shehabgamin commented on PR #16409:
URL: https://github.com/apache/datafusion/pull/16409#issuecomment-2972618052
Not sure if it makes sense to commit the script I used, so I'll paste it
here for now:
```
"""
WARNING:
- This script extracts only basic, straightforward tests.
- It is not comprehensive and will not capture most function tests.
- Intended as a quick-and-dirty tool for generating minimal Spark
function tests.
- Run this script from the root directory of the Sail project.
"""
import glob
import json
import os
import re
from pyspark.sql import SparkSession
# From project root in Sail: https://github.com/lakehq/sail
FUNCTIONS_PATH = "crates/sail-spark-connect/tests/gold_data/function/"
def extract_simple_function_arguments(query):
"""
Extract arguments from simple function calls of pattern:
SELECT SOME_FUNC(ARG0, ARG1, .... ARGN);
Only accepts basic literal arguments - no arrays, nested functions, etc.
Example queries NOT accepted:
- query = "SELECT any(col) FROM VALUES (NULL), (true), (false) AS
tab(col);"
- query = "SELECT array_append(CAST(null as Array<Int>), 2);"
- query = "SELECT array_append(array('b', 'd', 'c', 'a'), 'd');"
- query = "SELECT * FROM explode(collection => array(10, 20));"
- query = "SELECT cast('10' as int);"
Example queries accepted:
- query = "SELECT ceil(5);"
- query = "SELECT ceil(3.1411, -3);"
- query = "SELECT now();"
"""
if any(f in query.lower() for f in ["cast", "map", "from",
"raise_error", "regexp", "rlike", " in "]):
return None
pattern = r'SELECT\s+\w+\s*\(([^)]*)\)\s*;\s*'
match = re.search(pattern, query, re.IGNORECASE | re.DOTALL)
if not match:
return None
args_string = match.group(1).strip()
if not args_string: # Empty function call
return []
# Filter out complex arguments - reject if contains brackets, parens,
etc...
if any(char in args_string for char in ['[', ']', '(', ')']):
return None
arguments = re.split(r',(?=(?:[^"\']*["\'][^"\']*["\'])*[^"\']*$)',
args_string)
arguments = [arg.strip() for arg in arguments if arg.strip()]
return arguments
def extract_function_name(query):
pattern = r'SELECT\s+(\w+)\s*\(([^)]*)\)\s*;\s*'
match = re.search(pattern, query, re.IGNORECASE | re.DOTALL)
if match:
return match.group(1).strip()
return None
def create_typed_query(query, func_name, type_results):
if not type_results:
return query
typed_args = []
for key, spark_type in type_results.items():
if key.startswith('typeof(') and key.endswith(')'):
arg = key[7:-1]
typed_args.append(f"{arg}::{spark_type}")
typed_query = f"SELECT {func_name}({', '.join(typed_args)});"
return [f"# Original Query: {query}", f"# PySpark 3.5.5 Result:
{type_results}", typed_query]
def main():
spark = SparkSession.builder.getOrCreate()
function_dict = {}
json_files = glob.glob(os.path.join(FUNCTIONS_PATH, "*.json"))
num_queries = 0
for file_path in json_files:
with open(file_path, "r") as f:
data = json.load(f)
directory_name = os.path.basename(file_path).removesuffix('.json')
if directory_name not in function_dict:
function_dict[directory_name] = {}
for test in data["tests"]:
if len(test["input"]["schema"]["fields"]) != 1:
# Skip generator tests with multiple fields
continue
if "exception" in test:
# Skip tests that are expected to raise exceptions
continue
query = test["input"]["query"].strip()
arguments = extract_simple_function_arguments(query)
if arguments is not None:
func_name = extract_function_name(query)
if func_name is not None:
func_call = re.sub('select', '', query,
flags=re.IGNORECASE).strip().rstrip(';').strip()
if arguments:
typeof_parts = [f"typeof({arg})" for arg in
arguments]
combined_query = f"SELECT {func_call},
typeof({func_call}), {', '.join(typeof_parts)};"
else:
combined_query = f"SELECT {func_call},
typeof({func_call});"
print(f"ORIGINAL QUERY: {query}\nRUNNING QUERY:
{combined_query}")
try:
result = spark.sql(combined_query).collect()
except Exception as e:
if "CANNOT_PARSE_DATATYPE" in str(e):
print(f"Skipping query due to unsupported
datatype: {e}")
continue
else:
raise
if len(result) != 1:
spark.stop()
raise ValueError(f"Unexpected result length:
{len(result)} for query: {combined_query}")
result_row = result[0]
type_results = {}
for i in range(2, len(result_row)):
col_name = result_row.__fields__[i]
type_results[col_name.lower()] = result_row[i]
typed_query = create_typed_query(query, func_name,
type_results)
if func_name.lower() not in
function_dict[directory_name]:
function_dict[directory_name][func_name.lower()] = []
function_dict[directory_name][func_name.lower()].append(typed_query)
num_queries += 1
print(f"Processed {num_queries} queries from {len(json_files)} JSON
files.")
base_dir = os.path.join("tmp", "slt")
for directory, functions in function_dict.items():
dir_path = os.path.join(base_dir, directory)
os.makedirs(dir_path, exist_ok=True)
for func_name, queries in functions.items():
file_path = os.path.join(dir_path, f"{func_name}.slt")
with open(file_path, 'w') as f:
for query_data in queries:
f.write(f"#{query_data[0]}\n")
f.write(f"#{query_data[1]}\n")
f.write("#query\n")
f.write(f"#{query_data[2]}\n")
f.write("\n")
spark.stop()
return function_dict
if __name__ == "__main__":
main()
```
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