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/1874#issuecomment-362945533,https://api.github.com/repos/pydata/xarray/issues/1874,362945533,MDEyOklzc3VlQ29tbWVudDM2Mjk0NTUzMw==,1217238,2018-02-04T22:26:44Z,2018-02-04T22:26:44Z,MEMBER,"> Then I need to write the data to a postgres DB. I have tried parsing the array and using an INSERT for every row, but this is taking a very long time (weeks).

I'm not a particular expert on postgres but I suspect it indeed has some sort of bulk insert facilities.

> However, when trying to convert my xarray Dataset to a Pandas Dataframe, I ran out of memory quickly.

If you're working with a 47GB netCDF file, you probably don't have a lot of memory to spare. Often `pandas.DataFrame` objects can use significantly more memory than `xarray.Dataset`, especially keeping in mind that an xarray Dataset can lazily reference data on disk but a DataFrame is always in memory. The best strategy is probably to slice the Dataset into small pieces and to individually convert those.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,293293632