Parse JSON with map of list - json

Question

I am new to scala and JSON parsing and need some help. I need to parse the complex JSON (below) to get the values of "name" in "dimension" key i.e I need PLATFORM and OS_VERSION.
I tried multiple options, but it is not working. Any help is appreciated
This is a snippet of the code I tried, but I am not able to proceed further in parsing the list. I believe the 'ANY' keyword is causing some mismatch / issues.
import org.json4s._
import org.json4s.jackson.JsonMethods._
implicit val formats = org.json4s.DefaultFormats
val mapJSON = parse(tmp).extract[Map[String, Any]]
println(mapJSON)
//for ((k,v) <- mapJSON) printf("key: %s, value: %s\n", k, v)
val list_map = mapJSON("dimensions")
{
"uuid": "uuidddd",
"last_modified": 1559080222953,
"version": "2.6.1.0",
"name": "FULL_DAY_2_mand_date",
"is_draft": false,
"model_name": "FULL_DAY_1_may05",
"description": "",
"null_string": null,
"dimensions": [
{
"name": "PLATFORM",
"table": "tbl1",
"column": "PLATFORM",
"derived": null
},
{
"name": "OS_VERSION",
"table": "tbl1",
"column": "OS_VERSION",
"derived": null
},
],
"measures": [
{
"name": "_COUNT_",
"function": {
"expression": "COUNT",
"parameter": {
"type": "constant",
"value": "1"
},
"returntype": "bigint"
}
},
{
"name": "UU",
"function": {
"expression": "COUNT_DISTINCT",
"parameter": {
"type": "column",
"value": "tbl1.USER_ID"
},
"returntype": "hllc(12)"
}
},
{
"name": "CONT_SIZE",
"function": {
"expression": "SUM",
"parameter": {
"type": "column",
"value": "tbl1.SIZE"
},
"returntype": "bigint"
}
},
{
"name": "CONT_COUNT",
"function": {
"expression": "SUM",
"parameter": {
"type": "column",
"value": "tbl1.COUNT"
},
"returntype": "bigint"
}
}
],
"dictionaries": [],
"rowkey": {
"rowkey_columns": [
{
"column": "tbl1.OS_VERSION",
"encoding": "dict",
"encoding_version": 1,
"isShardBy": false
},
{
"column": "tbl1.PLATFORM",
"encoding": "dict",
"encoding_version": 1,
"isShardBy": false
},
{
"column": "tbl1.DEVICE_FAMILY",
"encoding": "dict",
"encoding_version": 1,
"isShardBy": false
}
]
},
"hbase_mapping": {
"column_family": [
{
"name": "F1",
"columns": [
{
"qualifier": "M",
"measure_refs": [
"_COUNT_",
"CONT_SIZE",
"CONT_COUNT"
]
}
]
},
{
"name": "F2",
"columns": [
{
"qualifier": "M",
"measure_refs": [
"UU"
]
}
]
}
]
},
"aggregation_groups": [
{
"includes": [
"tbl1.PLATFORM",
"tbl1.OS_VERSION"
],
"select_rule": {
"hierarchy_dims": [],
"mandatory_dims": [
"tbl1.DATE_HR"
],
"joint_dims": []
}
}
],
"signature": "ttrrs==",
"notify_list": [],
"status_need_notify": [
"ERROR",
"DISCARDED",
"SUCCEED"
],
"partition_date_start": 0,
"partition_date_end": 3153600000000,
"auto_merge_time_ranges": [
604800000,
2419200000
],
"volatile_range": 0,
"retention_range": 0,
"engine_type": 4,
"storage_type": 2,
"override_kylin_properties": {
"job.queuename": "root.production.P0",
"is-mandatory-only-valid": "true"
},
"cuboid_black_list": [],
"parent_forward": 3,
"mandatory_dimension_set_list": [],
"snapshot_table_desc_list": []
}

Answer 1

You need to make more specific classes for parsing the data, something like this:
case class Dimension(name: String, table: String, column: String)
case class AllData(uuid: String, dimensions: List[Dimension])
val data = parse(tmp).extract[AllData]
val names = data.dimensions.map(_.name)