What are cursors and what are the situations you will use them

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SQL statements are good for set at a time operation. So it is good at handling set of data. But there are scenarios where we want to update row depending on certain criteria. we will loop through all rows and update data accordingly. There’s where cursors come in to picture.

Cursors in database management systems (DBMS) are programming constructs used to retrieve and manipulate data from a result set, typically within a procedural language like SQL or PL/SQL. They enable users to traverse through the rows of a result set one at a time, allowing for row-level processing.

Here are some situations where cursors are commonly used:

  1. Row-by-row processing: Cursors are useful when you need to perform operations on individual rows of a result set sequentially. For example, performing complex calculations or applying business rules to each row.
  2. Iterative processing: When you need to process a large result set step by step, rather than fetching all the data at once, cursors offer a way to handle data in manageable chunks, which can improve performance and resource utilization.
  3. Transaction management: Cursors are often used in conjunction with transactions to maintain data consistency and integrity. They allow for finer control over data manipulation within a transaction, especially in scenarios where data modifications depend on conditions or calculations involving multiple rows.
  4. Cursor variables: In some cases, cursor variables are used to dynamically define the result set for a cursor. This allows for more flexible query execution based on runtime conditions or parameters.
  5. Complex data retrieval: When dealing with hierarchical or nested data structures, cursors can be employed to navigate through the data in a structured manner, processing parent-child relationships or recursive queries.

However, it’s worth noting that while cursors provide flexibility in data processing, they can also introduce performance overhead, especially in large-scale operations. Therefore, it’s essential to use them judiciously and consider alternative approaches, such as set-based operations, whenever possible to optimize query performance.