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# Deploying a standalone Ballista cluster using cargo install

Another simple way to start a local cluster for testing purposes is to use cargo to install
the scheduler and executor crates.

```bash
cargo install --locked ballista-scheduler
cargo install --locked ballista-executor
```

With these crates installed, it is now possible to start a scheduler process.

```bash
RUST_LOG=info ballista-scheduler
```

The scheduler will bind to port 50050 by default.

Next, start an executor processes in a new terminal session.

```bash
RUST_LOG=info ballista-executor
```

The executor will bind to port 50051 by default. Additional executors can be started by
manually specifying a bind port. For example:

```bash
RUST_LOG=info ballista-executor --bind-port 50052
```

## Installing with Optional Features

Ballista supports optional features that can be enabled during installation using the `--features` flag.

### Spark-Compatible Functions

To enable Spark-compatible scalar, aggregate, and window functions from the `datafusion-spark` crate:

```bash
# Install scheduler with spark-compat feature
cargo install --locked --features spark-compat ballista-scheduler

# Install executor with spark-compat feature
cargo install --locked --features spark-compat ballista-executor

# Install CLI with spark-compat feature
cargo install --locked --features spark-compat ballista-cli
```

When the `spark-compat` feature is enabled, additional functions like `sha1`, `expm1`, `sha2`, and others become available in SQL queries.

> **Note:** The `spark-compat` feature provides Spark-compatible expressions and functions only, not full Apache Spark API compatibility.

For more details about Spark-compatible functions, see [Spark-Compatible Functions](../spark-compatible-functions.md).