feature:Add OceanBase Storage Support for Table Parser (#12923)

### What problem does this PR solve?

close #12770 

This PR adds OceanBase as a storage backend for the Table Parser. It
enables dynamic table schema storage via JSON and implements OceanBase
SQL execution for text-to-SQL retrieval.


### Type of change

- [ ] Bug Fix (non-breaking change which fixes an issue)
- [x] New Feature (non-breaking change which adds functionality)
- [ ] Documentation Update
- [ ] Refactoring
- [ ] Performance Improvement
- [ ] Other (please describe):

### Changes
- Table Parser stores row data into `chunk_data` when doc engine is
OceanBase. (table.py)
- OceanBase table schema adds `chunk_data` JSON column and migrates if
needed.
- Implemented OceanBase `sql()` to execute text-to-SQL results.
(ob_conn.py)
- Add `DOC_ENGINE_OCEANBASE` flag for engine detection (setting.py)

### Test
1. Set `DOC_ENGINE=oceanbase` (e.g. in `docker/.env`)
<img width="1290" height="783" alt="doc_engine_ob"
src="https://github.com/user-attachments/assets/7d1c609f-7bf2-4b2e-b4cc-4243e72ad4f1"
/>

2. Upload an Excel file to Knowledge Base.(for test, we use as below)
<img width="786" height="930" alt="excel"
src="https://github.com/user-attachments/assets/bedf82f2-cd00-426b-8f4d-6978a151231a"
/>

3. Choose **Table** as parsing method.
<img width="2550" height="1134" alt="parse_excel"
src="https://github.com/user-attachments/assets/aba11769-02be-4905-97e1-e24485e24cd0"
/>

4.Ask a natural language query in chat.
<img width="2550" height="1134" alt="query"
src="https://github.com/user-attachments/assets/26a910a6-e503-4ac7-b66a-f5754bbb0e91"
/>

rag/utils/ob_conn.py

@@ -49,6 +49,7 @@ logger = logging.getLogger('ragflow.ob_conn')
 column_order_id = Column("_order_id", Integer, nullable=True, comment="chunk order id for maintaining sequence")
 column_group_id = Column("group_id", String(256), nullable=True, comment="group id for external retrieval")
 column_mom_id = Column("mom_id", String(256), nullable=True, comment="parent chunk id")
+column_chunk_data = Column("chunk_data", JSON, nullable=True, comment="table parser row data")
 
 column_definitions: list[Column] = [
     Column("id", String(256), primary_key=True, comment="chunk id"),
@@ -89,6 +90,7 @@ column_definitions: list[Column] = [
     Column("rank_flt", Double, nullable=True, comment="rank of this entity"),
     Column("removed_kwd", String(256), nullable=True, index=True, server_default="'N'",
            comment="whether it has been deleted"),
+    column_chunk_data,
     Column("metadata", JSON, nullable=True, comment="metadata for this chunk"),
     Column("extra", JSON, nullable=True, comment="extra information of non-general chunk"),
     column_order_id,
@@ -754,7 +756,7 @@ class OBConnection(DocStoreConnection):
     Table operations
     """
 
-    def create_idx(self, indexName: str, knowledgebaseId: str, vectorSize: int):
+    def create_idx(self, indexName: str, knowledgebaseId: str, vectorSize: int, parser_id: str = None):
         vector_field_name = f"q_{vectorSize}_vec"
         vector_index_name = f"{vector_field_name}_idx"
 
@@ -793,7 +795,7 @@ class OBConnection(DocStoreConnection):
             )
 
             # new columns migration
-            for column in [column_order_id, column_group_id, column_mom_id]:
+            for column in [column_chunk_data, column_order_id, column_group_id, column_mom_id]:
                 _try_with_lock(
                     lock_name=f"ob_add_{column.name}_{indexName}",
                     check_func=lambda: self._column_exist(indexName, column.name),
@@ -1826,6 +1828,66 @@ class OBConnection(DocStoreConnection):
     SQL
     """
 
-    def sql(sql: str, fetch_size: int, format: str):
-        # TODO: execute the sql generated by text-to-sql
-        return None
+    def sql(self, sql: str, fetch_size: int = 1024, format: str = "json"):
+        logger.debug("OBConnection.sql get sql: %s", sql)
+
+        def normalize_sql(sql_text: str) -> str:
+            cleaned = sql_text.strip().rstrip(";")
+            cleaned = re.sub(r"[`]+", "", cleaned)
+            cleaned = re.sub(
+                r"json_extract_string\s*\(\s*([^,]+?)\s*,\s*([^)]+?)\s*\)",
+                r"JSON_UNQUOTE(JSON_EXTRACT(\1, \2))",
+                cleaned,
+                flags=re.IGNORECASE,
+            )
+            cleaned = re.sub(
+                r"json_extract_isnull\s*\(\s*([^,]+?)\s*,\s*([^)]+?)\s*\)",
+                r"(JSON_EXTRACT(\1, \2) IS NULL)",
+                cleaned,
+                flags=re.IGNORECASE,
+            )
+            return cleaned
+
+        def coerce_value(value: Any) -> Any:
+            if isinstance(value, np.generic):
+                return value.item()
+            if isinstance(value, bytes):
+                return value.decode("utf-8", errors="ignore")
+            return value
+
+        sql_text = normalize_sql(sql)
+        if fetch_size and fetch_size > 0:
+            sql_lower = sql_text.lstrip().lower()
+            if re.match(r"^(select|with)\b", sql_lower) and not re.search(r"\blimit\b", sql_lower):
+                sql_text = f"{sql_text} LIMIT {int(fetch_size)}"
+
+        logger.debug("OBConnection.sql to ob: %s", sql_text)
+
+        try:
+            res = self.client.perform_raw_text_sql(sql_text)
+        except Exception:
+            logger.exception("OBConnection.sql got exception")
+            raise
+
+        if res is None:
+            return None
+
+        columns = list(res.keys()) if hasattr(res, "keys") else []
+        try:
+            rows = res.fetchmany(fetch_size) if fetch_size and fetch_size > 0 else res.fetchall()
+        except Exception:
+            rows = res.fetchall()
+
+        rows_list = [[coerce_value(v) for v in list(row)] for row in rows]
+        result = {
+            "columns": [{"name": col, "type": "text"} for col in columns],
+            "rows": rows_list,
+        }
+
+        if format == "markdown":
+            header = "|" + "|".join(columns) + "|" if columns else ""
+            separator = "|" + "|".join(["---" for _ in columns]) + "|" if columns else ""
+            body = "\n".join(["|" + "|".join([str(v) for v in row]) + "|" for row in rows_list])
+            result["markdown"] = "\n".join([line for line in [header, separator, body] if line])
+
+        return result