darsha1706 commented on issue #7656:
URL: https://github.com/apache/iceberg/issues/7656#issuecomment-1577090186
hi @Thijsvandepoll ,
you can try this
def merge_row(row):
merged = spark.sql(f"""
MERGE INTO {namespace}.{table} A
USING (SELECT {row.col1} AS col1, {row.col2} AS col2) B
ON A.col1 = B.col1
WHEN MATCHED THEN UPDATE SET A.col1 = B.col1, A.col2 = B.col2
WHEN NOT MATCHED THEN INSERT *
""")
# Apply the UDF transformation
df = df.withColumn("col1", return_self("col1"))
# Iterate over each row and perform the merge operation
df.foreach(merge_row)
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