Add pre_execution_queries parameter to run setup queries before main query on Postgres and MySQL source

connectorx-cpp/src/lib.rs

@@ -176,7 +176,7 @@ pub unsafe extern "C" fn connectorx_scan(conn: *const c_char, query: *const c_ch
     let conn_str = unsafe { CStr::from_ptr(conn) }.to_str().unwrap();
     let query_str = unsafe { CStr::from_ptr(query) }.to_str().unwrap();
     let source_conn = SourceConn::try_from(conn_str).unwrap();
-    let record_batches = get_arrow(&source_conn, None, &[CXQuery::from(query_str)])
+    let record_batches = get_arrow(&source_conn, None, &[CXQuery::from(query_str)], None)
         .unwrap()
         .arrow()
         .unwrap();
@@ -281,7 +281,7 @@ pub unsafe extern "C" fn connectorx_scan_iter(
     }
 
     let arrow_iter: Box<dyn RecordBatchIterator> =
-        new_record_batch_iter(&source_conn, None, query_vec.as_slice(), batch_size);
+        new_record_batch_iter(&source_conn, None, query_vec.as_slice(), batch_size, None);
 
     Box::into_raw(Box::new(arrow_iter))
 }

connectorx-python/connectorx/__init__.py

@@ -131,6 +131,7 @@ def read_sql_pandas(
     partition_on: str | None = None,
     partition_range: tuple[int, int] | None = None,
     partition_num: int | None = None,
+    pre_execution_queries: list[str] | str | None = None,
 ) -> pd.DataFrame:
     """
     Run the SQL query, download the data from database into a dataframe.
@@ -160,6 +161,7 @@ def read_sql_pandas(
         partition_range=partition_range,
         partition_num=partition_num,
         index_col=index_col,
+        pre_execution_queries=pre_execution_queries,
     )
 
 
@@ -174,6 +176,7 @@ def read_sql(
     partition_range: tuple[int, int] | None = None,
     partition_num: int | None = None,
     index_col: str | None = None,
+    pre_execution_query: list[str] | str | None = None,
 ) -> pd.DataFrame: ...
 
 
@@ -188,6 +191,7 @@ def read_sql(
     partition_range: tuple[int, int] | None = None,
     partition_num: int | None = None,
     index_col: str | None = None,
+    pre_execution_query: list[str] | str | None = None,
 ) -> pd.DataFrame: ...
 
 
@@ -202,6 +206,7 @@ def read_sql(
     partition_range: tuple[int, int] | None = None,
     partition_num: int | None = None,
     index_col: str | None = None,
+    pre_execution_query: list[str] | str | None = None,
 ) -> pa.Table: ...
 
 
@@ -216,6 +221,7 @@ def read_sql(
     partition_range: tuple[int, int] | None = None,
     partition_num: int | None = None,
     index_col: str | None = None,
+    pre_execution_query: list[str] | str | None = None,
 ) -> mpd.DataFrame: ...
 
 
@@ -230,6 +236,7 @@ def read_sql(
     partition_range: tuple[int, int] | None = None,
     partition_num: int | None = None,
     index_col: str | None = None,
+    pre_execution_query: list[str] | str | None = None,
 ) -> dd.DataFrame: ...
 
 
@@ -244,6 +251,7 @@ def read_sql(
     partition_range: tuple[int, int] | None = None,
     partition_num: int | None = None,
     index_col: str | None = None,
+    pre_execution_query: list[str] | str | None = None,
 ) -> pl.DataFrame: ...
 
 
@@ -260,6 +268,7 @@ def read_sql(
     partition_num: int | None = None,
     index_col: str | None = None,
     strategy: str | None = None,
+    pre_execution_query: list[str] | str | None = None,
 ) -> pd.DataFrame | mpd.DataFrame | dd.DataFrame | pl.DataFrame | pa.Table:
     """
     Run the SQL query, download the data from database into a dataframe.
@@ -285,6 +294,9 @@ def read_sql(
       the index column to set; only applicable for return type "pandas", "modin", "dask".
     strategy
       strategy of rewriting the federated query for join pushdown
+    pre_execution_query
+      SQL query or list of SQL queries executed before main query; can be used to set runtime
+      configurations using SET statements; only applicable for source "Postgres" and "MySQL".
 
     Examples
     ========
@@ -358,6 +370,13 @@ def read_sql(
             raise ValueError("Partition on multiple queries is not supported.")
     else:
         raise ValueError("query must be either str or a list of str")
+
+    if isinstance(pre_execution_query, list):
+        pre_execution_queries = [remove_ending_semicolon(subquery) for subquery in pre_execution_query]
+    elif isinstance(pre_execution_query, str):
+        pre_execution_queries = [remove_ending_semicolon(pre_execution_query)]
+    else:
+        pre_execution_queries = None
 
     conn, protocol = rewrite_conn(conn, protocol)
 
@@ -370,6 +389,7 @@ def read_sql(
             queries=queries,
             protocol=protocol,
             partition_query=partition_query,
+            pre_execution_queries=pre_execution_queries,
         )
         df = reconstruct_pandas(result)
 
@@ -392,6 +412,7 @@ def read_sql(
             queries=queries,
             protocol=protocol,
             partition_query=partition_query,
+            pre_execution_queries=pre_execution_queries,
         )
         df = reconstruct_arrow(result)
         if return_type in {"polars"}:

connectorx-python/connectorx/connectorx.pyi

@@ -25,6 +25,7 @@ def read_sql(
     protocol: str | None,
     queries: list[str] | None,
     partition_query: dict[str, Any] | None,
+    pre_execution_queries: list[str] | None,
 ) -> _DataframeInfos: ...
 @overload
 def read_sql(
@@ -33,6 +34,7 @@ def read_sql(
     protocol: str | None,
     queries: list[str] | None,
     partition_query: dict[str, Any] | None,
+    pre_execution_queries: list[str] | None,
 ) -> _ArrowInfos: ...
 def partition_sql(conn: str, partition_query: dict[str, Any]) -> list[str]: ...
 def read_sql2(sql: str, db_map: dict[str, str]) -> _ArrowInfos: ...

connectorx-python/connectorx/tests/test_mysql.py

@@ -478,3 +478,52 @@ def test_mysql_cte(mysql_url: str) -> None:
 
 def test_connection_url(mysql_url: str) -> None:
     test_mysql_cte(ConnectionUrl(mysql_url))
+
+def test_mysql_single_pre_execution_queries(mysql_url: str) -> None:
+    pre_execution_query = "SET SESSION max_execution_time = 2151"
+    query = "SELECT @@SESSION.max_execution_time AS max_execution_time"
+    df = read_sql(mysql_url, query, pre_execution_query=pre_execution_query)
+    expected = pd.DataFrame(
+        index=range(1),
+        data={
+            "max_execution_time": pd.Series([2151], dtype="float64")
+        },
+    )
+    assert_frame_equal(df, expected, check_names=True)
+
+
+def test_mysql_multiple_pre_execution_queries(mysql_url: str) -> None:
+    pre_execution_query = [
+        "SET SESSION max_execution_time = 2151",
+        "SET SESSION wait_timeout = 2252",
+    ]
+    query = "SELECT @@SESSION.max_execution_time AS max_execution_time, @@SESSION.wait_timeout AS wait_timeout"
+    df = read_sql(mysql_url, query, pre_execution_query=pre_execution_query)
+    expected = pd.DataFrame(
+        index=range(1),
+        data={
+            "max_execution_time": pd.Series([2151], dtype="float64"),
+            "wait_timeout": pd.Series([2252], dtype="float64")
+        },
+    )
+    assert_frame_equal(df, expected, check_names=True)
+
+def test_mysql_partitioned_pre_execution_queries(mysql_url: str) -> None:
+    pre_execution_query = [
+        "SET SESSION max_execution_time = 2151",
+        "SET SESSION wait_timeout = 2252",
+    ]
+    query = [
+        'SELECT "max_execution_time" AS name, @@SESSION.max_execution_time AS setting',
+        'SELECT "wait_timeout" AS name, @@SESSION.wait_timeout AS setting'
+    ]
+    df = read_sql(mysql_url, query, pre_execution_query=pre_execution_query).sort_values(by=['name'])
+    expected = pd.DataFrame(
+        index=range(2),
+        data={
+            "name": pd.Series(["max_execution_time", "wait_timeout"], dtype="str"),
+            "setting": pd.Series([2151, 2252], dtype="float64"),
+        },
+    ).sort_values(by=['name'])
+
+    assert_frame_equal(df, expected, check_like=False)

connectorx-python/connectorx/tests/test_postgres.py

@@ -1008,4 +1008,53 @@ def test_postgres_partition_with_orderby_limit_desc(postgres_url: str) -> None:
         },
     )
     df.sort_values(by="test_int", inplace=True, ignore_index=True)
-    assert_frame_equal(df, expected, check_names=True)
+    assert_frame_equal(df, expected, check_names=True)
+
+def test_postgres_single_pre_execution_queries(postgres_url: str) -> None:
+    pre_execution_query = "SET SESSION statement_timeout = 2151"
+    query = "SELECT CAST(name AS TEXT) AS name, CAST(setting AS INTEGER) FROM pg_settings WHERE name = 'statement_timeout'"
+    df = read_sql(postgres_url, query, pre_execution_query=pre_execution_query)
+    expected = pd.DataFrame(
+        index=range(1),
+        data={
+            "name": pd.Series(["statement_timeout"], dtype="str"),
+            "setting": pd.Series([2151], dtype="Int64"),
+        },
+    )
+    assert_frame_equal(df, expected, check_names=True)
+
+def test_postgres_multiple_pre_execution_queries(postgres_url: str) -> None:
+    pre_execution_query = [
+        "SET SESSION statement_timeout = 2151",
+        "SET SESSION idle_in_transaction_session_timeout = 2252",
+    ]
+    query = "SELECT CAST(name AS TEXT) AS name, CAST(setting AS INTEGER) FROM pg_settings WHERE name IN ('statement_timeout', 'idle_in_transaction_session_timeout') ORDER BY name"
+    df = read_sql(postgres_url, query, pre_execution_query=pre_execution_query)
+    expected = pd.DataFrame(
+        index=range(2),
+        data={
+            "name": pd.Series(["idle_in_transaction_session_timeout", "statement_timeout"], dtype="str"),
+            "setting": pd.Series([2252, 2151], dtype="Int64"),
+        },
+    )
+    assert_frame_equal(df, expected, check_names=True)
+
+def test_postgres_partitioned_pre_execution_queries(postgres_url: str) -> None:
+    pre_execution_query = [
+        "SET SESSION statement_timeout = 2151",
+        "SET SESSION idle_in_transaction_session_timeout = 2252",
+    ]
+    query = [
+        "SELECT CAST(name AS TEXT) AS name, CAST(setting AS INTEGER) AS setting FROM pg_settings WHERE name = 'statement_timeout'", 
+        "SELECT CAST(name AS TEXT) AS name, CAST(setting AS INTEGER) AS setting FROM pg_settings WHERE name = 'idle_in_transaction_session_timeout'"
+    ]
+
+    df = read_sql(postgres_url, query, pre_execution_query=pre_execution_query).sort_values(by=['name'])
+    expected = pd.DataFrame(
+        index=range(2),
+        data={
+            "name": pd.Series(["statement_timeout", "idle_in_transaction_session_timeout"], dtype="str"),
+            "setting": pd.Series([2151, 2252], dtype="Int64"),
+        },
+    ).sort_values(by=['name'])
+    assert_frame_equal(df, expected, check_names=True)

connectorx-python/src/arrow.rs

@@ -15,10 +15,11 @@ pub fn write_arrow<'py>(
     source_conn: &SourceConn,
     origin_query: Option<String>,
     queries: &[CXQuery<String>],
+    pre_execution_queries: Option<&[String]>,
 ) -> Bound<'py, PyAny> {
     let ptrs = py.allow_threads(
         || -> Result<(Vec<String>, Vec<Vec<(uintptr_t, uintptr_t)>>), ConnectorXPythonError> {
-            let destination = get_arrow(source_conn, origin_query, queries)?;
+            let destination = get_arrow(source_conn, origin_query, queries, pre_execution_queries)?;
             let rbs = destination.arrow()?;
             Ok(to_ptrs(rbs))
         },

connectorx-python/src/cx_read_sql.rs

@@ -38,6 +38,7 @@ pub fn read_sql<'py>(
     protocol: Option<&str>,
     queries: Option<Vec<String>>,
     partition_query: Option<PyPartitionQuery>,
+    pre_execution_queries: Option<Vec<String>>,
 ) -> PyResult<Bound<'py, PyAny>> {
     let source_conn = parse_source(conn, protocol).map_err(|e| ConnectorXPythonError::from(e))?;
     let (queries, origin_query) = match (queries, partition_query) {
@@ -62,12 +63,14 @@ pub fn read_sql<'py>(
             &source_conn,
             origin_query,
             &queries,
+            pre_execution_queries.as_deref(),
         )?),
         "arrow" => Ok(crate::arrow::write_arrow(
             py,
             &source_conn,
             origin_query,
             &queries,
+            pre_execution_queries.as_deref(),
         )?),
         _ => Err(PyValueError::new_err(format!(
             "return type should be 'pandas' or 'arrow', got '{}'",

connectorx-python/src/lib.rs

@@ -39,16 +39,25 @@ fn connectorx(_: Python, m: &Bound<'_, PyModule>) -> PyResult<()> {
 }
 
 #[pyfunction]
-#[pyo3(signature = (conn, return_type, protocol=None, queries=None, partition_query=None))]
+#[pyo3(signature = (conn, return_type, protocol=None, queries=None, partition_query=None, pre_execution_queries=None))]
 pub fn read_sql<'py>(
     py: Python<'py>,
     conn: &str,
     return_type: &str,
     protocol: Option<&str>,
     queries: Option<Vec<String>>,
     partition_query: Option<cx_read_sql::PyPartitionQuery>,
+    pre_execution_queries: Option<Vec<String>>,
 ) -> PyResult<Bound<'py, PyAny>> {
-    cx_read_sql::read_sql(py, conn, return_type, protocol, queries, partition_query)
+    cx_read_sql::read_sql(
+        py,
+        conn,
+        return_type,
+        protocol,
+        queries,
+        partition_query,
+        pre_execution_queries,
+    )
 }
 
 #[pyfunction]

connectorx-python/src/pandas/dispatcher.rs

@@ -41,6 +41,10 @@ where
         }
     }
 
+    pub fn set_pre_execution_queries(&mut self, pre_execution_queries: Option<&[String]>) {
+        self.src.set_pre_execution_queries(pre_execution_queries);
+    }
+
     /// Start the data loading process.
     pub fn run(mut self, py: Python<'py>) -> Result<Bound<'py, PyAny>, TP::Error> {
         debug!("Run dispatcher");