getRecentPerformanceSamples

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Parameters

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Response

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Code Examples

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Basic Request

curl https://fra.rpc.orbitflare.com?api_key=YOUR-API-KEY -X POST -H "Content-Type: application/json" -d '{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "getRecentPerformanceSamples",
  "params": []
}'

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Request with Limit

curl https://fra.rpc.orbitflare.com?api_key=YOUR-API-KEY -X POST -H "Content-Type: application/json" -d '{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "getRecentPerformanceSamples",
  "params": [
    100
  ]
}'

​

Using web3.js

import { Connection } from '@solana/web3.js';

const connection = new Connection('https://fra.rpc.orbitflare.com?api_key=YOUR-API-KEY');

// Get recent performance samples
const samples = await connection.getRecentPerformanceSamples();
console.log('Performance samples:', samples);

// Calculate average TPS
function calculateAverageTPS(samples: any[]): number {
  const totalTransactions = samples.reduce(
    (sum, sample) => sum + sample.numTransactions,
    0
  );
  const totalSeconds = samples.reduce(
    (sum, sample) => sum + sample.samplePeriodSecs,
    0
  );
  return totalTransactions / totalSeconds;
}

​

Notes

1. Returns recent performance samples from the network
2. Each sample covers a period of time (typically 60 seconds)
3. Samples include transaction counts and slot information
4. The response is immediate as it reads from the current state
5. The default limit is 720 samples (approximately 12 hours)

​

Best Practices

1. Use appropriate limit based on your analysis needs
2. Cache results when appropriate to reduce RPC load
3. Monitor for significant changes in performance
4. Consider using websocket subscription for real-time updates
5. Handle network errors and retry when appropriate

​

Common Errors

​

Use Cases

1. Performance Analysis
   interface PerformanceMetrics {
     averageTPS: number;
     peakTPS: number;
     totalTransactions: number;
     totalSlots: number;
     metadata: {
       timestamp: number;
       sampleCount: number;
     };
   }
   
   async function analyzePerformance(
     limit: number = 720
   ): Promise<PerformanceMetrics> {
     const samples = await connection.getRecentPerformanceSamples(limit);
     
     const totalTransactions = samples.reduce(
       (sum, sample) => sum + sample.numTransactions,
       0
     );
     const totalSeconds = samples.reduce(
       (sum, sample) => sum + sample.samplePeriodSecs,
       0
     );
     const peakTPS = Math.max(
       ...samples.map(sample => sample.numTransactions / sample.samplePeriodSecs)
     );
     
     return {
       averageTPS: totalTransactions / totalSeconds,
       peakTPS,
       totalTransactions,
       totalSlots: samples.reduce((sum, sample) => sum + sample.numSlots, 0),
       metadata: {
         timestamp: Date.now(),
         sampleCount: samples.length
       }
     };
   }
   
2. Performance Monitoring
   interface PerformanceAlert {
     type: 'high_tps' | 'low_tps' | 'anomaly';
     currentTPS: number;
     threshold: number;
     metadata: {
       timestamp: number;
       slot: number;
     };
   }
   
   class PerformanceMonitor {
     private previousTPS: number | null = null;
     private readonly threshold = 0.2; // 20% change threshold
     
     async monitorPerformance(
       interval: number = 60000
     ): Promise<PerformanceAlert | null> {
       const samples = await connection.getRecentPerformanceSamples(1);
       const currentSample = samples[0];
       const currentTPS = currentSample.numTransactions / currentSample.samplePeriodSecs;
       
       if (this.previousTPS === null) {
         this.previousTPS = currentTPS;
         return null;
       }
       
       const change = Math.abs(currentTPS - this.previousTPS) / this.previousTPS;
       
       if (change > this.threshold) {
         const alert: PerformanceAlert = {
           type: change > 0 ? 'high_tps' : 'low_tps',
           currentTPS,
           threshold: this.threshold,
           metadata: {
             timestamp: Date.now(),
             slot: currentSample.slot
           }
         };
         
         this.previousTPS = currentTPS;
         return alert;
       }
       
       return null;
     }
   }
   
3. Performance History
   interface PerformanceHistory {
     samples: Array<{
       slot: number;
       tps: number;
       nonVoteTPS: number;
       timestamp: number;
     }>;
     summary: {
       averageTPS: number;
       peakTPS: number;
       totalTransactions: number;
     };
     metadata: {
       startTime: number;
       endTime: number;
       sampleCount: number;
     };
   }
   
   async function getPerformanceHistory(
     limit: number = 720
   ): Promise<PerformanceHistory> {
     const samples = await connection.getRecentPerformanceSamples(limit);
     
     const processedSamples = samples.map(sample => ({
       slot: sample.slot,
       tps: sample.numTransactions / sample.samplePeriodSecs,
       nonVoteTPS: sample.numNonVoteTransaction / sample.samplePeriodSecs,
       timestamp: Date.now() - (samples.length - samples.indexOf(sample)) * sample.samplePeriodSecs * 1000
     }));
     
     const totalTransactions = samples.reduce(
       (sum, sample) => sum + sample.numTransactions,
       0
     );
     const totalSeconds = samples.reduce(
       (sum, sample) => sum + sample.samplePeriodSecs,
       0
     );
     
     return {
       samples: processedSamples,
       summary: {
         averageTPS: totalTransactions / totalSeconds,
         peakTPS: Math.max(...processedSamples.map(sample => sample.tps)),
         totalTransactions
       },
       metadata: {
         startTime: processedSamples[0].timestamp,
         endTime: processedSamples[processedSamples.length - 1].timestamp,
         sampleCount: samples.length
       }
     };
   }