Sail MCP Server for Spark SQL

Created By

lakehqa year ago

Sail is an open-source computation framework that serves as a drop-in replacement for Apache Spark (SQL and DataFrame API) in both single-host and distributed settings. The built-in MCP server in Sail exposes tools for LLM agents to register datasets and execute Spark SQL queries.

# sail

# spark

Overview Content Tools Comments

Overview

what is Sail?

Sail is a unified platform designed for stream processing, batch processing, and compute-intensive workloads, including AI tasks. It serves as a drop-in replacement for Spark SQL and the Spark DataFrame API, functioning in both single-host and distributed environments.

how to use Sail?

To use Sail, install it via pip with pip install "pysail[spark]", or build it from source for optimized performance. Start the Sail server using command line, Python API, or deploy it on Kubernetes for distributed processing.

key features of Sail?

Unified processing for stream, batch, and AI workloads.
Drop-in replacement for Spark SQL and DataFrame API.
Supports local and distributed server setups.
Easy integration with PySpark.

use cases of Sail?

Real-time data analytics and processing.
Batch processing of large datasets.
AI model training and inference in a distributed environment.

FAQ from Sail?

Is Sail compatible with existing Spark applications?

Yes! Sail is designed to be a drop-in replacement for Spark SQL and DataFrame API.

Can I run Sail on Kubernetes?

Yes! Sail can be deployed on Kubernetes for distributed processing.

What support options are available for Sail?

LakeSail offers flexible enterprise support options for Sail.

Server Config

{
  "mcpServers": {
    "sail": {
      "command": "sail",
      "args": [
        "spark",
        "mcp-server",
        "--transport",
        "stdio"
      ]
    }
  }
}

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