rangareddy commented on issue #10770:
URL: https://github.com/apache/hudi/issues/10770#issuecomment-2578014935
Hi @Cpandey43
Below is the PySpark code to ingest Array[bytes] data.
```python
from pyspark.sql.types import StructType, StructField, ArrayType,
BinaryType, StringType
data = [
("1", [b"byte1", b"byte2"]),
("2", [b"byte3", b"byte4"]),
]
schema = StructType([
StructField("id", StringType(), True),
StructField("byte_array_column", ArrayType(BinaryType()), True),
])
df = spark.createDataFrame(data, schema)
df.show(truncate=False)
table_name = "hudi_array_byte_table"
output_path = f"s3a://warehouse/{table_name}"
hudi_options = {
"hoodie.table.name": table_name,
"hoodie.datasource.write.recordkey.field": "id",
"hoodie.datasource.write.partitionpath.field": "",
"hoodie.datasource.write.table.type": "COPY_ON_WRITE",
"hoodie.datasource.write.precombine.field": "id",
}
df.write.format("hudi") \
.options(**hudi_options) \
.mode("overwrite") \
.save(output_path)
hudi_df = spark.read.format("hudi").load(output_path)
hudi_df.show(truncate=False)
```
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