[jira] [Created] (SPARK-17963) Add examples (extend) in each function and improve documentation with arguments

["Hyukjin Kwon (JIRA)" <ji...@apache.org>]

Hyukjin Kwon created SPARK-17963:
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             Summary: Add examples (extend) in each function and improve documentation with arguments
                 Key: SPARK-17963
                 URL: https://issues.apache.org/jira/browse/SPARK-17963
             Project: Spark
          Issue Type: Documentation
          Components: SQL
            Reporter: Hyukjin Kwon


Currently, it seems function documentation is inconsistent and does not have examples ({{extend}} much.

For example, some functions have a bad indentation as below:

{code}
spark-sql> DESCRIBE FUNCTION last;
Function: last
Class: org.apache.spark.sql.catalyst.expressions.aggregate.Last
Usage: last(expr,isIgnoreNull) - Returns the last value of `child` for a group of rows.
    last(expr,isIgnoreNull=false) - Returns the last value of `child` for a group of rows.
      If isIgnoreNull is true, returns only non-null values.
{code}

{code}
spark-sql> DESCRIBE FUNCTION EXTENDED count;
Function: count
Class: org.apache.spark.sql.catalyst.expressions.aggregate.Count
Usage: count(*) - Returns the total number of retrieved rows, including rows containing NULL values.
    count(expr) - Returns the number of rows for which the supplied expression is non-NULL.
    count(DISTINCT expr[, expr...]) - Returns the number of rows for which the supplied expression(s) are unique and non-NULL.
Extended Usage:
No example for count.
{code}

whereas some do have a pretty one

{code}
spark-sql> DESCRIBE FUNCTION EXTENDED percentile_approx;
Function: percentile_approx
Class: org.apache.spark.sql.catalyst.expressions.aggregate.ApproximatePercentile
Usage:
      percentile_approx(col, percentage [, accuracy]) - Returns the approximate percentile value of numeric
      column `col` at the given percentage. The value of percentage must be between 0.0
      and 1.0. The `accuracy` parameter (default: 10000) is a positive integer literal which
      controls approximation accuracy at the cost of memory. Higher value of `accuracy` yields
      better accuracy, `1.0/accuracy` is the relative error of the approximation.

      percentile_approx(col, array(percentage1 [, percentage2]...) [, accuracy]) - Returns the approximate
      percentile array of column `col` at the given percentage array. Each value of the
      percentage array must be between 0.0 and 1.0. The `accuracy` parameter (default: 10000) is
       a positive integer literal which controls approximation accuracy at the cost of memory.
       Higher value of `accuracy` yields better accuracy, `1.0/accuracy` is the relative error of
       the approximation.

Extended Usage:
No example for percentile_approx.
{code}

Also, there are several inconsistent indentation, for example, {{_FUNC_(a,b)}} and {{_FUNC_(a, b)}} (note the indentation between arguments.

It'd be nicer if most of them have a good example with possible argument types.

Suggested format is as below for multiple line usage:

{code}
spark-sql> DESCRIBE FUNCTION EXTENDED rand;
Function: rand
Class: org.apache.spark.sql.catalyst.expressions.Rand
Usage:
      rand() - Returns a random column with i.i.d. uniformly distributed values in [0, 1].
        seed is given randomly.

      rand(seed) - Returns a random column with i.i.d. uniformly distributed values in [0, 1].
        seed should be an integer/long/NULL literal.

Extended Usage:
> SELECT rand();
 0.9629742951434543
> SELECT rand(0);
 0.8446490682263027
> SELECT rand(NULL);
 0.8446490682263027
{code}

For single line usage:

{code}
spark-sql> DESCRIBE FUNCTION EXTENDED date_add;
Function: date_add
Class: org.apache.spark.sql.catalyst.expressions.DateAdd
Usage: date_add(start_date, num_days) - Returns the date that is num_days after start_date.
Extended Usage:
> SELECT date_add('2016-07-30', 1);
 '2016-07-31'
{code}



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