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    Format, Parameters

    WHERE can keep the rows of data in the data streams that meet the conditions, and discard those that do not meet the conditions.


    • Format 1: where <condition>
    • Format 2: where <query> (Under development)
    • Parameters: see table below
    • Affected columns: all aliases and homologous columns from <condition> and <query>; non-homologous aliases will be trimmed to the shortest length so that they can become homologous columns before calculation
    Name Category Specification Description
    <condition> filter Filter with curly brackets removed Judgement conditions, rows that are judged as TRUE will be kept
    <query> query / Query statement, rows that return results will be kept

    WHERE can seperate some filtering conditions from Ultipa Filter to improve UQL readability; it can also realize subgraph queries as complex as graph() command.


    find().nodes({shape == "square"}) as n1
    find().nodes({shape == "round"}) as n2
    where n1.color == n2.color
    return n1, n2

    In the UQL statement above, WHERE trims the two non-homologous columns outputted from 2 node queries to the shortest length,3 rows, then filter each row

    where <condition>

    Example: find three-step transfer paths from Card CA001 to Card CA002, with two intermediate cards in the paths containing at least one card whose level is 5

    n({_id == "CA001"}).e().n({@card} as n1)
      .e().n({@card} as n2)
      .e().n({_id == "CA002"}) as p
    where n1.level == 5 || n2.level == 5
    return p{*}

    where <query> (Under Development)

    Example: find an intermediate card with alias 'agent' that satisfies conditions as shown in the image below: Card CA002 transfers money to Card CA001 via agent; agent is a neighbor to Card CA003 within 2 hops

    n({_id == "CA002"}).re().n({@card} as agent).re().n({_id == "CA001"})
    where n(agent).e()[*:2].n({_id == "CA003"})
    return agent{*}

    Analysis: WHERE further filters data columns "agent": it judges if the shortest paths from "agent" to Card CA003 exist, if true, then it passes "agent" to later "return"

    The example above can be put in a subgraph template as shown below:

      n({_id == "CA002"}).re().n({@card} as agent).re().n({_id == "CA001"}),
      n(agent).e()[*:2].n({_id == "CA003"})
    return agent{*}
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