Postgres supports left unary, right unary and binary operators. Operators can be overloaded; that is, the same operator name can be used for different operators that have different numbers and types of arguments. If there is an ambiguous situation and the system cannot determine the correct operator to use, it will return an error. You may have to typecast the left and/or right operands to help it understand which operator you meant to use.
Every operator is "syntactic sugar" for a call to an underlying function that does the real work; so you must first create the underlying function before you can create the operator. However, an operator is not merely syntactic sugar, because it carries additional information that helps the query planner optimize queries that use the operator. Much of this chapter will be devoted to explaining that additional information.
Here is an example of creating an operator for adding two complex numbers. We assume we've already created the definition of type complex. First we need a function that does the work; then we can define the operator:
CREATE FUNCTION complex_add(complex, complex)
RETURNS complex
AS '$PWD/obj/complex.so'
LANGUAGE 'c';
CREATE OPERATOR + (
leftarg = complex,
rightarg = complex,
procedure = complex_add,
commutator = +
);
Now we can do:
SELECT (a + b) AS c FROM test_complex; +----------------+ |c | +----------------+ |(5.2,6.05) | +----------------+ |(133.42,144.95) | +----------------+
We've shown how to create a binary operator here. To create unary operators, just omit one of leftarg (for left unary) or rightarg (for right unary). The procedure clause and the argument clauses are the only required items in CREATE OPERATOR. The COMMUTATOR clause shown in the example is an optional hint to the query optimizer. Further details about COMMUTATOR and other optimizer hints appear below.
Author: Written by Tom Lane.
A Postgres operator definition can include several optional clauses that tell the system useful things about how the operator behaves. These clauses should be provided whenever appropriate, because they can make for considerable speedups in execution of queries that use the operator. But if you provide them, you must be sure that they are right! Incorrect use of an optimization clause can result in backend crashes, subtly wrong output, or other Bad Things. You can always leave out an optimization clause if you are not sure about it; the only consequence is that queries might run slower than they need to.
Additional optimization clauses might be added in future versions of Postgres. The ones described here are all the ones that release 6.5 understands.
The COMMUTATOR clause, if provided, names an operator that is the commutator of the operator being defined. We say that operator A is the commutator of operator B if (x A y) equals (y B x) for all possible input values x,y. Notice that B is also the commutator of A. For example, operators '<' and '>' for a particular datatype are usually each others' commutators, and operator '+' is usually commutative with itself. But operator '-' is usually not commutative with anything.
The left argument type of a commuted operator is the same as the right argument type of its commutator, and vice versa. So the name of the commutator operator is all that Postgres needs to be given to look up the commutator, and that's all that need be provided in the COMMUTATOR clause.
When you are defining a self-commutative operator, you just do it. When you are defining a pair of commutative operators, things are a little trickier: how can the first one to be defined refer to the other one, which you haven't defined yet? There are two solutions to this problem:
One way is to omit the COMMUTATOR clause in the first operator that you define, and then provide one in the second operator's definition. Since Postgres knows that commutative operators come in pairs, when it sees the second definition it will automatically go back and fill in the missing COMMUTATOR clause in the first definition.
The other, more straightforward way is just to include COMMUTATOR clauses in both definitions. When Postgres processes the first definition and realizes that COMMUTATOR refers to a non-existent operator, the system will make a dummy entry for that operator in the system's pg_operator table. This dummy entry will have valid data only for the operator name, left and right argument types, and result type, since that's all that Postgres can deduce at this point. The first operator's catalog entry will link to this dummy entry. Later, when you define the second operator, the system updates the dummy entry with the additional information from the second definition. If you try to use the dummy operator before it's been filled in, you'll just get an error message. (Note: this procedure did not work reliably in Postgres versions before 6.5, but it is now the recommended way to do things.)
The NEGATOR clause, if provided, names an operator that is the negator of the operator being defined. We say that operator A is the negator of operator B if both return boolean results and (x A y) equals NOT (x B y) for all possible inputs x,y. Notice that B is also the negator of A. For example, '<' and '>=' are a negator pair for most datatypes. An operator can never be validly be its own negator.
Unlike COMMUTATOR, a pair of unary operators could validly be marked as each others' negators; that would mean (A x) equals NOT (B x) for all x, or the equivalent for right-unary operators.
An operator's negator must have the same left and/or right argument types as the operator itself, so just as with COMMUTATOR, only the operator name need be given in the NEGATOR clause.
Providing NEGATOR is very helpful to the query optimizer since it allows expressions like NOT (x = y) to be simplified into x <> y. This comes up more often than you might think, because NOTs can be inserted as a consequence of other rearrangements.
Pairs of negator operators can be defined using the same methods explained above for commutator pairs.
The RESTRICT clause, if provided, names a restriction selectivity estimation function for the operator (note that this is a function name, not an operator name). RESTRICT clauses only make sense for binary operators that return boolean. The idea behind a restriction selectivity estimator is to guess what fraction of the rows in a table will satisfy a WHERE-clause condition of the form
field OP constant
for the current operator and a particular constant value.
This assists the optimizer by giving it some idea of how many rows
will be eliminated by WHERE clauses that have this form. (What
happens if the constant is on the left, you may be wondering? Well,
that's one of the things that COMMUTATOR is for...)
Writing new restriction selectivity estimation functions is far beyond the scope of this chapter, but fortunately you can usually just use one of the system's standard estimators for many of your own operators. These are the standard restriction estimators:
eqsel for =
neqsel for <>
scalarltsel for < or <=
scalargtsel for > or >=
It might seem a little odd that these are the categories, but
they make sense if you think about it. '=' will typically accept
only a small fraction of the rows in a table; '<>' will
typically reject only a small fraction. '<' will accept a
fraction that depends on where the given constant falls in the
range of values for that table column (which, it just so happens,
is information collected by VACUUM ANALYZE and made available to
the selectivity estimator). '<=' will accept a slightly larger
fraction than '<' for the same comparison constant, but they're
close enough to not be worth distinguishing, especially since we're
not likely to do better than a rough guess anyhow. Similar remarks
apply to '>' and '>='.
You can frequently get away with using either eqsel or neqsel for operators that have very high or very low selectivity, even if they aren't really equality or inequality. For example, the approximate-equality geometric operators use eqsel on the assumption that they'll usually only match a small fraction of the entries in a table.
You can use scalarltsel and scalargtsel for comparisons on datatypes that have some sensible means of being converted into numeric scalars for range comparisons. If possible, add the datatype to those understood by the routine convert_to_scalar() in src/backend/utils/adt/selfuncs.c. (Eventually, this routine should be replaced by per-datatype functions identified through a column of the pg_type table; but that hasn't happened yet.) If you do not do this, things will still work, but the optimizer's estimates won't be as good as they could be.
There are additional selectivity functions designed for geometric operators in src/backend/utils/adt/geo_selfuncs.c: areasel, positionsel, and contsel. At this writing these are just stubs, but you may want to use them (or even better, improve them) anyway.
The JOIN clause, if provided, names a join selectivity estimation function for the operator (note that this is a function name, not an operator name). JOIN clauses only make sense for binary operators that return boolean. The idea behind a join selectivity estimator is to guess what fraction of the rows in a pair of tables will satisfy a WHERE-clause condition of the form
table1.field1 OP table2.field2
for the current operator. As with the RESTRICT clause, this
helps the optimizer very substantially by letting it figure out
which of several possible join sequences is likely to take the
least work.
As before, this chapter will make no attempt to explain how to write a join selectivity estimator function, but will just suggest that you use one of the standard estimators if one is applicable:
eqjoinsel for =
neqjoinsel for <>
scalarltjoinsel for < or <=
scalargtjoinsel for > or >=
areajoinsel for 2D area-based comparisons
positionjoinsel for 2D position-based comparisons
contjoinsel for 2D containment-based comparisons
The HASHES clause, if present, tells the system that it is OK to use the hash join method for a join based on this operator. HASHES only makes sense for binary operators that return boolean, and in practice the operator had better be equality for some data type.
The assumption underlying hash join is that the join operator can only return TRUE for pairs of left and right values that hash to the same hash code. If two values get put in different hash buckets, the join will never compare them at all, implicitly assuming that the result of the join operator must be FALSE. So it never makes sense to specify HASHES for operators that do not represent equality.
In fact, logical equality is not good enough either; the operator had better represent pure bitwise equality, because the hash function will be computed on the memory representation of the values regardless of what the bits mean. For example, equality of time intervals is not bitwise equality; the interval equality operator considers two time intervals equal if they have the same duration, whether or not their endpoints are identical. What this means is that a join using "=" between interval fields would yield different results if implemented as a hash join than if implemented another way, because a large fraction of the pairs that should match will hash to different values and will never be compared by the hash join. But if the optimizer chose to use a different kind of join, all the pairs that the equality operator says are equal will be found. We don't want that kind of inconsistency, so we don't mark interval equality as hashable.
There are also machine-dependent ways in which a hash join might fail to do the right thing. For example, if your datatype is a structure in which there may be uninteresting pad bits, it's unsafe to mark the equality operator HASHES. (Unless, perhaps, you write your other operators to ensure that the unused bits are always zero.) Another example is that the FLOAT datatypes are unsafe for hash joins. On machines that meet the IEEE floating point standard, minus zero and plus zero are different values (different bit patterns) but they are defined to compare equal. So, if float equality were marked HASHES, a minus zero and a plus zero would probably not be matched up by a hash join, but they would be matched up by any other join process.
The bottom line is that you should probably only use HASHES for equality operators that are (or could be) implemented by memcmp().
The SORT clauses, if present, tell the system that it is permissible to use the merge join method for a join based on the current operator. Both must be specified if either is. The current operator must be equality for some pair of data types, and the SORT1 and SORT2 clauses name the ordering operator ('<' operator) for the left and right-side data types respectively.
Merge join is based on the idea of sorting the left and righthand tables into order and then scanning them in parallel. So, both data types must be capable of being fully ordered, and the join operator must be one that can only succeed for pairs of values that fall at the "same place" in the sort order. In practice this means that the join operator must behave like equality. But unlike hashjoin, where the left and right data types had better be the same (or at least bitwise equivalent), it is possible to mergejoin two distinct data types so long as they are logically compatible. For example, the int2-versus-int4 equality operator is mergejoinable. We only need sorting operators that will bring both datatypes into a logically compatible sequence.
When specifying merge sort operators, the current operator and both referenced operators must return boolean; the SORT1 operator must have both input datatypes equal to the current operator's left argument type, and the SORT2 operator must have both input datatypes equal to the current operator's right argument type. (As with COMMUTATOR and NEGATOR, this means that the operator name is sufficient to specify the operator, and the system is able to make dummy operator entries if you happen to define the equality operator before the other ones.)
In practice you should only write SORT clauses for an '=' operator, and the two referenced operators should always be named '<'. Trying to use merge join with operators named anything else will result in hopeless confusion, for reasons we'll see in a moment.
There are additional restrictions on operators that you mark mergejoinable. These restrictions are not currently checked by CREATE OPERATOR, but a merge join may fail at runtime if any are not true:
The mergejoinable equality operator must have a commutator (itself if the two data types are the same, or a related equality operator if they are different).
There must be '<' and '>' ordering operators having the same left and right input datatypes as the mergejoinable operator itself. These operators must be named '<' and '>'; you do not have any choice in the matter, since there is no provision for specifying them explicitly. Note that if the left and right data types are different, neither of these operators is the same as either SORT operator. But they had better order the data values compatibly with the SORT operators, or mergejoin will fail to work.