# Launching a Spark application using the Amazon Redshift integration for Apache Spark
<a name="emr-spark-redshift-launch"></a>

For Amazon EMR releases 6.4 through 6.9, you must use the `--jars` or `--packages` option to specify which of the following JAR files you want to use. The `--jars` option specifies dependencies stored locally, in HDFS, or using HTTP/S. To see other file locations supported by the `--jars` option, see [Advanced Dependency Management](https://spark.apache.org/docs/latest/submitting-applications.html#advanced-dependency-management) in the Spark documentation. The `--packages` option specifies dependencies stored in the public Maven repo. 
+ `spark-redshift.jar`
+ `spark-avro.jar`
+ `RedshiftJDBC.jar`
+ `minimal-json.jar`

Amazon EMR releases 6.10.0 and higher don't require the `minimal-json.jar` dependency, and automatically install the other dependencies to each cluster by default. The following examples show how to launch a Spark application with the Amazon Redshift integration for Apache Spark.

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#### [ Amazon EMR 6.10.0 \+ ]

The following example shows how to launch a Spark application with the `spark-redshift` connector with Amazon EMR releases 6.10 and higher.

```
spark-submit my_script.py
```

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#### [ Amazon EMR 6.4.0 - 6.9.x ]

To launch a Spark application with the `spark-redshift` connector on Amazon EMR releases 6.4 through 6.9, you must use the `--jars` or `--packages` option, as the following example shows. Note that the paths listed with the `--jars` option are the default paths for the JAR files.

```
spark-submit \
  --jars /usr/share/aws/redshift/jdbc/RedshiftJDBC.jar,/usr/share/aws/redshift/spark-redshift/lib/spark-redshift.jar,/usr/share/aws/redshift/spark-redshift/lib/spark-avro.jar,/usr/share/aws/redshift/spark-redshift/lib/minimal-json.jar \
  my_script.py
```

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