kevinyu98 commented on a change in pull request #28120:
[SPARK-31349][SQL][DOCS] Document built-in aggregate functions in SQL Reference
URL: https://github.com/apache/spark/pull/28120#discussion_r404536117
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File path: docs/sql-ref-functions-builtin-aggregate.md
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@@ -19,4 +19,616 @@ license: |
limitations under the License.
---
-Aggregate functions
\ No newline at end of file
+Spark SQL provides build-in aggregate functions defined in the dataset API and
SQL interface. Aggregate functions
+operate on a group of rows and return a single value.
+
+Spark SQL aggregate functions are grouped as <code>agg_funcs</code> in Spark
SQL. Below is the list of functions.
+
+**Note:** All functions below have another signature which takes String as a
expression.
+
+<table class="table">
+ <thead>
+ <tr><th style="width:25%">Function</th><th>Parameter
Type(s)</th><th>Description</th></tr>
+ </thead>
+ <tbody>
+ <tr>
+ <td><b>{any | some | bool_or}</b>(<i>expression</i>)</td>
+ <td>boolean</td>
+ <td>Returns true if at least one value is true.</td>
+ </tr>
+ <tr>
+ <td><b>approx_count_distinct</b>(<i>expression[, relativeSD]</i>)</td>
+ <td>(long, double)</td>
+ <td>RelativeSD is the maximum estimation error allowed. Returns the
estimated cardinality by HyperLogLog++.</td>
+ </tr>
+ <tr>
+ <td><b>{avg | mean}</b>(<i>expression</i>)</td>
+ <td>numeric or string</td>
+ <td>Returns the average of values in the input expression.</td>
+ </tr>
+ <tr>
+ <td><b>{bool_and | every}</b>(<i>expression</i>)</td>
+ <td>boolean</td>
+ <td>Returns true if all values are true.</td>
+ </tr>
+ <tr>
+ <td><b>collect_list</b>(<i>expression</i>)</td>
+ <td>any</td>
+ <td>Collects and returns a list of non-unique elements. The function is
non-deterministic because the order of collected results depends on the order
of the rows which may be non-deterministic after a shuffle.</td>
+ </tr>
+ <tr>
+ <td><b>collect_set</b>(<i>expression</i>)</td>
+ <td>any</td>
+ <td>Collects and returns a set of unique elements. The function is
non-deterministic because the order of collected results depends on the order
of the rows which may be non-deterministic after a shuffle.</td>
+ </tr>
+ <tr>
+ <td><b>corr</b>(<i>expression1, expression2</i>)</td>
+ <td>double, double</td>
+ <td>Returns Pearson coefficient of correlation between a set of number
pairs.</td>
+ </tr>
+ <tr>
+ <td><b>count</b>([<b>DISTINCT</b>] {<i><b>*</b></i> | <i>expression1[,
expression2</i>]})</td>
+ <td>none; any</td>
+ <td>If specified <code>DISTINCT</code>, returns the number of rows for
which the supplied expression(s) are unique and not null; If specified `*`,
returns the total number of retrieved rows, including rows containing null;
Otherwise, returns the number of rows for which the supplied expression(s) are
all not null.</td>
+ </tr>
+ <tr>
+ <td><b>count_if</b>(<i>predicate</i>)</td>
+ <td>expression that will be used for aggregation calculation</td>
+ <td>Returns the count number from the predicate evaluate to `TRUE`
values.</td>
+ </tr>
+ <tr>
+ <td><b>count_min_sketch</b>(<i>expression, eps, confidence,
seed</i>)</td>
+ <td>integral or string or binary, double, double, integer</td>
+ <td>Eps and confidence are the double values between 0.0 and 1.0, seed
is a positive integer. Returns a count-min sketch of a expression with the
given esp, confidence and seed. The result is an array of bytes, which can be
deserialized to a `CountMinSketch` before usage. Count-min sketch is a
probabilistic data structure used for cardinality estimation using sub-linear
space.</td>
+ </tr>
+ <tr>
+ <td><b>covar_pop</b>(<i>expression1, expression2</i>)</td>
+ <td>double, double</td>
+ <td>Returns the population covariance of a set of number pairs.</td>
+ </tr>
+ <tr>
+ <td><b>covar_samp</b>(<i>expression1, expression2</i>)</td>
+ <td>double</td>
+ <td>Returns the sample covariance of a set of number pairs.</td>
+ </tr>
+ <tr>
+ <td><b>{first | first_value}</b>(<i>expression[, isIgnoreNull]</i>)</td>
+ <td>any, boolean</td>
+ <td>Returns the first value of expression for a group of rows. If
<code>isIgnoreNull</code> is true, returns only non-null values, default is
false. This function is non-deterministic.</td>
+ </tr>
+ <tr>
+ <td><b>kurtosis</b>(<i>expression</i>)</td>
+ <td>double</td>
+ <td>Returns the kurtosis value calculated from values of a group.</td>
+ </tr>
+ <tr>
+ <td><b>{last | last_value}</b>(<i>expression[, isIgnoreNull]</i>)</td>
+ <td>any, boolean</td>
+ <td>Returns the last value of expression for a group of rows. If
<code>isIgnoreNull</code> is true, returns only non-null values, default is
false. This function is non-deterministic.</td>
+ </tr>
+ <tr>
+ <td><b>max</b>(<i>expression</i>)</td>
+ <td>any numeric, string, date/time or arrays of these types</td>
+ <td>Returns the maximum value of the expression.</td>
+ </tr>
+ <tr>
+ <td><b>max_by</b>(<i>expression1, expression2</i>)</td>
+ <td>any numeric, string, date/time or arrays of these types</td>
+ <td>Returns the value of expression1 associated with the maximum value
of expression2.</td>
+ </tr>
+ <tr>
+ <td><b>min</b>(<i>expression</i>)</td>
+ <td>any numeric, string, date/time or arrays of these types</td>
+ <td>Returns the minimum value of the expression.</td>
+ </tr>
+ <tr>
+ <td><b>min_by</b>(<i>expression1, expression2</i>)</td>
+ <td>any numeric, string, date/time or arrays of these types</td>
+ <td>Returns the value of expression1 associated with the minimum value
of expression2.</td>
+ </tr>
+ <tr>
+ <td><b>percentile</b>(<i>expression, percentage [, frequency]</i>)</td>
+ <td>numeric Type, double, integral type</td>
+ <td>Percentage is a number between 0 and 1; Frequency is a positive
integer. Returns the exact percentile value of numeric expression at the given
percentage.</td>
+ </tr>
+ <tr>
+ <td><b>percentile</b>(<i>expression, <b>array</b>(percentage1 [,
percentage2]...) [, frequency]</i>)</td>
+ <td>numeric type; double; integral type</td>
+ <td>Percentage array is an array of number between 0 and 1; frequency is
a positive integer. Returns the exact percentile value array of numeric
expression at the given percentage(s).</td>
+ </tr>
+ <tr>
+ <td><b>{percentile_approx | percentile_approx}</b>(<i>expression,
percentage [, frequency]</i>)</td>
+ <td>numeric, date, timestamp; double; integral</td>
+ <td>Percentage is a number between 0 and 1; Frequency is a positive
integer. Returns the approximate percentile value of numeric expression at the
given percentage.</td>
+ </tr>
+ <tr>
+ <td><b>{percentile_approx | percentile_approx}</b>(<i>expression,
<b>array</b>(percentage1 [, percentage2]...) [, frequency]</i>)</td>
+ <td>numeric, date, timestamp; double; integral</td>
+ <td>Percentage is a number between 0 and 1; Frequency is a positive
integer. Returns the approximate percentile value of numeric expression at the
given percentage.</td>
+ </tr>
+ <tr>
+ <td><b>skewness</b>(<i>expression</i>)</td>
+ <td>double</td>
+ <td>Returns the skewness value calculated from values of a group.</td>
+ </tr>
+ <tr>
+ <td><b>{stddev_samp | stddev | std}</b>(<i>expression</i>)</td>
+ <td>double</td>
+ <td>Returns the sample standard deviation calculated from values of a
group.</td>
+ </tr>
+ <tr>
+ <td><b>stddev_pop</b>(<i>expression</i>)</td>
+ <td>double</td>
+ <td>Returns the population standard deviation calculated from values of
a group.</td>
+ </tr>
+ <tr>
+ <td><b>sum</b>(<i>expression</i>)</td>
+ <td>numeric</td>
+ <td>Returns the sum calculated from values of a group.</td>
+ </tr>
+ <tr>
+ <td><b>{variance | var_samp}</b>(<i>expression</i>)</td>
+ <td>double</td>
+ <td>Returns the sample variance calculated from values of a group.</td>
+ </tr>
+ <tr>
+ <td><b>var_pop</b>(<i>expression</i>)</td>
+ <td>double</td>
+ <td>Returns the population variance calculated from values of a
group.</td>
+ </tr>
+ </tbody>
+</table>
+
+### Examples
+{% highlight sql %}
+--base table
Review comment:
sure
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