Append & Update Time Series


  • Use timeSeriesFor.append for the following actions:

    • Create a new time series:
      Appending an entry to a time series that doesn't exist yet
      will create the time series and add the new entry to it.

    • Create a new time series entry:
      Appending a new entry to an existing time series
      will add the entry to the series at the specified timestamp.

    • Modify an existing time series entry:
      Use append to update the data of an existing entry with the specified timestamp.

  • Each call to append handles a single time series entry.

  • To append multiple entries in a single transaction you can:



append usage

Flow:

  • Open a session.
  • Create an instance of timeSeriesFor and pass it the following:
  • Call timeSeriesFor.append and pass it the time series entry details.
  • Call session.saveChanges for the action to take effect on the server.

Note:

  • A DocumentDoesNotExistException exception is thrown if the specified document does not exist.

Examples

Append entries with single value:


  • In this example, entries are appended with a single value.

  • Although a loop is used to append multiple entries,
    all entries are appended in a single transaction when saveChanges is executed.

// Open a session and store a new document
const session = documentStore.openSession();
await session.store(new User("John"), "users/john");

// Get an instance of 'timeSeriesFor'
// Pass the document ID and the time series name
const timeSeriesName = "HeartRates";
const tsf = session.timeSeriesFor("users/john", timeSeriesName);
  
// Create time series and add entries:
// ===================================

// Define an optional tag and some base time for the first entry:
const optionalTag = "watches/fitbit";
const baseTime = new Date();
baseTime.setUTCHours(0);

// The first 'append' call will create the 'HeartRates' time series on the document
// (since this series doesn't exist yet on the document) and insert the first entry
tsf.append(baseTime, 65, optionalTag);

// The next 'append' calls will add more entries to the 'HeartRates' time series
for (let i = 1; i < 10; i++)
{
    const nextMinute = new Date(baseTime.getTime() + 60_000 * i);
    const nextMeasurement = 65 + i;
    tsf.append(nextMinute, nextMeasurement, optionalTag);
}

// Modify an existing entry:
// =========================

// Modify the last entry that was added
// The entry with the specified time stamp will be updated
tsf.append(new Date(baseTime.getTime() + 60_000 * 9), 60, optionalTag);

// Save changes
await session.saveChanges();

// Results:
// ========
// * The document will contain a time series named "HeartRates" with 10 entries.
// * The entries' timestamps are saved on the server in UTC.

Append entries with multiple values:


  • In this example, we append multi-value StockPrice entries.

  • Notice the clarity gained by naming the values.

const session = documentStore.openSession();
await session.store(new User("John"), "users/john");

const tsf = session.timeSeriesFor("users/john", "StockPrices");

const optionalTag = "companies/kitchenAppliances";
const baseTime = new Date();
baseTime.setUTCHours(0);

const oneDay = 24 * 60 * 60 * 1000;
let nextDay = new Date(baseTime.getTime() + oneDay);

// Provide multiple values to the entity
tsf.append(nextDay, [ 52, 54, 63.5, 51.4, 9824 ], optionalTag);

nextDay = new Date(baseTime.getTime() + oneDay * 2);
tsf.append(nextDay, [ 54, 55, 61.5, 49.4, 8400 ], optionalTag);

nextDay = new Date(baseTime.getTime() + oneDay * 3);
tsf.append(nextDay, [ 55, 57, 65.5, 50, 9020 ], optionalTag);

await session.saveChanges();

// Results:
// ========
// * The document will contain a time series called "StockPrices" with 3 entries.
// * Each entry will have 5 values.
// * The entries' timestamps are saved on the server in UTC.
// Register the named values for the 'StockPrices' series on the server
await documentStore.timeSeries.register("Users",
    "StockPrices", ["open", "close", "high", "low", "volume"]);

const session = documentStore.openSession();
await session.store(new User("John"), "users/john");

// Get an instance of 'timeSeriesFor', pass:
// * the document ID
// * the time series name
// * the class that will hold the entry's values
const tsf = session.timeSeriesFor("users/john", "StockPrices", StockPrice);

const optionalTag = "companies/kitchenAppliances";
const baseTime = new Date();
baseTime.setUTCHours(0);
const oneDay = 24 * 60 * 60 * 1000;

// Provide the multiple values via the StockPrice class
const price1 = new StockPrice();
price1.open = 52;
price1.close = 54;
price1.high = 63.5;
price1.low = 51.4;
price1.volume = 9824;

let nextDay = new Date(baseTime.getTime() + oneDay);
tsf.append(nextDay, price1, optionalTag);

const price2 = new StockPrice();
price2.open = 54;
price2.close = 55;
price2.high = 61.5;
price2.low = 49.4;
price2.volume = 8400;

nextDay = new Date(baseTime.getTime() + oneDay * 2);
tsf.append(nextDay, price2, optionalTag);

const price3 = new StockPrice();
price3.open = 55;
price3.close = 57;
price3.high = 65.5;
price3.low = 50;
price3.volume = 9020;

nextDay = new Date(baseTime.getTime() + oneDay * 3);
tsf.append(nextDay, price3, optionalTag);

await session.saveChanges();

// Results:
// ========
// * The document will contain a time series called "StockPrices" with 3 entries.
// * Each entry will have 5 named values.
// * The entries' timestamps are saved on the server in UTC.
// This class is used in the "Named Values" example
class StockPrice {

    // Define the names for the entry values
    static TIME_SERIES_VALUES = ["open", "close", "high", "low", "volume"];
    
    constructor(
        open = 0,
        close = 0,
        high = 0,
        low = 0,
        volume = 0
    ) {
        Object.assign(this, {
            open,
            close,
            high,
            low,
            volume
        });
    }
}

Syntax

// Available overloads:
// ====================

append(timestamp, value);
append(timestamp, value, tag);

append(timestamp, values);
append(timestamp, values, tag); 

append(timestamp, entry);
append(timestamp, entry, tag);
append(entry);
Parameter Type Description
timestamp Date Time series entry's timestamp
value number Entry's value
values number[] Entry's values
tag string An optional tag for the entry
entry object object with the entry's values