anchor.diff:  )
   ----
   
  +== drill
  +
  +The `drill` function is designed to support efficient high cardinality aggregation. The `drill`
  +function sends a request to the `export` handler in a specific collection which includes a Streaming
  +Expression that the `export` handler applies to the sorted result set. The `export` handler then emits the aggregated tuples.
  +The `drill` function reads and emits the aggregated tuples fromn each shard maintaining the sort order,
  +but does not merge the aggregations. Streaming Expression functions can be wrapped around the `drill` function to
  +merge the aggregates.
  +
  +=== drill Parameters
  +
  +* `collection`: (Mandatory) the collection being searched.
  +* `q`: (Mandatory) The query to perform on the Solr index.
  +* `fl`: (Mandatory) The list of fields to return.
  +* `sort`: (Mandatory) The sort criteria.
  +* `expr`: The streaming expression that is sent to the export handler that operates over the sorted
  +result set. The `input()` function provides the stream of sorted tuples from the export handler (see examples below).
  +
  +=== drill Syntax
  +
  +Example 1: Basic drill syntax
  +
  +[source,text]
  +----
  +drill(articles,
  +      q="abstract:water",
  +      fl="author",
  +      sort="author asc",
  +      rollup(input(), over="author", count(*)))
  +----
  +
  +Example 2: A `rollup` wrapped around the `drill` function to sum the counts emitted from each shard.
  +
  +[source,text]
  +----
  +rollup(drill(articles,
  +             q="abstract:water",
  +             fl="author",
  +             sort="author asc",
  +             rollup(input(), over="author", count(*))),
  +       over="author",
  +       sum(count(*)))
  +----
  +
   == echo
   
   The `echo` function returns a single Tuple echoing its text parameter. `Echo` is the simplest stream source designed to provide text
  
positive.code:            max(a_f),
             avg(a_i),
             avg(a_f),
             count(*))
  ----
  
  
negative.code:       max(a_f),
        avg(a_i),
        avg(a_f),
        per(a_f, 50),
        per(a_f, 75),
        count(*))
  ----
  
  