mustafasrepo opened a new pull request, #7040:
URL: https://github.com/apache/arrow-datafusion/pull/7040

   # Which issue does this PR close?
   
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   Closes [#6190](https://github.com/apache/arrow-datafusion/issues/6190).
   
   # Rationale for this change
   
   Primary key information specifies that some of the columns in the table, 
would consist of unique values. This contract enables us to support additional 
queries, currently cannot be run by datafusiuon.
   Consider the query below
   ```sql
   SELECT sn, amount
               FROM sales_global
               GROUP BY sn
   ```
   When `sn` is `PRIMARY KEY` (each `sn` will have unique values) we know that, 
all the columns the table `sales_global`  can be emitted after aggregation 
(since for each group all rows would have same value). In terms of 
functionality, above query and following query 
   ```sql
   SELECT sn, amount
               FROM sales_global
               GROUP BY sn, amount
   ```
   are same. The reason is that, since column `sn` already consists of unique 
values; both `GROUP BY sn, amount` and `GROUP BY sn` will produce groups that 
consist of single row. 
   ```sql
   SELECT sn, amount
               FROM sales_global
               GROUP BY sn
   ```
   Above query can run in Postgre. However, datafusion can only emit `sn` after 
aggregation from the original table. With this PR above query also supported by 
Datafusion.
   
   As part of this PR, we keep track of identifier key (where primary key is a 
special case) to accomplish this.  To illusturate what an identifier key is 
   Consider table below
   | a  | b |
   | ---- | --- |
   | 1  | USD    |
   | 2 | USD    |
   | 3    | TRY    |
   
   In table above, `column a` consists of unique values, it is primary key. We 
store this information as 
   ```rust
   IdentifierKeyGroup{
     identifier_key_indices: vec![0], 
     is_unique: true, 
     associated_indices: vec![0, 1])
   }
   ```
   this means that, when we know the value of `0th` column, we will know the 
values of `0th and 1st` columns deterministically. And each row will be unique.
   As an another example, consider table below,
   | a | b | 
   | ----- | ----- | 
   | 1  | USD |
   | 1  | USD |
   | 2 | USD |
   | 2 | USD |
   | 3    | TRY |
   | 3    | TRY |
   
   In the example above,  `column a` is not primary key, however, still knowing 
value of `a` enables us to know value of `b` deterministically. We encode this 
information as 
   ```rust
   IdentifierKeyGroup{
     identifier_key_indices: vec![0], 
     is_unique: false, 
     associated_indices: vec![0, 1])
   }
   ```
   All of these information are propagated from the primary key information at 
the source. These analysis enables us to support complex queries. As an 
example, while we can support query below
   ```sql
   SELECT r.sn, SUM(l.amount), r.amount
     FROM sales_global_with_pk AS l
     JOIN sales_global_with_pk AS r
     ON l.sn >= r.sn
     GROUP BY r.sn
     ORDER BY r.sn
   ```
   we reject, following query
   ```sql
   SELECT l.sn, r.sn, SUM(l.amount), r.amount
     FROM sales_global_with_pk AS l
     JOIN sales_global_with_pk AS r
     ON l.sn >= r.sn
     GROUP BY l.sn
     ORDER BY l.sn
   ```
   because second query, uses an unassociated column(`r.sn`) with `l.sn` after 
group by, whereas, first query uses only associated columns(`r.sn`, `r.amount`) 
with `r.sn` during projection.
   
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   # What changes are included in this PR?
   
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   # Are these changes tested?
   Yes, new tests that show supported functionality are added to the 
`groupby.slt` file.
   
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