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copied!<p>I'll try an explanation... </p> <p><strong>eq_ref</strong> – imagine that you have two tables. Table A with columns (id, text) where id is a primary key. Table B with the same columns (id, text) where id is a primary key. Table A has the following data:</p> <pre><code>1, Hello 2, How are </code></pre> <p>Table B has the following data:</p> <pre><code>1, world! 2, you? </code></pre> <p>Imagine eq_ref as JOIN between A and B:</p> <pre><code>select A.text, B.text where A.ID = B.ID </code></pre> <p>This JOIN is very fast because for each row scanned in table A there can be only <strong>ONE</strong> row in table B which satisfies the JOIN condition. One and no more than one. That is because B.id is UNIQUE. Here you are a <em>pseudo</em> code which illustrates the processing at server side:</p> <pre><code>foreach (rowA in A) { if (existsInBRowWithID(rowA.id) { addToResult(rowA.text, getRowInBWithID(rowA.id).text); break; } } </code></pre> <p><strong>ref</strong> - Now imagine another table C with columns (id, text) in which id an index but a non UNIQUE one. Table C has the following data:</p> <pre><code>1, John! 1, Jack! </code></pre> <p>Imagine ref as JOIN between A and C:</p> <pre><code>select A.text, C.text where A.ID = C.ID </code></pre> <p>Here you are a pseudo code which illustrates the processing at server side:</p> <pre><code>foreach (rowA in A) { foreach (rowC in C) { if (rowA.id == rowC.id) { addToResult(rowA.text, rowC.text); } } } </code></pre> <p>This JOIN is NOT as fast as the former one because for each row scanned in table A there are <strong>SEVERAL</strong> possible rows in table C which may satisfy the JOIN condition (no break in the loop above). That is because C.ID is NOT UNIQUE.</p> <p>I hope that helps...</p> <p>Cheerz!</p>

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