I have a file which has bunch of columns and one column called jsonstring
is of string type which has json strings in it… let\'s say the format is the following
With Spark 2.2 you could use the function from_json which does the JSON parsing for you.
from_json(e: Column, schema: String, options: Map[String, String]): Column parses a column containing a JSON string into a
StructType
orArrayType
ofStructTypes
with the specified schema.
With the support for flattening nested columns by using *
(star) that seems the best solution.
// the input dataset (just a single JSON blob)
val jsonstrings = Seq("""{
"key1": "value1",
"key2": {
"level2key1": "level2value1",
"level2key2": "level2value2"
}
}""").toDF("jsonstring")
// define the schema of JSON messages
import org.apache.spark.sql.types._
val key2schema = new StructType()
.add($"level2key1".string)
.add($"level2key2".string)
val schema = new StructType()
.add($"key1".string)
.add("key2", key2schema)
scala> schema.printTreeString
root
|-- key1: string (nullable = true)
|-- key2: struct (nullable = true)
| |-- level2key1: string (nullable = true)
| |-- level2key2: string (nullable = true)
val messages = jsonstrings
.select(from_json($"jsonstring", schema) as "json")
.select("json.*") // <-- flattening nested fields
scala> messages.show(truncate = false)
+------+---------------------------+
|key1 |key2 |
+------+---------------------------+
|value1|[level2value1,level2value2]|
+------+---------------------------+
scala> messages.select("key1", "key2.*").show(truncate = false)
+------+------------+------------+
|key1 |level2key1 |level2key2 |
+------+------------+------------+
|value1|level2value1|level2value2|
+------+------------+------------+
You can use withColumn + udf + json4s:
import org.json4s.{DefaultFormats, MappingException}
import org.json4s.jackson.JsonMethods._
import org.apache.spark.sql.functions._
def getJsonContent(jsonstring: String): (String, String) = {
implicit val formats = DefaultFormats
val parsedJson = parse(jsonstring)
val value1 = (parsedJson \ "key1").extract[String]
val level2value1 = (parsedJson \ "key2" \ "level2key1").extract[String]
(value1, level2value1)
}
val getJsonContentUDF = udf((jsonstring: String) => getJsonContent(jsonstring))
df.withColumn("parsedJson", getJsonContentUDF(df("jsonstring")))