ORDER BY¶

The ORDER BY keyword sorts the resulting DataFrame in ascending or descending order. By default, it sorts the records in ascending order. NULLs are sorted in accordance with the optional NULLS FIRST or NULLS LAST keywords.

If the null ordering is not provided, then the default ordering depends on if the column is ascending or descending. For ascending order, by default NULL values are returned at the end, while for descending order nulls are returned at the front. If the order of nulls matter we strongly recommend explicitly providing either NULLS FIRST or NULLS LAST.

SELECT <COLUMN_NAMES>
FROM <TABLE_NAME>
ORDER BY <ORDERED_COLUMN_NAMES> [ASC|DESC] [NULLS FIRST|LAST]

For Example:

SELECT A, B FROM table1 ORDER BY B, A DESC NULLS LAST

Example Usage¶

>>>@bodo.jit
... def g(df):
...    bc = bodosql.BodoSQLContext({"CUSTOMERS":df})
...    query = "SELECT name, balance FROM customers ORDER BY balance"
...    res = bc.sql(query)
...    return res

>>>customers_df = pd.DataFrame({
...     "CUSTOMERID": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
...     "NAME": ["Deangelo Todd","Nikolai Kent","Eden Heath", "Taliyah Martinez",
...                 "Demetrius Chavez","Weston Jefferson","Jonathon Middleton",
...                 "Shawn Winters","Keely Hutchinson", "Darryl Rosales",],
...     "BALANCE": [1123.34, 2133.43, 23.58, 8345.15, 943.43, 68.34, 12764.50, 3489.25, 654.24, 25645.39]
... })

>>>g(customers_df)
                NAME   BALANCE
2          Eden Heath     23.58
5    Weston Jefferson     68.34
8    Keely Hutchinson    654.24
4    Demetrius Chavez    943.43
0       Deangelo Todd   1123.34
1        Nikolai Kent   2133.43
7       Shawn Winters   3489.25
3    Taliyah Martinez   8345.15
6  Jonathon Middleton  12764.50
9      Darryl Rosales  25645.39