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This feature has been a thorn in our sides for a long time, causing many grammatical ambiguity problems. It doesn't seem worth the pain to continue to support it, so remove it. There are some follow-on improvements we can make in the grammar, but this commit only removes the bare minimum number of productions, plus assorted backend support code. Note that pg_dump and psql continue to have full support, since they may be used against older servers. However, pg_dump warns about postfix operators. There is also a check in pg_upgrade. Documentation-wise, I (tgl) largely removed the "left unary" terminology in favor of saying "prefix operator", which is a more standard and IMO less confusing term. I included a catversion bump, although no initial catalog data changes here, to mark the boundary at which oprkind = 'r' stopped being valid in pg_operator. Mark Dilger, based on work by myself and Robert Haas; review by John Naylor Discussion: https://postgr.es/m/38ca86db-42ab-9b48-2902-337a0d6b8311@2ndquadrant.com
487 lines
22 KiB
Plaintext
487 lines
22 KiB
Plaintext
<!-- doc/src/sgml/xoper.sgml -->
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<sect1 id="xoper">
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<title>User-Defined Operators</title>
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<indexterm zone="xoper">
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<primary>operator</primary>
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<secondary>user-defined</secondary>
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</indexterm>
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<para>
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Every operator is <quote>syntactic sugar</quote> for a call to an
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underlying function that does the real work; so you must
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first create the underlying function before you can create
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the operator. However, an operator is <emphasis>not merely</emphasis>
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syntactic sugar, because it carries additional information
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that helps the query planner optimize queries that use the
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operator. The next section will be devoted to explaining
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that additional information.
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</para>
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<para>
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<productname>PostgreSQL</productname> supports prefix
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and infix operators. Operators can be
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overloaded;<indexterm><primary>overloading</primary><secondary>operators</secondary></indexterm>
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that is, the same operator name can be used for different operators
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that have different numbers and types of operands. When a query is
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executed, the system determines the operator to call from the
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number and types of the provided operands.
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</para>
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<para>
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Here is an example of creating an operator for adding two complex
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numbers. We assume we've already created the definition of type
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<type>complex</type> (see <xref linkend="xtypes"/>). First we need a
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function that does the work, then we can define the operator:
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<programlisting>
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CREATE FUNCTION complex_add(complex, complex)
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RETURNS complex
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AS '<replaceable>filename</replaceable>', 'complex_add'
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LANGUAGE C IMMUTABLE STRICT;
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CREATE OPERATOR + (
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leftarg = complex,
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rightarg = complex,
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function = complex_add,
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commutator = +
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);
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</programlisting>
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</para>
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<para>
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Now we could execute a query like this:
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<screen>
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SELECT (a + b) AS c FROM test_complex;
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c
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-----------------
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(5.2,6.05)
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(133.42,144.95)
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</screen>
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</para>
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<para>
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We've shown how to create a binary operator here. To create a prefix
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operator, just omit the <literal>leftarg</literal>.
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The <literal>function</literal>
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clause and the argument clauses are the only required items in
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<command>CREATE OPERATOR</command>. The <literal>commutator</literal>
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clause shown in the example is an optional hint to the query
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optimizer. Further details about <literal>commutator</literal> and other
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optimizer hints appear in the next section.
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</para>
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</sect1>
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<sect1 id="xoper-optimization">
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<title>Operator Optimization Information</title>
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<indexterm zone="xoper-optimization">
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<primary>optimization information</primary>
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<secondary>for operators</secondary>
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</indexterm>
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<para>
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A <productname>PostgreSQL</productname> operator definition can include
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several optional clauses that tell the system useful things about how
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the operator behaves. These clauses should be provided whenever
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appropriate, because they can make for considerable speedups in execution
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of queries that use the operator. But if you provide them, you must be
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sure that they are right! Incorrect use of an optimization clause can
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result in slow queries, subtly wrong output, or other Bad Things.
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You can always leave out an optimization clause if you are not sure
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about it; the only consequence is that queries might run slower than
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they need to.
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</para>
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<para>
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Additional optimization clauses might be added in future versions of
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<productname>PostgreSQL</productname>. The ones described here are all
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the ones that release &version; understands.
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</para>
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<para>
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It is also possible to attach a planner support function to the function
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that underlies an operator, providing another way of telling the system
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about the behavior of the operator.
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See <xref linkend="xfunc-optimization"/> for more information.
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</para>
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<sect2>
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<title><literal>COMMUTATOR</literal></title>
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<para>
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The <literal>COMMUTATOR</literal> clause, if provided, names an operator that is the
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commutator of the operator being defined. We say that operator A is the
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commutator of operator B if (x A y) equals (y B x) for all possible input
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values x, y. Notice that B is also the commutator of A. For example,
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operators <literal><</literal> and <literal>></literal> for a particular data type are usually each others'
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commutators, and operator <literal>+</literal> is usually commutative with itself.
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But operator <literal>-</literal> is usually not commutative with anything.
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</para>
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<para>
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The left operand type of a commutable operator is the same as the
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right operand type of its commutator, and vice versa. So the name of
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the commutator operator is all that <productname>PostgreSQL</productname>
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needs to be given to look up the commutator, and that's all that needs to
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be provided in the <literal>COMMUTATOR</literal> clause.
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</para>
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<para>
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It's critical to provide commutator information for operators that
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will be used in indexes and join clauses, because this allows the
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query optimizer to <quote>flip around</quote> such a clause to the forms
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needed for different plan types. For example, consider a query with
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a WHERE clause like <literal>tab1.x = tab2.y</literal>, where <literal>tab1.x</literal>
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and <literal>tab2.y</literal> are of a user-defined type, and suppose that
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<literal>tab2.y</literal> is indexed. The optimizer cannot generate an
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index scan unless it can determine how to flip the clause around to
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<literal>tab2.y = tab1.x</literal>, because the index-scan machinery expects
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to see the indexed column on the left of the operator it is given.
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<productname>PostgreSQL</productname> will <emphasis>not</emphasis> simply
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assume that this is a valid transformation — the creator of the
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<literal>=</literal> operator must specify that it is valid, by marking the
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operator with commutator information.
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</para>
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<para>
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When you are defining a self-commutative operator, you just do it.
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When you are defining a pair of commutative operators, things are
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a little trickier: how can the first one to be defined refer to the
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other one, which you haven't defined yet? There are two solutions
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to this problem:
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<itemizedlist>
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<listitem>
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<para>
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One way is to omit the <literal>COMMUTATOR</literal> clause in the first operator that
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you define, and then provide one in the second operator's definition.
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Since <productname>PostgreSQL</productname> knows that commutative
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operators come in pairs, when it sees the second definition it will
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automatically go back and fill in the missing <literal>COMMUTATOR</literal> clause in
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the first definition.
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</para>
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</listitem>
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<listitem>
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<para>
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The other, more straightforward way is just to include <literal>COMMUTATOR</literal> clauses
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in both definitions. When <productname>PostgreSQL</productname> processes
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the first definition and realizes that <literal>COMMUTATOR</literal> refers to a nonexistent
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operator, the system will make a dummy entry for that operator in the
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system catalog. This dummy entry will have valid data only
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for the operator name, left and right operand types, and result type,
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since that's all that <productname>PostgreSQL</productname> can deduce
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at this point. The first operator's catalog entry will link to this
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dummy entry. Later, when you define the second operator, the system
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updates the dummy entry with the additional information from the second
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definition. If you try to use the dummy operator before it's been filled
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in, you'll just get an error message.
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</para>
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</listitem>
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</itemizedlist>
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</para>
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</sect2>
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<sect2>
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<title><literal>NEGATOR</literal></title>
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<para>
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The <literal>NEGATOR</literal> clause, if provided, names an operator that is the
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negator of the operator being defined. We say that operator A
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is the negator of operator B if both return Boolean results and
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(x A y) equals NOT (x B y) for all possible inputs x, y.
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Notice that B is also the negator of A.
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For example, <literal><</literal> and <literal>>=</literal> are a negator pair for most data types.
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An operator can never validly be its own negator.
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</para>
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<para>
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Unlike commutators, a pair of unary operators could validly be marked
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as each other's negators; that would mean (A x) equals NOT (B x)
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for all x.
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</para>
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<para>
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An operator's negator must have the same left and/or right operand types
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as the operator to be defined, so just as with <literal>COMMUTATOR</literal>, only the operator
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name need be given in the <literal>NEGATOR</literal> clause.
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</para>
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<para>
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Providing a negator is very helpful to the query optimizer since
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it allows expressions like <literal>NOT (x = y)</literal> to be simplified into
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<literal>x <> y</literal>. This comes up more often than you might think, because
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<literal>NOT</literal> operations can be inserted as a consequence of other rearrangements.
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</para>
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<para>
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Pairs of negator operators can be defined using the same methods
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explained above for commutator pairs.
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</para>
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</sect2>
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<sect2>
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<title><literal>RESTRICT</literal></title>
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<para>
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The <literal>RESTRICT</literal> clause, if provided, names a restriction selectivity
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estimation function for the operator. (Note that this is a function
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name, not an operator name.) <literal>RESTRICT</literal> clauses only make sense for
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binary operators that return <type>boolean</type>. The idea behind a restriction
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selectivity estimator is to guess what fraction of the rows in a
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table will satisfy a <literal>WHERE</literal>-clause condition of the form:
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<programlisting>
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column OP constant
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</programlisting>
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for the current operator and a particular constant value.
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This assists the optimizer by
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giving it some idea of how many rows will be eliminated by <literal>WHERE</literal>
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clauses that have this form. (What happens if the constant is on
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the left, you might be wondering? Well, that's one of the things that
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<literal>COMMUTATOR</literal> is for...)
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</para>
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<para>
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Writing new restriction selectivity estimation functions is far beyond
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the scope of this chapter, but fortunately you can usually just use
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one of the system's standard estimators for many of your own operators.
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These are the standard restriction estimators:
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<simplelist>
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<member><function>eqsel</function> for <literal>=</literal></member>
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<member><function>neqsel</function> for <literal><></literal></member>
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<member><function>scalarltsel</function> for <literal><</literal></member>
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<member><function>scalarlesel</function> for <literal><=</literal></member>
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<member><function>scalargtsel</function> for <literal>></literal></member>
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<member><function>scalargesel</function> for <literal>>=</literal></member>
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</simplelist>
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</para>
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<para>
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You can frequently get away with using either <function>eqsel</function> or <function>neqsel</function> for
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operators that have very high or very low selectivity, even if they
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aren't really equality or inequality. For example, the
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approximate-equality geometric operators use <function>eqsel</function> on the assumption that
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they'll usually only match a small fraction of the entries in a table.
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</para>
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<para>
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You can use <function>scalarltsel</function>, <function>scalarlesel</function>,
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<function>scalargtsel</function> and <function>scalargesel</function> for comparisons on
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data types that have some sensible means of being converted into numeric
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scalars for range comparisons. If possible, add the data type to those
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understood by the function <function>convert_to_scalar()</function> in
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<filename>src/backend/utils/adt/selfuncs.c</filename>.
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(Eventually, this function should be replaced by per-data-type functions
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identified through a column of the <classname>pg_type</classname> system catalog; but that hasn't happened
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yet.) If you do not do this, things will still work, but the optimizer's
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estimates won't be as good as they could be.
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</para>
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<para>
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Another useful built-in selectivity estimation function
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is <function>matchingsel</function>, which will work for almost any
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binary operator, if standard MCV and/or histogram statistics are
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collected for the input data type(s). Its default estimate is set to
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twice the default estimate used in <function>eqsel</function>, making
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it most suitable for comparison operators that are somewhat less
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strict than equality. (Or you could call the
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underlying <function>generic_restriction_selectivity</function>
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function, providing a different default estimate.)
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</para>
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<para>
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There are additional selectivity estimation functions designed for geometric
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operators in <filename>src/backend/utils/adt/geo_selfuncs.c</filename>: <function>areasel</function>, <function>positionsel</function>,
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and <function>contsel</function>. At this writing these are just stubs, but you might want
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to use them (or even better, improve them) anyway.
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</para>
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</sect2>
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<sect2>
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<title><literal>JOIN</literal></title>
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<para>
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The <literal>JOIN</literal> clause, if provided, names a join selectivity
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estimation function for the operator. (Note that this is a function
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name, not an operator name.) <literal>JOIN</literal> clauses only make sense for
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binary operators that return <type>boolean</type>. The idea behind a join
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selectivity estimator is to guess what fraction of the rows in a
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pair of tables will satisfy a <literal>WHERE</literal>-clause condition of the form:
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<programlisting>
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table1.column1 OP table2.column2
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</programlisting>
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for the current operator. As with the <literal>RESTRICT</literal> clause, this helps
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the optimizer very substantially by letting it figure out which
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of several possible join sequences is likely to take the least work.
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</para>
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<para>
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As before, this chapter will make no attempt to explain how to write
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a join selectivity estimator function, but will just suggest that
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you use one of the standard estimators if one is applicable:
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<simplelist>
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<member><function>eqjoinsel</function> for <literal>=</literal></member>
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<member><function>neqjoinsel</function> for <literal><></literal></member>
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<member><function>scalarltjoinsel</function> for <literal><</literal></member>
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<member><function>scalarlejoinsel</function> for <literal><=</literal></member>
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<member><function>scalargtjoinsel</function> for <literal>></literal></member>
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<member><function>scalargejoinsel</function> for <literal>>=</literal></member>
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<member><function>matchingjoinsel</function> for generic matching operators</member>
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<member><function>areajoinsel</function> for 2D area-based comparisons</member>
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<member><function>positionjoinsel</function> for 2D position-based comparisons</member>
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<member><function>contjoinsel</function> for 2D containment-based comparisons</member>
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</simplelist>
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</para>
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</sect2>
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<sect2>
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<title><literal>HASHES</literal></title>
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<para>
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The <literal>HASHES</literal> clause, if present, tells the system that
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it is permissible to use the hash join method for a join based on this
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operator. <literal>HASHES</literal> only makes sense for a binary operator that
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returns <literal>boolean</literal>, and in practice the operator must represent
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equality for some data type or pair of data types.
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</para>
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<para>
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The assumption underlying hash join is that the join operator can
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only return true for pairs of left and right values that hash to the
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same hash code. If two values get put in different hash buckets, the
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join will never compare them at all, implicitly assuming that the
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result of the join operator must be false. So it never makes sense
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to specify <literal>HASHES</literal> for operators that do not represent
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some form of equality. In most cases it is only practical to support
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hashing for operators that take the same data type on both sides.
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However, sometimes it is possible to design compatible hash functions
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for two or more data types; that is, functions that will generate the
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same hash codes for <quote>equal</quote> values, even though the values
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have different representations. For example, it's fairly simple
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to arrange this property when hashing integers of different widths.
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</para>
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<para>
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To be marked <literal>HASHES</literal>, the join operator must appear
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in a hash index operator family. This is not enforced when you create
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the operator, since of course the referencing operator family couldn't
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exist yet. But attempts to use the operator in hash joins will fail
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at run time if no such operator family exists. The system needs the
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operator family to find the data-type-specific hash function(s) for the
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operator's input data type(s). Of course, you must also create suitable
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hash functions before you can create the operator family.
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</para>
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<para>
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Care should be exercised when preparing a hash function, because there
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are machine-dependent ways in which it might fail to do the right thing.
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For example, if your data type is a structure in which there might be
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uninteresting pad bits, you cannot simply pass the whole structure to
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<function>hash_any</function>. (Unless you write your other operators and
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functions to ensure that the unused bits are always zero, which is the
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recommended strategy.)
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Another example is that on machines that meet the <acronym>IEEE</acronym>
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floating-point standard, negative zero and positive zero are different
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values (different bit patterns) but they are defined to compare equal.
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If a float value might contain negative zero then extra steps are needed
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to ensure it generates the same hash value as positive zero.
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</para>
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<para>
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A hash-joinable operator must have a commutator (itself if the two
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operand data types are the same, or a related equality operator
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if they are different) that appears in the same operator family.
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If this is not the case, planner errors might occur when the operator
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is used. Also, it is a good idea (but not strictly required) for
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a hash operator family that supports multiple data types to provide
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equality operators for every combination of the data types; this
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allows better optimization.
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</para>
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<note>
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<para>
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The function underlying a hash-joinable operator must be marked
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immutable or stable. If it is volatile, the system will never
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attempt to use the operator for a hash join.
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</para>
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</note>
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<note>
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<para>
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If a hash-joinable operator has an underlying function that is marked
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strict, the
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function must also be complete: that is, it should return true or
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false, never null, for any two nonnull inputs. If this rule is
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not followed, hash-optimization of <literal>IN</literal> operations might
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generate wrong results. (Specifically, <literal>IN</literal> might return
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false where the correct answer according to the standard would be null;
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or it might yield an error complaining that it wasn't prepared for a
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null result.)
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</para>
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</note>
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</sect2>
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<sect2>
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<title><literal>MERGES</literal></title>
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<para>
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The <literal>MERGES</literal> clause, if present, tells the system that
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it is permissible to use the merge-join method for a join based on this
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operator. <literal>MERGES</literal> only makes sense for a binary operator that
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returns <literal>boolean</literal>, and in practice the operator must represent
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equality for some data type or pair of data types.
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</para>
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<para>
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Merge join is based on the idea of sorting the left- and right-hand tables
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into order and then scanning them in parallel. So, both data types must
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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
|
|
<quote>same place</quote>
|
|
in the sort order. In practice this means that the join operator must
|
|
behave like equality. But it is possible to merge-join two
|
|
distinct data types so long as they are logically compatible. For
|
|
example, the <type>smallint</type>-versus-<type>integer</type>
|
|
equality operator is merge-joinable.
|
|
We only need sorting operators that will bring both data types into a
|
|
logically compatible sequence.
|
|
</para>
|
|
|
|
<para>
|
|
To be marked <literal>MERGES</literal>, the join operator must appear
|
|
as an equality member of a <literal>btree</literal> index operator family.
|
|
This is not enforced when you create
|
|
the operator, since of course the referencing operator family couldn't
|
|
exist yet. But the operator will not actually be used for merge joins
|
|
unless a matching operator family can be found. The
|
|
<literal>MERGES</literal> flag thus acts as a hint to the planner that
|
|
it's worth looking for a matching operator family.
|
|
</para>
|
|
|
|
<para>
|
|
A merge-joinable operator must have a commutator (itself if the two
|
|
operand data types are the same, or a related equality operator
|
|
if they are different) that appears in the same operator family.
|
|
If this is not the case, planner errors might occur when the operator
|
|
is used. Also, it is a good idea (but not strictly required) for
|
|
a <literal>btree</literal> operator family that supports multiple data types to provide
|
|
equality operators for every combination of the data types; this
|
|
allows better optimization.
|
|
</para>
|
|
|
|
<note>
|
|
<para>
|
|
The function underlying a merge-joinable operator must be marked
|
|
immutable or stable. If it is volatile, the system will never
|
|
attempt to use the operator for a merge join.
|
|
</para>
|
|
</note>
|
|
</sect2>
|
|
</sect1>
|