Fix SQL statement length issues and improve batch processing

- Add SQL length monitoring and automatic batch splitting
- Reduce default batch size from 100 to 20 to prevent large SQL statements
- Add detailed error logging for SQL execution failures
- Implement recursive batch splitting for oversized SQL statements
- Set 1MB limit for SQL statement length

This resolves issues where large batches create SQL statements that
exceed database limits, causing vector insertion failures.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

api/core/rag/datasource/vdb/clickzetta/clickzetta_vector.py

@@ -35,7 +35,7 @@ class ClickzettaConfig(BaseModel):
     vcluster: str = "default_ap"
     schema: str = "dify"
     # Advanced settings
-    batch_size: int = 100
+    batch_size: int = 20  # Reduced batch size to avoid large SQL statements
     enable_inverted_index: bool = True  # Enable inverted index for full-text search
     analyzer_type: str = "chinese"  # Analyzer type for full-text search: keyword, english, chinese, unicode
     analyzer_mode: str = "smart"  # Analyzer mode: max_word, smart
@@ -329,9 +329,31 @@ class ClickzettaVector(BaseVector):
         columns = f"id, {Field.CONTENT_KEY.value}, {Field.METADATA_KEY.value}, {Field.VECTOR.value}"
         insert_sql = f"INSERT INTO {self._config.schema}.{self._table_name} ({columns}) VALUES {','.join(values)}"
         
+        # Log SQL length for debugging
+        sql_length = len(insert_sql)
+        logger.debug(f"SQL statement length: {sql_length} characters")
+        
+        # If SQL is too long, split into smaller batches
+        if sql_length > 1000000:  # 1MB limit
+            logger.warning(f"SQL statement too long ({sql_length} chars), splitting batch")
+            mid_point = len(batch_docs) // 2
+            # Split and process recursively
+            self._insert_batch_impl(batch_docs[:mid_point], batch_embeddings[:mid_point], 
+                                   batch_index, batch_size, total_batches)
+            self._insert_batch_impl(batch_docs[mid_point:], batch_embeddings[mid_point:], 
+                                   batch_index + mid_point, batch_size, total_batches)
+            return
+        
         with self._connection.cursor() as cursor:
-            cursor.execute(insert_sql)
-            logger.info(f"Inserted batch {batch_index // batch_size + 1}/{total_batches}")
+            try:
+                cursor.execute(insert_sql)
+                logger.info(f"Inserted batch {batch_index // batch_size + 1}/{total_batches} "
+                           f"({len(batch_docs)} docs, SQL: {sql_length} chars)")
+            except Exception:
+                logger.exception(f"SQL execution failed. SQL length: {sql_length}")
+                logger.exception(f"First 500 chars of SQL: {insert_sql[:500]}")
+                logger.exception(f"Last 500 chars of SQL: {insert_sql[-500:]}")
+                raise
 
     def text_exists(self, id: str) -> bool:
         """Check if a document exists by ID."""