Understanding the Problem and Requirements

As a data analyst or business intelligence developer, you often need to perform complex data transformations and aggregations on large datasets. One such scenario is when you have a table representing transactional data and another table containing feature information, including display orders. Your goal might be to pivot this feature data based on specific parts existing in the input data.

In this blog post, we will explore how to achieve conditional aggregation of features based on the existence of certain parts in the input data. This involves joining the parts data with both the input data and the feature data, filtering for relevant combinations, and then aggregating the results.

Setting Up the Test Environment

To illustrate this concept, let’s set up a basic test environment using SQL Server 2012. We’ll create three tables: #InputData, #Features, and #PartsData.

CREATE TABLE #InputData (
    PartC INT,
    PartX  INT
)

INSERT INTO #InputData (PartC, PartX)
VALUES (1290, 1590)

CREATE TABLE #features (
    FeatureId  INT,
    FeatureName NVARCHAR(50),
    DisplayOrder  INT
)

INSERT INTO #features (FeatureId, FeatureName, DisplayOrder)
VALUES (124003, 'Current', 1),
       (157301, 'Voltage', 2),
       (980012, 'Resistor', 3)

CREATE TABLE #partsdata (
    PartId  INT,
    FeatureId INT,
    FeatureValue NVARCHAR(20)
)

INSERT INTO #partsdata (PartId, FeatureId, FeatureValue)
VALUES (1290, 124003, '40V'),
       (1290, 157301, '50k'),
       (1290, 980012, '90A'),
       (1590, 124003, '30V'),
       (1590, 157301, '70k'),
       (1590, 980012, '20A')

Solution Overview

The approach to solve this problem involves the following steps:

1. Joining the #PartsData table with both the #InputData and #Features tables.
2. Filtering for relevant combinations of parts and features based on existence in both input data and feature lists.
3. Aggregating the results to display features as required.

Solution Details

The solution can be achieved through conditional aggregation, using SQL Server’s built-in aggregation functions like MAX, SUM, COUNT, etc.

SELECT d.PartC, d.PartX,
    MAX(CASE WHEN p.PartId = d.PartC AND f.FeatureName = 'Current' THEN f.FeatureValue END) AS Current_C,
    MAX(CASE WHEN p.PartId = d.PartX AND f.FeatureName = 'Current' THEN f.FeatureValue END) AS Current_X,
    MAX(CASE WHEN p.PartId = d.PartC AND f.FeatureName = 'Voltage' THEN f.FeatureValue END) AS Voltage_C,
    MAX(CASE WHEN p.PartId = d.PartX AND f.FeatureName = 'Voltage' THEN f.FeatureValue END) AS Voltage_X,
    MAX(CASE WHEN p.PartId = d.PartC AND f.FeatureName = 'Resistor' THEN f.FeatureValue END) AS Resistor_C,
    MAX(CASE WHEN p.PartId = d.PartX AND f.FeatureName = 'Resistor' THEN f.FeatureValue END) AS Resistor_X
FROM #PartsData p
INNER JOIN #InputData d ON p.PartId IN (d.PartC, d.PartX)
INNER JOIN #Features f ON p.FeatureId = f.FeatureId
GROUP BY d.PartC, d.PartX

This SQL statement performs the following operations:

• It joins #PartsData with both #InputData and #Features, using inner joins to only include relevant data.
• It applies conditional aggregation for each feature (Current, Voltage, Resistor) based on whether its corresponding part exists in either input data or feature list. The maximum value is chosen as the aggregated result.

Visualizing the Results

To illustrate the results of this SQL statement, we can use a pivot function to display the features horizontally and group them by parts.

SELECT PartC, PartX,
    [Current] = MAX(CASE WHEN f.FeatureName = 'Current' THEN p.FeatureValue END),
    [Voltage] = MAX(CASE WHEN f.FeatureName = 'Voltage' THEN p.FeatureValue END),
    [Resistor] = MAX(CASE WHEN f.FeatureName = 'Resistor' THEN p.FeatureValue END)
FROM (
    SELECT d.PartC, d.PartX,
        CASE WHEN d.PartId IN (PartC, PartX) AND f.FeatureName = 'Current' THEN p.FeatureValue ELSE NULL END AS [Current],
        CASE WHEN d.PartId IN (PartC, PartX) AND f.FeatureName = 'Voltage' THEN p.FeatureValue ELSE NULL END AS [Voltage],
        CASE WHEN d.PartId IN (PartC, PartX) AND f.FeatureName = 'Resistor' THEN p.FeatureValue ELSE NULL END AS [Resistor]
    FROM #PartsData p
    INNER JOIN #InputData d ON p.PartId IN (d.PartC, d.PartX)
    INNER JOIN #Features f ON p.FeatureId = f.FeatureId
) AS subquery
GROUP BY PartC, PartX
ORDER BY PartC, PartX

Conclusion

Conditional aggregation and pivot operations are fundamental concepts in data analysis. In this post, we explored how to use SQL Server’s conditional aggregation functions to achieve a specific requirement involving feature value based on parts existing in the input data table.

We covered setting up a basic test environment using sample tables, understanding the requirements, and then solving it with SQL Server’s built-in aggregation functions like MAX, SUM, etc., along with pivot functionality for displaying results horizontally.

This technique can be applied to similar scenarios where conditional aggregations are required, making data analysis more efficient and effective.

Last modified on 2024-12-10