我试图将一个JSON字符串解析为Scala中的case类（所以我可以进行过滤数据处理等）。 经过一些研究后，我将与spray-json一起进行，因为链接上有几个例子。遗憾的是，该链接未显示如何使用具有数组的嵌套字段解析JSON。
我正在使用下面的代码在Scala笔记本上测试我的代码并且它可以正常工作。
// Dependencies
io.spray spray-json_2.10 1.3.2
import spray.json._
import DefaultJsonProtocol._ // if you don't supply your own Protocol (see below)
// simple source
val source = """{
"EventId": "29ca61f3-b8b6-41e7-8236-802fa232e7cf",
"Timestamp": "2016-03-09T20:14:07.5535193Z",
"StartTime": "2016-03-09T02:51:04.397",
"EndTime": "2016-03-09T02:51:04.397",
"ActiveStates": "{\"No Motion\":1,\"Motion Detected\":1,\"Face Detected\":1}",
"Created": "2016-03-09T02:51:04.397",
"Modified": "2016-03-09T02:51:04.397"
}"""
// simple case class
case class claX( EventId: String,
Timestamp: String,
StartTime: String,
EndTime: String,
ActiveStates: String,
Created: String,
Modified: String)
object MyJsonProtocol extends DefaultJsonProtocol {
implicit val claXFormat = jsonFormat7(claX)
}
import MyJsonProtocol._
import spray.json._
val json = source.parseJson // parse string to json
val cx0 = json.convertTo[claX] // convert to class claX
我的问题是当JSON字符串在其中包含嵌套“Product”类的数据中嵌套数组时。这是示例JSON：
{
"EventId": "29ca61f3-b8b6-41e7-8236-802fa232e7cf",
"Timestamp": "2016-03-09T20:14:07.5535193Z",
"StartTime": "2016-03-09T02:51:04.397",
"EndTime": "2016-03-09T02:51:04.397",
"ActiveStates": "{\"No Motion\":1,\"Motion Detected\":1,\"Face Detected\":1}",
"Created": "2016-03-09T02:51:04.397",
"Modified": "2016-03-09T02:51:04.397",
"Data": {
"AgeRange": {
"Name": "30 - 35"
},
"Company": {
"Id": "f3ad1744-0ead-458a-9416-852c43ccde24"
},
"CompanyType": {
"Name": "Retailer"
},
"ConnectorType": {
"Name": "Camera Capturing"
},
"Content": {
"Ids": [
"0c0f0a9a-fece-4b3e-abb4-0f508d357220"
]
},
"Customer": {
"LoyaltyId": 0
},
"DeviceRegistries": [
{
"Id": "f19f5daa-e9b9-43d0-91a7-51da4fdd0e31",
"DeviceName": "Company 3 Cooler",
"DeviceType": "CCU"
}
],
"Emotion": {
"Name": "Happy"
},
"Gender": {
"Name": "Male"
},
"Products": [
{
"Name": "Molson Canadian",
"ProductCategory": "Beverage",
"InventoryTrackingNumberType": "SKU",
"InventoryTrackingNumber": "438654935776",
"ProductPrice": {
"RetailPrice": 2.1,
"RetailPriceSymbol": "?",
"PromotionPrice": 1.8,
"PromotionPriceSymbol": "?"
}
},
{
"Name": "Coors Original",
"ProductCategory": "Beverage",
"InventoryTrackingNumberType": "SKU",
"InventoryTrackingNumber": "438654935775",
"ProductPrice": {
"RetailPrice": 1.1,
"RetailPriceSymbol": "?",
"PromotionPrice": 0.8,
"PromotionPriceSymbol": "?"
}
},
{
"Name": "Coors Light",
"ProductCategory": "Beverage",
"InventoryTrackingNumberType": "SKU",
"InventoryTrackingNumber": "438654935778",
"ProductPrice": {
"RetailPrice": 6.1,
"RetailPriceSymbol": "?",
"PromotionPrice": 5.8,
"PromotionPriceSymbol": "?"
}
},
{
"Name": "Blue Moon",
"ProductCategory": "Beverage",
"InventoryTrackingNumberType": "SKU",
"InventoryTrackingNumber": "438654935777",
"ProductPrice": {
"RetailPrice": 4.1,
"RetailPriceSymbol": "?",
"PromotionPrice": 3.8,
"PromotionPriceSymbol": "?"
}
}
],
"Race": {
"Name": "Latin"
},
"Region": {
"Name": "Region 01"
},
"SensorRegistry": {
"Name": "Company 3 Camera 01"
},
"SensorType": {
"Name": "Proximity"
},
"SfuRegistries": {
"Ids": [
"7effea8c-56dd-4905-bbc3-2158d14cd7cc",
"24a7253d-174a-44f0-8145-483cc0f45adb",
"bc970c8e-7e41-4889-859b-55c6a3f8ba5d",
"46e599f5-8082-499f-b5d0-9d611409a652"
]
},
"Shelves": {
"Ids": [
"ea442504-7d64-4c01-bdde-1eb46e53b81c",
"d6fe9c78-e21b-4a57-b620-99a7d94d46f9"
]
},
"State": {
"Name": "Face Detected"
},
"StockLevel": {
"OnHand": 0
},
"Store": {
"Id": "268c852d-86b8-4b7c-b865-2f29a3e2307e"
},
"Unit": {
"Id": "52c58781-b2bf-46ea-81ad-b9d9fbacb471"
},
"UnitType": {
"Name": "5-Shelf Cooler"
}
},
"id": "54bfd971-0fec-4e0e-87cc-851a697705e9"
}
我又制作了两个案例类来管理“产品”和“价格”
case class ProductPrice(RetailPrice: Double,
RetailPriceSymbol: Double,
PromotionPrice: Double,
PromotionPriceSymbol: Double)
case class Product(Name: String,
ProductCategory: String,
InventoryTrackingNumberType: String,
InventoryTrackingNumber: String,
ProductPrice: ProductPrice)
我不知道的是你如何将它结合起来，以便将JSON中的数据节点正确解析为claXBig（其中JSON字符串中的所有内容都被正确解析）。 这就是我绊倒的地方：
case class claX2( EventId: String,
Timestamp: String,
StartTime: String,
EndTime: String,
ActiveStates: String,
Created: String,
Modified: String,
Data: Map[String, Any]) // <- how do I parse this and the nested products
object MyJsonProtocol2 extends DefaultJsonProtocol {
implicit val claXFormat2 = jsonFormat8(claX2)
}
我还尝试使用代码here加载更大的JSON（这些'事件'的集合）
所以我在下面添加了一个新的case类来处理'event's或claX2
的数组case class claX2Collection(clax2s: Array[claX2])
extends IndexedSeq[claX2] {
def apply(index: Int) = clax2s(index) //<- not sure what this mean
def length = clax2s.length // or whether index is doing anything
}
我认为claX2Collection在编译时是正确的。但是下面的代码肯定是错误的，但需要从JSON数组加载事件集合
implicit object claX2JsonFormat extends RootJsonFormat[claX2]{
def write(f: claX2) = {
val buf = scala.collection.mutable.ArrayBuffer(
"events" -> JsString("claX2"), // <- error
"Timestamp" -> JsObject(f.Timestamp), // error
"StartTime" -> JsObject(f.StartTime), // error
"EndTime" -> JsObject(f.EndTime), // error
"ActiveStates" -> JsObject(f.ActiveStates), // error
"Created" -> JsObject(f.Created), // errors
"Modified" -> JsObject(f.Modified), // errors
"Data" -> JsObject(f.Data) // errors
)
}
def read(value:JsValue) = {
val jso = value.asJsObject
// not sure what to do here but
// assuming I have to pick out
val EventId = jso.fields.get("EventId")
Timestamp = jso.fields.get("Timestamp")
StartTime = jso.fields.get("StartTime")
EndTime = jso.fields.get("EndTime")
ActiveStates = jso.fields.get("ActiveStates")
Created = jso.fields.get("Created")
Modified = jso.fields.get("Modified")
Data = jso.fields.get("Data")
claX2(EventId,Timestamp,StartTime,EndTime,ActiveStates,Created,
Modified,Data)
}
}
当修复它时，它应该能够读取此JSON：
{
"type": "EventCollection",
"events": [
{
"EventId": "29ca61f3-b8b6-41e7-8236-802fa232e7cf",
"Timestamp": "2016-03-09T20:14:07.5535193Z",
"StartTime": "2016-03-09T02:51:04.397",
"EndTime": "2016-03-09T02:51:04.397",
"ActiveStates": "{\"No Motion\":1,\"Motion Detected\":1,\"Face Detected\":1}",
"Created": "2016-03-09T02:51:04.397",
"Modified": "2016-03-09T02:51:04.397",
"Data": {
"AgeRange": {
"Name": "30 - 35"
},
"Company": {
"Id": "f3ad1744-0ead-458a-9416-852c43ccde24"
},
"CompanyType": {
"Name": "Retailer"
},
"ConnectorType": {
"Name": "Camera Capturing"
},
"Content": {
"Ids": [
"0c0f0a9a-fece-4b3e-abb4-0f508d357220"
]
},
"Customer": {
"LoyaltyId": 0
},
"DeviceRegistries": [
{
"Id": "f19f5daa-e9b9-43d0-91a7-51da4fdd0e31",
"DeviceName": "Company 3 Cooler",
"DeviceType": "CCU"
}
],
"Emotion": {
"Name": "Happy"
},
"Gender": {
"Name": "Male"
},
"Products": [
{
"Name": "Molson Canadian",
"ProductCategory": "Beverage",
"InventoryTrackingNumberType": "SKU",
"InventoryTrackingNumber": "438654935776",
"ProductPrice": {
"RetailPrice": 2.1,
"RetailPriceSymbol": "?",
"PromotionPrice": 1.8,
"PromotionPriceSymbol": "?"
}
},
{
"Name": "Coors Original",
"ProductCategory": "Beverage",
"InventoryTrackingNumberType": "SKU",
"InventoryTrackingNumber": "438654935775",
"ProductPrice": {
"RetailPrice": 1.1,
"RetailPriceSymbol": "?",
"PromotionPrice": 0.8,
"PromotionPriceSymbol": "?"
}
},
{
"Name": "Coors Light",
"ProductCategory": "Beverage",
"InventoryTrackingNumberType": "SKU",
"InventoryTrackingNumber": "438654935778",
"ProductPrice": {
"RetailPrice": 6.1,
"RetailPriceSymbol": "?",
"PromotionPrice": 5.8,
"PromotionPriceSymbol": "?"
}
},
{
"Name": "Blue Moon",
"ProductCategory": "Beverage",
"InventoryTrackingNumberType": "SKU",
"InventoryTrackingNumber": "438654935777",
"ProductPrice": {
"RetailPrice": 4.1,
"RetailPriceSymbol": "?",
"PromotionPrice": 3.8,
"PromotionPriceSymbol": "?"
}
}
],
"Race": {
"Name": "Latin"
},
"Region": {
"Name": "Region 01"
},
"SensorRegistry": {
"Name": "Company 3 Camera 01"
},
"SensorType": {
"Name": "Proximity"
},
"SfuRegistries": {
"Ids": [
"7effea8c-56dd-4905-bbc3-2158d14cd7cc",
"24a7253d-174a-44f0-8145-483cc0f45adb",
"bc970c8e-7e41-4889-859b-55c6a3f8ba5d",
"46e599f5-8082-499f-b5d0-9d611409a652"
]
},
"Shelves": {
"Ids": [
"ea442504-7d64-4c01-bdde-1eb46e53b81c",
"d6fe9c78-e21b-4a57-b620-99a7d94d46f9"
]
},
"State": {
"Name": "Face Detected"
},
"StockLevel": {
"OnHand": 0
},
"Store": {
"Id": "268c852d-86b8-4b7c-b865-2f29a3e2307e"
},
"Unit": {
"Id": "52c58781-b2bf-46ea-81ad-b9d9fbacb471"
},
"UnitType": {
"Name": "5-Shelf Cooler"
}
},
"id": "54bfd971-0fec-4e0e-87cc-851a697705e9"
},
{
"EventId": "29ca61f3-b8b6-41e7-8236-802fa232e7cf",
"Timestamp": "2016-03-09T20:14:07.5535193Z",
"StartTime": "2016-03-09T02:51:04.397",
"EndTime": "2016-03-09T02:51:04.397",
"ActiveStates": "{\"No Motion\":1,\"Motion Detected\":1,\"Face Detected\":1}",
"Created": "2016-03-09T02:51:04.397",
"Modified": "2016-03-09T02:51:04.397",
"Data": {
"AgeRange": {
"Name": "30 - 35"
},
"Company": {
"Id": "f3ad1744-0ead-458a-9416-852c43ccde24"
},
"CompanyType": {
"Name": "Retailer"
},
"ConnectorType": {
"Name": "Camera Capturing"
},
"Content": {
"Ids": [
"0c0f0a9a-fece-4b3e-abb4-0f508d357220"
]
},
"Customer": {
"LoyaltyId": 0
},
"DeviceRegistries": [
{
"Id": "f19f5daa-e9b9-43d0-91a7-51da4fdd0e31",
"DeviceName": "Company 3 Cooler",
"DeviceType": "CCU"
}
],
"Emotion": {
"Name": "Happy"
},
"Gender": {
"Name": "Male"
},
"Products": [
{
"Name": "Molson Canadian",
"ProductCategory": "Beverage",
"InventoryTrackingNumberType": "SKU",
"InventoryTrackingNumber": "438654935776",
"ProductPrice": {
"RetailPrice": 2.1,
"RetailPriceSymbol": "?",
"PromotionPrice": 1.8,
"PromotionPriceSymbol": "?"
}
},
{
"Name": "Coors Original",
"ProductCategory": "Beverage",
"InventoryTrackingNumberType": "SKU",
"InventoryTrackingNumber": "438654935775",
"ProductPrice": {
"RetailPrice": 1.1,
"RetailPriceSymbol": "?",
"PromotionPrice": 0.8,
"PromotionPriceSymbol": "?"
}
},
{
"Name": "Coors Light",
"ProductCategory": "Beverage",
"InventoryTrackingNumberType": "SKU",
"InventoryTrackingNumber": "438654935778",
"ProductPrice": {
"RetailPrice": 6.1,
"RetailPriceSymbol": "?",
"PromotionPrice": 5.8,
"PromotionPriceSymbol": "?"
}
},
{
"Name": "Blue Moon",
"ProductCategory": "Beverage",
"InventoryTrackingNumberType": "SKU",
"InventoryTrackingNumber": "438654935777",
"ProductPrice": {
"RetailPrice": 4.1,
"RetailPriceSymbol": "?",
"PromotionPrice": 3.8,
"PromotionPriceSymbol": "?"
}
}
],
"Race": {
"Name": "Latin"
},
"Region": {
"Name": "Region 01"
},
"SensorRegistry": {
"Name": "Company 3 Camera 01"
},
"SensorType": {
"Name": "Proximity"
},
"SfuRegistries": {
"Ids": [
"7effea8c-56dd-4905-bbc3-2158d14cd7cc",
"24a7253d-174a-44f0-8145-483cc0f45adb",
"bc970c8e-7e41-4889-859b-55c6a3f8ba5d",
"46e599f5-8082-499f-b5d0-9d611409a652"
]
},
"Shelves": {
"Ids": [
"ea442504-7d64-4c01-bdde-1eb46e53b81c",
"d6fe9c78-e21b-4a57-b620-99a7d94d46f9"
]
},
"State": {
"Name": "Face Detected"
},
"StockLevel": {
"OnHand": 0
},
"Store": {
"Id": "268c852d-86b8-4b7c-b865-2f29a3e2307e"
},
"Unit": {
"Id": "52c58781-b2bf-46ea-81ad-b9d9fbacb471"
},
"UnitType": {
"Name": "5-Shelf Cooler"
}
},
"id": "54bfd971-0fec-4e0e-87cc-851a697705e9"
}
]
}
答案 0 :(得分：2)
这是完整的解决方案 解决方案和数据文件的git repo是here
import spray.json._
import DefaultJsonProtocol._
object parseJson {
def main(args: Array[String]){
// case classes for all the nested information in the
case class Ids(Ids: Seq[String])
case class Id(Id: String)
case class Name(Name: String)
case class OnHand(OnHand: Int)
case class LoyaltyId(LoyaltyId: Int)
case class ProductPrice(RetailPrice: Double,
RetailPriceSymbol: String,
PromotionPrice: Double,
PromotionPriceSymbol: String)
case class Product(Name: String,
ProductCategory: String,
InventoryTrackingNumberType: String,
InventoryTrackingNumber: String,
ProductPrice: ProductPrice)
case class Data(Content: Ids,
SfuRegistries: Ids,
AgeRange: Name,
Company: Id,
SensorType: Name,
StockLevel: OnHand,
Region: Name,
UnitType: Name,
Emotion: Name,
Shelves: Ids,
Customer: LoyaltyId,
DeviceRegistries: Seq[Map[String, String]],
ConnectorType: Name,
CompanyType: Name,
State: Name,
Gender: Name,
SensorRegistry: Name,
Race: Name,
Store: Id,
Products: Seq[Product])
case class Element(EventId: String,
Timestamp: String,
StartTime: String,
EndTime: String,
ActiveStates: String,
Created: String,
Modified: String,
Data: Data)
// This is the code that is blowing up
case class RootCollection(items: Array[Element]) extends IndexedSeq[Element]{
def apply(index: Int) = items(index)
def length = items.length
}
object MyJsonProtocol extends DefaultJsonProtocol {
implicit val nameFormat = jsonFormat1(Name)
implicit val productPriceFormat = jsonFormat4(ProductPrice)
implicit val productFormat = jsonFormat5(Product)
implicit val loyaltyIdFormat = jsonFormat1(LoyaltyId)
implicit val onHandFormat = jsonFormat1(OnHand)
implicit val idFormat = jsonFormat1(Id)
implicit val idsFormat = jsonFormat1(Ids)
implicit val dateFormat = jsonFormat20(Data)
implicit val ElementFormat = jsonFormat8(Element)
implicit object RootCollectionFormat extends RootJsonFormat[RootCollection] {
def read(value: JsValue) = RootCollection(value.convertTo[Array[Element]])
def write(f: RootCollection) = JsArray(f.toJson)
}
}
import MyJsonProtocol._
println("Running Parse JSON")
val input = scala.io.Source.fromFile("sample2.json")("UTF-8").mkString.parseJson
//println("JSON string read:")
//println(input)
val jsonCollection = input.convertTo[RootCollection]
// print some items
jsonCollection.map(y => y.Data.Products.map(x => println(x)))
println(jsonCollection.length)
}
}
答案 1 :(得分：0)
更像是： - ）
TableEntity case class claX2(
EventId: String,
Timestamp: String,
StartTime: String,
EndTime: String,
ActiveStates: String,
Created: String,
Modified: String,
Data: Data)
case class Data(Content: Ids,
SfuRegistries: Ids,
AgeRange: Name,
Company: Id,
SensorType: Name,
StockLevel: OnHand,
Region: Name,
UnitType: Name,
Emotion: Name,
Shelves: Ids,
Customer: LoyaltyId,
DeviceRegistries: Seq[Map[String, String]],
ConnectorType: Name,
CompanyType: Name,
State: Name,
Gender: Name,
SensorRegistry: Name,
Race: Name,
Store: Id,
Products: Seq[Product])