[SPARK-36683][SQL] Add new built-in SQL functions: SEC and CSC
### What changes were proposed in this pull request? Add new built-in SQL functions: secant and cosecant, and add them as Scala and Python functions. ### Why are the changes needed? Cotangent has been supported in Spark SQL but Secant and Cosecant are missing though I believe they can be used as much as cot. Related Links: [SPARK-20751](https://github.com/apache/spark/pull/17999) [SPARK-36660](https://github.com/apache/spark/pull/33906) ### Does this PR introduce _any_ user-facing change? Yes, users can now use these functions. ### How was this patch tested? Unit tests Closes #33988 from yutoacts/SPARK-36683. Authored-by: Yuto Akutsu <yuto.akutsu@oss.nttdata.com> Signed-off-by: Kousuke Saruta <sarutak@oss.nttdata.com>
This commit is contained in:
Yuto Akutsu
Kousuke Saruta
parent
4cc39cfe15
commit
30d17b6333
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@ -394,6 +394,7 @@ Functions
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covar_samp
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crc32
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create_map
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csc
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cume_dist
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current_date
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current_timestamp
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@ -511,6 +512,7 @@ Functions
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rtrim
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schema_of_csv
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schema_of_json
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sec
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second
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sentences
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sequence
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@ -253,6 +253,8 @@ def product(col):
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def acos(col):
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"""
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Computes inverse cosine of the input column.
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.. versionadded:: 1.4.0
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Returns
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@ -278,6 +280,8 @@ def acosh(col):
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def asin(col):
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"""
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Computes inverse sine of the input column.
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.. versionadded:: 1.3.0
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@ -304,6 +308,8 @@ def asinh(col):
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def atan(col):
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"""
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Compute inverse tangent of the input column.
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.. versionadded:: 1.4.0
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Returns
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@ -345,6 +351,8 @@ def ceil(col):
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def cos(col):
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"""
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Computes cosine of the input column.
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.. versionadded:: 1.4.0
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Parameters
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@ -362,6 +370,8 @@ def cos(col):
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def cosh(col):
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"""
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Computes hyperbolic cosine of the input column.
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.. versionadded:: 1.4.0
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Parameters
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@ -379,6 +389,8 @@ def cosh(col):
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def cot(col):
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"""
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Computes cotangent of the input column.
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.. versionadded:: 3.3.0
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Parameters
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@ -394,6 +406,25 @@ def cot(col):
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return _invoke_function_over_column("cot", col)
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def csc(col):
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"""
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Computes cosecant of the input column.
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.. versionadded:: 3.3.0
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Parameters
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----------
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col : :class:`~pyspark.sql.Column` or str
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Angle in radians
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Returns
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-------
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:class:`~pyspark.sql.Column`
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Cosecant of the angle.
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"""
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return _invoke_function_over_column("csc", col)
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@since(1.4)
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def exp(col):
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"""
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@ -451,6 +482,25 @@ def rint(col):
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return _invoke_function_over_column("rint", col)
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def sec(col):
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"""
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Computes secant of the input column.
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.. versionadded:: 3.3.0
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Parameters
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----------
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col : :class:`~pyspark.sql.Column` or str
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Angle in radians
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Returns
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-------
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:class:`~pyspark.sql.Column`
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Secant of the angle.
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"""
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return _invoke_function_over_column("sec", col)
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@since(1.4)
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def signum(col):
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"""
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@ -461,6 +511,8 @@ def signum(col):
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def sin(col):
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"""
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Computes sine of the input column.
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.. versionadded:: 1.4.0
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Parameters
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@ -477,6 +529,8 @@ def sin(col):
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def sinh(col):
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"""
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Computes hyperbolic sine of the input column.
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.. versionadded:: 1.4.0
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Parameters
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@ -495,6 +549,8 @@ def sinh(col):
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def tan(col):
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"""
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Computes tangent of the input column.
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.. versionadded:: 1.4.0
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Parameters
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@ -512,6 +568,8 @@ def tan(col):
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def tanh(col):
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"""
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Computes hyperbolic tangent of the input column.
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.. versionadded:: 1.4.0
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Parameters
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@ -302,6 +302,7 @@ def cos(col: ColumnOrName) -> Column: ...
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def cosh(col: ColumnOrName) -> Column: ...
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def cot(col: ColumnOrName) -> Column: ...
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def count(col: ColumnOrName) -> Column: ...
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def csc(col: ColumnOrName) -> Column: ...
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def cume_dist() -> Column: ...
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def degrees(col: ColumnOrName) -> Column: ...
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def dense_rank() -> Column: ...
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@ -339,6 +340,7 @@ def rank() -> Column: ...
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def rint(col: ColumnOrName) -> Column: ...
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def row_number() -> Column: ...
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def rtrim(col: ColumnOrName) -> Column: ...
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def sec(col: ColumnOrName) -> Column: ...
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def signum(col: ColumnOrName) -> Column: ...
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def sin(col: ColumnOrName) -> Column: ...
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def sinh(col: ColumnOrName) -> Column: ...
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@ -18,13 +18,15 @@
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import datetime
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from itertools import chain
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import re
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import math
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from py4j.protocol import Py4JJavaError
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from pyspark.sql import Row, Window
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from pyspark.sql import Row, Window, types
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from pyspark.sql.functions import udf, input_file_name, col, percentile_approx, \
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lit, assert_true, sum_distinct, sumDistinct, shiftleft, shiftLeft, shiftRight, \
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shiftright, shiftrightunsigned, shiftRightUnsigned, octet_length, bit_length
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from pyspark.testing.sqlutils import ReusedSQLTestCase
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shiftright, shiftrightunsigned, shiftRightUnsigned, octet_length, bit_length, \
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sec, csc, cot
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from pyspark.testing.sqlutils import ReusedSQLTestCase, SQLTestUtils
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class FunctionsTests(ReusedSQLTestCase):
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@ -109,37 +111,28 @@ class FunctionsTests(ReusedSQLTestCase):
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def test_math_functions(self):
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df = self.sc.parallelize([Row(a=i, b=2 * i) for i in range(10)]).toDF()
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from pyspark.sql import functions
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import math
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def get_values(l):
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return [j[0] for j in l]
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def assert_close(a, b):
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c = get_values(b)
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diff = [abs(v - c[k]) < 1e-6 for k, v in enumerate(a)]
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return sum(diff) == len(a)
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assert_close([math.cos(i) for i in range(10)],
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SQLTestUtils.assert_close([math.cos(i) for i in range(10)],
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df.select(functions.cos(df.a)).collect())
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assert_close([math.cos(i) for i in range(10)],
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SQLTestUtils.assert_close([math.cos(i) for i in range(10)],
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df.select(functions.cos("a")).collect())
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assert_close([math.sin(i) for i in range(10)],
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SQLTestUtils.assert_close([math.sin(i) for i in range(10)],
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df.select(functions.sin(df.a)).collect())
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assert_close([math.sin(i) for i in range(10)],
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SQLTestUtils.assert_close([math.sin(i) for i in range(10)],
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df.select(functions.sin(df['a'])).collect())
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assert_close([math.pow(i, 2 * i) for i in range(10)],
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SQLTestUtils.assert_close([math.pow(i, 2 * i) for i in range(10)],
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df.select(functions.pow(df.a, df.b)).collect())
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assert_close([math.pow(i, 2) for i in range(10)],
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SQLTestUtils.assert_close([math.pow(i, 2) for i in range(10)],
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df.select(functions.pow(df.a, 2)).collect())
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assert_close([math.pow(i, 2) for i in range(10)],
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SQLTestUtils.assert_close([math.pow(i, 2) for i in range(10)],
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df.select(functions.pow(df.a, 2.0)).collect())
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assert_close([math.hypot(i, 2 * i) for i in range(10)],
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SQLTestUtils.assert_close([math.hypot(i, 2 * i) for i in range(10)],
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df.select(functions.hypot(df.a, df.b)).collect())
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assert_close([math.hypot(i, 2 * i) for i in range(10)],
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SQLTestUtils.assert_close([math.hypot(i, 2 * i) for i in range(10)],
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df.select(functions.hypot("a", u"b")).collect())
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assert_close([math.hypot(i, 2) for i in range(10)],
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SQLTestUtils.assert_close([math.hypot(i, 2) for i in range(10)],
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df.select(functions.hypot("a", 2)).collect())
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assert_close([math.hypot(i, 2) for i in range(10)],
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SQLTestUtils.assert_close([math.hypot(i, 2) for i in range(10)],
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df.select(functions.hypot(df.a, 2)).collect())
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def test_inverse_trig_functions(self):
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@ -157,6 +150,23 @@ class FunctionsTests(ReusedSQLTestCase):
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for c in cols:
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self.assertIn(f"{alias}(a)", repr(f(c)))
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def test_reciprocal_trig_functions(self):
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# SPARK-36683: Tests for reciprocal trig functions (SEC, CSC and COT)
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lst = [0.0, math.pi / 6, math.pi / 4, math.pi / 3, math.pi / 2,
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math.pi, 3 * math.pi / 2, 2 * math.pi]
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df = self.spark.createDataFrame(lst, types.DoubleType())
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def to_reciprocal_trig(func):
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return [1.0 / func(i) if func(i) != 0 else math.inf for i in lst]
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SQLTestUtils.assert_close(to_reciprocal_trig(math.cos),
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df.select(sec(df.value)).collect())
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SQLTestUtils.assert_close(to_reciprocal_trig(math.sin),
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df.select(csc(df.value)).collect())
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SQLTestUtils.assert_close(to_reciprocal_trig(math.tan),
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df.select(cot(df.value)).collect())
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def test_rand_functions(self):
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df = self.df
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from pyspark.sql import functions
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@ -16,6 +16,7 @@
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#
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import datetime
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import math
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import os
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import shutil
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import tempfile
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@ -243,6 +244,13 @@ class SQLTestUtils(object):
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for f in functions:
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self.spark.sql("DROP FUNCTION IF EXISTS %s" % f)
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@staticmethod
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def assert_close(a, b):
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c = [j[0] for j in b]
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diff = [abs(v - c[k]) < 1e-6 if math.isfinite(v) else v == c[k]
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for k, v in enumerate(a)]
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return sum(diff) == len(a)
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class ReusedSQLTestCase(ReusedPySparkTestCase, SQLTestUtils):
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@classmethod
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@ -361,6 +361,7 @@ object FunctionRegistry {
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expression[Ceil]("ceil"),
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expression[Ceil]("ceiling", true),
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expression[Cos]("cos"),
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expression[Sec]("sec"),
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expression[Cosh]("cosh"),
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expression[Conv]("conv"),
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expression[ToDegrees]("degrees"),
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@ -392,6 +393,7 @@ object FunctionRegistry {
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expression[Signum]("sign", true),
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expression[Signum]("signum"),
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expression[Sin]("sin"),
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expression[Csc]("csc"),
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expression[Sinh]("sinh"),
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expression[StringToMap]("str_to_map"),
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expression[Sqrt]("sqrt"),
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@ -299,6 +299,29 @@ case class Cos(child: Expression) extends UnaryMathExpression(math.cos, "COS") {
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override protected def withNewChildInternal(newChild: Expression): Cos = copy(child = newChild)
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}
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@ExpressionDescription(
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usage = """
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_FUNC_(expr) - Returns the secant of `expr`, as if computed by `1/java.lang.Math.cos`.
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""",
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arguments = """
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Arguments:
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* expr - angle in radians
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""",
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examples = """
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Examples:
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> SELECT _FUNC_(0);
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1.0
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""",
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since = "3.3.0",
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group = "math_funcs")
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case class Sec(child: Expression)
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extends UnaryMathExpression((x: Double) => 1 / math.cos(x), "SEC") {
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override def doGenCode(ctx: CodegenContext, ev: ExprCode): ExprCode = {
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defineCodeGen(ctx, ev, c => s"${ev.value} = 1 / java.lang.Math.cos($c);")
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}
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override protected def withNewChildInternal(newChild: Expression): Sec = copy(child = newChild)
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}
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@ExpressionDescription(
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usage = """
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_FUNC_(expr) - Returns the hyperbolic cosine of `expr`, as if computed by
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@ -655,6 +678,29 @@ case class Sin(child: Expression) extends UnaryMathExpression(math.sin, "SIN") {
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override protected def withNewChildInternal(newChild: Expression): Sin = copy(child = newChild)
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}
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@ExpressionDescription(
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usage = """
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_FUNC_(expr) - Returns the cosecant of `expr`, as if computed by `1/java.lang.Math.sin`.
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""",
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arguments = """
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Arguments:
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* expr - angle in radians
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""",
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examples = """
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Examples:
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> SELECT _FUNC_(1);
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1.1883951057781212
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""",
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since = "3.3.0",
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group = "math_funcs")
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case class Csc(child: Expression)
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extends UnaryMathExpression((x: Double) => 1 / math.sin(x), "CSC") {
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override def doGenCode(ctx: CodegenContext, ev: ExprCode): ExprCode = {
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defineCodeGen(ctx, ev, c => s"${ev.value} = 1 / java.lang.Math.sin($c);")
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}
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override protected def withNewChildInternal(newChild: Expression): Csc = copy(child = newChild)
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}
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@ExpressionDescription(
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usage = """
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_FUNC_(expr) - Returns hyperbolic sine of `expr`, as if computed by `java.lang.Math._FUNC_`.
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@ -187,6 +187,20 @@ class MathExpressionsSuite extends SparkFunSuite with ExpressionEvalHelper {
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checkConsistencyBetweenInterpretedAndCodegen(Sin, DoubleType)
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}
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test("csc") {
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def f: (Double) => Double = (x: Double) => 1 / math.sin(x)
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testUnary(Csc, f)
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checkConsistencyBetweenInterpretedAndCodegen(Csc, DoubleType)
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val nullLit = Literal.create(null, NullType)
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val intNullLit = Literal.create(null, IntegerType)
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val intLit = Literal.create(1, IntegerType)
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checkEvaluation(checkDataTypeAndCast(Csc(nullLit)), null, EmptyRow)
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checkEvaluation(checkDataTypeAndCast(Csc(intNullLit)), null, EmptyRow)
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checkEvaluation(checkDataTypeAndCast(Csc(intLit)), 1 / math.sin(1), EmptyRow)
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checkEvaluation(checkDataTypeAndCast(Csc(-intLit)), 1 / math.sin(-1), EmptyRow)
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checkEvaluation(checkDataTypeAndCast(Csc(0)), 1 / math.sin(0), EmptyRow)
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}
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test("asin") {
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testUnary(Asin, math.asin, (-10 to 10).map(_ * 0.1))
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testUnary(Asin, math.asin, (11 to 20).map(_ * 0.1), expectNaN = true)
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@ -215,6 +229,20 @@ class MathExpressionsSuite extends SparkFunSuite with ExpressionEvalHelper {
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checkConsistencyBetweenInterpretedAndCodegen(Cos, DoubleType)
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}
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test("sec") {
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def f: (Double) => Double = (x: Double) => 1 / math.cos(x)
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testUnary(Sec, f)
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checkConsistencyBetweenInterpretedAndCodegen(Sec, DoubleType)
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val nullLit = Literal.create(null, NullType)
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val intNullLit = Literal.create(null, IntegerType)
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val intLit = Literal.create(1, IntegerType)
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checkEvaluation(checkDataTypeAndCast(Sec(nullLit)), null, EmptyRow)
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checkEvaluation(checkDataTypeAndCast(Sec(intNullLit)), null, EmptyRow)
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checkEvaluation(checkDataTypeAndCast(Sec(intLit)), 1 / math.cos(1), EmptyRow)
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checkEvaluation(checkDataTypeAndCast(Sec(-intLit)), 1 / math.cos(-1), EmptyRow)
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checkEvaluation(checkDataTypeAndCast(Sec(0)), 1 / math.cos(0), EmptyRow)
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}
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test("acos") {
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testUnary(Acos, math.acos, (-10 to 10).map(_ * 0.1))
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testUnary(Acos, math.acos, (11 to 20).map(_ * 0.1), expectNaN = true)
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@ -1809,6 +1809,15 @@ object functions {
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*/
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def cot(e: Column): Column = withExpr { Cot(e.expr) }
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/**
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* @param e angle in radians
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* @return cosecant of the angle
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*
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* @group math_funcs
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* @since 3.3.0
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*/
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def csc(e: Column): Column = withExpr { Csc(e.expr) }
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/**
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* Computes the exponential of the given value.
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*
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@ -2197,6 +2206,15 @@ object functions {
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*/
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def bround(e: Column, scale: Int): Column = withExpr { BRound(e.expr, Literal(scale)) }
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/**
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* @param e angle in radians
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* @return secant of the angle
|
||||
*
|
||||
* @group math_funcs
|
||||
* @since 3.3.0
|
||||
*/
|
||||
def sec(e: Column): Column = withExpr { Sec(e.expr) }
|
||||
|
||||
/**
|
||||
* Shift the given value numBits left. If the given value is a long value, this function
|
||||
* will return a long value else it will return an integer value.
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
<!-- Automatically generated by ExpressionsSchemaSuite -->
|
||||
## Summary
|
||||
- Number of queries: 362
|
||||
- Number of queries: 364
|
||||
- Number of expressions that missing example: 12
|
||||
- Expressions missing examples: bigint,binary,boolean,date,decimal,double,float,int,smallint,string,timestamp,tinyint
|
||||
## Schema of Built-in Functions
|
||||
|
|
@ -82,6 +82,7 @@
|
|||
| org.apache.spark.sql.catalyst.expressions.CreateMap | map | SELECT map(1.0, '2', 3.0, '4') | struct<map(1.0, 2, 3.0, 4):map<decimal(2,1),string>> |
|
||||
| org.apache.spark.sql.catalyst.expressions.CreateNamedStruct | named_struct | SELECT named_struct("a", 1, "b", 2, "c", 3) | struct<named_struct(a, 1, b, 2, c, 3):struct<a:int,b:int,c:int>> |
|
||||
| org.apache.spark.sql.catalyst.expressions.CreateNamedStruct | struct | SELECT struct(1, 2, 3) | struct<struct(1, 2, 3):struct<col1:int,col2:int,col3:int>> |
|
||||
| org.apache.spark.sql.catalyst.expressions.Csc | csc | SELECT csc(1) | struct<CSC(1):double> |
|
||||
| org.apache.spark.sql.catalyst.expressions.CsvToStructs | from_csv | SELECT from_csv('1, 0.8', 'a INT, b DOUBLE') | struct<from_csv(1, 0.8):struct<a:int,b:double>> |
|
||||
| org.apache.spark.sql.catalyst.expressions.CumeDist | cume_dist | SELECT a, b, cume_dist() OVER (PARTITION BY a ORDER BY b) FROM VALUES ('A1', 2), ('A1', 1), ('A2', 3), ('A1', 1) tab(a, b) | struct<a:string,b:int,cume_dist() OVER (PARTITION BY a ORDER BY b ASC NULLS FIRST RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW):double> |
|
||||
| org.apache.spark.sql.catalyst.expressions.CurrentCatalog | current_catalog | SELECT current_catalog() | struct<current_catalog():string> |
|
||||
|
|
@ -241,6 +242,7 @@
|
|||
| org.apache.spark.sql.catalyst.expressions.RowNumber | row_number | SELECT a, b, row_number() OVER (PARTITION BY a ORDER BY b) FROM VALUES ('A1', 2), ('A1', 1), ('A2', 3), ('A1', 1) tab(a, b) | struct<a:string,b:int,row_number() OVER (PARTITION BY a ORDER BY b ASC NULLS FIRST ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW):int> |
|
||||
| org.apache.spark.sql.catalyst.expressions.SchemaOfCsv | schema_of_csv | SELECT schema_of_csv('1,abc') | struct<schema_of_csv(1,abc):string> |
|
||||
| org.apache.spark.sql.catalyst.expressions.SchemaOfJson | schema_of_json | SELECT schema_of_json('[{"col":0}]') | struct<schema_of_json([{"col":0}]):string> |
|
||||
| org.apache.spark.sql.catalyst.expressions.Sec | sec | SELECT sec(0) | struct<SEC(0):double> |
|
||||
| org.apache.spark.sql.catalyst.expressions.Second | second | SELECT second('2009-07-30 12:58:59') | struct<second(2009-07-30 12:58:59):int> |
|
||||
| org.apache.spark.sql.catalyst.expressions.SecondsToTimestamp | timestamp_seconds | SELECT timestamp_seconds(1230219000) | struct<timestamp_seconds(1230219000):timestamp> |
|
||||
| org.apache.spark.sql.catalyst.expressions.Sentences | sentences | SELECT sentences('Hi there! Good morning.') | struct<sentences(Hi there! Good morning., , ):array<array<string>>> |
|
||||
|
|
|
|||
|
|
@ -40,6 +40,14 @@ select 5 % 3;
|
|||
select pmod(-7, 3);
|
||||
|
||||
-- math functions
|
||||
select sec(1);
|
||||
select sec(null);
|
||||
select sec(0);
|
||||
select sec(-1);
|
||||
select csc(1);
|
||||
select csc(null);
|
||||
select csc(0);
|
||||
select csc(-1);
|
||||
select cot(1);
|
||||
select cot(null);
|
||||
select cot(0);
|
||||
|
|
|
|||
|
|
@ -1,5 +1,5 @@
|
|||
-- Automatically generated by SQLQueryTestSuite
|
||||
-- Number of queries: 69
|
||||
-- Number of queries: 77
|
||||
|
||||
|
||||
-- !query
|
||||
|
|
@ -258,6 +258,70 @@ struct<pmod(-7, 3):int>
|
|||
2
|
||||
|
||||
|
||||
-- !query
|
||||
select sec(1)
|
||||
-- !query schema
|
||||
struct<SEC(1):double>
|
||||
-- !query output
|
||||
1.8508157176809255
|
||||
|
||||
|
||||
-- !query
|
||||
select sec(null)
|
||||
-- !query schema
|
||||
struct<SEC(NULL):double>
|
||||
-- !query output
|
||||
NULL
|
||||
|
||||
|
||||
-- !query
|
||||
select sec(0)
|
||||
-- !query schema
|
||||
struct<SEC(0):double>
|
||||
-- !query output
|
||||
1.0
|
||||
|
||||
|
||||
-- !query
|
||||
select sec(-1)
|
||||
-- !query schema
|
||||
struct<SEC(-1):double>
|
||||
-- !query output
|
||||
1.8508157176809255
|
||||
|
||||
|
||||
-- !query
|
||||
select csc(1)
|
||||
-- !query schema
|
||||
struct<CSC(1):double>
|
||||
-- !query output
|
||||
1.1883951057781212
|
||||
|
||||
|
||||
-- !query
|
||||
select csc(null)
|
||||
-- !query schema
|
||||
struct<CSC(NULL):double>
|
||||
-- !query output
|
||||
NULL
|
||||
|
||||
|
||||
-- !query
|
||||
select csc(0)
|
||||
-- !query schema
|
||||
struct<CSC(0):double>
|
||||
-- !query output
|
||||
Infinity
|
||||
|
||||
|
||||
-- !query
|
||||
select csc(-1)
|
||||
-- !query schema
|
||||
struct<CSC(-1):double>
|
||||
-- !query output
|
||||
-1.1883951057781212
|
||||
|
||||
|
||||
-- !query
|
||||
select cot(1)
|
||||
-- !query schema
|
||||
|
|
|
|||
|
|
@ -117,6 +117,11 @@ class MathFunctionsSuite extends QueryTest with SharedSparkSession {
|
|||
testOneToOneMathFunction(sin, math.sin)
|
||||
}
|
||||
|
||||
test("csc") {
|
||||
testOneToOneMathFunction(csc,
|
||||
(x: Double) => (1 / math.sin(x)) )
|
||||
}
|
||||
|
||||
test("asin") {
|
||||
testOneToOneMathFunction(asin, math.asin)
|
||||
}
|
||||
|
|
@ -134,6 +139,11 @@ class MathFunctionsSuite extends QueryTest with SharedSparkSession {
|
|||
testOneToOneMathFunction(cos, math.cos)
|
||||
}
|
||||
|
||||
test("sec") {
|
||||
testOneToOneMathFunction(sec,
|
||||
(x: Double) => (1 / math.cos(x)) )
|
||||
}
|
||||
|
||||
test("acos") {
|
||||
testOneToOneMathFunction(acos, math.acos)
|
||||
}
|
||||
|
|
@ -151,6 +161,11 @@ class MathFunctionsSuite extends QueryTest with SharedSparkSession {
|
|||
testOneToOneMathFunction(tan, math.tan)
|
||||
}
|
||||
|
||||
test("cot") {
|
||||
testOneToOneMathFunction(cot,
|
||||
(x: Double) => (1 / math.tan(x)) )
|
||||
}
|
||||
|
||||
test("atan") {
|
||||
testOneToOneMathFunction(atan, math.atan)
|
||||
}
|
||||
|
|
|
|||
Loading…
Reference in a new issue