hive.exec.parallel参数控制在同一个sql中的不同的job是否可以同时运行,默认为false.
下面是对于该参数的测试过程:
测试sql:
select r1.a
from (select t.a from sunwg_10 t join sunwg_10000000 s on t.a=s.b) r1 join (select s.b from sunwg_100000 t join sunwg_10 s on t.a=s.b) r2 on (r1.a=r2.b);
1,
Set hive.exec.parallel=false;
当参数为false的时候,三个job是顺序的执行
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hive>
set
hive.
exec
.parallel=
false
;
hive>
select
r1.a
>
from
(
select
t.a
from
sunwg_10 t
join
sunwg_10000000 s
on
t.a=s.b) r1
join
(
select
s.b
from
sunwg_100000 t
join
sunwg_10 s
on
t.a=s.b) r2
on
(r1.a=r2.b);
Total MapReduce jobs = 3
Launching Job 1
out
of
3
Number
of
reduce tasks
not
specified. Estimated
from
input data
size
: 1
In
order
to
change the average
load
for
a reducer (
in
bytes):
set
hive.
exec
.reducers.bytes.per.reducer=<number>
In
order
to
limit the maximum number
of
reducers:
set
hive.
exec
.reducers.
max
=<number>
In
order
to
set
a constant number
of
reducers:
set
mapred.reduce.tasks=<number>
Cannot run job locally: Input
Size
(= 397778060)
is
larger than hive.
exec
.mode.
local
.auto.inputbytes.
max
(= -1)
Starting Job = job_201208241319_2001905, Tracking URL = http://hdpjt:50030/jobdetails.jsp?jobid=job_201208241319_2001905
Kill Command = /dhwdata/hadoop/bin/../bin/hadoop job -Dmapred.job.tracker=hdpjt:9001 -kill job_201208241319_2001905
Hadoop job information
for
Stage-1: number
of
mappers: 7; number
of
reducers: 1
2012-09-07 17:55:40,854 Stage-1 map = 0%, reduce = 0%
2012-09-07 17:55:55,663 Stage-1 map = 14%, reduce = 0%
2012-09-07 17:56:00,506 Stage-1 map = 56%, reduce = 0%
2012-09-07 17:56:10,254 Stage-1 map = 100%, reduce = 0%
2012-09-07 17:56:19,871 Stage-1 map = 100%, reduce = 29%
2012-09-07 17:56:30,000 Stage-1 map = 100%, reduce = 75%
2012-09-07 17:56:34,799 Stage-1 map = 100%, reduce = 100%
Ended Job = job_201208241319_2001905
Launching Job 2
out
of
3
Number
of
reduce tasks
not
specified. Estimated
from
input data
size
: 1
In
order
to
change the average
load
for
a reducer (
in
bytes):
set
hive.
exec
.reducers.bytes.per.reducer=<number>
In
order
to
limit the maximum number
of
reducers:
set
hive.
exec
.reducers.
max
=<number>
In
order
to
set
a constant number
of
reducers:
set
mapred.reduce.tasks=<number>
Cannot run job locally: Input
Size
(= 3578060)
is
larger than hive.
exec
.mode.
local
.auto.inputbytes.
max
(= -1)
Starting Job = job_201208241319_2002054, Tracking URL = http://hdpjt:50030/jobdetails.jsp?jobid=job_201208241319_2002054
Kill Command = /dhwdata/hadoop/bin/../bin/hadoop job -Dmapred.job.tracker=hdpjt:9001 -kill job_201208241319_2002054
Hadoop job information
for
Stage-4: number
of
mappers: 2; number
of
reducers: 1
2012-09-07 17:56:43,343 Stage-4 map = 0%, reduce = 0%
2012-09-07 17:56:48,124 Stage-4 map = 50%, reduce = 0%
2012-09-07 17:56:55,816 Stage-4 map = 100%, reduce = 0%
Ended Job = job_201208241319_2002054
Launching Job 3
out
of
3
Number
of
reduce tasks
not
specified. Estimated
from
input data
size
: 1
In
order
to
change the average
load
for
a reducer (
in
bytes):
set
hive.
exec
.reducers.bytes.per.reducer=<number>
In
order
to
limit the maximum number
of
reducers:
set
hive.
exec
.reducers.
max
=<number>
In
order
to
set
a constant number
of
reducers:
set
mapred.reduce.tasks=<number>
Cannot run job locally: Input
Size
(= 596)
is
larger than hive.
exec
.mode.
local
.auto.inputbytes.
max
(= -1)
Starting Job = job_201208241319_2002120, Tracking URL = http://hdpjt:50030/jobdetails.jsp?jobid=job_201208241319_2002120
Kill Command = /dhwdata/hadoop/bin/../bin/hadoop job -Dmapred.job.tracker=hdpjt:9001 -kill job_201208241319_2002120
Hadoop job information
for
Stage-2: number
of
mappers: 2; number
of
reducers: 1
2012-09-07 17:57:12,641 Stage-2 map = 0%, reduce = 0%
2012-09-07 17:57:19,571 Stage-2 map = 50%, reduce = 0%
2012-09-07 17:57:25,199 Stage-2 map = 100%, reduce = 0%
2012-09-07 17:57:29,210 Stage-2 map = 100%, reduce = 100%
Ended Job = job_201208241319_2002120
OK
abcdefghijk_0
abcdefghijk_1
abcdefghijk_2
abcdefghijk_3
abcdefghijk_4
abcdefghijk_5
abcdefghijk_6
abcdefghijk_7
abcdefghijk_8
abcdefghijk_9
Time
taken: 135.944 seconds
|
2,
但是可以看出来其实两个子查询中的sql并无关系,可以并行的跑
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hive>
set
hive.
exec
.parallel=
true
;
hive>
select
r1.a
>
from
(
select
t.a
from
sunwg_10 t
join
sunwg_10000000 s
on
t.a=s.b) r1
join
(
select
s.b
from
sunwg_100000 t
join
sunwg_10 s
on
t.a=s.b) r2
on
(r1.a=r2.b);
Total MapReduce jobs = 3
Launching Job 1
out
of
3
Launching Job 2
out
of
3
Number
of
reduce tasks
not
specified. Estimated
from
input data
size
: 1
In
order
to
change the average
load
for
a reducer (
in
bytes):
set
hive.
exec
.reducers.bytes.per.reducer=<number>
In
order
to
limit the maximum number
of
reducers:
set
hive.
exec
.reducers.
max
=<number>
In
order
to
set
a constant number
of
reducers:
set
mapred.reduce.tasks=<number>
Cannot run job locally: Input
Size
(= 397778060)
is
larger than hive.
exec
.mode.
local
.auto.inputbytes.
max
(= -1)
Number
of
reduce tasks
not
specified. Estimated
from
input data
size
: 1
In
order
to
change the average
load
for
a reducer (
in
bytes):
set
hive.
exec
.reducers.bytes.per.reducer=<number>
In
order
to
limit the maximum number
of
reducers:
set
hive.
exec
.reducers.
max
=<number>
In
order
to
set
a constant number
of
reducers:
set
mapred.reduce.tasks=<number>
Cannot run job locally: Input
Size
(= 3578060)
is
larger than hive.
exec
.mode.
local
.auto.inputbytes.
max
(= -1)
Starting Job = job_201208241319_2001452, Tracking URL = http://hdpjt:50030/jobdetails.jsp?jobid=job_201208241319_2001452
Kill Command = /dhwdata/hadoop/bin/../bin/hadoop job -Dmapred.job.tracker=hdpjt:9001 -kill job_201208241319_2001452
Starting Job = job_201208241319_2001453, Tracking URL = http://hdpjt:50030/jobdetails.jsp?jobid=job_201208241319_2001453
Kill Command = /dhwdata/hadoop/bin/../bin/hadoop job -Dmapred.job.tracker=hdpjt:9001 -kill job_201208241319_2001453
Hadoop job information
for
Stage-4: number
of
mappers: 2; number
of
reducers: 1
Hadoop job information
for
Stage-1: number
of
mappers: 7; number
of
reducers: 1
2012-09-07 17:52:10,558 Stage-4 map = 0%, reduce = 0%
2012-09-07 17:52:10,588 Stage-1 map = 0%, reduce = 0%
2012-09-07 17:52:22,827 Stage-1 map = 14%, reduce = 0%
2012-09-07 17:52:22,880 Stage-4 map = 100%, reduce = 0%
2012-09-07 17:52:27,678 Stage-1 map = 22%, reduce = 0%
2012-09-07 17:52:28,701 Stage-1 map = 36%, reduce = 0%
2012-09-07 17:52:31,137 Stage-1 map = 93%, reduce = 0%
2012-09-07 17:52:33,551 Stage-1 map = 100%, reduce = 0%
2012-09-07 17:52:36,427 Stage-4 map = 100%, reduce = 100%
Ended Job = job_201208241319_2001453
2012-09-07 17:52:42,883 Stage-1 map = 100%, reduce = 33%
2012-09-07 17:52:45,431 Stage-1 map = 100%, reduce = 70%
2012-09-07 17:52:47,526 Stage-1 map = 100%, reduce = 76%
2012-09-07 17:52:51,829 Stage-1 map = 100%, reduce = 84%
Ended Job = job_201208241319_2001452
Launching Job 3
out
of
3
Number
of
reduce tasks
not
specified. Estimated
from
input data
size
: 1
In
order
to
change the average
load
for
a reducer (
in
bytes):
set
hive.
exec
.reducers.bytes.per.reducer=<number>
In
order
to
limit the maximum number
of
reducers:
set
hive.
exec
.reducers.
max
=<number>
In
order
to
set
a constant number
of
reducers:
set
mapred.reduce.tasks=<number>
Cannot run job locally: Input
Size
(= 596)
is
larger than hive.
exec
.mode.
local
.auto.inputbytes.
max
(= -1)
Starting Job = job_201208241319_2001621, Tracking URL = http://hdpjt:50030/jobdetails.jsp?jobid=job_201208241319_2001621
Kill Command = /dhwdata/hadoop/bin/../bin/hadoop job -Dmapred.job.tracker=hdpjt:9001 -kill job_201208241319_2001621
Hadoop job information
for
Stage-2: number
of
mappers: 2; number
of
reducers: 1
2012-09-07 17:53:07,081 Stage-2 map = 0%, reduce = 0%
2012-09-07 17:53:10,351 Stage-2 map = 50%, reduce = 0%
2012-09-07 17:53:11,380 Stage-2 map = 100%, reduce = 0%
2012-09-07 17:53:18,132 Stage-2 map = 100%, reduce = 100%
Ended Job = job_201208241319_2001621
OK
abcdefghijk_0
abcdefghijk_1
abcdefghijk_2
abcdefghijk_3
abcdefghijk_4
abcdefghijk_5
abcdefghijk_6
abcdefghijk_7
abcdefghijk_8
abcdefghijk_9
Time
taken: 108.301 seconds
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总结:
在资源充足的时候hive.exec.parallel会让那些存在并发job的sql运行得更快,但同时消耗更多的资源
可以评估下hive.exec.parallel对我们的刷新任务是否有帮助.
转自 ：http://www.oratea.net/?p=1377
本文转自茄子_2008博客园博客，原文链接：http://www.cnblogs.com/xd502djj/archive/2013/05/08/3067699.html，如需转载请自行联系原作者。
