SQL Select Left Join to Filter Multiple Conditions on the Same Table

As a technical blogger, I’ve encountered numerous questions and queries from developers who are struggling with filtering data in SQL. One such question that caught my attention was about using SELECT DISTINCT with a left join and multiple conditions. The question posed by the developer had a scalar function within the WHERE clause, which is generally considered bad practice.

In this article, we will delve into the best practices of filtering data in SQL and explore how to rewrite the given query without using a scalar function in the WHERE clause. We’ll also cover some advanced topics related to left joins, subqueries, and indexing to improve the performance of our queries.

Understanding Left Joins

Before we dive into the solution, let’s take a moment to understand what a left join is. A left join (also known as a left outer join) returns all records from the left table and the matching records from the right table. If there are no matches, the result will contain null values for the right table.

Here’s an example:

Suppose we have two tables: NPTable and IPTable. We want to perform a left join on these tables based on the IPtId column.

CREATE TABLE NPTable (
    PCNId INT PRIMARY KEY,
    IPd INT
);

CREATE TABLE IPTable (
    IRId INT,
    IPtId INT
);

The first few rows of both tables look like this:

NPTable

IPTable

Now, let’s perform a left join on these tables based on the IPtId column.

SELECT NP.PCNId, IP.IPtId, IP.IRId
FROM NPTable NP
LEFT JOIN IPTable IP ON NP.IPd = IP.IPtId;

The result will be:

Filtering Data with Multiple Conditions

Now that we understand left joins, let’s address the main question at hand. The developer wants to filter data based on multiple conditions without using a scalar function in the WHERE clause. The original query uses a SELECT DISTINCT statement with an inner join and a left join.

SELECT DISTINCT IP.IRId  
FROM cmp.NPTable NP
INNER JOIN IPTable IP ON IP.IPtId = NP.IPd
LEFT JOIN  IPCTable IPC ON IPC.IPId = NP.IPId AND IPC.IsNC= 1 
WHERE NP.PCN Id = @PCNId  
AND fGetCount(IP.IPId) = 0  

The subquery fGetCount(IP.IPId) is used to filter rows where the count of records in the IPCTable with IsCopy = 1 and IPId matching the current row is zero. However, using a scalar function within the WHERE clause is considered bad practice.

Solution

To rewrite the query without using a scalar function in the WHERE clause, we can update the same table in the WHERE condition instead of filtering it out.

SELECT DISTINCT IP.IRId  
FROM cmp.NPTable NP
INNER JOIN IPTable IP ON IP.IPtId = NP.IPd
LEFT JOIN  IPCTable IPC ON IPC.IPId = NP.IPId AND IPC.IsNC= 1 
WHERE NP.PCN Id = @PCNId AND IPC.IsCopy = 0;

In this revised query, we’re using the same table IPC to filter out rows where IsCopy = 1. This approach eliminates the need for a subquery and makes the code more efficient.

Additional Tips

• Indexing: In most databases, indexing can significantly improve the performance of queries. For this specific query, creating an index on the IPId column in both tables would be beneficial.

CREATE INDEX idx_IPCTable_IPId ON IPTable(IPId); CREATE INDEX idx_NPTable_IPd ON NPTable(IPd);

*   **Subqueries**: Subqueries can be useful when you need to filter data based on complex conditions. However, using subqueries with joins can lead to performance issues.
    ```markdown
SELECT DISTINCT IRId  
FROM (SELECT IP.IRId FROM IPTable IP WHERE IP.IPtId IN (SELECT NP.IPd FROM NPTable NP WHERE NP.PCN Id = @PCNId)) AS temp;

• Sandboxing: In some cases, you might need to execute a query in a sandboxed environment. This is useful when working with sensitive data or testing queries without affecting production databases.

SELECT DISTINCT IRId
FROM (SELECT IP.IRId FROM IPTable IP WHERE IP.IPtId IN (SELECT NP.IPd FROM NPTable NP WHERE NP.PCN Id = @PCNId)) AS temp;

## Conclusion

Filtering data in SQL can be challenging, especially when dealing with complex conditions. However, by understanding left joins and subqueries, you can rewrite queries to make them more efficient.

In this article, we've explored how to filter data using `SELECT DISTINCT` with a left join and multiple conditions without using scalar functions in the WHERE clause. We've also discussed some additional tips for optimizing query performance, including indexing, subqueries, and sandboxing.

Last modified on 2024-01-17