How is the bottom layer of sum in sql implemented?

The underlying implementation principles of SUM in SQL include: preparation phase: allocate memory buffers and obtain qualified rows. Accumulation phase: Add the column values ​​of each row to the accumulator (memory variable). Optimization phase: Use data structures to optimize traversal and skip special values. Result stage: Return the sum of the buffers as the final result.

The underlying implementation principle of SUM in SQL

The SUM operation is used in SQL to calculate the values ​​in one or more rows. The sum of values. Its underlying implementation involves the following steps:

1. Preparation phase

• The database engine allocates a memory buffer to store the results.
• Get rows that match the query conditions from a data source (such as a table or view).

2. Accumulation phase

• For each row, the engine adds the value of the specified column to the accumulator in the buffer.
• The accumulator is a memory variable used to store the currently calculated sum.

3. Optimization phase

• The engine may use efficient data structures (such as B-trees) to optimize the traversal of rows.
• It can skip NULL or NaN values ​​since they do not affect the sum.

4. Result Phase

• Once all rows have been traversed, the engine returns the sum of the buffers as the final result of SUM.

Implementation details:

• Accumulators typically use the same type as the column data type.
• The engine can process multiple threads in parallel to improve performance.
• For large data sets, the engine may use batch processing technology to improve efficiency.
• Some database systems may have specialized SUM implementations that are optimized for specific data types or situations.

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