pyspark.pandas.read_sql_query#
- pyspark.pandas.read_sql_query(sql, con, index_col=None, **options)[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 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_table
- Read SQL database table into a DataFrame. 
- read_sql
 - Examples - >>> ps.read_sql_query('SELECT * FROM table_name', 'jdbc:postgresql:db_name')