> For the complete documentation index, see [llms.txt](https://george-jen.gitbook.io/data-science-and-apache-spark/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://george-jen.gitbook.io/data-science-and-apache-spark/basic-spark-package.md).

# Basic Spark Package

If you are not running Scala under spark-shell, you are likely needing to import some basic Spark packages such as

```
import org.apache.spark.SparkContext
import org.apache.spark.SparkConf
```

You will also need to define Spark conf and 

```
val sparkConf = new SparkConf()
  .setAppName("getTweets").setMaster("local[3]")
```

Note, in this example, local\[3] means your driver program runs on the local driver node only and to use up to 3 CPUs

You will need to create SparkContext, based on sparkConf you created earlier

```
val sc = new SparkContext(sparkConf)
```

Note, if you start $SPSRK\_HOME/bin/spark-shell, or use Spylon Kernel in jupyter-notebook, Spark Context sc is created for you automatically and you do not need to run

```
val sc = new SparkContext(sparkConf)
```