![]() The above scripts first establishes a connection to the database and then execute a query the results of the query is then stored in a list which is then converted to a Pandas data frame a Spark data frame is then created based on the Pandas data frame. option("url", f"jdbc:sqlserver://localhost:1433 databaseName=" Use the following code to setup Spark session and then read the data via JDBC.įrom pyspark import SparkContext, SparkConf, SQLContextĪppName = "PySpark SQL Server Example - via JDBC" For this demo, the driver path is ‘sqljdbc_7.2/enu/mssql-jdbc-7.2.1.jre8.jar’. Via JDBC driver for SQL Serverĭownload Microsoft JDBC Driver for SQL Server from the following website:Ĭopy the driver into the folder where you are going to run the Python scripts. ODBC Driver 13 for SQL Server is also available in my system. For SQL Server Authentication, the following login is available:
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