Let us try to simulate this error
from pyspark.sql import SparkSession
import os
# Create a SparkSession
spark = SparkSession.builder.appName("SomeTestsForIncompleteWriteSimulation").getOrCreate()
# Sample DataFrame
data = [("A", 1), ("B", 2), ("A", 3), ("C", 5)]
df = spark.createDataFrame(data, ["col1", "col2"])
# Simulate an error during write
try:
df.write.partitionBy("col1").mode("overwrite").csv("/tmp/output", header=True)
except Exception as e:
print("Simulating write error:", e)
# Check for existence of "_SUCCESS" file in local /tmp
success_file = "/tmp/output/_SUCCESS"
if os.path.exists(success_file):
print("_SUCCESS file found (might not reflect reality if error occurred earlier)")
else:
print("_SUCCESS file missing (indicates incomplete write)")
and the output
_SUCCESS file missing (indicates incomplete write)
Mich Talebzadeh | Technologist | Data | Generative AI | Financial Fraud
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Disclaimer: The information provided is correct to the best of my knowledge but of course cannot be guaranteed . It is essential to note that, as with any advice, quote "one test result is worth one-thousand expert opinions (Werner Von Braun)".