Adding upstream version 24.0.0.upstream/24.0.0

Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>

1 files changed, 0 insertions, 71 deletions

diff --git a/tests/dataframe/integration/test_grouped_data.py b/tests/dataframe/integration/test_grouped_data.py
deleted file mode 100644
index 2768dda..0000000
--- a/tests/dataframe/integration/test_grouped_data.py
+++ /dev/null
@@ -1,71 +0,0 @@
-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)