Cursor Management and Iteration

You will utilize cursors to process large result sets incrementally without exhausting system memory.

In this lesson, you will learn how to use cursors to process massive result sets in chunks, ensuring your database doesn't crash from memory exhaustion.

The Problem: Memory Overload

When you execute a standard SELECT statement in PostgreSQL, the system typically fetches the entire result set into memory so it can be returned to your application. If a table contains millions of rows, this can lead to memory pressure or "out of memory" errors. To handle this, we use a cursor.

Think of a cursor as a "pointer" or a bookmark that tracks your position within a large query result. Instead of loading everything at once, you keep the query open and fetch only the rows you need at that exact moment.

Using Cursors in PL/pgSQL

To use a cursor, you must wrap your work in a transaction. The cursor life cycle involves declaring the cursor, opening it, fetching rows, and finally closing it.

Here is how you would iterate through a massive table using a cursor:

DO $$
DECLARE
    -- 1. Declare the cursor
    my_cursor CURSOR FOR SELECT id, data FROM massive_table;
    row_record RECORD;
BEGIN
    -- 2. Open the cursor
    OPEN my_cursor;

    LOOP
        -- 3. Fetch rows into the variable
        FETCH NEXT FROM my_cursor INTO row_record;
        
        -- Exit loop if no more rows are found
        EXIT WHEN NOT FOUND;
        
        -- Process the row
        RAISE NOTICE 'Processing ID: %', row_record.id;
    END LOOP;

    -- 4. Close the cursor to free resources
    CLOSE my_cursor;
END $$;

Why This Matters

By using FETCH, you dictate how much data enters the MemoryContext at one time. If you fetch 1,000 rows, process them, and then fetch the next 1,000, your memory footprint remains constant regardless of whether the table has ten thousand or ten billion rows.

Once you are done, always CLOSE the cursor. Since cursors exist within the scope of a transaction, they hold onto resources (and locks) until they are closed or the transaction completes. Using them wisely allows you to perform heavy batch operations without overwhelming the system.

Key Takeaway: Cursors allow you to trade a single, large memory allocation for a controlled, incremental stream of data, preventing system instability when working with massive result sets.