[Bug] [flink] Could not read External Tables

### Search before asking

- [X] I searched in the [issues](https://github.com/apache/incubator-paimon/issues) and found nothing similar.

### Paimon version

0.5

### Compute Engine

Flink 1.16.2

### Minimal reproduce step

[upload_excel.xlsx](https://github.com/apache/incubator-paimon/files/12459344/upload_excel.xlsx)
1. I trans this excel to parquet

df = pd.read_excel(args.file, sheet_name='data')
parquet_file = '/tmp/parquet_file/' + args.name + '.parquet'
df.to_parquet(parquet_file, index=False)`

2. I upload this parquet to "hdfs://draco01:9870/tmp/flink1.17.1/upload_parquet/table_name.parquet"
3. I create external table :

CREATE TABLE default_database.table_name (
col1 string,
col2 bigint,
col3 string,
col4 date,
col5 string,
PRIMARY KEY (col1,col2) NOT ENFORCED
) WITH (
'connector' = 'paimon',
'path' = 'hdfs://draco01:9870/tmp/flink1.17.1/upload_parquet/table_name.parquet'
);

4. Could read the schema:
+------+--------+-------+-----------------+--------+-----------+
| name | type | null | key | extras | watermark |
+------+--------+-------+-----------------+--------+-----------+
| col1 | STRING | FALSE | PRI(col1, col2) | | |
| col2 | BIGINT | FALSE | PRI(col1, col2) | | |
| col3 | STRING | TRUE | | | |
| col4 | DATE | TRUE | | | |
| col5 | STRING | TRUE | | | |
+------+--------+-------+-----------------+--------+-----------+
5 rows in set
5. Could not read the data, it shows below:
`Caused by: org.apache.hadoop.ipc.RpcException: RPC response exceeds maximum data length`

### What doesn't meet your expectations?

Want to know how to fix it.

### Anything else?

_No response_

### Are you willing to submit a PR?

- [ ] I'm willing to submit a PR!

The report provides upload_excel.xlsx, a pandas-to-Parquet conversion, an HDFS path, and the Flink SQL CREATE TABLE as reproduction entry points. Reproduce the read with Paimon 0.5 and Flink 1.16.2, then trace the “RPC response exceeds maximum data length” error; done when the external table data can be read without it.

Written by the indexing model from the issue text.