html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/1255#issuecomment-278390511,https://api.github.com/repos/pydata/xarray/issues/1255,278390511,MDEyOklzc3VlQ29tbWVudDI3ODM5MDUxMQ==,1217238,2017-02-08T17:02:38Z,2017-02-08T17:02:38Z,MEMBER,"The usual place to start is with profiling. Here's what `%prun xr.concat(das)` gets me:
https://gist.github.com/shoyer/97dff50d5892e3437d4864d93e85ead2

So indeed, each index is getting converted into a NumPy array. Profiling suggests `Variable.equals` is a likely culprit (0.863/1.159 seconds) and indeed we call `.data` there:
https://github.com/pydata/xarray/blob/d49014d0357d08289cf99aeb54bcefe48ed6e7a0/xarray/core/variable.py#L1000

The good news is that pandas already has it's own vectorized `.equals` method for indexes. So we should either add a special case if `._data` is a PandasIndexWrapper for the generic `Variable.equals` method, or perhaps better yet add a subclass method `IndexVariable.equals` that always call `.equals` on the indexes instead of caling `ops.array_equiv` on `.data`.","{""total_count"": 1, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 1, ""rocket"": 0, ""eyes"": 0}",,206241490