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.
BodoSQL's default NULLS FIRST and NULLS LAST behavior is controlled by
an environment variable BODO_SQL_STYLE which has two currently supported
values:
SNOWFLAKE(the default)SPARK
If BODO_SQL_STYLE is set to SNOWFLAKE then the default behavior is NULLS LAST
for ascending order and NULLS FIRST for descending order. If BODO_SQL_STYLE is
set to SPARK then the default behavior is NULLS FIRST for ascending order and
NULLS LAST for descending order. If you are transitioning a query from any other
system we strongly recommend manually specifying NULLS FIRST or NULLS LAST to
ensure the correct behavior.
SELECT <COLUMN_NAMES>
FROM <TABLE_NAME>
ORDER BY <ORDERED_COLUMN_NAMES> [ASC|DESC] [NULLS FIRST|LAST]
For Example:
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