blackflash997997 opened a new issue, #7108:
URL: https://github.com/apache/paimon/issues/7108

   ### Search before asking
   
   - [x] I searched in the [issues](https://github.com/apache/paimon/issues) 
and found nothing similar.
   
   
   ### Paimon version
   
   flink catalog:
   ```
   CREATE CATALOG paimon_catalog WITH (
       'type' = 'paimon',
       'metastore' = 'hive',
       'uri' = 'thrift://xxx:9083',
       'warehouse' = 'jfs://poc-jfs/user/hive/lakehouse_paimon',
       'table-default.metadata.iceberg.storage'='hive-catalog',
       'table-default.metadata.iceberg.uri'='thrift://x:9083'xxx
   );
   
   USE CATALOG paimon_catalog;
   ```
   i'm using following sql write data from kafka
   ```
   insert into my_database.paimon_table
   select *,
   DATE_FORMAT(SYSTEMDATE,'yyyyMMdd') -- this is a partition field : dt
   from kafka
   where `TIME` IS NOT NULL
   ;
   ```
   then i use spark-sql to query:
   ```
   spark-sql  --conf 
spark.sql.catalog.spark_catalog=org.apache.iceberg.spark.SparkSessionCatalog 
--conf spark.sql.catalog.spark_catalog.type=hive
   
   select * from my_database.paimon_table where dt=20251231
   ```
   
   and i found that spark would scan all data to find these  "dt=20251231" rows
   
   
   I also found that using the `describe formatted my_database.paimon_table; `  
did not display the `# Metadata Columns` fields that would be present when 
creating the `paimon` table using `spark-sql`.
   
   like following, there is no `# Metadata Columns` ,which cause using 
partition field to filter data failed
   ```
   ......
   dt                      string                  from deserializer   
                                                                       
   # Detailed Table Information                                                
   Catalog                 spark_catalog                               
   Database                paimon_flink1                               
   Table                   zvos_flink_14_append2                       
   Owner                   zoomspace                                   
   Created Time            Thu Jan 22 17:40:42 CST 2026                        
   Last Access             Thu Jan 22 17:40:42 CST 2026                        
   Created By              Spark 2.2 or prior                          
   Type                    MANAGED                                     
   Provider                hive                                        
   Comment                                                             
   Table Properties        [metadata.iceberg.storage=hive-catalog, 
metadata.iceberg.uri=thrift://xxxx:9083, 
metadata_location=jfs://poc-jfs/user/hive/lakehouse_paimon/iceberg/paimon_flink1/zvos_flink_14_append2/metadata/v3.metadata.json,
 partition=dt, 
previous_metadata_location=jfs://poc-jfs/user/hive/lakehouse_paimon/iceberg/paimon_flink1/zvos_flink_14_append2/metadata/v2.metadata.json,
 storage_handler=org.apache.paimon.hive.PaimonStorageHandler, 
table_type=PAIMON, transient_lastDdlTime=1769074842]                         
   Statistics              87763321 bytes                              
   Location                
jfs://poc-jfs/user/hive/lakehouse_paimon/paimon_flink1.db/zvos_flink_14_append2 
                    
   Serde Library           org.apache.paimon.hive.PaimonSerDe                   
       
   InputFormat             org.apache.paimon.hive.mapred.PaimonInputFormat      
               
   OutputFormat            org.apache.paimon.hive.mapred.PaimonOutputFormat     
                       
   
   ```
   
   ### Compute Engine
   
   paimon version: 1.4.1 snapshot
   Write: using flink 1.20.1 on yarn with JuiceFS filesystem
   Read: using spark3.5.2 、iceberg 1.6.1 
   
   ### Minimal reproduce step
   
   use flink to write a partition-key table with iceberg metadata,
   use ` where partition-key=xxxx ` to filter data
   
   ### What doesn't meet your expectations?
   
   use ` where partition-key=xxxx ` to filter data would be scan a specific 
path  ,not scan all data
   
   ### Anything else?
   
   _No response_
   
   ### Are you willing to submit a PR?
   
   - [ ] I'm willing to submit a PR!


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