[GitHub] [iceberg] saimigo commented on issue #7554: How to ensure the data is not repeated when using spark to write to the iceberg table

["saimigo (via GitHub)" <gi...@apache.org>]

saimigo commented on issue #7554:
URL: https://github.com/apache/iceberg/issues/7554#issuecomment-1538033546

   > @saimigo Are you appending the data, or overwriting? In the case of the first, you can call [`.dropDuplicates` using Spark](https://spark.apache.org/docs/3.1.2/api/python/reference/api/pyspark.sql.DataFrame.dropDuplicates.html). In the case of incremental data, you need to perform a [merge operation](https://iceberg.apache.org/docs/latest/spark-writes/#merge-into).
   
   Appending the data, If I use the merge into operation, do I need to create a new table every time, and then delete this table after merging? 


-- 
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.

To unsubscribe, e-mail: issues-unsubscribe@iceberg.apache.org

For queries about this service, please contact Infrastructure at:
users@infra.apache.org


---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@iceberg.apache.org
For additional commands, e-mail: issues-help@iceberg.apache.org