Before diving into these tasks, you know those times when you connect to a database and spend hours writing queries, and then you think: I wish I could run several different queries at once and see the results together!
Back in the day, I’d open SQL Server Management Studio, write a few join queries, and then try to combine them somehow. But now, things are a bit different, especially with cloud-based services, microservices, and so on.
This thing called QueryMultiple actually comes into play here. Imagine you have a web application and users navigate your site needing data from multiple sources. For example, you want to display a product list but the stock info is in a separate database, the price info is in a different service, and reviews are stored elsewhere. Previously, you’d fetch these individually and then merge the results in your code, right?
That’s exactly where capabilities like QueryMultiple can be lifesavers. With this feature, you can run multiple queries in a single request and receive all the results at once. Think about it: less network traffic, faster response times. Isn’t that great?
Regarding how this works technically, the general concept is quite simple. You provide a list of queries, and the system executes them asynchronously. When results arrive, it delivers them all together. It’s like going to a restaurant and ordering both the main course and dessert simultaneously, and the waiter brings both at the same time. That’s the analogy here.
The Power of Combining Database Queries
Of course, this logic isn’t limited to databases. It can be used for fetching data from different APIs, reading from files, and in many other scenarios. The key is when you need to aggregate data from multiple sources.
For example, think of a reporting system that requires sales data, stock levels, and customer info. If these are in different systems, fetching them one by one can take time. Using QueryMultiple to get everything in a single call shortens report preparation time and reduces server load.
By the way, for those curious which database or framework offers this feature; it’s mostly seen in ORM (Object-Relational Mapping) tools. For instance, lightweight and fast ORM tools like Dapper support advanced query features like this. Sometimes, even the database drivers themselves support asynchronous or batch operations for such cases.
The core advantage is utilizing parallel processing and concurrency. While one query waits, others run in the background. This significantly shortens total operation time. In the past, I’d manually use tasks like `Task.WhenAll`, but such ready-made solutions make it much easier. That’s why many modern frameworks have started supporting this feature.
Practical Example: Let’s see it with code
Let’s not talk too much and look at a simple C# example. Suppose you want to fetch user information and the user’s orders in a single query. This requires accessing two different tables.
First, let’s review an outdated or naive approach, where we fetch data one at a time and then combine them:
// WRONG APPROACH – Fetching Queries Individually
public async Task<UserAndOrders> GetUserAndOrdersAsync_Wrong(int userId, IDbConnection dbConnection){
var user = await dbConnection.QueryFirstOrDefaultAsync<User>("SELECT * FROM Users WHERE Id = @Id", new { Id = userId });
var orders = await dbConnection.QueryAsync<Order>("SELECT * FROM Orders WHERE UserId = @UserId", new { UserId = userId });
// Manually merge results
var result = new UserAndOrders
{
User = user,
Orders = orders.ToList()
};
return result;
}
As you see, it fetches the user first, then the orders. These are two separate database queries. This method works fine, but what if we need more data? Each additional call adds to the wait, and over time, it becomes slow.
Now let’s see the smarter way—using QueryMultiple to do it in one go:
// CORRECT APPROACH – Using QueryMultiple
public async Task<UserAndOrders> GetUserAndOrdersAsync_Correct(int userId, IDbConnection dbConnection){
var sql = @"
SELECT * FROM Users WHERE Id = @Id;
SELECT * FROM Orders WHERE UserId = @UserId;
";
using (var multi = await dbConnection.QueryMultipleAsync(sql, new { Id = userId, UserId = userId }))
{
var user = await multi.ReadFirstOrDefaultAsync<User>();
var orders = await multi.ReadAsync<Order>();
return new UserAndOrders
{
User = user,
Orders = orders.ToList()
};
}
}
That’s it! With just one SQL command, you can run as many queries as needed. Thanks to Dapper’s `QueryMultipleAsync` method, you first combine all your queries into a single string, then use methods like `multi.ReadFirstOrDefaultAsync` and `multi.ReadAsync` to retrieve results sequentially. This offers a significant performance boost.
Also, remember that the order of queries is important. If you want to fetch the user first, you need to write the SQL accordingly; otherwise, the first `multi.ReadFirstOrDefaultAsync()` call might get the second query’s result. That could lead to confusion.
What are the Benefits?
Using QueryMultiple provides major advantages in scenarios where you need to fetch data from multiple sources. It shortens development time, boosts performance. Imagine on a large e-commerce site, loading a product detail page with product info, similar products, and stock status—using QueryMultiple can truly be a game-changer.
This technology isn’t limited to databases alone. It can be applied for fetching data from multiple APIs simultaneously, which is common in microservice architectures. When a main service needs to aggregate data from several microservices, this method is quite useful. Basically, it allows you to do a lot with minimal effort.
In conclusion, if your data access layer needs better performance and cleaner code, exploring features like QueryMultiple is highly recommended. It will make your code more efficient and more readable. Try it, and you’ll see the difference. Isn’t that great?