I want to join two tables which have 4 identical column names (ID, FieldID, FieldCropYear, UpdateUTC). I want to join those two tables on FieldID. 

I used this query:

```
 SELECT * FROM `xxx.yyy.111` AS ACT
    INNER JOIN `xxx.yyy.222` AS BOUND
    ON BOUND.FieldID = ACT.FieldID
    AND BOUND.FieldCropYear = ACT.FieldCropYear

```

After running it, i get the following error: `Duplicate column names in the result are not supported. Found duplicate(s): ID, FieldID, FieldCropYear, UpdateUTC`

Is it possible to select \* but rename those 4 columns in one dataframe? What is the most efficient way to deal with it? 
Is it possible something like:

```
    SELECT * 
EXCEPT(ID, FieldID, UpdateUTC, FieldCropYear), 
                     ID as ID_b,
                     FieldID as FieldID_b,
                     UpdateUTC as UpdateUTC_b,
                     FieldCropYear as FieldCropYear_b
FROM `xxx.yyy.222` AS BOUND
    INNER JOIN `xxx.yyy.111` AS ACT
    ON BOUND.FieldID_b = ACT.FieldID
    AND BOUND.FieldCropYear_b = ACT.FieldCropYear

```