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Version: Upcoming

MLink TickerBasket

SpiderRock provides a TickerBasket feature via MLink REST (WebSockets coming) that allows clients to group multiple tickers into named baskets for efficient querying. This feature is available through the MLink/REST API.

Overview​

MLink TickerBasket enables clients to:

  • Group multiple tickers into named baskets
  • Query data for all tickers in a basket using a single parameter
  • Achieve faster query performance compared to WHERE clause filtering
  • Scale efficiently from small (10 tickers) to large (200+ tickers) baskets

To use TickerBasket, clients must:

  1. Secure an MLink API Key
  2. Connect to an MLink/WebSocket or REST server
  3. Define baskets using TickerItemDef messages
  4. Query using the basket number parameter

TickerBasket Workflow​

Key Messages​

MessageSourceDescription
TickerItemDefClientDefine tickers in a basket

Workflow​

  1. Client Sends TickerItemDef Objects:

    • Send multiple TickerItemDef objects to the MLink server
    • Each object represents a ticker with key details (ticker symbol, asset type, ticker source)
    • Include a basketNumber field to group tickers into a single basket
    • Include a userName field to identify the basket owner

  2. Post Basket Definitions:

    • Post using: POST /rest/proto?cmd=postmsgs&postaction=I
    • Each TickerItemDef adds one ticker to the specified basket
    • Baskets can contain varying numbers of tickers (10-200+), each being its own object.
    • Baskets are user-specific: the same basket number can exist for different users

  3. Query Using TickerBasket Parameter:

    • Use the tickerbasket parameter with the basket number
    • Example: GET /rest/proto?cmd=getmsgs&msgtype=OptionNbboQuote&tickerbasket=0000-0000-0000-0001
    • Server processes the query for all tickers in the basket

API Reference​

TickerItemDef Message​

The TickerItemDef message is used to define individual tickers within a basket.

Primary Key Fields:

  • ticker (TickerKey): The ticker symbol, asset type, and ticker source
  • basketNumber (HexLong): The basket identifier (can be formatted with or without dashes, e.g., 1 or 0000-0000-0000-0001)
  • userName: The username that owns this basket - your username

Body Fields:

  • clientFirm (ClientFirm): The client firm associated withyour userName - not mandatory
  • timestamp (Timestamp): Timestamp - not mandatory

Example TickerItemDef POST with Objects as Body:

POST /rest/json?cmd=postmsgs&postaction=I
{
  "header": {
    "mTyp": "TickerItemDef"
  },
  "message": {
    "pkey": {
      "ticker": {
        "at": "EQT",
        "ts": "NMS",
        "tk": "AAPL"
      },
      "basketNumber": "0000-1111-2222-3333",
      "userName": "YOUR_USERNAME"
    },
    "clientFirm": "YOUR_CLIENT_FIRM",
    "timestamp": "2025-01-01 12:00:00.000000"
  }
}

Query Parameter​

Parameter Name: tickerbasket

Format: HexLong (supports both 1 and 0000-0000-0000-0001 formats)

Usage: Add to any getmsgs or getcount query

Examples:

GET /rest/json?cmd=getmsgs&msgtype=StockBookQuote&tickerbasket=1
GET /rest/json?cmd=getmsgs&msgtype=OptionNbboQuote&tickerbasket=1&l=5000
GET /rest/json?cmd=getcount&msgtype=LiveImpliedQuote&tickerbasket=0000-0000-0000-0001

Supported Message Types​

TickerBasket filtering works with message types that have one of the following key types in their schema (primary key OR body fields):

  • TickerKey in Primary Key: Messages like StockBookQuote, StockPrint
  • OptionKey in Primary Key: Messages like OptionNbboQuote, LiveImpliedQuote
  • ExpiryKey in Primary Key: Messages like LiveSurfaceCurve

Features​

  • Performance Optimization: Faster query performance compared to WHERE clause filtering, especially for queries involving multiple tickers
  • Scalability: Support for baskets ranging from 10 to 200+ tickers
  • Flexible Querying: Use basket number as a single parameter instead of complex WHERE clauses
  • Named Baskets: Organize tickers into logical groups with unique basket numbers
  • Combined Filtering: Can be combined with other query parameters like where, limit, etc.

Error Handling​

The server returns specific error messages for common issues:

  • Basket Not Found: TickerBasket: basket {basketNumber} not found for user {userName}
  • Empty Basket: TickerBasket: basket {basketNumber} is empty
  • Unsupported Message Type: TickerBasket: message type {messageType} does not support ticker basket filtering
  • Invalid Format: invld param: tickerbasket ({value})

Best Practices​

  1. Basket Size: Keep baskets to a reasonable size (10-200 tickers) for optimal performance
  2. Combining Filters: TickerBasket works well with other filters, but complex WHERE clauses may negate performance benefits

Example Use Cases​

Example 1: Equity Quote Basket​

# Define basket with 3 equity tickers
POST /rest/json?cmd=postmsgs&postaction=I
[Multiple TickerItemDef messages with basketNumber=1]

# Query all quotes for basket
GET /rest/json?cmd=getmsgs&msgtype=StockBookQuote&tickerbasket=1

Example 2: Option Quote Basket​

# Define basket with option underliers (Ticker)
POST /rest/json?cmd=postmsgs&postaction=I
[Multiple TickerItemDef messages with basketNumber=2]

# Query all option quotes for basket
GET /rest/json?cmd=getmsgs&msgtype=OptionNbboQuote&tickerbasket=2&l=5000

Example 3: Combined with WHERE Clause​

# Query options in basket with additional filtering
GET /rest/json?cmd=getmsgs&msgtype=OptionNbboQuote&tickerbasket=1&where=okey.tk:eq:2025-01-17