How to put data from ResultSet to HashMap using Lambda expression?

Question

I have a table in my SQL Server 2012 Database as follows:

Student:
ID, CardNo, Name, ZipCode, city, ...

I'm writing a Java desktop application using JDK 8, in which I want to put selected rows from this table in a HashMap with CardNo as key and Name as value.

What's the efficient way to fill this HashMap using a lambda expression?

Note: CardNo is unique.

Answer 1

Here is a simpler way:

List<Student> students = xxxDao.retrieveStudents();

Map<Integer, String> map = students.stream()
            .collect(Collectors.toMap(Student::getCardNo, Student::getName));

Also, you could add a static import for Collectors.toMap and make the expression even more readable.

Answer 2

How about this:

List<Student> students = xxxDao.findFromDB();
Map<String, String> map = students.stream().collect(
                                   Collectors.groupingBy(Student::getCardNo, 
                                              Collectors.collectingAndThen(
                                                         Collectors.mapping(Student::getName, 
                                                                    Collectors.toList()), nameList->nameList.get(0))));

-------------------------------------------------------split line------------------------------------------------------------------

This way I give above is much rather complex, and thanks to the @FedericoPeraltaSchaffner, there is other more simple way to express what we want. Since CardNo is unique, just use Collectors.toMap

List<Student> students = xxxDao.findFromDB();
Map<String, String> map = students.stream().collect(Collectors.toMap(Student::getCardNo, Student::getName));

Answer 3

Why use a lambda? Keep it simple:

ResultSet resultSet = stmt.executeQuery(query); // assuming this

Map<String, String> map = new HashMap<>();
while(resultSet.next())
    map.put(resultSet.getString("CardNo"), resultSet.getString("Name"));

Using streams/lambdas is not automatically the best option, as here.