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, 43 deletions

diff --git a/tests/dataframe/integration/test_session.py b/tests/dataframe/integration/test_session.py
deleted file mode 100644
index 3bb3e20..0000000
--- a/tests/dataframe/integration/test_session.py
+++ /dev/null
@@ -1,43 +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 TestSessionFunc(DataFrameValidator):
-    def test_sql_simple_select(self):
-        query = "SELECT fname, lname FROM employee"
-        df = self.spark.sql(query)
-        dfs = self.sqlglot.sql(query)
-        self.compare_spark_with_sqlglot(df, dfs)
-
-    def test_sql_with_join(self):
-        query = """
-        SELECT
-            e.employee_id
-            , s.store_id    
-        FROM
-            employee e
-            INNER JOIN
-            store s
-            ON
-                e.store_id = s.store_id
-        """
-        df = (
-            self.spark.sql(query)
-            .groupBy(F.col("store_id"))
-            .agg(F.countDistinct(F.col("employee_id")))
-        )
-        dfs = (
-            self.sqlglot.sql(query)
-            .groupBy(SF.col("store_id"))
-            .agg(SF.countDistinct(SF.col("employee_id")))
-        )
-        self.compare_spark_with_sqlglot(df, dfs, skip_schema_compare=True)
-
-    def test_nameless_column(self):
-        query = "SELECT MAX(age) FROM employee"
-        df = self.spark.sql(query)
-        dfs = self.sqlglot.sql(query)
-        # Spark will alias the column to `max(age)` while sqlglot will alias to `_col_0` so their schemas will differ
-        self.compare_spark_with_sqlglot(df, dfs, skip_schema_compare=True)