Documentation

Impala SQL Agent

The Impala SQL Agent is a specialized component that enables natural language interaction with Apache Impala databases, providing intelligent query generation and data analysis capabilities optimized for Hadoop environments.

Impala SQL Agent Component

Impala SQL Agent interface and configuration options

Configuration Parameters

Required Parameters

  • Language Model: The AI model for processing
  • Host: Impala server hostname
  • Port: Impala server port
  • Database: Target database name
  • Authentication: Authentication credentials

Optional Configuration

  • Query Options: Query settings
    • batchSize: Batch size for results
    • timeout: Query timeout
    • memLimit: Memory limit
  • Performance: Performance settings
    • parallelism: Query parallelism
    • resourcePool: Resource pool
    • queueSize: Query queue size
  • Security: Security options
    • ssl: SSL configuration
    • kerberos: Kerberos settings

Output Format

{
  "result": {
    "query": {
      "sql": string,
      "parameters": object
    },
    "data": {
      "columns": array,
      "rows": array,
      "rowCount": number
    },
    "metadata": {
      "executionTime": string,
      "bytesScanned": number,
      "queryProfile": object
    }
  }
}

Example Usage

const impalaSQLAgent = new ImpalaSQLAgent({
  languageModel: "gpt-4",
  host: "impala.example.com",
  port: 21050,
  database: "analytics",
  authentication: {
    username: process.env.IMPALA_USER,
    password: process.env.IMPALA_PASSWORD
  },
  queryOptions: {
    batchSize: 1000,
    timeout: 300,
    memLimit: "4GB"
  },
  performance: {
    parallelism: 8,
    resourcePool: "default",
    queueSize: 100
  },
  security: {
    ssl: {
      enabled: true,
      verify: true
    },
    kerberos: {
      principal: "impala/host@REALM",
      keytab: "/path/to/keytab"
    }
  }
});

const result = await impalaSQLAgent.process({
  input: "Show monthly revenue trends by product category"
});

Best Practices

  • Use appropriate memory limits
  • Optimize query parallelism
  • Enable result caching
  • Monitor resource usage
  • Implement security best practices