[英]Spark from_json - StructType and ArrayType
I have a data set that comes in as XML, and one of the nodes contains JSON. 我有一个以XML形式出现的数据集,其中一个节点包含JSON。 Spark is reading this in as a StringType, so I am trying to use from_json() to convert the JSON to a DataFrame.
Spark正在将其作为StringType读取,因此我尝试使用from_json()将JSON转换为DataFrame。
I am able to convert a string of JSON, but how do I write the schema to work with an Array? 我能够转换一串JSON,但是如何编写模式以使用数组呢?
String without Array - Working nicely 没有数组的字符串 - 工作得很好
import org.apache.spark.sql.functions._
val schemaExample = new StructType()
.add("FirstName", StringType)
.add("Surname", StringType)
val dfExample = spark.sql("""select "{ \"FirstName\":\"Johnny\", \"Surname\":\"Boy\" }" as theJson""")
val dfICanWorkWith = dfExample.select(from_json($"theJson", schemaExample))
dfICanWorkWith.collect()
// Results \\
res19: Array[org.apache.spark.sql.Row] = Array([[Johnny,Boy]])
String with an Array - Can't figure this one out 带有数组的字符串 - 无法解决这个问题
import org.apache.spark.sql.functions._
val schemaExample2 = new StructType()
.add("", ArrayType(new StructType()
.add("FirstName", StringType)
.add("Surname", StringType)
)
)
val dfExample2= spark.sql("""select "[{ \"FirstName\":\"Johnny\", \"Surname\":\"Boy\" }, { \"FirstName\":\"Franky\", \"Surname\":\"Man\" }" as theJson""")
val dfICanWorkWith = dfExample2.select(from_json($"theJson", schemaExample2))
dfICanWorkWith.collect()
// Result \\
res22: Array[org.apache.spark.sql.Row] = Array([null])
The problem is that you don't have a fully qualified json. 问题是你没有完全合格的json。 Your json is missing a couple of things:
你的json缺少一些东西:
Try replacing it with: 尝试将其替换为:
val dfExample2= spark.sql("""select "{\"\":[{ \"FirstName\":\"Johnny\", \"Surname\":\"Boy\" }, { \"FirstName\":\"Franky\", \"Surname\":\"Man\" }]}" as theJson""")
and you will get: 你会得到:
scala> dfICanWorkWith.collect()
res12: Array[org.apache.spark.sql.Row] = Array([[WrappedArray([Johnny,Boy], [Franky,Man])]])
as of spark 2.4 the schema_of_json
function helps: 从spark 2.4开始,
schema_of_json
函数有助于:
> SELECT schema_of_json('[{"col":0}]');
array<struct<col:int>>
in your case you can then use the below code to parse that array of son objects: 在您的情况下,您可以使用以下代码来解析该子对象数组:
scala> spark.sql("""select from_json("[{ \"FirstName\":\"Johnny\", \"Surname\":\"Boy\" }, { \"FirstName\":\"Franky\", \"Surname\":\"Man\" }]", 'array<struct<FirstName:string,Surname:string>>' ) as theJson""").show(false)
+------------------------------+
|theJson |
+------------------------------+
|[[Johnny, Boy], [Franky, Man]]|
+------------------------------+
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