Create and deliver personalized experiences across digital properties at scale
Build engaging websites with intuitive web content management
Leverage a complete UI toolbox for web, mobile and desktop development
Build, protect and deploy apps across any platform and mobile device
Build mobile apps for iOS, Android and Windows Phone
Rapidly develop, manage and deploy business apps, delivered as SaaS in the cloud
Automate UI, load and performance testing for web, desktop and mobile
Host, deploy and scale Node.js, Java and .NET Core apps on premise or in the cloud
Optimize data integration with high-performance connectivity
Automate decision processes with a no-code business rules engine
Globally scale websites with innovative content management and infrastructure approaches
Content-focused web and mobile solution for empowering marketers
Faster, tailored mobile experiences for any device and data source
UX and app modernization to powerfully navigate today's digital landscape
Fuel agility with ever-ready applications, built in the cloud
Apache Spark, the open source big data processing framework, was built for speed, ease and complex analytics. Learn how to access Salesforce data in Spark.
Spark has several comprehensive advantages to MapReduce technologies such as Hadoop and Storm. Spark has an advanced directed acyclic graph (DAG) pattern that supports cyclic data flows and also allows programmers to develop multi-step pipelines. Several tasks can be performed on the same data through in-memory data sharing across DAGs. Using Apache Spark, one can run up to 100 times faster in memory and that is one of the major reasons most organizations want to use Spark.
The tricky part is getting access to data stored in other applications to leverage the power of Spark. A common scenario we see is the development of sophisticated transformations in the Spark framework with cloud application data, such as Salesforce, Eloqua or Marketo. Many developers are turning to the Progress DataDirect Salesforce Spark Connector and DataSource API of Spark to integrate Salesforce data in Spark. Sai Krishna Bobba, a developer evangelist at DataDirect, created this quick tutorial below to help you get started with your connection:
spark-shell --jars /path_to_driver/sforce.jar
val dataframe_salesforce = sqlContext.read.format("jdbc").option("url","jdbc:datadirect:sforce://login.salesforce.com;").option("driver","com.ddtek.jdbc.sforce.SForceDriver").option("dbtable","SFORCE.<
dataframe_salesforce.sqlContext.sql("select * from account").collect.foreach(println)
You should be able to see your result as shown below:
We hope this tutorial helped you access Salesforce data and process your datasets in Spark. This demonstration is not limited to Salesforce. In fact, you can use the Spark’s DataSource API with any of the DataDirect JDBC Spark connectors or DataDirect Cloud JDBC Spark connectors to connect and integrate to over 50+ datasources including SaaS, Relational and Big data sources.
Please contact us if you have any questions and share your comments below.
Nishanth Kadiyala is a Technical Marketing Manager at Progress. He has worked as a Software IT professional for 3 years during which he actively pursued several technologies including database designing, SQL querying and Cloud Computing. He is currently pursuing his MBA at UNC Chapel Hill and concentrating in Marketing. At UNC, he became proficient with data analytic tools such as MEXL and R. He is interested in the SaaS, Cloud and data integration technologies that are revolutionizing the world we live in.
Copyright © 2016, Progress Software Corporation and/or its subsidiaries or affiliates.
All Rights Reserved.
Progress, Telerik, and certain product names used herein are trademarks or registered trademarks of Progress Software Corporation and/or one of its subsidiaries or affiliates in the U.S. and/or other countries. See Trademarks or appropriate markings.