To run these examples
- Log into Github
- press
.(the period key) to run vscode - Install the Malloy Extension when prompted (or manually)
Malloy natively understands how to work with tables that have nested structs and arrays (including raw JSON) and makes easy to query and transform.
Take list of individual flights and map/reduce into individual aircraft sessions per day. Display their routes for each day on a map. Classic Map/Reduce.
When drawing an histogram, you need to figure out a proper bin size to group the data. This pattern dyamically computes bin sizing. The binning automatically adusts with in filtered and nesting situations.
Sometime data comes in with duplicates. We can base a query on a SQL Query to remove duplicates
Using DuckDB wwe can query from Web API endpoints. This example pulls from the github and runs some transformation queries against the results
Malloy has a special 'index' operator that produces a result that contains all the dimensional values in a graph weighed by whatever measure you think is important. The index can be built by reading the whole graph or sampling a subset of records. The index is useful in suggesting filters and for basic understanding of a data set and perhaps informing an LLM.