Binary Search

Owned by Computer Science Department
Last updated: Aug 02, 2023
2 min read

In a database, binary search can be used as an optimization technique to efficiently retrieve data when searching for specific values in an indexed column. The binary search algorithm is particularly useful for quickly locating data in a sorted index, reducing the time and resources required for data retrieval.

Here's how binary search works in the context of a database:

  1. Sorted Index: To perform a binary search in a database, there must be a sorted index on the column being searched. The index stores the sorted values of the column along with pointers to the corresponding rows in the table.

  2. Initialization: The search starts with the entire index as the search space. The binary search algorithm maintains two pointers, "low" and "high," which initially point to the first and last entries of the index, respectively.

  3. Midpoint Calculation: Calculate the midpoint index as (low + high) / 2. If the index has an even number of entries, you can choose to round up or down. Typically, integer division is used, and the midpoint is (low + high) / 2.

  4. Comparison: Compare the value at the midpoint index with the target value being searched for.

  5. Updating Search Space: Depending on the comparison, we update the search space:

    • If the midpoint value is equal to the target value, we have found the entry, and the search is successful.

    • If the midpoint value is less than the target value, the target must be in the right half of the search space. So, we set low = midpoint + 1 to narrow down the search to the right half.

    • If the midpoint value is greater than the target value, the target must be in the left half of the search space. So, we set high = midpoint - 1 to narrow down the search to the left half.

  6. Repeat: Repeat steps 3 to 5 until the target value is found, or the search space is exhausted (i.e., low > high). If the search space is exhausted and the target value is not found, then the value does not exist in the index or the associated table.

Binary search in a database is commonly used when executing queries that involve lookups based on indexed columns. It is especially efficient for large datasets, as it has a time complexity of O(log n), where n is the number of index entries. This makes binary search a powerful tool for improving the performance of data retrieval operations in database systems. However, to benefit from binary search, the index must be properly maintained and the column values must be kept sorted.