How can I efficiently calculate Hamming distance between binary strings in SQL?

Hamming Distance Calculation on Binary Strings in SQL

Problem Statement:

Database tables often store SHA256 hashes as binary values. The Hamming distance, representing the number of bitwise differences between two hashes, is a crucial metric for similarity analysis. This article aims to provide a SQL solution to calculate the Hamming distance between a given value and each hash in a specified column.

Existing Inefficient Approach:

Breaking down binary strings into smaller integer chunks, computing Hamming distance for each chunk, and then summing the results is a cumbersome and performance-limited method.

Improved Approach:

Storing hashes in multiple BIGINT columns instead of a single BINARY column significantly improves performance. This allows the creation of custom functions that can efficiently calculate the Hamming distance between multiple BIGINT values.

Hamming Distance Function for BIGINTs:

The following custom function can be created to calculate the Hamming distance between four BIGINTs:

<code class="sql">CREATE FUNCTION HAMMINGDISTANCE(
  A0 BIGINT, A1 BIGINT, A2 BIGINT, A3 BIGINT, 
  B0 BIGINT, B1 BIGINT, B2 BIGINT, B3 BIGINT
)
RETURNS INT DETERMINISTIC
RETURN 
  BIT_COUNT(A0 ^ B0) +
  BIT_COUNT(A1 ^ B1) +
  BIT_COUNT(A2 ^ B2) +
  BIT_COUNT(A3 ^ B3);</code>

Usage Example:

With this function, you can sort table entries by their Hamming distance to a provided value using the following query:

<code class="sql">SELECT * FROM table 
  ORDER BY HAMMINGDISTANCE(col0, col1, col2, col3, UNHEX(<insert supplied sha256 hash here>)) ASC 
  LIMIT 10</code>

Conclusion:

Splitting SHA256 hashes into four BIGINT columns and using a custom function is a highly efficient approach for calculating Hamming distance in SQL. This method significantly improves performance over storing hashes as BINARY values and employing conventional integer-based calculations.

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