Creating a Kotlin data class without parameters - json

hope I can get some valued assistance with a little issue I'm trying to work.
I've got an API endpoint which is sending data with the following request schema:
{
"type": String,
"coordinates": [
0.949492,
48.77163
]
}
As can be seen; the coordinates from the search are provided as two INT values, without parameters.
I'm trying to create an automated test for this, and I've put the above in a data class so it can be used all over the suite as-needed.
My data class is currently looking like the below example, but I don't know how to properly define a list for coordinates without a val or var parameter. I've defined it as a var called "list" for now so it stops throwing compilation errors. How should I be representing this list of coordinates?
data class SearchRequest(
val type: String,
val coordinates: List<Coordinates>
)
data class Coordinates(
var list: Int
)

The second parameter is a list of Float values, there is no need to create a separate class for that, Float can be used:
data class SearchRequest(
val type: String,
val coordinates: List<Float>
)

In addition to the answers above, you can also download a plugin from android studio that does this for you by just pasting the API's JSON format. The plugin name is JSON to Kotlin class converter, I think.👍🏻

Related

How to split the data of NodeObject in Apache Flink

I'm using Flink to process the data coming from some data source (such as Kafka, Pravega etc).
In my case, the data source is Pravega, which provided me a flink connector.
My data source is sending me some JSON data as below:
{"key": "value"}
{"key": "value2"}
{"key": "value3"}
...
...
Here is my piece of code:
PravegaDeserializationSchema<ObjectNode> adapter = new PravegaDeserializationSchema<>(ObjectNode.class, new JavaSerializer<>());
FlinkPravegaReader<ObjectNode> source = FlinkPravegaReader.<ObjectNode>builder()
.withPravegaConfig(pravegaConfig)
.forStream(stream)
.withDeserializationSchema(adapter)
.build();
final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
DataStream<ObjectNode> dataStream = env.addSource(source).name("Pravega Stream");
dataStream.map(new MapFunction<ObjectNode, String>() {
#Override
public String map(ObjectNode node) throws Exception {
return node.toString();
}
})
.keyBy("word") // ERROR
.timeWindow(Time.seconds(10))
.sum("count");
As you see, I used the FlinkPravegaReader and a proper deserializer to get the JSON stream coming from Pravega.
Then I try to transform the JSON data into a String, KeyBy them and count them.
However, I get an error:
The program finished with the following exception:
Field expression must be equal to '*' or '_' for non-composite types.
org.apache.flink.api.common.operators.Keys$ExpressionKeys.<init>(Keys.java:342)
org.apache.flink.streaming.api.datastream.DataStream.keyBy(DataStream.java:340)
myflink.StreamingJob.main(StreamingJob.java:114)
It seems that KeyBy threw this exception.
Well, I'm not a Flink expert so I don't know why. I've read the source code of the official example WordCount. In that example, there is a custtom splitter, which is used to split the String data into words.
So I'm thinking if I need to use some kind of splitter in this case too? If so, what kind of splitter should I use? Can you show me an example? If not, why did I get such an error and how to solve it?
I guess you have read the document about how to specify keys
Specify keys
The example codes use keyby("word") because word is a field of POJO type WC.
// some ordinary POJO (Plain old Java Object)
public class WC {
public String word;
public int count;
}
DataStream<WC> words = // [...]
DataStream<WC> wordCounts = words.keyBy("word").window(/*window specification*/);
In your case, you put a map operator before keyBy, and the output of this map operator is a string. So there is obviously no word field in your case. If you actually want to group this string stream, you need to write it like this .keyBy(String::toString)
Or you can even implement a customized keySelector to generate your own key.
Customized Key Selector

Kotlin - Array property in data class error

I'm modelling some JSON - and using the following lines
data class Metadata(
val id: String,
val creators: Array<CreatorsModel>
)
along with:
data class CreatorsModel (
val role: String,
val name: String
)
However keep seeing the error: Array property in data class error.
Any ideas why this is?
FYI, the JSON looks like:
{
"id": "123",
"creators": [{
"role": "Author",
"name": "Marie"
}
]
}
In Kotlin you should aim to use List instead of Array where possible. Array has some JVM implications, and although the compiler will let you, the IDE may prompt you to override equals and hashcode manually. Using List will make things much simpler.
You can find out more about the difference here: Difference between List and Array types in Kotlin

How to properly use JSON.parse in kotlinjs with enums?

During my fresh adventures with kotlin-react I hit a hard stop when trying to parse some data from my backend which contains enum values.
Spring-Boot sends the object in JSON form like this:
{
"id": 1,
"username": "Johnny",
"role": "CLIENT"
}
role in this case is the enum value and can have the two values CLIENT and LECTURER. If I were to parse this with a java library or let this be handled by Spring-Boot, role would be parsed to the corresponding enum value.
With kotlin-js' JSON.parse, that wouldn't work and I would have a simple string value in there.
After some testing, I came up with this snippet
val json = """{
"id": 1,
"username": "Johnny",
"role": "CLIENT",
}"""
val member: Member = JSON.parse(json) { key: String, value: Any? ->
if (key == "role") Member.Role.valueOf(value.toString())
else value
}
in which I manually have to define the conversion from the string value to the enum.
Is there something I am missing that would simplify this behaviour?
(I am not referring to using ids for the JSON and the looking those up, etc. I am curious about some method in Kotlin-JS)
I have the assumption there is not because the "original" JSON.parse in JS doesn't do this and Kotlin does not add any additional stuff in there but I still have hope!
As far as I know, no.
The problem
Kotlin.JS produces an incredibly weird type situation when deserializing using the embedded JSON class, which actually is a mirror for JavaScript's JSON class. While I haven't done much JavaScript, its type handling is near non-existent. Only manual throws can enforce it, so JSON.parse doesn't care if it returns a SomeCustomObject or a newly created object with the exact same fields.
As an example of that, if you have two different classes with the same field names (no inheritance), and have a function that accepts a variable, it doesn't care which of those (or a third for that matter) it receives as long as the variables it tries accessing on the class exists.
The type issues manifest themselves into Kotlin. Now wrapping it back to Kotlin, consider this code:
val json = """{
"x": 1, "y": "yes", "z": {
"x": 42, "y": 314159, "z": 444
}
}""".trimIndent()
data class SomeClass(val x: Int, val y: String, val z: Struct)
data class Struct(val x: Int, val y: Int, val z: Int)
fun main(args: Array<String>) {
val someInstance = JSON.parse<SomeClass>(json)
if(someInstance.z::class != Struct::class) {
println("Incompatible types: Required ${Struct::class}, found ${someInstance.z::class}");
}
}
What would you expect this to print? The natural would be to expect a Struct. The type is also explicitly declared
Unfortunately, that is not the case. Instead, it prints:
Incompatible types: Required class Struct, found class Any
The point
The embedded JSON de/serializer isn't good with types. You might be able to fix this by using a different serializing library, but I'll avoid turning this into a "use [this] library".
Essentially, JSON.parse fails to parse objects as expected. If you entirely remove the arguments and try a raw JSON.parse(json); on the JSON in your question, you'll get a role that is a String and not a Role, which you might expect. And with JSON.parse doing no type conversion what so ever, that means you have two options: using a library, or using your approach.
Your approach will unfortunately get complicated if you have nested objects, but with the types being changed, the only option you appear to have left is explicitly parsing the objects manually.
TL;DR: your approach is fine.

Lagom: events are not json seralized in cassandra

I need my events to be stored as json in cassandra (So I can read them with some gui client directly from db).
I've followed lagom's guide https://www.lagomframework.com/documentation/1.4.x/scala/Serialization.html (Enabling JSON Serialization), but events are still stored in something like binary or other format.
Here is what I've done:
Created Serializer Registry
object ProjectSerializerRegistry extends JsonSerializerRegistry {
override def serializers: Seq[JsonSerializer[_]] = Seq(
JsonSerializer[ProjectCreated],
)
}
Registered it:
abstract class ProjectsApplication(context: LagomApplicationContext)
extends LagomApplication(context)
with CassandraPersistenceComponents
with LagomKafkaComponents
with AhcWSComponents {
...
// Register the JSON serializer registry
override lazy val jsonSerializerRegistry = ProjectSerializerRegistry
}
Here is the event itself:
case class ProjectCreated(id: String, name: String, createdAt: DateTime) extends ProjectEvent
object ProjectCreated {
implicit val format: OFormat[ProjectCreated] = Json.format[ProjectCreated]
}
After sending command to entity which causes ProjectCreated event and executing query select event from projects.messages I expected to see something like this in cassandra:
{
"id": "prj-1",
"name": "Project 1",
"createdAt": "2018-05-04 01:16:00"
}
But instead, I see something like this in event column:
0x7b226d657373616765223a224869227d
Did I miss something? Or may be it is some compressed or encoded json value?
This is in hexadecimal format. You can convert it into string using online hex-to-string decoder like https://codebeautify.org/hex-string-converter or can create one on your own.
This is correct. The events are stored in binary blobs. if you want to decode these values, you can use the cassandra function blobAsText:
select blobastext(event) from table.messages
This shows the decoded event. If it results in a json object, your serialization works correctly.
There is also a textAsBlob function.

Parsing nodes on JSON with Scala -

I've been asked to parse a JSON file to get all the buses that are over a specified speed inputed by the user.
The JSON file can be downloaded here
It's like this:
{
"COLUMNS": [
"DATAHORA",
"ORDEM",
"LINHA",
"LATITUDE",
"LONGITUDE",
"VELOCIDADE"
],
"DATA": [
[
"04-16-2015 00:00:55",
"B63099",
"",
-22.7931,
-43.2943,
0
],
[
"04-16-2015 00:01:02",
"C44503",
781,
-22.853649,
-43.37616,
25
],
[
"04-16-2015 00:11:40",
"B63067",
"",
-22.7925,
-43.2945,
0
],
]
}
The thing is: I'm really new to scala and I have never worked with json before (shame on me). What I need is to get the "Ordem", "Linha" and "Velocidade" from DATA node.
I created a case class to enclousure all the data so as to later look for those who are over the specified speed.
case class Bus(ordem: String, linha: Int, velocidade: Int)
I did this reading the file as a textFile and spliting. Although this way, I need to foreknow the content of the file in order to go to the lines after DATA node.
I want to know how to do this using a JSON parser. I've tried many solutions, but I couldn't adapt to my problem, because I need to extract all the lines from DATA node instead of nodes inside one node.
Can anyone help me?
PS: Sorry for my english, not a native speaker.
First of all, you need to understand the different JSON data types. The basic types in JSON are numbers, strings, booleans, arrays, and objects. The data returned in your example is an object with two keys: COLUMNS and DATA. The COLUMNS key has a value that is an array of strings and numbers. The DATA key has a value which is an array of arrays of strings.
You can use a library like PlayJSON to work with this type of data:
val js = Json.parse(x).as[JsObject]
val keys = (js \ "COLUMNS").as[List[String]]
val values = (js \ "DATA").as[List[List[JsValue]]]
val busses = values.map(valueList => {
val keyValues = (keys zip valueList).toMap
for {
ordem <- keyValues("ORDEM").asOpt[String]
linha <- keyValues("LINHA").asOpt[Int]
velocidade <- keyValues("VELOCIDADE").asOpt[Int]
} yield Bus(ordem, linha, velocidade)
})
Note the use of asOpt when converting the properties to the expected types. This operator converts the key-values to the provided type if possible (wrapped in Some), and returns None otherwise. So, if you want to provide a default value instead of ignoring other results, you could use keyValues("LINHA").asOpt[Int].getOrElse(0), for example.
You can read more about the Play JSON methods used here, like \ and as, and asOpt in their docs.
You can use Spark SQL to achieve it. Refer section under JSON Datasets here
In essence, Use spark APIs to load a JSON and register it as temp table.
You can run your SQL queries on the table from there.
As seen on #Ben Reich answer, that code works great. Thank you very much.
Although, my Json had some type problems on "Linha". As it can be seen on the JSON example that I put on the Question, there are "" and also numbers, e.g., 781.
When trying to do keyValues("LINHA").asOpt[Int].getOrElse(0), it was producing an error saying that value flatMap is not a member of Int.
So, I had to change some things:
case class BusContainer(ordem: String, linha: String, velocidade: Int)
val jsonString = fromFile("./project/rj_onibus_gps.json").getLines.mkString
val js = Json.parse(jsonString).as[JsObject]
val keys = (js \ "COLUMNS").as[List[String]]
val values = (js \ "DATA").as[List[List[JsValue]]]
val buses = values.map(valueList => {
val keyValues = (keys zip valueList).toMap
println(keyValues("ORDEM"),keyValues("LINHA"),keyValues("VELOCIDADE"))
for {
ordem <- keyValues("ORDEM").asOpt[String]
linha <- keyValues("LINHA").asOpt[Int].orElse(keyValues("LINHA").asOpt[String])
velocidade <- keyValues("VELOCIDADE").asOpt[Int]
} yield BusContainer(ordem, linha.toString, velocidade)
})
Thanks for the help!