Sistema de ejecución de procedimientos almacenados Oracle

// Procesamiento paralelo
public async Task<IEnumerable<T>> ProcessLargeDataset<T>(string procedureName)
{
    using var cursor = await _executor.ExecuteCursorAsync(procedureName);
    return await cursor
        .AsParallel()
        .WithDegreeOfParallelism(Environment.ProcessorCount)
        .Select(row => Transform<T>(row))
        .ToListAsync();
}

public class AdaptiveCompression
{
    public byte[] Compress(byte[] data)
    {
        return data.Length switch
        {
            > 1_000_000 => CompressGzip(data),      // Grandes datasets
            > 100_000 => CompressBrotli(data),      // Datasets medianos
            _ => CompressLz4(data)                   // Datasets pequeños
        };
    }
}

// Verificación de Redis con timeout
public async Task<bool> IsRedisAvailableAsync()
{
    using var timeoutCts = new CancellationTokenSource(TimeSpan.FromSeconds(2));
    
    if (!_redis.IsConnected)
        return false;
    
    var ping = await _redis.GetDatabase().PingAsync();
    return ping != TimeSpan.MaxValue && ping < TimeSpan.FromSeconds(1);
}
                                    

public async Task<IActionResult> ExecuteStoredProcedure(
    [FromBody] SpRequest request,
    [FromHeader(Name = "X-Correlation-ID")] string correlationId)
{
    using var activity = _activitySource.StartActivity("ExecuteSP");
    activity?.SetTag("sp.name", request.ProcedureName);
    activity?.SetTag("correlation.id", correlationId);
    
    // Ejecución y tracking...
}

public class AdaptiveRateLimiter
{
    public async Task<bool> ShouldAllowRequest(string clientId)
    {
        var clientMetrics = await _metricService.GetClientMetrics(clientId);
        return await ML.PredictThreat(clientMetrics) switch
        {
            ThreatLevel.Low => true,
            ThreatLevel.Medium => ApplyStandardLimit(),
            ThreatLevel.High => false
        };
    }
}

public class PredictiveCacheManager
{
    public async Task WarmupCache()
    {
        var predictions = await _mlModel.PredictPopularRequests();
        await Parallel.ForEachAsync(predictions, async (pred, ct) =>
        {
            await _cache.PrefetchAsync(pred.Key, pred.Probability);
        });
    }
}

// Análisis automático de riesgo de deadlock
public async Task<DeadlockAnalysisResult> AnalyzeStoredProcedure(string procedureName)
{
    var patterns = await ExtractDeadlockPatterns(procedureName);
    var riskScore = CalculateRiskScore(patterns);
    
    if (riskScore > 70)
        TriggerPreventiveAlert(procedureName, riskScore);
        
    return new DeadlockAnalysisResult { RiskScore = riskScore };
}