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copied!<p>You are quoting the wrong part of documentation. If you have a look at the doc of <code>[.data.table</code> you will read:</p> <blockquote> <p>When i is a data.table, x must have a key, meaning join i to x and <strong>return the rows in x that match</strong>. An equi-join is performed between each column in i to each column in x’s key in order. This is similar to base R functionality of sub- setting a matrix by a 2-column matrix, and in higher dimensions subsetting an n-dimensional array by an n-column matrix</p> </blockquote> <p>I admit the description of the package (the part you quoted) is somewhat confusing, because it seems to say that the "["-operation can be used instead of merge. But I think what it says is: if x and y are both data.tables we use a join on an index (which is invoked like merge) instead of binary search.</p> <hr> <p><em>One more thing:</em></p> <p>The data.table library I installed via <code>install.packages</code> was missing the <code>merge.data.table method</code>, so using <code>merge</code> would call <code>merge.data.frame</code>. After installing the <a href="http://r-forge.r-project.org/projects/datatable/" rel="nofollow noreferrer">package from R-Forge</a> R used the faster <code>merge.data.table</code> method. </p> <p>You can check if you have the merge.data.table method by checking the output of:</p> <pre><code>methods(generic.function="merge") </code></pre> <hr> <p><strong>EDIT [Answer no longer valid]:</strong> This answer refers to data.table version 1.3. In version 1.5.3 the behaviour of data.table changed and x[y] returns the expected results. Thank you <a href="https://stackoverflow.com/users/403310/matthew-dowle">Matthew Dowle</a>, author of data.table, for pointing this out in the comments.</p>

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