[
https://issues.apache.org/jira/browse/HIVE-503?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Min Zhou updated HIVE-503:
--------------------------
Description:
distinct
# OK
{code:sql}
select
col
from
tbl
{code}
# FAILED
{code:sql}
select
col1,
col2
from
tbl
{code}
distinguish distinct aggregate function
# OK
{code:sql}
select
count(distinct col % 10)
from
tbl
{code}
# OK
{code:sql}
select
count(distinct col1% 10)
count(distinct col1% 9)
from
tbl
{code}
# OK
{code:sql}
select
count(distinct col1 % 10)
count(distinct col2 % 9)
from
tbl
{code}
# OK
{code:sql}
select
sum(distinct col1 % 10),
count(distinct col2 % 9)
from
tbl
{code}
# OK
{code:sql}
select
max(distinct substr(col1, 1, 10)),
count(distinct col2 % 9)
from
tbl
{code}
Distinct aggregate function is in connection with the all aggregate function,
it essentially is an aggregate function.
Only one result each aggregate function will produce, it's very able one
mapreduce job do two different aggregate expression simultaneously.
was:
distinct
# OK
{code:sql}
select
col
from
tbl
{code}
# FAILED
{code:sql}
select
col1,
col2
from
tbl
{code}
distinguish distinct aggregate function
# OK
{code:sql}
select
count(distinct col% 10)
from
tbl
{code}
# OK
{code:sql}
select
count(distinct col1% 10)
count(distinct col1% 9)
from
tbl
{code}
# OK
{code:sql}
select
count(distinct col1% 10)
count(distinct col2 % 9)
from
tbl
{code}
> improvement on distinct: distinguish distinct aggregate function from distinct
> ------------------------------------------------------------------------------
>
> Key: HIVE-503
> URL: https://issues.apache.org/jira/browse/HIVE-503
> Project: Hadoop Hive
> Issue Type: Improvement
> Reporter: Min Zhou
>
> distinct
> # OK
> {code:sql}
> select
> col
> from
> tbl
> {code}
> # FAILED
> {code:sql}
> select
> col1,
> col2
> from
> tbl
> {code}
> distinguish distinct aggregate function
> # OK
> {code:sql}
> select
> count(distinct col % 10)
> from
> tbl
> {code}
> # OK
> {code:sql}
> select
> count(distinct col1% 10)
> count(distinct col1% 9)
> from
> tbl
> {code}
> # OK
> {code:sql}
> select
> count(distinct col1 % 10)
> count(distinct col2 % 9)
> from
> tbl
> {code}
> # OK
> {code:sql}
> select
> sum(distinct col1 % 10),
> count(distinct col2 % 9)
> from
> tbl
> {code}
> # OK
> {code:sql}
> select
> max(distinct substr(col1, 1, 10)),
> count(distinct col2 % 9)
> from
> tbl
> {code}
> Distinct aggregate function is in connection with the all aggregate function,
> it essentially is an aggregate function.
> Only one result each aggregate function will produce, it's very able one
> mapreduce job do two different aggregate expression simultaneously.
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