This specification documents how field names in output record batches should be generated based on given user queries. The filed name rules apply to Datafusion queries planned from both SQL queries and Dataframe APIs.
- All field names MUST not contain relation/table qualifier.
- Both
SELECT t1.id
,SELECT id
anddf.select_columns(&["id"])
SHOULD result in field name:id
- Both
- Function names MUST be converted to lowercase.
SELECT AVG(c1)
SHOULD result in field name:avg(c1)
- Literal string MUST not be wrapped with quotes or double quotes.
SELECT 'foo'
SHOULD result in field name:foo
- Operator expressions MUST be wrapped with parentheses.
SELECT -2
SHOULD result in field name:(- 2)
- Operator and operand MUST be separated by spaces.
SELECT 1+2
SHOULD result in field name:(1 + 2)
- Function arguments MUST be separated by a comma
,
and a space.SELECT f(c1,c2)
anddf.select(vec![f.udf("f")?.call(vec![col("c1"), col("c2")])])
SHOULD result in field name:f(c1, c2)
Data schema for test sample queries:
CREATE TABLE t1 (id INT, a VARCHAR(5));
INSERT INTO t1 (id, a) VALUES (1, 'foo');
INSERT INTO t1 (id, a) VALUES (2, 'bar');
CREATE TABLE t2 (id INT, b VARCHAR(5));
INSERT INTO t2 (id, b) VALUES (1, 'hello');
INSERT INTO t2 (id, b) VALUES (2, 'world');
Query:
SELECT t1.id, a, t2.id, b
FROM t1
JOIN t2 ON t1.id = t2.id
Datafusion Arrow record batches output:
id | a | id | b |
---|---|---|---|
1 | foo | 1 | hello |
2 | bar | 2 | world |
Spark, MySQL 8 and PostgreSQL 13 output:
id | a | id | b |
---|---|---|---|
1 | foo | 1 | hello |
2 | bar | 2 | world |
SQLite 3 output:
id | a | b |
---|---|---|
1 | foo | hello |
2 | bar | world |
Query:
SELECT ABS(t1.id), abs(-id) FROM t1;
Datafusion Arrow record batches output:
abs(id) | abs((- id)) |
---|---|
1 | 1 |
2 | 2 |
Spark output:
abs(id) | abs((- id)) |
---|---|
1 | 1 |
2 | 2 |
MySQL 8 output:
ABS(t1.id) | abs(-id) |
---|---|
1 | 1 |
2 | 2 |
PostgreSQL 13 output:
abs | abs |
---|---|
1 | 1 |
2 | 2 |
SQlite 3 output:
ABS(t1.id) | abs(-id) |
---|---|
1 | 1 |
2 | 2 |
Query:
SELECT t1.id + ABS(id), ABS(id * t1.id) FROM t1;
Datafusion Arrow record batches output:
id + abs(id) | abs(id * id) |
---|---|
2 | 1 |
4 | 4 |
Spark output:
id + abs(id) | abs(id * id) |
---|---|
2 | 1 |
4 | 4 |
MySQL 8 output:
t1.id + ABS(id) | ABS(id * t1.id) |
---|---|
2 | 1 |
4 | 4 |
PostgreSQL output:
?column? | abs |
---|---|
2 | 1 |
4 | 4 |
SQLite output:
t1.id + ABS(id) | ABS(id * t1.id) |
---|---|
2 | 1 |
4 | 4 |
Query:
SELECT 1, 2+5, 'foo_bar';
Datafusion Arrow record batches output:
1 | (2 + 5) | foo_bar |
---|---|---|
1 | 7 | foo_bar |
Spark output:
1 | (2 + 5) | foo_bar |
---|---|---|
1 | 7 | foo_bar |
MySQL output:
1 | 2+5 | foo_bar |
---|---|---|
1 | 7 | foo_bar |
PostgreSQL output:
?column? | ?column? | ?column? |
---|---|---|
1 | 7 | foo_bar |
SQLite 3 output:
1 | 2+5 | 'foo_bar' |
---|---|---|
1 | 7 | foo_bar |