pyspark.pandas.read_sql_query¶
-
pyspark.pandas.read_sql_query(sql: str, con: str, index_col: Union[str, List[str], None] = None, **options: Any) → pyspark.pandas.frame.DataFrame[source]¶ Read SQL query into a DataFrame.
Returns a DataFrame corresponding to the result set of the query string. Optionally provide an index_col parameter to use one of the columns as the index, otherwise default index will be used.
Note
Some database might hit the issue of Spark: SPARK-27596
- Parameters
- sqlstring SQL query
SQL query to be executed.
- constr
A JDBC URI could be provided as as str.
Note
The URI must be JDBC URI instead of Python’s database URI.
- index_colstring or list of strings, optional, default: None
Column(s) to set as index(MultiIndex).
- optionsdict
All other options passed directly into Spark’s JDBC data source.
- Returns
- DataFrame
See also
read_sql_tableRead SQL database table into a DataFrame.
read_sql
Examples
>>> ps.read_sql_query('SELECT * FROM table_name', 'jdbc:postgresql:db_name')