MAX Function

An aggregate function that returns the maximum value from a set of numbers. Opposite of the MIN function. Its single argument can be numeric column, or the numeric result of a function or expression applied to the column value. Rows with a NULL value for the specified column are ignored. If the table is empty, or all the values supplied to MAX are NULL, MAX returns NULL.

Syntax:

MAX([DISTINCT | ALL] expression) [OVER (analytic_clause)]

When the query contains a GROUP BY clause, returns one value for each combination of grouping values.

Restrictions: In Impala 2.0 and higher, this function can be used as an analytic function, but with restrictions on any window clause. For MAX() and MIN(), the window clause is only allowed if the start bound is UNBOUNDED PRECEDING.

Return type: Same as the input value, except for CHAR and VARCHAR arguments which produce a STRING result

Complex type considerations:

To access a column with a complex type (ARRAY, STRUCT, or MAP) in an aggregation function, you unpack the individual elements using join notation in the query, and then apply the function to the final scalar item, field, key, or value at the bottom of any nested type hierarchy in the column. See Complex Types (CDH 5.5 or higher only) for details about using complex types in Impala.

The following example demonstrates calls to several aggregation functions using values from a column containing nested complex types (an ARRAY of STRUCT items). The array is unpacked inside the query using join notation. The array elements are referenced using the ITEM pseudocolumn, and the structure fields inside the array elements are referenced using dot notation. Numeric values such as SUM() and AVG() are computed using the numeric R_NATIONKEY field, and the general-purpose MAX() and MIN() values are computed from the string N_NAME field.
describe region;
+-------------+-------------------------+---------+
| name        | type                    | comment |
+-------------+-------------------------+---------+
| r_regionkey | smallint                |         |
| r_name      | string                  |         |
| r_comment   | string                  |         |
| r_nations   | array<struct<           |         |
|             |   n_nationkey:smallint, |         |
|             |   n_name:string,        |         |
|             |   n_comment:string      |         |
|             | >>                      |         |
+-------------+-------------------------+---------+

select r_name, r_nations.item.n_nationkey
  from region, region.r_nations as r_nations
order by r_name, r_nations.item.n_nationkey;
+-------------+------------------+
| r_name      | item.n_nationkey |
+-------------+------------------+
| AFRICA      | 0                |
| AFRICA      | 5                |
| AFRICA      | 14               |
| AFRICA      | 15               |
| AFRICA      | 16               |
| AMERICA     | 1                |
| AMERICA     | 2                |
| AMERICA     | 3                |
| AMERICA     | 17               |
| AMERICA     | 24               |
| ASIA        | 8                |
| ASIA        | 9                |
| ASIA        | 12               |
| ASIA        | 18               |
| ASIA        | 21               |
| EUROPE      | 6                |
| EUROPE      | 7                |
| EUROPE      | 19               |
| EUROPE      | 22               |
| EUROPE      | 23               |
| MIDDLE EAST | 4                |
| MIDDLE EAST | 10               |
| MIDDLE EAST | 11               |
| MIDDLE EAST | 13               |
| MIDDLE EAST | 20               |
+-------------+------------------+

select
  r_name,
  count(r_nations.item.n_nationkey) as count,
  sum(r_nations.item.n_nationkey) as sum,
  avg(r_nations.item.n_nationkey) as avg,
  min(r_nations.item.n_name) as minimum,
  max(r_nations.item.n_name) as maximum,
  ndv(r_nations.item.n_nationkey) as distinct_vals
from
  region, region.r_nations as r_nations
group by r_name
order by r_name;
+-------------+-------+-----+------+-----------+----------------+---------------+
| r_name      | count | sum | avg  | minimum   | maximum        | distinct_vals |
+-------------+-------+-----+------+-----------+----------------+---------------+
| AFRICA      | 5     | 50  | 10   | ALGERIA   | MOZAMBIQUE     | 5             |
| AMERICA     | 5     | 47  | 9.4  | ARGENTINA | UNITED STATES  | 5             |
| ASIA        | 5     | 68  | 13.6 | CHINA     | VIETNAM        | 5             |
| EUROPE      | 5     | 77  | 15.4 | FRANCE    | UNITED KINGDOM | 5             |
| MIDDLE EAST | 5     | 58  | 11.6 | EGYPT     | SAUDI ARABIA   | 5             |
+-------------+-------+-----+------+-----------+----------------+---------------+

Examples:

-- Find the largest value for this column in the table.
select max(c1) from t1;
-- Find the largest value for this column from a subset of the table.
select max(c1) from t1 where month = 'January' and year = '2013';
-- Find the largest value from a set of numeric function results.
select max(length(s)) from t1;
-- Can also be used in combination with DISTINCT and/or GROUP BY.
-- Return more than one result.
select month, year, max(purchase_price) from store_stats group by month, year;
-- Filter the input to eliminate duplicates before performing the calculation.
select max(distinct x) from t1;
The following examples show how to use MAX() in an analytic context. They use a table containing integers from 1 to 10. Notice how the MAX() is reported for each input value, as opposed to the GROUP BY clause which condenses the result set.
select x, property, max(x) over (partition by property) as max from int_t where property in ('odd','even');
+----+----------+-----+
| x  | property | max |
+----+----------+-----+
| 2  | even     | 10  |
| 4  | even     | 10  |
| 6  | even     | 10  |
| 8  | even     | 10  |
| 10 | even     | 10  |
| 1  | odd      | 9   |
| 3  | odd      | 9   |
| 5  | odd      | 9   |
| 7  | odd      | 9   |
| 9  | odd      | 9   |
+----+----------+-----+
Adding an ORDER BY clause lets you experiment with results that are cumulative or apply to a moving set of rows (the "window"). The following examples use MAX() in an analytic context (that is, with an OVER() clause) to display the smallest value of X encountered up to each row in the result set. The examples use two columns in the ORDER BY clause to produce a sequence of values that rises and falls, to illustrate how the MAX() result only increases or stays the same throughout each partition within the result set. The basic ORDER BY x clause implicitly activates a window clause of RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW, which is effectively the same as ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW, therefore all of these examples produce the same results:
select x, property,
  max(x) over (order by property, x desc) as 'maximum to this point'
from int_t where property in ('prime','square');
+---+----------+-----------------------+
| x | property | maximum to this point |
+---+----------+-----------------------+
| 7 | prime    | 7                     |
| 5 | prime    | 7                     |
| 3 | prime    | 7                     |
| 2 | prime    | 7                     |
| 9 | square   | 9                     |
| 4 | square   | 9                     |
| 1 | square   | 9                     |
+---+----------+-----------------------+

select x, property,
  max(x) over
  (
    order by property, x desc
    rows between unbounded preceding and current row
  ) as 'maximum to this point'
from int_t where property in ('prime','square');
+---+----------+-----------------------+
| x | property | maximum to this point |
+---+----------+-----------------------+
| 7 | prime    | 7                     |
| 5 | prime    | 7                     |
| 3 | prime    | 7                     |
| 2 | prime    | 7                     |
| 9 | square   | 9                     |
| 4 | square   | 9                     |
| 1 | square   | 9                     |
+---+----------+-----------------------+

select x, property,
  max(x) over
  (
    order by property, x desc
    range between unbounded preceding and current row
  ) as 'maximum to this point'
from int_t where property in ('prime','square');
+---+----------+-----------------------+
| x | property | maximum to this point |
+---+----------+-----------------------+
| 7 | prime    | 7                     |
| 5 | prime    | 7                     |
| 3 | prime    | 7                     |
| 2 | prime    | 7                     |
| 9 | square   | 9                     |
| 4 | square   | 9                     |
| 1 | square   | 9                     |
+---+----------+-----------------------+
The following examples show how to construct a moving window, with a running maximum taking into account all rows before and 1 row after the current row. Because of a restriction in the Impala RANGE syntax, this type of moving window is possible with the ROWS BETWEEN clause but not the RANGE BETWEEN clause. Because of an extra Impala restriction on the MAX() and MIN() functions in an analytic context, the lower bound must be UNBOUNDED PRECEDING.
select x, property,
  max(x) over
  (
    order by property, x
    rows between unbounded preceding and 1 following
  ) as 'local maximum'
from int_t where property in ('prime','square');
+---+----------+---------------+
| x | property | local maximum |
+---+----------+---------------+
| 2 | prime    | 3             |
| 3 | prime    | 5             |
| 5 | prime    | 7             |
| 7 | prime    | 7             |
| 1 | square   | 7             |
| 4 | square   | 9             |
| 9 | square   | 9             |
+---+----------+---------------+

-- Doesn't work because of syntax restriction on RANGE clause.
select x, property,
  max(x) over
  (
    order by property, x
    range between unbounded preceding and 1 following
  ) as 'local maximum'
from int_t where property in ('prime','square');
ERROR: AnalysisException: RANGE is only supported with both the lower and upper bounds UNBOUNDED or one UNBOUNDED and the other CURRENT ROW.

Related information:

Impala Analytic Functions, MIN Function, AVG Function