ExplorData24 commented on issue #9205:
URL: https://github.com/apache/iceberg/issues/9205#issuecomment-1838761423

   @nastra 
   Yes, even I tested with iceberg 1.4.2:
   
![image](https://github.com/apache/iceberg/assets/149940691/33d504c1-90f9-4c33-a7ce-2a17912621ce)
   
![image](https://github.com/apache/iceberg/assets/149940691/bc6ef6df-5306-4559-9545-9ed67a837abe)
   
   import os
   import pyspark
   from pyspark.sql import SparkSession
   
   WAREHOUSE = os.environ.get("WAREHOUSE", "s3a://warehouse/")  # Remplacez par 
votre emplacement S3
   AWS_ACCESS_KEY = os.environ.get("AWS_ACCESS_KEY", "0kzFsHD1pFazfIyvBi7S")  
   AWS_SECRET_KEY = os.environ.get("AWS_SECRET_KEY", 
"hC0ZNEwmSuHaU5jjjAv2aMo7oucXcJoj7vfSSH7g") 
   AWS_S3_ENDPOINT = os.environ.get("AWS_S3_ENDPOINT", 
"http://minioserver:9000";)
   conf = (
       pyspark.SparkConf()
       .setAppName('example')
       .set('spark.jars.packages', 
'org.apache.hadoop:hadoop-aws:3.3.2,org.apache.iceberg:iceberg-spark-runtime-3.3_2.12:1.4.2,software.amazon.awssdk:bundle:2.17.178,software.amazon.awssdk:url-connection-client:2.17.178')
       .set('spark.sql.extensions', 
'org.apache.iceberg.spark.extensions.IcebergSparkSessionExtensions')
       .set('spark.sql.catalog.iceberg', 
'org.apache.iceberg.spark.SparkCatalog')
       .set('spark.sql.catalog.iceberg.type', 'hadoop')
       .set('spark.sql.catalog.iceberg.io-impl', 
'org.apache.iceberg.aws.s3.S3FileIO')
       .set('spark.sql.catalog.iceberg.warehouse', WAREHOUSE)
       .set('spark.hadoop.fs.s3a.access.key', AWS_ACCESS_KEY)
       .set('spark.hadoop.fs.s3a.secret.key', AWS_SECRET_KEY)
       .set('spark.hadoop.fs.s3a.endpoint', AWS_S3_ENDPOINT)
       .set('spark.hadoop.fs.s3a.path.style.access', 'true')
       .set('spark.hadoop.fs.s3a.connection.ssl.enabled', 'true')
       .set('spark.executor.extraJavaOptions', 
'-Dcom.amazonaws.services.s3.enableV4=true')  
       .set('spark.driver.extraJavaOptions', 
'-Dcom.amazonaws.services.s3.enableV4=true')  
   )
   spark = SparkSession.builder.config(conf=conf).getOrCreate()
   print("Spark Running")
   spark.sql("CREATE TABLE iceberg.tab (name string) USING iceberg;")
   It always brings together the same error:
   
![image](https://github.com/apache/iceberg/assets/149940691/fa612063-b619-4b40-9cc2-02a5ec9c2876)
   


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