dbcli/sqlglot
1
0
Fork 0
Code Issues Activity

Adding upstream version 9.0.1.

Browse source 
Signed-off-by: Daniel Baumann <daniel@debian.org>
This commit is contained in:
Daniel Baumann 2025-02-13 14:47:39 +01:00
parent 768d386bf5
commit fca0265317
Signed by: daniel
GPG key ID: FBB4F0E80A80222F
87 changed files with 7994 additions and 421 deletions
Download patch file Download diff file Expand all files Collapse all files

71
tests/dataframe/integration/test_grouped_data.py Normal file
View file

@ -0,0 +1,71 @@
from pyspark.sql import functions as F
from sqlglot.dataframe.sql import functions as SF
from tests.dataframe.integration.dataframe_validator import DataFrameValidator
class TestDataframeFunc(DataFrameValidator):
def test_group_by(self):
df_employee = self.df_spark_employee.groupBy(self.df_spark_employee.age).agg(
F.min(self.df_spark_employee.employee_id)
)
dfs_employee = self.df_sqlglot_employee.groupBy(self.df_sqlglot_employee.age).agg(
SF.min(self.df_sqlglot_employee.employee_id)
)
self.compare_spark_with_sqlglot(df_employee, dfs_employee, skip_schema_compare=True)
def test_group_by_where_non_aggregate(self):
df_employee = (
self.df_spark_employee.groupBy(self.df_spark_employee.age)
.agg(F.min(self.df_spark_employee.employee_id).alias("min_employee_id"))
.where(F.col("age") > F.lit(50))
)
dfs_employee = (
self.df_sqlglot_employee.groupBy(self.df_sqlglot_employee.age)
.agg(SF.min(self.df_sqlglot_employee.employee_id).alias("min_employee_id"))
.where(SF.col("age") > SF.lit(50))
)
self.compare_spark_with_sqlglot(df_employee, dfs_employee)
def test_group_by_where_aggregate_like_having(self):
df_employee = (
self.df_spark_employee.groupBy(self.df_spark_employee.age)
.agg(F.min(self.df_spark_employee.employee_id).alias("min_employee_id"))
.where(F.col("min_employee_id") > F.lit(1))
)
dfs_employee = (
self.df_sqlglot_employee.groupBy(self.df_sqlglot_employee.age)
.agg(SF.min(self.df_sqlglot_employee.employee_id).alias("min_employee_id"))
.where(SF.col("min_employee_id") > SF.lit(1))
)
self.compare_spark_with_sqlglot(df_employee, dfs_employee)
def test_count(self):
df = self.df_spark_employee.groupBy(self.df_spark_employee.age).count()
dfs = self.df_sqlglot_employee.groupBy(self.df_sqlglot_employee.age).count()
self.compare_spark_with_sqlglot(df, dfs)
def test_mean(self):
df = self.df_spark_employee.groupBy().mean("age", "store_id")
dfs = self.df_sqlglot_employee.groupBy().mean("age", "store_id")
self.compare_spark_with_sqlglot(df, dfs)
def test_avg(self):
df = self.df_spark_employee.groupBy("age").avg("store_id")
dfs = self.df_sqlglot_employee.groupBy("age").avg("store_id")
self.compare_spark_with_sqlglot(df, dfs)
def test_max(self):
df = self.df_spark_employee.groupBy("age").max("store_id")
dfs = self.df_sqlglot_employee.groupBy("age").max("store_id")
self.compare_spark_with_sqlglot(df, dfs)
def test_min(self):
df = self.df_spark_employee.groupBy("age").min("store_id")
dfs = self.df_sqlglot_employee.groupBy("age").min("store_id")
self.compare_spark_with_sqlglot(df, dfs)
def test_sum(self):
df = self.df_spark_employee.groupBy("age").sum("store_id")
dfs = self.df_sqlglot_employee.groupBy("age").sum("store_id")
self.compare_spark_with_sqlglot(df, dfs)