171 trino 연결 추가

.env.example

@@ -153,3 +153,11 @@ PGVECTOR_COLLECTION=table_info_db
 
 # VectorDB 설정
 VECTORDB_TYPE=faiss  # faiss 또는 pgvector
+
+
+# TRINO_HOST=localhost
+# TRINO_PORT=8080
+# TRINO_USER=admin
+# TRINO_PASSWORD=password
+# TRINO_CATALOG=delta
+# TRINO_SCHEMA=default

db_utils/__init__.py

@@ -13,6 +13,7 @@
 from .duckdb_connector import DuckDBConnector
 from .databricks_connector import DatabricksConnector
 from .snowflake_connector import SnowflakeConnector
+from .trino_connector import TrinoConnector
 
 env_path = os.path.join(os.getcwd(), ".env")
 
@@ -54,6 +55,7 @@ def get_db_connector(db_type: Optional[str] = None, config: Optional[DBConfig] =
             "duckdb": DuckDBConnector,
             "databricks": DatabricksConnector,
             "snowflake": SnowflakeConnector,
+            "trino": TrinoConnector,
         }
 
     if db_type not in connector_map:

db_utils/trino_connector.py

@@ -0,0 +1,120 @@
+import pandas as pd
+from .base_connector import BaseConnector
+from .config import DBConfig
+from .logger import logger
+
+try:
+    import trino
+except Exception as e:  # pragma: no cover
+    trino = None
+    _import_error = e
+
+
+class TrinoConnector(BaseConnector):
+    """
+    Connect to Trino and execute SQL queries.
+    """
+
+    connection = None
+
+    def __init__(self, config: DBConfig):
+        """
+        Initialize the TrinoConnector with connection parameters.
+
+        Parameters:
+            config (DBConfig): Configuration object containing connection parameters.
+        """
+        self.host = config["host"]
+        self.port = config["port"] or 8080
+        self.user = config.get("user") or "anonymous"
+        self.password = config.get("password")
+        self.database = config.get("database")  # e.g., catalog.schema
+        self.extra = config.get("extra") or {}
+        self.http_scheme = self.extra.get("http_scheme", "http")
+        self.catalog = self.extra.get("catalog")
+        self.schema = self.extra.get("schema")
+
+        # If database given as "catalog.schema", split into fields
+        if self.database and (not self.catalog or not self.schema):
+            if "." in self.database:
+                db_catalog, db_schema = self.database.split(".", 1)
+                self.catalog = self.catalog or db_catalog
+                self.schema = self.schema or db_schema
+
+        self.connect()
+
+    def connect(self) -> None:
+        """
+        Establish a connection to the Trino cluster.
+        """
+        if trino is None:
+            logger.error(f"Failed to import trino driver: {_import_error}")
+            raise _import_error
+
+        try:
+            auth = None
+            if self.password:
+                # If HTTP, ignore password to avoid insecure auth error
+                if self.http_scheme == "http":
+                    logger.warning(
+                        "Password provided for HTTP; ignoring password. "
+                        "Set TRINO_HTTP_SCHEME=https to enable password authentication."
+                    )
+                else:
+                    # Basic auth over HTTPS
+                    auth = trino.auth.BasicAuthentication(self.user, self.password)
+
+            self.connection = trino.dbapi.connect(
+                host=self.host,
+                port=self.port,
+                user=self.user,
+                http_scheme=self.http_scheme,
+                catalog=self.catalog,
+                schema=self.schema,
+                auth=auth,
+                # Optional: session properties
+                # session_properties={}
+            )
+            logger.info("Successfully connected to Trino.")
+        except Exception as e:
+            logger.error(f"Failed to connect to Trino: {e}")
+            raise
+
+    def run_sql(self, sql: str) -> pd.DataFrame:
+        """
+        Execute a SQL query and return the result as a pandas DataFrame.
+
+        Parameters:
+            sql (str): SQL query string to be executed.
+
+        Returns:
+            pd.DataFrame: Result of the SQL query as a pandas DataFrame.
+        """
+        try:
+            cursor = self.connection.cursor()
+            cursor.execute(sql)
+            columns = (
+                [desc[0] for desc in cursor.description] if cursor.description else []
+            )
+            rows = cursor.fetchall() if cursor.description else []
+            return pd.DataFrame(rows, columns=columns)
+        except Exception as e:
+            logger.error(f"Failed to execute SQL query on Trino: {e}")
+            raise
+        finally:
+            try:
+                cursor.close()
+            except Exception:
+                pass
+
+    def close(self) -> None:
+        """
+        Close the connection to the Trino cluster.
+        """
+        if self.connection:
+            try:
+                self.connection.close()
+            except Exception:
+                pass
+            logger.info("Connection to Trino closed.")
+        self.connection = None

pyproject.toml

@@ -45,6 +45,7 @@ dependencies = [
   "google-cloud-bigquery>=3.20.1,<4.0.0",
   "pgvector==0.3.6",
   "langchain-postgres==0.0.15",
+  "trino>=0.329.0,<1.0.0",
 ]
 
 [project.scripts]
@@ -82,4 +83,3 @@ dev-dependencies = [
   "pytest>=8.3.5",
 ]
 
-