Скачать или смотреть Efficiently Insert Data into a Different Table with a Custom Pattern in SQL

Learn how to transform and insert data from one table to another with custom column patterns using SQL queries.
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Transforming and Inserting Data into SQL Tables with a Custom Pattern

In the world of SQL, it is common to encounter scenarios where data needs to be reformatted or organized differently. One such challenge arises when you want to insert data from one table into another, following a specific structure or pattern. This post will explore how to carry out this task effectively using SQL queries.

The Problem

Let’s start with an example to illustrate the issue. Consider a table named table1 with the following structure and data:

idcodeprice110005.3210014.3310026.5410037.5The goal is to transform and insert this data into another table, table2, which should look like this:

idcodepricecode1price2110005.310014.3210026.510037.5The challenge is to combine the even and odd code and price values into their respective new columns in table2.

The Solution

To achieve this transformation, we can utilize the power of SQL's SELECT statement paired with conditional aggregation. The following query gives an efficient method to extract and format the required data for table2.

SQL Query Breakdown

[[See Video to Reveal this Text or Code Snippet]]

Explanation of the Query:

row_number(): This function generates a unique identifier for each row in the result set based on the order of MIN(code). This is used to create the id for table2.

MAX(CASE WHEN ...): This is a conditional aggregation method. It checks whether the code is odd or even and places the values into their corresponding columns (code1, price1, code2, price2).

For odd codes, it assigns values to code1 and price1.

For even codes, it assigns values to code2 and price2.

GROUP BY CEILING(code / 2.0): This clause is crucial as it groups records by pairs so that odd and even entries can be assigned correctly in derived columns.

Conclusion

By using the above SQL query, you can successfully insert and reshape data from one table to another in a customized format. This method not only streamlines the data migration process but also ensures clarity and organization in the new table structure. SQL’s flexibility with functions like ROW_NUMBER() and conditional aggregation makes these transformations efficient and manageable.

Now you have a valuable approach to tackle similar challenges in your own SQL database management tasks. Let’s get coding!