valkey-time-series

This package provides support for the ValkeyTimeSeries module, which adds a time series data structure to Valkey. It extends the Node Valkey client to include functions for each of the ValkeyTimeSeries commands.

To use these extra commands, your Valkey server must have the ValkeyTimeSeries module installed.

Usage

For a complete example, see time-series.js in the Node Valkey examples folder.

Creating Time Series data structure in Valkey

The TS.CREATE command creates a new time series.

Here, we'll create a new time series "temperature":

import { createClient } from 'valkey';
import { TimeSeriesDuplicatePolicies, TimeSeriesEncoding, TimeSeriesAggregationType } from 'valkey-time-series';

...

 const created = await client.ts.create('temperature', {
    RETENTION: 86400000, // 1 day in milliseconds
    ENCODING: TimeSeriesEncoding.UNCOMPRESSED, // No compression - When not specified, the option is set to COMPRESSED
    DUPLICATE_POLICY: TimeSeriesDuplicatePolicies.BLOCK, // No duplicates - When not specified: set to the global DUPLICATE_POLICY configuration of the database (which by default, is BLOCK).
  });

    if (created === 'OK') {
    console.log('Created timeseries.');
  } else {
    console.log('Error creating timeseries :(');
    process.exit(1);
  }

Adding new value to a Time Series data structure in Valkey

With ValkeyTimeSeries, we can add a single value to time series data structure using the TS.ADD command and if we would like to add multiple values we can use the TS.MADD command.

let value = Math.floor(Math.random() * 1000) + 1; // Random data point value
  let currentTimestamp = 1640995200000; // Jan 1 2022 00:00:00
  let num = 0;

  while (num < 10000) {
    // Add a new value to the timeseries, providing our own timestamp:
    // https://valkey.io/commands/ts.add/
    await client.ts.add('temperature', currentTimestamp, value);
    console.log(`Added timestamp ${currentTimestamp}, value ${value}.`);

    num += 1;
    value = Math.floor(Math.random() * 1000) + 1; // Get another random value
    currentTimestamp += 1000; // Move on one second.
  }

  // Add multiple values to the timeseries in round trip to the server:
  // https://valkey.io/commands/ts.madd/
  const response = await client.ts.mAdd([{
    key: 'temperature',
    timestamp: currentTimestamp + 60000,
    value: Math.floor(Math.random() * 1000) + 1
  }, {
    key: 'temperature',
    timestamp: currentTimestamp + 120000,
    value: Math.floor(Math.random() * 1000) + 1
  }]);

Retrieving Time Series data from Valkey

With ValkeyTimeSeries, we can retrieve the time series data using the TS.RANGE command by passing the criteria as follows:

// Query the timeseries with TS.RANGE:
  // https://valkey.io/commands/ts.range/
  const fromTimestamp = 1640995200000; // Jan 1 2022 00:00:00
  const toTimestamp = 1640995260000; // Jan 1 2022 00:01:00
  const rangeResponse = await client.ts.range('temperature', fromTimestamp, toTimestamp, {
    // Group into 10 second averages.
    AGGREGATION: {
      type: TimeSeriesAggregationType.AVERAGE,
      timeBucket: 10000
    }
  });

  console.log('RANGE RESPONSE:');
  // rangeResponse looks like:
  // [
  //   { timestamp: 1640995200000, value: 356.8 },
  //   { timestamp: 1640995210000, value: 534.8 },
  //   { timestamp: 1640995220000, value: 481.3 },
  //   { timestamp: 1640995230000, value: 437 },
  //   { timestamp: 1640995240000, value: 507.3 },
  //   { timestamp: 1640995250000, value: 581.2 },
  //   { timestamp: 1640995260000, value: 600 }
  // ]

Altering Time Series data Stored in Valkey

ValkeyTimeSeries includes commands that can update values in a time series data structure.

Using the TS.ALTER command, we can update time series retention like this:

  // https://valkey.io/commands/ts.alter/
  const alterResponse = await client.ts.alter('temperature', {
    RETENTION: 0 // Keep the entries forever
  });

Retrieving Information about the timeseries Stored in Valkey

ValkeyTimeSeries also includes commands that can help to view the information on the state of a time series.

Using the TS.INFO command, we can view timeseries information like this:

 // Get some information about the state of the timeseries.
  // https://valkey.io/commands/ts.info/
  const tsInfo = await client.ts.info('temperature');

  // tsInfo looks like this:
  // {
  //   totalSamples: 1440,
  //   memoryUsage: 28904,
  //   firstTimestamp: 1641508920000,
  //   lastTimestamp: 1641595320000,
  //   retentionTime: 86400000,
  //   chunkCount: 7,
  //   chunkSize: 4096,
  //   chunkType: 'uncompressed',
  //   duplicatePolicy: 'block',
  //   labels: [],
  //   sourceKey: null,
  //   rules: []
  // }