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/1897#issuecomment-364298613,https://api.github.com/repos/pydata/xarray/issues/1897,364298613,MDEyOklzc3VlQ29tbWVudDM2NDI5ODYxMw==,6815844,2018-02-09T00:45:15Z,2018-02-09T01:11:34Z,MEMBER,"> Or we could switch LazilyIndexedArray to store a chain of successive indexing operations, but that would potentially have non-desirable performance implications.

I think we can store the chain of successive indexing operations, and apply them sequentially when the evaluation.
But I am wondering if this operation has an advantage to the eager indexing. 
(The total computation cost would be the same?)

A workaround would be to take care outer/basic indexers and vectorized indexers separately,
i.e, we can combine successive outer/basic indexers as we are doing now, and store the vectorized indexers and apply them at the evaluation time.
It would gain some benefit from the lazy indexing (if we can assume vectorized indexing is not so frequent.). ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,295621576
https://github.com/pydata/xarray/issues/1897#issuecomment-364281173,https://api.github.com/repos/pydata/xarray/issues/1897,364281173,MDEyOklzc3VlQ29tbWVudDM2NDI4MTE3Mw==,6815844,2018-02-08T23:13:40Z,2018-02-08T23:13:40Z,MEMBER,"I do not yet understand around here, but I guess `cache=True` implies to load all the data into memory but is still indexed lazily?
Is it reasonable to convert this directly to np.ndarray?
Or if it is not, the solution would be
+ Just improve the error message
+ Support vectorised indexing with `LazilyIndexedArray` (needs work)","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,295621576