|
+------------------------------------------------------------------------+--------------+--------------+----------+---------+

希望他的帮助！

另一答案

您可以简单地将to_json内置函数与.withColumn函数结合使用

val logs = sc.textFile("/Users/vgk/data/tiny.json")
val df = spark.read.json(logs)
import org.apache.spark.sql.functions._
df.withColumn("value", to_json(struct(df.columns.map(col): _*))).show(false)

甚至更好，不要使用sparkContext的textFile读作rdd，只需使用sparkSession读取json文件为

val df = spark.read.json("/Users/vgk/data/tiny.json")

import org.apache.spark.sql.functions._
df.withColumn("value", to_json(struct(df.columns.map(col): _*))).show(false)

你应该得到

+--------------+----------+---------+--------------+------------------------------------------------------------------------+
|colors        |eliminated|origin   |team          |value                                                                   |
+--------------+----------+---------+--------------+------------------------------------------------------------------------+
|gold,red,black|null      |Las Vegas|Golden Knights|{"colors":"gold,red,black","origin":"Las Vegas","team":"Golden Knights"}|
|null          |true      |San Jose |Sharks        |{"eliminated":"true","origin":"San Jose","team":"Sharks"}               |
|red,green,gold|null      |Minnesota|Wild          |{"colors":"red,green,gold","origin":"Minnesota","team":"Wild"}          |
+--------------+----------+---------+--------------+------------------------------------------------------------------------+