On Fri, Apr 7, 2017 at 01:06:53PM -0400, Tom Lane wrote:
> Bruce Momjian <br...@momjian.us> writes:
> > This change is not on my patch yes but what do you think about changing
> > "regular" and "normal" aggregate designations to "generic"? That seems
> > clearer because the aggregates work in non-window and window contexts.
>
> I don't think "generic" is le mot juste here. What's more generic about
> avg() than about mode(), for instance?
>
> My dictionary says "generic" means "characteristic of a class or group
> of things", which doesn't seem to have anything to do with this.
>
> I actually think "regular" might be a better choice than "normal" for this
> purpose, mainly because somebody looking for statistical aggregates might
> think that "normal" has something to do with normal distributions. So
> maybe we should leave that one group of uses alone and s/normal/regular/
> in section 9.20. But in any case it would help to define the term
> explicitly in both sections.
I don't think adding another defined term in this dense text is going to
help so I just specified "general-purpose and statistical aggregates"
where needed; patch attached.
I didn't touch any mention of "normal" in reference to
pg_aggregate.aggfnoid where normal/"n" has a specific meaning.
--
Bruce Momjian <br...@momjian.us> http://momjian.us
EnterpriseDB http://enterprisedb.com
+ As you are, so once was I. As I am, so you will be. +
+ Ancient Roman grave inscription +
diff --git a/doc/src/sgml/advanced.sgml b/doc/src/sgml/advanced.sgml
new file mode 100644
index 1e45511..7563131
*** a/doc/src/sgml/advanced.sgml
--- b/doc/src/sgml/advanced.sgml
*************** COMMIT;
*** 328,335 ****
A <firstterm>window function</> performs a calculation across a set of
table rows that are somehow related to the current row. This is comparable
to the type of calculation that can be done with an aggregate function.
! But unlike regular aggregate functions, use of a window function does not
! cause rows to become grouped into a single output row — the
rows retain their separate identities. Behind the scenes, the window
function is able to access more than just the current row of the query
result.
--- 328,335 ----
A <firstterm>window function</> performs a calculation across a set of
table rows that are somehow related to the current row. This is comparable
to the type of calculation that can be done with an aggregate function.
! However, window functions do not cause rows to become grouped into a single
! output row like non-window aggregate calls would. Instead, the
rows retain their separate identities. Behind the scenes, the window
function is able to access more than just the current row of the query
result.
*************** SELECT depname, empno, salary, avg(salar
*** 363,382 ****
<structname>empsalary</>, and there is one output row for each row in the
table. The fourth column represents an average taken across all the table
rows that have the same <structfield>depname</> value as the current row.
! (This actually is the same function as the regular <function>avg</>
! aggregate function, but the <literal>OVER</> clause causes it to be
! treated as a window function and computed across an appropriate set of
! rows.)
</para>
<para>
A window function call always contains an <literal>OVER</> clause
directly following the window function's name and argument(s). This is what
! syntactically distinguishes it from a regular function or aggregate
! function. The <literal>OVER</> clause determines exactly how the
rows of the query are split up for processing by the window function.
! The <literal>PARTITION BY</> list within <literal>OVER</> specifies
! dividing the rows into groups, or partitions, that share the same
values of the <literal>PARTITION BY</> expression(s). For each row,
the window function is computed across the rows that fall into the
same partition as the current row.
--- 363,381 ----
<structname>empsalary</>, and there is one output row for each row in the
table. The fourth column represents an average taken across all the table
rows that have the same <structfield>depname</> value as the current row.
! (This actually is the same function as the non-window <function>avg</>
! aggregate, but the <literal>OVER</> clause causes it to be
! treated as a window function and computed across the window frame.)
</para>
<para>
A window function call always contains an <literal>OVER</> clause
directly following the window function's name and argument(s). This is what
! syntactically distinguishes it from a normal function or non-window
! aggregate. The <literal>OVER</> clause determines exactly how the
rows of the query are split up for processing by the window function.
! The <literal>PARTITION BY</> clause within <literal>OVER</>
! divides the rows into groups, or partitions, that share the same
values of the <literal>PARTITION BY</> expression(s). For each row,
the window function is computed across the rows that fall into the
same partition as the current row.
*************** FROM empsalary;
*** 411,418 ****
</screen>
As shown here, the <function>rank</> function produces a numerical rank
! within the current row's partition for each distinct <literal>ORDER BY</>
! value, in the order defined by the <literal>ORDER BY</> clause.
<function>rank</> needs no explicit parameter, because its behavior
is entirely determined by the <literal>OVER</> clause.
</para>
--- 410,417 ----
</screen>
As shown here, the <function>rank</> function produces a numerical rank
! for each distinct <literal>ORDER BY</> value in the current row's
! partition, using the order defined by the <literal>ORDER BY</> clause.
<function>rank</> needs no explicit parameter, because its behavior
is entirely determined by the <literal>OVER</> clause.
</para>
*************** FROM empsalary;
*** 424,443 ****
if any. For example, a row removed because it does not meet the
<literal>WHERE</> condition is not seen by any window function.
A query can contain multiple window functions that slice up the data
! in different ways by means of different <literal>OVER</> clauses, but
they all act on the same collection of rows defined by this virtual table.
</para>
<para>
We already saw that <literal>ORDER BY</> can be omitted if the ordering
of rows is not important. It is also possible to omit <literal>PARTITION
! BY</>, in which case there is just one partition containing all the rows.
</para>
<para>
There is another important concept associated with window functions:
for each row, there is a set of rows within its partition called its
! <firstterm>window frame</>. Many (but not all) window functions act only
on the rows of the window frame, rather than of the whole partition.
By default, if <literal>ORDER BY</> is supplied then the frame consists of
all rows from the start of the partition up through the current row, plus
--- 423,442 ----
if any. For example, a row removed because it does not meet the
<literal>WHERE</> condition is not seen by any window function.
A query can contain multiple window functions that slice up the data
! in different ways using different <literal>OVER</> clauses, but
they all act on the same collection of rows defined by this virtual table.
</para>
<para>
We already saw that <literal>ORDER BY</> can be omitted if the ordering
of rows is not important. It is also possible to omit <literal>PARTITION
! BY</>, in which case there is a single partition containing all rows.
</para>
<para>
There is another important concept associated with window functions:
for each row, there is a set of rows within its partition called its
! <firstterm>window frame</>. Some window functions act only
on the rows of the window frame, rather than of the whole partition.
By default, if <literal>ORDER BY</> is supplied then the frame consists of
all rows from the start of the partition up through the current row, plus
*************** SELECT salary, sum(salary) OVER (ORDER B
*** 515,521 ****
elsewhere, such as in <literal>GROUP BY</>, <literal>HAVING</>
and <literal>WHERE</literal> clauses. This is because they logically
execute after the processing of those clauses. Also, window functions
! execute after regular aggregate functions. This means it is valid to
include an aggregate function call in the arguments of a window function,
but not vice versa.
</para>
--- 514,520 ----
elsewhere, such as in <literal>GROUP BY</>, <literal>HAVING</>
and <literal>WHERE</literal> clauses. This is because they logically
execute after the processing of those clauses. Also, window functions
! execute after non-window aggregate functions. This means it is valid to
include an aggregate function call in the arguments of a window function,
but not vice versa.
</para>
diff --git a/doc/src/sgml/func.sgml b/doc/src/sgml/func.sgml
new file mode 100644
index 6d7c7b8..adab303
*** a/doc/src/sgml/func.sgml
--- b/doc/src/sgml/func.sgml
*************** NULL baz</literallayout>(3 rows)</entry>
*** 13166,13178 ****
<para>
<firstterm>Aggregate functions</firstterm> compute a single result
! from a set of input values. The built-in normal aggregate functions
! are listed in
! <xref linkend="functions-aggregate-table"> and
! <xref linkend="functions-aggregate-statistics-table">.
! The built-in ordered-set aggregate functions
! are listed in <xref linkend="functions-orderedset-table"> and
! <xref linkend="functions-hypothetical-table">. Grouping operations,
which are closely related to aggregate functions, are listed in
<xref linkend="functions-grouping-table">.
The special syntax considerations for aggregate
--- 13166,13179 ----
<para>
<firstterm>Aggregate functions</firstterm> compute a single result
! from a set of input values. The built-in general-purpose aggregate
! functions are listed in <xref linkend="functions-aggregate-table">
! and statistical aggregates in <xref
! linkend="functions-aggregate-statistics-table">.
! The built-in within-group ordered-set aggregate functions
! are listed in <xref linkend="functions-orderedset-table">
! while the built-in within-group hypothetical-set ones are in <xref
! linkend="functions-hypothetical-table">. Grouping operations,
which are closely related to aggregate functions, are listed in
<xref linkend="functions-grouping-table">.
The special syntax considerations for aggregate
*************** SELECT xmlagg(x) FROM (SELECT x FROM tes
*** 14413,14429 ****
<para>
The built-in window functions are listed in
<xref linkend="functions-window-table">. Note that these functions
! <emphasis>must</> be invoked using window function syntax; that is an
<literal>OVER</> clause is required.
</para>
<para>
! In addition to these functions, any built-in or user-defined normal
! aggregate function (but not ordered-set or hypothetical-set aggregates)
can be used as a window function; see
<xref linkend="functions-aggregate"> for a list of the built-in aggregates.
Aggregate functions act as window functions only when an <literal>OVER</>
! clause follows the call; otherwise they act as regular aggregates.
</para>
<table id="functions-window-table">
--- 14414,14432 ----
<para>
The built-in window functions are listed in
<xref linkend="functions-window-table">. Note that these functions
! <emphasis>must</> be invoked using window function syntax, i.e., an
<literal>OVER</> clause is required.
</para>
<para>
! In addition to these functions, any built-in or user-defined
! general-purpose or statistical
! aggregate (i.e., not ordered-set or hypothetical-set aggregates)
can be used as a window function; see
<xref linkend="functions-aggregate"> for a list of the built-in aggregates.
Aggregate functions act as window functions only when an <literal>OVER</>
! clause follows the call; otherwise they act as non-window aggregates
! and return a single row for the entire set.
</para>
<table id="functions-window-table">
*************** SELECT xmlagg(x) FROM (SELECT x FROM tes
*** 14488,14494 ****
<entry>
<type>double precision</type>
</entry>
! <entry>relative rank of the current row: (<function>rank</> - 1) / (total rows - 1)</entry>
</row>
<row>
--- 14491,14497 ----
<entry>
<type>double precision</type>
</entry>
! <entry>relative rank of the current row: (<function>rank</> - 1) / (total partition rows - 1)</entry>
</row>
<row>
*************** SELECT xmlagg(x) FROM (SELECT x FROM tes
*** 14501,14507 ****
<entry>
<type>double precision</type>
</entry>
! <entry>relative rank of the current row: (number of rows preceding or peer with current row) / (total rows)</entry>
</row>
<row>
--- 14504,14510 ----
<entry>
<type>double precision</type>
</entry>
! <entry>cumulative distribution: (number of partition rows preceding or peer with current row) / total partition rows</entry>
</row>
<row>
*************** SELECT xmlagg(x) FROM (SELECT x FROM tes
*** 14634,14642 ****
All of the functions listed in
<xref linkend="functions-window-table"> depend on the sort ordering
specified by the <literal>ORDER BY</> clause of the associated window
! definition. Rows that are not distinct in the <literal>ORDER BY</>
! ordering are said to be <firstterm>peers</>; the four ranking functions
! are defined so that they give the same answer for any two peer rows.
</para>
<para>
--- 14637,14646 ----
All of the functions listed in
<xref linkend="functions-window-table"> depend on the sort ordering
specified by the <literal>ORDER BY</> clause of the associated window
! definition. Rows that are not distinct when considering only the
! <literal>ORDER BY</> columns are said to be <firstterm>peers</>.
! The four ranking functions (including <function>cume_dist</>) are
! defined so that they give the same answer for all peer rows.
</para>
<para>
*************** SELECT xmlagg(x) FROM (SELECT x FROM tes
*** 14679,14684 ****
--- 14683,14696 ----
</para>
</note>
+ <para>
+ <function>cume_dist</> computes the fraction of partition rows that
+ are less than or equal to the current row and its peers, while
+ <function>percent_rank</> computes the fraction of partition rows that
+ are less than the current row, assuming the current row does not exist
+ in the partition.
+ </para>
+
</sect1>
<sect1 id="functions-subquery">
diff --git a/doc/src/sgml/syntax.sgml b/doc/src/sgml/syntax.sgml
new file mode 100644
index 40f722c..a2d136e
*** a/doc/src/sgml/syntax.sgml
--- b/doc/src/sgml/syntax.sgml
*************** SELECT string_agg(a ORDER BY a, ',') FRO
*** 1664,1670 ****
<para>
Placing <literal>ORDER BY</> within the aggregate's regular argument
list, as described so far, is used when ordering the input rows for
! a <quote>normal</> aggregate for which ordering is optional. There is a
subclass of aggregate functions called <firstterm>ordered-set
aggregates</> for which an <replaceable>order_by_clause</replaceable>
is <emphasis>required</>, usually because the aggregate's computation is
--- 1664,1671 ----
<para>
Placing <literal>ORDER BY</> within the aggregate's regular argument
list, as described so far, is used when ordering the input rows for
! general-purpose and statistical aggregates, for which ordering is
! optional. There is a
subclass of aggregate functions called <firstterm>ordered-set
aggregates</> for which an <replaceable>order_by_clause</replaceable>
is <emphasis>required</>, usually because the aggregate's computation is
*************** SELECT string_agg(a ORDER BY a, ',') FRO
*** 1675,1681 ****
inside <literal>WITHIN GROUP (...)</>, as shown in the final syntax
alternative above. The expressions in
the <replaceable>order_by_clause</replaceable> are evaluated once per
! input row just like normal aggregate arguments, sorted as per
the <replaceable>order_by_clause</replaceable>'s requirements, and fed
to the aggregate function as input arguments. (This is unlike the case
for a non-<literal>WITHIN GROUP</> <replaceable>order_by_clause</>,
--- 1676,1682 ----
inside <literal>WITHIN GROUP (...)</>, as shown in the final syntax
alternative above. The expressions in
the <replaceable>order_by_clause</replaceable> are evaluated once per
! input row just like regular aggregate arguments, sorted as per
the <replaceable>order_by_clause</replaceable>'s requirements, and fed
to the aggregate function as input arguments. (This is unlike the case
for a non-<literal>WITHIN GROUP</> <replaceable>order_by_clause</>,
*************** SELECT string_agg(a ORDER BY a, ',') FRO
*** 1683,1689 ****
argument expressions preceding <literal>WITHIN GROUP</>, if any, are
called <firstterm>direct arguments</> to distinguish them from
the <firstterm>aggregated arguments</> listed in
! the <replaceable>order_by_clause</replaceable>. Unlike normal aggregate
arguments, direct arguments are evaluated only once per aggregate call,
not once per input row. This means that they can contain variables only
if those variables are grouped by <literal>GROUP BY</>; this restriction
--- 1684,1690 ----
argument expressions preceding <literal>WITHIN GROUP</>, if any, are
called <firstterm>direct arguments</> to distinguish them from
the <firstterm>aggregated arguments</> listed in
! the <replaceable>order_by_clause</replaceable>. Unlike regular aggregate
arguments, direct arguments are evaluated only once per aggregate call,
not once per input row. This means that they can contain variables only
if those variables are grouped by <literal>GROUP BY</>; this restriction
*************** FROM generate_series(1,10) AS s(i);
*** 1779,1788 ****
<para>
A <firstterm>window function call</firstterm> represents the application
of an aggregate-like function over some portion of the rows selected
! by a query. Unlike regular aggregate function calls, this is not tied
to grouping of the selected rows into a single output row — each
row remains separate in the query output. However the window function
! is able to scan all the rows that would be part of the current row's
group according to the grouping specification (<literal>PARTITION BY</>
list) of the window function call.
The syntax of a window function call is one of the following:
--- 1780,1789 ----
<para>
A <firstterm>window function call</firstterm> represents the application
of an aggregate-like function over some portion of the rows selected
! by a query. Unlike non-window aggregate calls, this is not tied
to grouping of the selected rows into a single output row — each
row remains separate in the query output. However the window function
! has access to all the rows that would be part of the current row's
group according to the grouping specification (<literal>PARTITION BY</>
list) of the window function call.
The syntax of a window function call is one of the following:
*************** UNBOUNDED FOLLOWING
*** 1831,1850 ****
named window in the <literal>WINDOW</literal> clause; see the
<xref linkend="sql-select"> reference page for details. It's worth
pointing out that <literal>OVER wname</> is not exactly equivalent to
! <literal>OVER (wname)</>; the latter implies copying and modifying the
window definition, and will be rejected if the referenced window
specification includes a frame clause.
</para>
<para>
! The <literal>PARTITION BY</> option groups the rows of the query into
<firstterm>partitions</>, which are processed separately by the window
function. <literal>PARTITION BY</> works similarly to a query-level
<literal>GROUP BY</> clause, except that its expressions are always just
expressions and cannot be output-column names or numbers.
Without <literal>PARTITION BY</>, all rows produced by the query are
treated as a single partition.
! The <literal>ORDER BY</> option determines the order in which the rows
of a partition are processed by the window function. It works similarly
to a query-level <literal>ORDER BY</> clause, but likewise cannot use
output-column names or numbers. Without <literal>ORDER BY</>, rows are
--- 1832,1851 ----
named window in the <literal>WINDOW</literal> clause; see the
<xref linkend="sql-select"> reference page for details. It's worth
pointing out that <literal>OVER wname</> is not exactly equivalent to
! <literal>OVER (wname ...)</>; the latter implies copying and modifying the
window definition, and will be rejected if the referenced window
specification includes a frame clause.
</para>
<para>
! The <literal>PARTITION BY</> clause groups the rows of the query into
<firstterm>partitions</>, which are processed separately by the window
function. <literal>PARTITION BY</> works similarly to a query-level
<literal>GROUP BY</> clause, except that its expressions are always just
expressions and cannot be output-column names or numbers.
Without <literal>PARTITION BY</>, all rows produced by the query are
treated as a single partition.
! The <literal>ORDER BY</> clause determines the order in which the rows
of a partition are processed by the window function. It works similarly
to a query-level <literal>ORDER BY</> clause, but likewise cannot use
output-column names or numbers. Without <literal>ORDER BY</>, rows are
*************** UNBOUNDED FOLLOWING
*** 1921,1937 ****
<para>
The built-in window functions are described in <xref
linkend="functions-window-table">. Other window functions can be added by
! the user. Also, any built-in or user-defined normal aggregate function
! can be used as a window function. Ordered-set aggregates presently
! cannot be used as window functions, however.
</para>
<para>
The syntaxes using <literal>*</> are used for calling parameter-less
aggregate functions as window functions, for example
<literal>count(*) OVER (PARTITION BY x ORDER BY y)</>.
! The asterisk (<literal>*</>) is customarily not used for non-aggregate window functions.
! Aggregate window functions, unlike normal aggregate functions, do not
allow <literal>DISTINCT</> or <literal>ORDER BY</> to be used within the
function argument list.
</para>
--- 1922,1938 ----
<para>
The built-in window functions are described in <xref
linkend="functions-window-table">. Other window functions can be added by
! the user. Also, any built-in or user-defined general-purpose or
! statistical aggregate can be used as a window function. (Ordered-set
! and hypothetical-set aggregates cannot presently be used as window functions.)
</para>
<para>
The syntaxes using <literal>*</> are used for calling parameter-less
aggregate functions as window functions, for example
<literal>count(*) OVER (PARTITION BY x ORDER BY y)</>.
! The asterisk (<literal>*</>) is customarily not used for
! window-specific functions. Window-specific functions do not
allow <literal>DISTINCT</> or <literal>ORDER BY</> to be used within the
function argument list.
</para>
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