[Bug] "show table extended like" sql is not supported

### Search before asking

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

### Paimon version

0.8.1

### Compute Engine

spark

### Minimal reproduce step

show table extended like 'paimon_order_pt_tag' PARTITION (pt='20240701')
```
24/07/05 23:34:50 ERROR SparkDriverRest: pt is not a valid partition column in table `hive_metastore`.`bigdata`.`paimon_order_pt_tag`.
org.apache.spark.sql.AnalysisException: pt is not a valid partition column in table `hive_metastore`.`bigdata`.`paimon_order_pt_tag`.
at org.apache.spark.sql.errors.QueryCompilationErrors$.invalidPartitionColumnKeyInTableError(QueryCompilationErrors.scala:2432)
at org.apache.spark.sql.util.PartitioningUtils$.$anonfun$normalizePartitionSpec$3(PartitioningUtils.scala:78)
at scala.Option.getOrElse(Option.scala:189)
at org.apache.spark.sql.util.PartitioningUtils$.$anonfun$normalizePartitionSpec$1(PartitioningUtils.scala:78)
at scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:286)
at scala.collection.Iterator.foreach(Iterator.scala:943)
at scala.collection.Iterator.foreach$(Iterator.scala:943)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1431)
at scala.collection.IterableLike.foreach(IterableLike.scala:74)
at scala.collection.IterableLike.foreach$(IterableLike.scala:73)
at scala.collection.AbstractIterable.foreach(Iterable.scala:56)
at scala.collection.TraversableLike.map(TraversableLike.scala:286)
at scala.collection.TraversableLike.map$(TraversableLike.scala:279)
at scala.collection.AbstractTraversable.map(Traversable.scala:108)
at org.apache.spark.sql.util.PartitioningUtils$.normalizePartitionSpec(PartitioningUtils.scala:76)
at org.apache.spark.sql.execution.command.ShowTablesCommand.run(tables.scala:911)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:75)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:73)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.executeCollect(commands.scala:84)
at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.$anonfun$applyOrElse$1(QueryExecution.scala:107)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:125)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:201)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:108)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:900)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:66)
at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:107)
at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:98)
at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:461)
at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(origin.scala:76)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:461)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:32)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:32)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:32)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:437)
at org.apache.spark.sql.execution.QueryExecution.eagerlyExecuteCommands(QueryExecution.scala:98)
at org.apache.spark.sql.execution.QueryExecution.commandExecuted$lzycompute(QueryExecution.scala:85)
at org.apache.spark.sql.execution.QueryExecution.commandExecuted(QueryExecution.scala:83)
at org.apache.spark.sql.Dataset.(Dataset.scala:220)
at org.apache.spark.sql.Dataset$.$anonfun$ofRows$2(Dataset.scala:100)
```

### What doesn't meet your expectations?

Execution failure

### Anything else?

_No response_

### Are you willing to submit a PR?

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

No source file or test is named. Start by reproducing `SHOW TABLE EXTENDED LIKE 'paimon_order_pt_tag' PARTITION (pt='20240701')` with Spark and Paimon 0.8.1, then trace the command's partition handling. Done means the statement executes successfully for a valid Paimon partition without Spark's invalid-partition-column error.

Written by the indexing model from the issue text.