[VL] date_format returns wrong results

### Backend

VL (Velox)

### Bug description

Velox evaluates `date_format(timestamp'12345-01-01 01:01:01', 'yyyy-MM')` to `'12345-07'`, whereas vanilla Spark evaluates the same expression to `'+12345-07'`. This can be an issue because `unix_timestamp` in vanilla Spark only supports `'+12345-07'`. If `date_format` is executed in Velox and the result is used as an argument to `unix_timestamp` in vanilla Spark, there will be a failure.

```scala
// Somehow CREATE TABLE doesn't work with five-digit year timestamps
spark.sql("select timestamp'12345-01-01 01:01:01' c").write.mode("overwrite").save("x")
spark.read.load("x").createOrReplaceTempView("t")

// date_format is run in Velox
spark.sql("select date_format(c, 'yyyy-MM') from t").explain()
// == Physical Plan ==
// VeloxColumnarToRowExec
// +- ^(14) ProjectExecTransformer [date_format(c#83, yyyy-MM, Some(Etc/UTC)) AS date_format(c, yyyy-MM)#85]
// +- ^(14) NativeFileScan parquet [c#83] Batched: true, DataFilters: [], Format: Parquet, Location: InMemoryFileIndex(1 paths)[file:/ssd/chungmin/repos/spark34/x], PartitionFilters: [], PushedFilters: [], ReadSchema: struct

// Use collect() instead of show(), as show() makes the function run in vanilla Spark in Spark 3.5 due to the inserted ToPrettyString function.
spark.sql("select date_format(c, 'yyyy-MM') from t").collect()
// Array([12345-01])

spark.sql("create table t2 as select date_format(c, 'yyyy-MM') c from t")
spark.sql("set spark.gluten.enabled = false")
spark.sql("select unix_timestamp(c, 'yyyy-MM') from t2").collect()
// 24/04/25 02:01:01 ERROR TaskResources: Task 8 failed by error:
// org.apache.spark.SparkUpgradeException: [INCONSISTENT_BEHAVIOR_CROSS_VERSION.PARSE_DATETIME_BY_NEW_PARSER] You may get a different result due to the upgrading to Spark >= 3.0:
// Fail to parse '12345-01' in the new parser. You can set "spark.sql.legacy.timeParserPolicy" to "LEGACY" to restore the behavior before Spark 3.0, or set to "CORRECTED" and treat it as an invalid datetime string.
// ...
```

Spark uses `java.time.format.DateTimeFormatter` for `date_format`.

```scala
import java.time.{LocalDate, ZoneId}
import java.time.format.DateTimeFormatter

DateTimeFormatter.ofPattern("yyyy").withZone(ZoneId.of("Z")).format(LocalDate.of(12345, 1, 1))
// "+12345"
```

OpenJDK 1.8.0_402, 11.0.22, 21.0.2 all behave the same. It is not documented in the class in general, but for some constants it is mentioned that [years outside of 0000-9999 will have a prefixed positive or negative symbol](https://docs.oracle.com/en%2Fjava%2Fjavase%2F21%2Fdocs%2Fapi%2F%2F/java.base/java/time/format/DateTimeFormatter.html#ISO_LOCAL_DATE).

Five-digit years should be extremely rare in real world applications, but it's breaking Delta unit tests.

The issue occurs with Spark 3.4.2 and 3.5.1. Didn't check older versions.

### Spark version

None

### Spark configurations

spark.plugins=org.apache.gluten.GlutenPlugin
spark.gluten.enabled=true
spark.gluten.sql.columnar.backend.lib=velox
spark.memory.offHeap.enabled=true
spark.memory.offHeap.size=28g

### System information

Velox System Info v0.0.2
Commit: 45dc46a9dd8a4197876da4c661d856f73d31673f
CMake Version: 3.28.3
System: Linux-6.5.0-1018-azure
Arch: x86_64
C++ Compiler: /usr/bin/c++
C++ Compiler Version: 11.4.0
C Compiler: /usr/bin/cc
C Compiler Version: 11.4.0
CMake Prefix Path: /usr/local;/usr;/;/ssd/linuxbrew/.linuxbrew/Cellar/cmake/3.28.3;/usr/local;/usr/X11R6;/usr/pkg;/opt

### Relevant logs

_No response_

Start by tracing the Velox implementation of date_format and the Spark SQL entry point for this expression, then compare its handling of years outside 0000–9999 with Java DateTimeFormatter. Reproduce the five-digit-year example and verify that the result includes the required sign and remains compatible with unix_timestamp.

Written by the indexing model from the issue text.