How to parse JsonArray in Scala and writing them in a DataFrame? - json

Question

Using my Scala HTTP Client I retrieved a response in JSON format from an API GET call.
My end goal is to write this JSON content to an AWS S3 bucket in order to make it available as a table on RedShift running a simple AWS Glue crawler.
My thinking is to parse this JSON message and somehow converting into a Spark DataFrame, so later on I can save it to my preferred S3 location in the format of .csv, .parquet, or whatever.
The JSON file looks like this
{
"response": {
"status": "OK",
"start_element": 0,
"num_elements": 100,
"categories": [
{
"id": 1,
"name": "Airlines",
"is_sensitive": false,
"last_modified": "2010-03-19 17:48:36",
"requires_whitelist_on_external": false,
"requires_whitelist_on_managed": false,
"is_brand_eligible": true,
"requires_whitelist": false,
"whitelist": {
"geos": [],
"countries_and_brands": []
}
},
{
"id": 2,
"name": "Apparel",
"is_sensitive": false,
"last_modified": "2010-03-19 17:48:36",
"requires_whitelist_on_external": false,
"requires_whitelist_on_managed": false,
"is_brand_eligible": true,
"requires_whitelist": false,
"whitelist": {
"geos": [],
"countries_and_brands": []
}
}
],
"count": 148,
"dbg_info": {
"warnings": [],
"version": "1.18.1621",
"output_term": "categories"
}
}
}
The content I would like to map to a Dataframe is the one contained by the "categories" JSON Array.
I have managed to parse the message using json4s.JsonMethods method parse this way:
val parsedJson = parse(request) \\ "categories"
Obtaining the following:
output: org.json4s.JValue = JArray(List(JObject(List((id,JInt(1)), (name,JString(Airlines)), (is_sensitive,JBool(false)), (last_modified,JString(2010-03-19 17:48:36)), (requires_whitelist_on_external,JBool(false)), (requires_whitelist_on_managed,JBool(false)), (is_brand_eligible,JBool(true)), (requires_whitelist,JBool(false)), (whitelist,JObject(List((geos,JArray(List())), (countries_and_brands,JArray(List()))))))), JObject(List((id,JInt(2)), (name,JString(Apparel)), (is_sensitive,JBool(false)), (last_modified,JString(2010-03-19 17:48:36)), (requires_whitelist_on_external,JBool(false)), (requires_whitelist_on_managed,JBool(false)), (is_brand_eligible,JBool(true)), (requires_whitelist,JBool(false)), (whitelist,JObject(List((geos,JArray(List())), (countries_and_brands,JArray(List()))))))))
However, I am completely lost on how to proceed. I have even tried using another library for Scala called uJson:
val json = (ujson.read(request))
val tuples = json("response")("categories").arr /* <-- categories is an array */ .map { item =>
(item("id"), item("name"))
This time I have only parsed two fields for testing, but this shouldn't change much. Hence, I obtained the following structure:
tuples: scala.collection.mutable.ArrayBuffer[(ujson.Value, ujson.Value, ujson.Value, ujson.Value)] = ArrayBuffer((1,"Airlines",false,"2010-03-19 17:48:36"), (2,"Apparel",false,"2010-03-19 17:48:36"))
However, also this time I do not know how to move forward and everything I try results in errors, mostly related to format incompatibility.
Please, feel free to propose any other approach to achieve my goal even if it changes totally my workflow. I rather learn something properly. Thanks

Answer 1

We can use the following code to convert JSON to Spark Dataframe/Dataset
val df00 =
spark.read.option("multiline","true").json(Seq(JSON_OUTPUT).toDS())