# SP Product Entry
Analysis generated on: 4/2/2025 10:12:19 AM
---
## SQL Statement
```sql
SELECT [SP Products].ProductID, [SP none].PartNumber, [SP Products].PartsPerUnit, [SP Products].Obsolete
FROM [SP none] LEFT JOIN [SP Products] ON [SP none].PartNumber = [SP Products].PartNumber
ORDER BY [SP Products].ProductID, [SP none].PartNumber;

```
## Dependencies
- *None*
## Parameters
- *None*
## What it does
**SQL Code Description**

### Overview

This SQL code retrieves data from two tables, `SP none` and `SP Products`, and joins them based on a common column `PartNumber`. The resulting data is then sorted and returned.

### Breakdown

#### Table Selection
The code selects columns from the following tables:

* `[SP Products]`: Retrieves columns `ProductID`, `PartsPerUnit`, and `Obsolete`.
* `[SP none]`: Retrieves all rows, regardless of whether a match exists in the joined table.
* The selected data is retrieved using the following aliases:
	+ `[SP Products]` for `SP Products`
	+ `[SP none]` for `SP none`

#### Join Operation
The code performs a LEFT JOIN operation between the two tables based on the common column `PartNumber`. This means that:

* All rows from `[SP none]` are included in the result set, even if there is no matching row in `[SP Products]`.
* For each match found in `[SP Products]`, the corresponding columns from both tables are included in the result set.

#### Sorting
The resulting data is sorted in ascending order based on two columns:

1. `[SP Products].ProductID`
2. `[SP none].PartNumber`

This ensures that the rows with matching `PartNumber` values are grouped together, followed by rows without matches.

### Output

The final output will be a table containing all rows from `[SP none]`, along with the corresponding columns from `[SP Products]`. The data is sorted as specified above.