Can a dask dataframe with a unordered index cause silent errors?
<p>Methods around dask.DataFrame all seem to make sure, that the index column is sorted. However, by using <code>from_delayed</code>, it is possible to construct a dask dataframe that has a index column, which is not sorted:</p>

<pre><code>pdf1 = delayed(pd.DataFrame(dict(A=[1,2,3], B = [1,1,1])).set_index('A'))
pdf2 = delayed(pd.DataFrame(dict(A=[1,2,3], B = [1,1,1])).set_index('A'))
ddf = dd.from_delayed([pdf1,pdf2]) #dask.DataFrame with unordered index
</code></pre>

<p>The combination [index is set, index is not sorted, divisions are unknown] is something that I have never seen among dataframes that dask created itself. So my questions are:</p>

<ul>
<li>Is dask tested to work well with dataframes like this?</li>
<li>Might it even be that calculations on such dataframes give wrong results silently, e.g. because they assume the index to be sorted or are performed on an incomplete subset of data?</li>
<li>Or more general: If the index column is not sorted, does it only slow down access by index or does it break functionality?</li>
</ul>