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What are the different modes in which you can submit Spark jobs? Explain each.

Spark/Big Dataeasy0.5 min read

**Local**: `--master local[N]` or `local[*]`. Single JVM; N threads. Dev and unit tests. No distribution. **Standalone**: `--master spark://host:7077`. Spark's built-in cluster manager. Simple; no YARN/K8s. Rare in prod. **YARN**: `--master yarn`, `--deploy-mode...

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Asked at 1 company
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1,863
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Dunnhumby
Key Concepts Tested
spark

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Expert Answer
102 words

Local: --master local[N] or local[*]. Single JVM; N threads. Dev and unit tests. No distribution.

Standalone: --master spark://host:7077. Spark's built-in cluster manager. Simple; no YARN/K8s. Rare in prod.

YARN: --master yarn, --deploy-mode client|cluster. Client: driver on submission machine; cluster: driver on worker. Cluster preferred for prod—driver survives client disconnect.

Kubernetes: --master k8s://.... Container-native; scale to zero; cloud-native.

Why Deploy Mode Matters: Client mode: driver uses client resources; client crash = job fail. Cluster: driver in cluster; resilient.

Scalability Trade-offs: K8s elastic; YARN stable for Hadoop shops. Local is not scalable.

Cost Implications: Cluster mode enables spot/preemptible for workers; driver on stable node.

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