aggro 😡

In memory dataset bucketing and metrics, inspired by Elasticsearch aggregations

Installation

go get -u github.com/snikch/aggro

Example

Given a dataset…

rows := []map[string]interface{}{
        {"location": "Auckland", "department": "Engineering", "salary": 120000, "start_date": "2016-01-31T22:00:00Z"},
        {"location": "Auckland", "department": "Engineering", "salary": 80000, "start_date": "2016-03-23T22:00:00Z"},
        {"location": "Auckland", "department": "Marketing", "salary": 90000, "start_date": "2016-01-31T22:00:00Z"},
        {"location": "Auckland", "department": "Marketing", "salary": 150000, "start_date": "2016-01-23T22:00:00Z"},
        {"location": "Wellington", "department": "Engineering", "salary": 120000, "start_date": "2016-01-23T22:00:00Z"},
        {"location": "Wellington", "department": "Engineering", "salary": 160000, "start_date": "2016-03-23T22:00:00Z"},
        {"location": "Wellington", "department": "Engineering", "salary": 120000, "start_date": "2016-02-02T22:00:00Z"},
    }

Initialize aggro, build aggregations and run…

// Build a dataset that contains a *Table representing your data.
dataset := &Dataset{
    Table: &Table{
        Fields: []Field{
            {"location", "string"},
            {"department", "string"},
            {"salary", "number"},
            {"start_date", "datetime"},
        },
    },
}
// Add our rows to our dataset.
err := dataset.AddRows(rows...)
if err != nil {
    return err
}
// Build our query specifying preferred metrics and bucket composition.
query := &Query{
    Metrics: []Metric{
        {Type: "max", Field: "salary"},
        {Type: "min", Field: "salary"},
    },
    Bucket: &Bucket{
        Field: &Field{
            Name: "location",
            Type: "string",
        },
        Sort: &SortOptions{
            Type: "alphabetical",
        },
        Bucket: &Bucket{
            Field: &Field{
                Name: "department",
                Type: "string",
            },
            Sort: &SortOptions{
                Type: "alphabetical",
            },
        },
    },
}
// Run it.
results, err := dataset.Run(query)
if err != nil {
    return err
}

Find a list of available measurers here