# Spark

**Package:** `flyteplugins.spark`

Use this to configure a SparkContext for a your task. Task's marked with this will automatically execute
natively onto K8s as a distributed execution of spark

## Parameters

```python
class Spark(
    spark_conf: typing.Optional[typing.Dict[str, str]],
    hadoop_conf: typing.Optional[typing.Dict[str, str]],
    executor_path: typing.Optional[str],
    applications_path: typing.Optional[str],
    driver_pod: typing.Optional[flyte._pod.PodTemplate],
    executor_pod: typing.Optional[flyte._pod.PodTemplate],
)
```
| Parameter | Type | Description |
|-|-|-|
| `spark_conf` | `typing.Optional[typing.Dict[str, str]]` | Spark configuration dictionary. |
| `hadoop_conf` | `typing.Optional[typing.Dict[str, str]]` | Hadoop configuration dictionary. |
| `executor_path` | `typing.Optional[str]` | Path to the Python binary for PySpark execution. |
| `applications_path` | `typing.Optional[str]` | Path to the main application file. |
| `driver_pod` | `typing.Optional[flyte._pod.PodTemplate]` | Pod template for the driver pod. |
| `executor_pod` | `typing.Optional[flyte._pod.PodTemplate]` | Pod template for the executor pods. |

---
**Source**: https://github.com/unionai/unionai-docs/blob/main/content/api-reference/integrations/spark/packages/flyteplugins.spark/spark.md
**HTML**: https://www.union.ai/docs/v2/union/api-reference/integrations/spark/packages/flyteplugins.spark/spark/