Metrics Engine

In-memory SQL compliant metrics engine for advance analytics calculations, features or alert based triggers


This guide explains how to use the Metrics Engine by defining SQL expressions that store metrics and the runtime frequency using a policy.

Joule provides a SQL compliant metrics engine. The engine computes SQL query based metrics using a runtime policy using the events stored within auto generated event tables.

Key features

  • ANSI SQL compliant metrics calculation definition

  • Apply calculated metrics within processors

  • Pre-computed metrics import

  • Runtime policy

  • Metric management

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Below computes a single family of metrics BidMovingAverage at set time intervals and saved to an in-memory standardQuoteAnalyticsStream.BidMovingAverage SQL table. The emit definition performs a query lookup against eh table and returns the avg_bid_max for each matching symbol.

processing unit:
  metrics engine:
    runtime policy:
      frequency: 1
      startup delay: 2
      time unit: MINUTES

    foreach metric compute:
        - name: BidMovingAverage
          metric key: symbol
          table definition: standardQuoteAnalyticsStream.BidMovingAverage (symbol VARCHAR, avg_bid_min FLOAT, avg_bid_avg FLOAT,avg_bid_max FLOAT)
            SELECT symbol,
            MIN(bid) AS 'avg_bid_min',
            AVG(bid) AS 'avg_bid_avg',
            MAX(bid) AS 'avg_bid_max'
            FROM standardQuoteAnalyticsStream.quote
            ingestTime >= date_trunc('minutes',now() - INTERVAL 2 MINUTES) AND ingestTime <= date_trunc('minutes',now())
            GROUP BY symbol
            ORDER BY 1;
          truncate on start: true
          compaction policy:
            frequency: 8
            time unit: HOURS

  select: "symbol, BidMovingAverage.avg_bid_max;WHERE symbol=${symbol} 'avg_bid_max'"

group by:
  - symbol

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