Support the null values in bloom_filter Spark aggregate

### Backend

VL (Velox)

### Bug description

Currently, the velox BloomFilterAggregate checks the input row and throws an exception if there are some null values in the row.
An example is：

```scala
val schema2 = new StructType().add("a2", IntegerType, nullable = true)
.add("b2", LongType, nullable = true)
.add("c2", IntegerType, nullable = true)
.add("d2", IntegerType, nullable = true)
.add("e2", IntegerType, nullable = true)
.add("f2", IntegerType, nullable = true)
val data2 = Seq(Seq(67, 17L, 45, 91, null, null),
Seq(98, 63L, 0, 89, null, 40),
Seq(null, null, 68, 75, 20, 19))
val rdd2 = spark.sparkContext.parallelize(data2)
val rddRow2 = rdd2.map(s => Row.fromSeq(s))
spark.createDataFrame(rddRow2, schema2).write.saveAsTable(table)

SELECT bloom_filter_agg(b2) from table
```

The exception is:

```scala
java.lang.RuntimeException: Exception: VeloxUserError
Error Source: USER
Error Code: INVALID_ARGUMENT
Reason: First argument of bloom_filter_agg cannot be null
Retriable: False
Expression: !decodedRaw_.mayHaveNulls()
Function: addSingleGroupRawInput
```

### Spark version

None

### Spark configurations

_No response_

### System information

_No response_

### Relevant logs

_No response_

Start with the Velox BloomFilterAggregate implementation and reproduce the provided Spark SQL query using nullable columns. The fix is done when bloom_filter_agg accepts the example rows containing null values without raising the reported invalid-argument exception.

Written by the indexing model from the issue text.