ROLLUP is suitable for hierarchical dimension statistics, generating subtotals and totals; CUBE generates a summary of all dimension combinations. ROLLUP generates hierarchical aggregations in field order, such as subtotal and total sum of Region → Products; CUBE enumerates all combinations, such as Regional Products, Regional Total, Product Total and Full Table Total Total. When using ROLLUP, you need to pay attention to the field order. CUBE may cause the result to expand, and the effectiveness of the combination needs to be judged based on business. Both can be used to identify the summary rows using the GROUPING function to improve the readability of the result and optimize performance.

ROLLUP and CUBE of SQL are advanced tools for data aggregation, especially suitable for scenarios that require multi-level statistical analysis. They can automatically generate subtotals and totals for different dimension combinations, saving you the hassle of manually writing multiple GROUP BY .

What is ROLLUP?

ROLLUP is a way of grouping by hierarchy, which generates subtotals for each layer and adds a total total row at the end. It is suitable for data with obvious hierarchical relationships, such as year, month, day, or region, province, city, etc.

For example, suppose you have a sales table sales_data that contains fields region , product , and amount , and you want to see sales for each product in each region, as well as sales for each region and total sales for all regions:

 SELECT region, product, SUM(amount) AS total_amount
FROM sales_data
GROUP BY ROLLUP (region, product);

The results will include:

• Sales per product in each region
• Total sales per region (product is listed as NULL)
• Total sales in all regions (region and product are NULL)

Recommended usage:

• Priority to using ROLLUP when your dimension has a clear hierarchy
• Pay attention to the sorting problem. ROLLUP is to build hierarchies in the order of fields you wrote.

What's the difference between CUBE?

The biggest difference between CUBE and ROLLUP is that it enumerates all possible combinations of dimensions and generates a row of results for each combination. That is, if you use three grouping fields, CUBE will generate 2^3 = 8 combinations.

Or the example above, change to CUBE :

 SELECT region, product, SUM(amount) AS total_amount
FROM sales_data
GROUP BY CUBE (region, product);

The results you will see include:

• Sales per product in each region
• Total sales per region (product is NULL)
• Total sales of each product (region is NULL)
• Total sales of all data (all NULL)

Recommended usage:

• Use CUBE when you need to view the summary data of all dimension combinations
• Note that the result set may become large, especially when there are many dimensions
• If some combinations have no meaning (such as a dimension is time and another is a category), CUBE may generate some "meaningless" combination rows

What should I pay attention to in practical applications?

1. NULL value identification problem
   In the results of ROLLUP or CUBE , NULL means "a summary of this level". In order to distinguish these NULLs from NULLs in the original data, you can use GROUPING() function to determine whether a column is a summary row.

    SELECT 
     region, 
     product,
     SUM(amount) AS total_amount,
     GROUPING(region) AS is_region_total,
     GROUPING(product) AS is_product_total
   FROM sales_data
   GROUP BY CUBE (region, product);

2. Performance considerations
   Especially for CUBE, when there are many grouping fields, the execution efficiency will decrease. At this time, you need to consider whether all combinations are really needed, or whether there is a way to filter first and then aggregate.

3. Results display processing
   When displaying these results in the front-end or report tool, pay attention to processing the NULL fields, usually replaced with labels such as "total" and "subtotal" to improve readability.

---

Overall, ROLLUP is more suitable for hierarchical dimensional statistics, while CUBE is more flexible but has more complex results. Choosing the right tools according to business needs can greatly simplify the writing of aggregation query.

Basically that's all, not complicated but it's easy to ignore details.

The above is the detailed content of Aggregating Data Using SQL ROLLUP and CUBE Clauses. For more information, please follow other related articles on the PHP Chinese website!