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

To use the integration with EMR Serverless 6.9.0, pass the required Spark-Redshift dependencies with your Spark job. Use `--jars` to include Redshift connector related libraries. To access other file locations supported by the `--jars` option, refer to the [Advanced Dependency Management](https://spark.apache.org/docs/latest/submitting-applications.html#advanced-dependency-management) section of the Apache Spark documentation. 
+ `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 demonstrate how to launch a Spark application with the Amazon Redshift integration for Apache Spark.

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#### [ Amazon EMR 6.10.0 \$1 ]

Launch a Spark job on Amazon EMR Serverless with the Amazon Redshift integration for Apache Spark on EMR Serverless release 6.10.0 and higher.

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

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#### [ Amazon EMR 6.9.0 ]

To launch a Spark job on Amazon EMR Serverless with the Amazon Redshift integration for Apache Spark on EMR Serverless release 6.9.0, use the `--jars` option as shown in the following example. Note that the paths listed with the `--jars` option are the default paths for the JAR files.

```
--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
```

```
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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