# DSS and Spark[¶](https://doc.dataiku.com/dss/latest/spark/index.html#dss-and-spark "Permalink to this headline")

* Usage of Spark in DSS

+ SparkSQL recipes

+ Visual recipes

+ Python code

- Note about Spark code in Python notebooks

+ R code

- Note about Spark code in R notebooks

+ Scala code

- Spark Scala, PySpark & SparkR recipes

- Spark Scala, PySpark & SparkR notebooks

- Note about Spark code in Scala notebooks

+ Machine Learning with MLLib

+ Machine Learning with H2O Sparkling Water

* Spark configurations

* Interacting with DSS datasets

+ Hadoop FS datasets

+ S3 datasets

+ Other

* Spark pipelines

+ Enabling Spark pipelines

+ Creating a Spark pipeline

+ Configuring behavior for intermediate datasets

+ Limitations

* Limitations and attention points

* Setting up Spark integration

+ Unmanaged Spark on Kubernetes

+ Main steps

- Configure DSS

- Build your Docker images

- Create the Spark configuration

Spark is a general engine for distributed computation. Once Spark integration is setup, DSS will offer settings to choose Spark as a job’s execution engine in various components.
