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       Takes two regexes and a snippet of code. Creates an aggregator that
       creates a map. Keys in the map correspond to pairs of fields chosen by
       matching the regexes against the fields from input records. Values in the
       map are produced by aggregators which the snippet must act as a factory
       for ($f1 is the first field, $f2 is the second field).
 
       Example(s):
          To find the covariance of all x-named fields with all y-named fields:
             for_field(qr/^x/, qr/^y/, <<covar($f1, $f2)>>)
 
    map_reduce_agg(<snippet>, <snippet>[, <snippet>])
    map_reduce_aggregator(<snippet>, <snippet>[, <snippet>])
    mr_agg(<snippet>, <snippet>[, <snippet>])
    mr_aggregator(<snippet>, <snippet>[, <snippet>])
       Take a map snippet, a reduce snippet, and an optional squish snippet to
       produce an ad-hoc aggregator based on map reduce. The map snippet takes $r
       representing a record and returns its mapped value. The reduce snippet
       takes $a and $b representing two mapped values and combines them. Finally,
       the squish snippet takes a mapped value $a representing all the records
       and produces the final answer for the aggregator.
 
       Example(s):
          Track count and sum to produce average:
             mr_agg(<<[1, {{ct}}]>>, <<[$a->[0] + $b->[0], $a->[1] + $b->[1]]>>, <<$a->[1] / $a->[0]>>)
 
    rec()
    record()
       A valuation that just returns the entire record.
 
    snip(snip)
       Takes a snippet and returns both the snippet and the snippet as a
       valuation. Used to distinguished snippets from scalars in cases where it
       matters, e.g. min('{{x}}') interprets it is a keyspec when it was meant to
       be a snippet (and then a valuation), min(snip('{{x}}')) does what is
       intended. This is used internally by <<...>> and in fact <<...>> just
       translates to snip('...').
 
    subset_agg(<snippet>, <aggregator>)
    subset_aggregator(<snippet>, <aggregator>)
       Takes a snippate to act as a record predicate and an aggregator and
       produces an aggregator that acts as the provided aggregator as run on the
       filtered view.
 
       Example(s):
           An aggregator that counts the number of records with a time not above 6 seconds:
              subset_agg(<<{{time_ms}} <= 6000>>, ct())
 
    type_agg(obj)
    type_scalar(obj)
    type_val(obj)
       Force the object into a specific type. Can be used to force certain
       upconversions (or avoid them).
 
    valuation(sub { ... })
    val(sub { ... })
       Takes a subref, creates a valuation that represents it. The subref will
       get the record as its first and only argument.
 
       Example(s):
          To get the square of the "x" field:
             val(sub{ $[0]->{x} ** 2 })
 
    xform(<aggregator>, <snippet>)
       Takes an aggregator and a snippet and produces an aggregator the
       represents invoking the snippet on the aggregator's result.
 
       Example(s):
          To take the difference between the first and second time fields of the record collection:
             xform(recs(), <<{{1/time}} - {{0/time}}>>)
 

=head1 SEE ALSO

=over

=item * See L<App::RecordStream> for an overview of the scripts and the system

=item * Run C<recs examples> or see L<App::RecordStream::Manual::Examples> for a set of simple recs examples

=item * Run C<recs story> or see L<App::RecordStream::Manual::Story> for a humorous introduction to RecordStream

=item * Every command has a C<--help> mode available to print out usage and
examples for the particular command, just like the output above.

=back