Prerequisites:
Access: Access to both SAP Datasphere and Databricks.Credentials: Have Databricks authentication credentials ready.
Steps:
Login to Datasphere: In the home screen of the datasphere, Expand the navigation bar on the left and click “Configuration”.
Database Access Click database access and then click Database Analysis Users
Then click “Create” to create a database access user
Enter the Database Analysis username suffixEnable Space Schema AccessSet Database Analysis user expires in Never option.
Once created it will generate a Hostname, Port Number and Password and make sure that Enable Space schema access has been enabled, so by this you can be able to access Datasphere’s all spaces and its schemas
Login to DatabricksGo to Workspace, create Cluster
In the cluster, paste this code to connect to datasphere and Databricks
Python
import org.apache.spark.sql.SparkSession
# Initialize Spark Session
spark = SparkSession.builder()
.appName(“SAP HANA Connection”)
.config(“spark.jars”, “/usr/sap/hdbclient/ngdbc-2.4.62.jar”)
.getOrCreate()
# JDBC URL
jdbcUrl = “jdbc:sap://zeus.hana.prod.eu-central-1.whatever.cloud.sap:443/?encrypt=true&validateCertificate=false¤tschema=MYSCHEMA”
# Connection Properties
connectionProperties = {
“user” : “MYUSER”,
“password” : “mypassword”,
“driver” : “com.sap.db.jdbc.Driver”
}
# Query to Select all the Data from MYTABLE
val query = “SELECT * FROM MYTABLE”
# Read Data from JDBC Connection into DataFrame
val df = spark.read.jdbc(jdbcUrl, query, connectionProperties)
Once code is executed successfully, the connection is established between the Datasphere and Databricks.
Prerequisites:Access: Access to both SAP Datasphere and Databricks.Credentials: Have Databricks authentication credentials ready.Steps:Login to Datasphere: In the home screen of the datasphere, Expand the navigation bar on the left and click “Configuration”. Database Access Click database access and then click Database Analysis Users Then click “Create” to create a database access user Enter the Database Analysis username suffixEnable Space Schema AccessSet Database Analysis user expires in Never option. Once created it will generate a Hostname, Port Number and Password and make sure that Enable Space schema access has been enabled, so by this you can be able to access Datasphere’s all spaces and its schemas Login to DatabricksGo to Workspace, create Cluster In the cluster, paste this code to connect to datasphere and DatabricksPythonimport org.apache.spark.sql.SparkSession # Initialize Spark Sessionspark = SparkSession.builder() .appName(“SAP HANA Connection”) .config(“spark.jars”, “/usr/sap/hdbclient/ngdbc-2.4.62.jar”) .getOrCreate() # JDBC URLjdbcUrl = “jdbc:sap://zeus.hana.prod.eu-central-1.whatever.cloud.sap:443/?encrypt=true&validateCertificate=false¤tschema=MYSCHEMA” # Connection PropertiesconnectionProperties = { “user” : “MYUSER”, “password” : “mypassword”, “driver” : “com.sap.db.jdbc.Driver”} # Query to Select all the Data from MYTABLEval query = “SELECT * FROM MYTABLE” # Read Data from JDBC Connection into DataFrameval df = spark.read.jdbc(jdbcUrl, query, connectionProperties) Once code is executed successfully, the connection is established between the Datasphere and Databricks. Read More Technology Blogs by Members articles
#SAP
#SAPTechnologyblog
