Nested Avro fields flattened as VARCHAR instead of native types when using useSchemaDiscovery

Nested Avro fields flattened as VARCHAR instead of native types when using useSchemaDiscovery with kafka input format wrapping avro_stream

### Affected Version
31.0.0

### Description

When ingesting Kafka data using the kafka input format wrapping avro_stream with Schema Registry, nested Avro fields lose their type information during auto-flattening and become VARCHAR,
even with useSchemaDiscovery: true.

**Setup:**
- Single-node Druid 31.0.0 cluster (Helm chart, MiddleManager mode)
- Kafka supervisor with kafka input format + avro_stream value format + Confluent Schema Registry
- dimensionsSpec: { useSchemaDiscovery: true }
- No flattenSpec defined

**Avro schema (simplified):**
```
{"name": "items", "type": {"type": "array", "items": {"type": "record", "fields": [
{"name": "price", "type": ["null", "double"]},
{"name": "quantity", "type": ["null", "long"]}
]}}}
```

**Expected behaviour:**
With useSchemaDiscovery: true, auto-flattened fields like items_0_price_ should be detected as DOUBLE, and items_0_quantity_ as BIGINT.

**Actual behaviour:**
- Top-level Avro fields are typed correctly (e.g. createdNanos → BIGINT)
- Nested/array fields are auto-flattened with underscore notation (e.g. items_0_price_, items_0_quantity_, metadata_someField_) but typed as VARCHAR
- Values are string representations: "217000.0" instead of 217000.0
- This affects ~110 out of 118 columns in our table — only 4 are BIGINT (all top-level)

**Verified with:**
```
SELECT COLUMN_NAME, DATA_TYPE
FROM INFORMATION_SCHEMA.COLUMNS
WHERE TABLE_NAME = 'my_datasource'

SELECT "items_0_price_" FROM "my_datasource" LIMIT 1
-- Returns: "217000.0" (string, not numeric)
```
**Impact:**
All arithmetic on nested numeric fields requires explicit CAST:
CAST("items_0_quantity_" AS DOUBLE) * CAST("items_0_price_" AS DOUBLE) AS notional

Supervisor config (relevant parts):
```
{
"inputFormat": {
"type": "kafka",
"headerFormat": { "type": "string" },
"keyFormat": { "type": "json" },
"valueFormat": {
"type": "avro_stream",
"avroBytesDecoder": {
"type": "schema_registry",
"url": "http://schema-registry:8081/"
}
}
},
"dimensionsSpec": {
"useSchemaDiscovery": true
}
}
```
**Workaround:**
Define explicit flattenSpec with useFieldDiscovery: true for top-level fields and manually list every nested path. Impractical for wide schemas with 100+ nested fields.

**Questions:**
1. Is this expected — does auto-flattening serialise nested values to strings before schema discovery runs?
2. Is there a configuration to preserve Avro types for auto-flattened nested fields without a manual flattenSpec?
3. Would a PR to propagate Avro schema types through the flattening step be welcome?

Start by tracing the Kafka input format's avro_stream value format, schema-registry decoder, and dimensionsSpec useSchemaDiscovery flow, comparing how top-level and nested or array fields are represented. Reproduce the case with the supplied Avro schema and INFORMATION_SCHEMA query; done means nested numeric fields such as items_0_price_ and items_0_quantity_ retain native numeric types without explicit casts.

Written by the indexing model from the issue text.