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new a6db459328d [MINOR] Removing redundant parentheses from SQL function
docs
a6db459328d is described below
commit a6db459328d7aa75e43097ddf2286c146646810a
Author: panbingkun <pbk1...@gmail.com>
AuthorDate: Fri Jul 14 08:40:21 2023 +0900
[MINOR] Removing redundant parentheses from SQL function docs
### What changes were proposed in this pull request?
The pr aims to removing redundant parentheses from SQL function docs.
### Why are the changes needed?
Make the document clearer, reduce misunderstandings.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
- Manually test.
Closes #41984 from panbingkun/minor_function_docs.
Authored-by: panbingkun <pbk1...@gmail.com>
Signed-off-by: Hyukjin Kwon <gurwls...@apache.org>
---
python/pyspark/sql/connect/functions.py | 2 +-
python/pyspark/sql/functions.py | 4 ++--
.../spark/sql/catalyst/expressions/aggregate/MaxByAndMinBy.scala | 4 ++--
.../org/apache/spark/sql/catalyst/expressions/jsonExpressions.scala | 2 +-
sql/core/src/test/resources/sql-functions/sql-expression-schema.md | 4 ++--
5 files changed, 8 insertions(+), 8 deletions(-)
diff --git a/python/pyspark/sql/connect/functions.py
b/python/pyspark/sql/connect/functions.py
index c6445f110c0..1be759d9b6e 100644
--- a/python/pyspark/sql/connect/functions.py
+++ b/python/pyspark/sql/connect/functions.py
@@ -195,7 +195,7 @@ def _invoke_higher_order_function(
:param name: Name of the expression
:param cols: a list of columns
- :param funs: a list of((*Column) -> Column functions.
+ :param funs: a list of (*Column) -> Column functions.
:return: a Column
"""
diff --git a/python/pyspark/sql/functions.py b/python/pyspark/sql/functions.py
index d7a2f529fa6..b2017627598 100644
--- a/python/pyspark/sql/functions.py
+++ b/python/pyspark/sql/functions.py
@@ -12770,7 +12770,7 @@ def arrays_zip(*cols: "ColumnOrName") -> Column:
Examples
--------
>>> from pyspark.sql.functions import arrays_zip
- >>> df = spark.createDataFrame([(([1, 2, 3], [2, 4, 6], [3, 6]))],
['vals1', 'vals2', 'vals3'])
+ >>> df = spark.createDataFrame([([1, 2, 3], [2, 4, 6], [3, 6])], ['vals1',
'vals2', 'vals3'])
>>> df = df.select(arrays_zip(df.vals1, df.vals2,
df.vals3).alias('zipped'))
>>> df.show(truncate=False)
+------------------------------------+
@@ -13041,7 +13041,7 @@ def _invoke_higher_order_function(
:param name: Name of the expression
:param cols: a list of columns
- :param funs: a list of((*Column) -> Column functions.
+ :param funs: a list of (*Column) -> Column functions.
:return: a Column
"""
diff --git
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/MaxByAndMinBy.scala
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/MaxByAndMinBy.scala
index 096a42686a3..56941c9de45 100644
---
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/MaxByAndMinBy.scala
+++
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/MaxByAndMinBy.scala
@@ -96,7 +96,7 @@ abstract class MaxMinBy extends DeclarativeAggregate with
BinaryLike[Expression]
usage = "_FUNC_(x, y) - Returns the value of `x` associated with the maximum
value of `y`.",
examples = """
Examples:
- > SELECT _FUNC_(x, y) FROM VALUES (('a', 10)), (('b', 50)), (('c', 20))
AS tab(x, y);
+ > SELECT _FUNC_(x, y) FROM VALUES ('a', 10), ('b', 50), ('c', 20) AS
tab(x, y);
b
""",
group = "agg_funcs",
@@ -119,7 +119,7 @@ case class MaxBy(valueExpr: Expression, orderingExpr:
Expression) extends MaxMin
usage = "_FUNC_(x, y) - Returns the value of `x` associated with the minimum
value of `y`.",
examples = """
Examples:
- > SELECT _FUNC_(x, y) FROM VALUES (('a', 10)), (('b', 50)), (('c', 20))
AS tab(x, y);
+ > SELECT _FUNC_(x, y) FROM VALUES ('a', 10), ('b', 50), ('c', 20) AS
tab(x, y);
a
""",
group = "agg_funcs",
diff --git
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/jsonExpressions.scala
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/jsonExpressions.scala
index 32c41cba4e1..0bbae04fb89 100644
---
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/jsonExpressions.scala
+++
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/jsonExpressions.scala
@@ -663,7 +663,7 @@ case class JsonToStructs(
{"[1]":{"b":2}}
> SELECT _FUNC_(map('a', 1));
{"a":1}
- > SELECT _FUNC_(array((map('a', 1))));
+ > SELECT _FUNC_(array(map('a', 1)));
[{"a":1}]
""",
group = "json_funcs",
diff --git a/sql/core/src/test/resources/sql-functions/sql-expression-schema.md
b/sql/core/src/test/resources/sql-functions/sql-expression-schema.md
index 11dca77fada..71fde8c7268 100644
--- a/sql/core/src/test/resources/sql-functions/sql-expression-schema.md
+++ b/sql/core/src/test/resources/sql-functions/sql-expression-schema.md
@@ -398,10 +398,10 @@
| org.apache.spark.sql.catalyst.expressions.aggregate.Last | last | SELECT
last(col) FROM VALUES (10), (5), (20) AS tab(col) | struct<last(col):int> |
| org.apache.spark.sql.catalyst.expressions.aggregate.Last | last_value |
SELECT last_value(col) FROM VALUES (10), (5), (20) AS tab(col) |
struct<last_value(col):int> |
| org.apache.spark.sql.catalyst.expressions.aggregate.Max | max | SELECT
max(col) FROM VALUES (10), (50), (20) AS tab(col) | struct<max(col):int> |
-| org.apache.spark.sql.catalyst.expressions.aggregate.MaxBy | max_by | SELECT
max_by(x, y) FROM VALUES (('a', 10)), (('b', 50)), (('c', 20)) AS tab(x, y) |
struct<max_by(x, y):string> |
+| org.apache.spark.sql.catalyst.expressions.aggregate.MaxBy | max_by | SELECT
max_by(x, y) FROM VALUES ('a', 10), ('b', 50), ('c', 20) AS tab(x, y) |
struct<max_by(x, y):string> |
| org.apache.spark.sql.catalyst.expressions.aggregate.Median | median | SELECT
median(col) FROM VALUES (0), (10) AS tab(col) | struct<median(col):double> |
| org.apache.spark.sql.catalyst.expressions.aggregate.Min | min | SELECT
min(col) FROM VALUES (10), (-1), (20) AS tab(col) | struct<min(col):int> |
-| org.apache.spark.sql.catalyst.expressions.aggregate.MinBy | min_by | SELECT
min_by(x, y) FROM VALUES (('a', 10)), (('b', 50)), (('c', 20)) AS tab(x, y) |
struct<min_by(x, y):string> |
+| org.apache.spark.sql.catalyst.expressions.aggregate.MinBy | min_by | SELECT
min_by(x, y) FROM VALUES ('a', 10), ('b', 50), ('c', 20) AS tab(x, y) |
struct<min_by(x, y):string> |
| org.apache.spark.sql.catalyst.expressions.aggregate.Mode | mode | SELECT
mode(col) FROM VALUES (0), (10), (10) AS tab(col) | struct<mode(col):int> |
| org.apache.spark.sql.catalyst.expressions.aggregate.Percentile | percentile
| SELECT percentile(col, 0.3) FROM VALUES (0), (10) AS tab(col) |
struct<percentile(col, 0.3, 1):double> |
| org.apache.spark.sql.catalyst.expressions.aggregate.RegrAvgX | regr_avgx |
SELECT regr_avgx(y, x) FROM VALUES (1, 2), (2, 2), (2, 3), (2, 4) AS tab(y, x)
| struct<regr_avgx(y, x):double> |
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