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<p>
The logical operators that represent a pig script and tools for manipulating
those operators.  The logical layer contains the logical operators themselves,
as well as validators that check the logical plan, an optimizer, and a general
visitor utility for working with the logical plans.

<h2> Design </h2>
<p>
Logical operators use the operator, plan, visitor, and optimizer framework
provided by the {@link org.apache.pig.impl.plan} package.
<p>
Logical operators consist of both relational and expression operators.
Relational operators work on an entire bag.  Expression operators work on an
element of a tuple (which may also be a bag).  Due to Pig's nested data and
execution model the distinction between relational and expression operators is
not always clear.  And some operators such as LOProject function as both.
<p>
In a traditional data base system, a query execution plan is constructed from
relational operators, such as project, filter, sort, aggregate, join.  Each of
these may contain an expression tree, made up of expression operators.  For
example, consider a SQL query <code>select a from T where a = 5;</code>.  The
where clause would be represented by a filter operator with an expression tree
for <code>a=5</code>.
<p>
Pig takes a similar approach, except that the operators contained inside of a
relational operator may also be relational.  For example, a foreach statement
that has a nested script, such as <code>foreach B { C = distinct $1; generate
group, COUNT(C);}</code>.  This foreach needs to contain not just an
expression tree but the distinct relational operator.  For this reason, Pig's
relational operators do not contain expression trees.  Instead they contain
one or more LogicalPlans themselves.  This allows Pig to arbitrarily nest
the logical plan.  In this sense Pig is more similar to a traditional
procedural language where certain statements (e.g. if, while) can contain any
other statement in the language rather than being like SQL where the statement
execution tends to be more linear.

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