Как с помощью Stream API вывести все слова по алфавиту и не создавая новый стрим слово которое встречается максимальное кол-во раз

Вот текст в моем файле: “Hello world! Cat is animal. Dog is animal too. Car is not animal.”

import java.io.*; import java.util.Arrays; import java.util.Map; import java.util.function.Function; import java.util.stream.Collectors; import java.util.stream.Stream;  public class Main {      public static void main(String[] args) {         try {             File file = new File("D:/test/file.txt");             FileReader fileReader = new FileReader(file);              BufferedReader bufferedReader = new BufferedReader(fileReader);               String line;             while((line = bufferedReader.readLine()) != null) {                 Stream.of(line.split("[^A-Za-zА-Яа-я0-9]+"))                         .map(String::toLowerCase)                         .collect(Collectors.groupingBy(Function.identity(), Collectors.counting()))                         .entrySet()                         .stream()                         .sorted(Map.Entry.comparingByKey())                         .forEach(System.out::println);              }              bufferedReader.close(); // закрываем поток         } catch (Exception e) {             e.printStackTrace();         }     } } 

На выходе я получаю строки отсортированные в алфавитном порядке:

animal=3 car=1 cat=1 dog=1 hello=1 is=3 not=1 too=1 world=1

Но я хочу не создавая отдельный стрим (в моем понимании какой-то промежуточной операцией) вывести еще и строку которая встречается наибольшее количество раз, если их несколько вывести их в алфавитном порядке

how to manipulate firestore stream with rxdart

I want to modify stream data i got from Firestore, by adding a new property and editing existing ones.

I tried to do that using RXdart

PublishSubject<QuerySnapshot> _fixtureStreamController = PublishSubject<QuerySnapshot>();   Observable<QuerySnapshot> get counterObservable => _fixtureStreamController.stream; Firestore.instance.collection("places").snapshots().listen((data) {       data.documents.map((d) => {          d['name'].toUpperCase();          d['newProperty'] = 'new data';       });       _fixtureStreamController.add(data);     } ); 

I expect to get a new stream that i can use in StreamBuilder

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Australia Graduate Visa Post-Study Work stream study documents with credit exemption

I’m applying for a Graduate Visa in Australia (Post-Study Work stream). I understand that the study requirements is 2 years.

My education condition is as following:

  1. I studied master degree in 1.5 years (I got credit for a semester because of my bachelor degree)
  2. I studied bachelor degree in 1 year

Both studies are in Australia.

My question:

When I apply for Graduate Visa Post-Study Work stream, do I need to include both my bachelor and master transcripts?

This is the website that includes the visa details: https://immi.homeaffairs.gov.au/visas/getting-a-visa/visa-listing/temporary-graduate-485/post-study-work#HowTo

Design pattern that can be used for checking and handling a change in version number for incoming JSON message into data stream?

I have a Spark Streaming Job which processes messages coming from Kafka.

My incoming json that I process sort of looks like

{"sv" : 1.0, "field1" : "some data"} 

The only thing I do is put these in a MYSQL database.

However, I need to process these messages differently based on the schema version number!

For instance, I may get data that looks like the below in the same stream

{"sv" : 1.0, "field1" : "some data"}  {"sv" : 1.1, "field1" : "some data", "field2" : "new data"}  {"sv" : 1.2, "field1" : "some data", "field2" : "new data", "field3" : "data"} 

Now what I do is I have a function that formats the data for me like so

  def formatData(json: String): Option[Data] = {      var outputData: Option[Data] = None      val jsonObject = new JSONObject(json)      outputData = formatDataBasedOnSchemaVersion(jsonObject)      outputData    } 

and another function that formats based on a schema version number

  private def formatDataBasedOnSchemaVersion(jsonObject: JSONObject): Option[Data] = {      val outputData = {       jsonObject.getDouble("sv") match {         case 1.0 => Some(formatVersion_1_0(jsonObject))         case 1.1 => Some(formatVersion_1_1(jsonObject))         case 1.2 => Some(formatVersion_1_2(jsonObject))         case x: Double => logger.warn("No formatter found for schema version: " + x); None       }     }      outputData   } 

An example of my format function can look like

  private def formatVersion_1_2(jsonObject: JSONObject): Data = {      val f1 = jsonObject.getString("field1")     val f2 = jsonObject.getString("field2")     val f3 = jsonObject.getString("field3")      val data = Data(f1,f2,f3)      data    } 

In the format_1_0 function, all I do is pull out the “field1” parameter.

My Data class is simple DTO it just looks like

case class Data(field1: String, field2: String, field3: String) 

If I get schema version 1.0, field2 and field3 are left blank and inserted into the DB as blank values.

The problem is, I have to hard code in the schema version numbers like “1.0”, “1.1” etc.. and design a new method to pull out the extra fields. So for every schema change, I have to edit the code and add a new method to pull out the new data. So is there any better pattern I can use that can handle this? Or maybe a framework? I’ve heard of ORM would this help with that problem or would I still need to make similar code changes for schema version changes?

Find the top N numbers in an endless stream of integers in a functional programming style

I came across this interesting Scala problem and not sure how to solve it:

class TopN {   def findTopN(n: Int)(stream: Stream[Int]): List[Int] = {    ???   } }  

This is a test of abstract data engineering skills.

The function findTopN(…) in TopN is supposed to find the top N highest unique integers in a presumed endless stream of integers. To process the Stream of Int, you can only hold a few values in memory at a given time. Therefore, a memory efficient way to process this list is required.