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test/scenario2_large_table.js

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+#!/usr/bin/env node
+// Scenario 2: Deep Dive Analysis (Large Arrow Table)
+// Tests large Arrow tables (> 1MB) sent via HTTP fileserver
+
+const { SmartSend } = require('../js_bridge');
+
+// Configuration
+const ANALYSIS_SUBJECT = "analysis_results";
+const NATS_URL = "nats://localhost:4222";
+
+// Create correlation ID for tracing
+const correlationId = require('uuid').v4();
+
+// Sender: Send large Arrow table to Julia
+async function sendLargeTable() {
+    // Create a large DataFrame-like structure (10 million rows)
+    // For testing, we'll create a smaller but still large table
+    const numRows = 1000000; // 1 million rows
+    
+    const data = {
+        id: Array.from({ length: numRows }, (_, i) => i + 1),
+        value: Array.from({ length: numRows }, () => Math.random()),
+        category: Array.from({ length: numRows }, () => ['A', 'B', 'C'][Math.floor(Math.random() * 3)])
+    };
+    
+    // Convert to Arrow Table
+    const { Table, Vector, RecordBatch } = require('apache-arrow');
+    
+    const idVector = Vector.from(data.id);
+    const valueVector = Vector.from(data.value);
+    const categoryVector = Vector.from(data.category);
+    
+    const table = Table.from({
+        id: idVector,
+        value: valueVector,
+        category: categoryVector
+    });
+    
+    // Send via SmartSend with type="table"
+    const env = await SmartSend(
+        ANALYSIS_SUBJECT,
+        table,
+        "table",
+        { correlationId }
+    );
+    
+    console.log(`Sent large table with ${numRows} rows`);
+    console.log(`Correlation ID: ${correlationId}`);
+    console.log(`Transport: ${env.transport}`);
+    console.log(`URL: ${env.url || 'N/A'}`);
+}
+
+// Run the sender
+sendLargeTable().catch(console.error);