Understanding Composite Primary Keys and Aggregate Functions in Ignite

Introduction to Composite Primary Keys

In relational databases, a composite primary key is a combination of two or more columns that uniquely identify each row in a table. This design choice is used when there are multiple columns that together serve as the primary identifier for a record. In our example, we have a table T1 with both column a and column b as part of its composite primary key.

When using aggregate functions like COUNT, SUM, or AVG on these types of tables, the database needs to determine how to handle grouped rows. The goal is to group rows based on one of the columns in the composite primary key (e.g., a) and then perform the aggregation operation on the other column(s).

Ignite’s GROUP BY Clause Behavior

Ignite, a high-performance NoSQL data store designed for modern distributed systems, uses its own version of SQL. In this context, when trying to execute an aggregate function like COUNT or AVG over columns in a composite primary key table, Ignite will not behave as expected if you only include one column from the primary key group.

This limitation is due to Ignite’s internal data structure and how it optimizes query performance. When performing queries with multiple columns, especially those used for grouping (in this case, a), the database engine groups rows based on these specified keys. Since we’re interested in aggregating over another column (b), Ignite assumes you want to group by one of the primary key columns, which would be column a.

Example Scenario

Let’s walk through an example scenario that demonstrates the challenge posed by using a composite primary key with Ignite.

Suppose we have a table T1 with a composite primary key consisting of columns a, b, and c. We want to calculate the total number of rows for each unique combination of values in column a and b.

Here’s an example query that tries to accomplish this:

SELECT a, b, c, COUNT(*) as row_count
FROM T1 
GROUP BY a, b;

However, Ignite will not allow us to include both a and b in the GROUP BY clause because it assumes b must be one of the primary key columns. To achieve our desired result, we need to find an alternative approach.

Precomputing Aggregate Values

One possible solution is to precompute aggregate values for each combination of column values in the composite primary key (a, c) and then join this data with another table that contains column values for b. This method has several benefits:

• It allows us to include multiple columns in our aggregation results.
• The computation can be parallelized across nodes, improving performance.

Here’s an example of how you might precompute these aggregates:

-- Create a temporary result table with the required aggregate values
SELECT a, c, COUNT(*) as row_count
FROM T1 
GROUP BY a, c;

-- Rename this result set to something useful

-- Now, we can join this table with another table that contains column 'b'
SELECT r.a, b.b, r.c, r.row_count
FROM renamed_result_table r
INNER JOIN T2 b ON r.a = b.a;

In our example, r represents the temporary result set from the first query, and T2 is another table containing the values for column b.

This method requires more planning and data manipulation but can provide a powerful way to handle composite primary keys with multiple columns.

Calculating Specific Values

Another approach might be to simply calculate the specific values you’re interested in for each row. For example, if you want only to retrieve the value of column b, you could do so as follows:

SELECT b.b 
FROM T1 a
INNER JOIN (
  SELECT c, COUNT(c) as cnt 
  FROM T1 
  GROUP BY c
) counts ON a.c = counts.c;

In this case, we’re still grouping by column c, which is part of our composite primary key. However, by including the COUNT aggregation function, we can determine how many times each value in column b appears.

Again, since Ignite only allows us to group by one of the columns from the composite primary key (a), this method requires some creativity to work around its limitations.

Conclusion

When working with tables that have a composite primary key, it’s essential to understand how your specific database system handles grouped rows and aggregate functions. In our example with Ignite, we discovered two alternative methods for retrieving certain values from a table: precomputing these values and then joining them with another table, or calculating the desired value directly using an inner join.

These approaches might require more planning and data manipulation than traditional SQL queries but can provide powerful ways to handle composite primary keys.

Last modified on 2023-08-02