我的 Hive Query 抛出了这个异常。
Hadoop job information for Stage-1: number of mappers: 6; number of reducers: 1
2013-05-22 12:08:32,634 Stage-1 map = 0%, reduce = 0%
2013-05-22 12:09:19,984 Stage-1 map = 100%, reduce = 100%
Ended Job = job_201305221200_0001 with errors
Error during job, obtaining debugging information...
Examining task ID: task_201305221200_0001_m_000007 (and more) from job job_201305221200_0001
Examining task ID: task_201305221200_0001_m_000003 (and more) from job job_201305221200_0001
Examining task ID: task_201305221200_0001_m_000001 (and more) from job job_201305221200_0001
Task with the most failures(4):
-----
Task ID:
task_201305221200_0001_m_000001
URL:
http://ip-10-134-7-119.ap-southeast-1.compute.internal:9100/taskdetails.jsp?jobid=job_201305221200_0001&tipid=task_201305221200_0001_m_000001
Possible error:
Out of memory due to hash maps used in map-side aggregation.
Solution:
Currently hive.map.aggr.hash.percentmemory is set to 0.5. Try setting it to a lower value. i.e 'set hive.map.aggr.hash.percentmemory = 0.25;'
-----
Counters:
FAILED: Execution Error, return code 2 from org.apache.hadoop.hive.ql.exec.MapRedTask
select
uri,
count(*) as hits
from
iislog
where
substr(cs_cookie,instr(cs_Cookie,'cwc'),30) like '%CWC%'
and uri like '%.aspx%'
and logdate = '2013-02-07'
group by uri
order by hits Desc;
我在 8 个 EMR 核心实例上尝试了这个,其中 1 个大型主实例在 8Gb 数据上。首先我尝试使用外部表(数据位置是 s3 的路径)。之后,我将数据从 S3 下载到 EMR 并使用本机配置单元表。但是在他们两个中我都遇到了同样的错误。
FYI, i am using regex serde to parse the iislogs.
'org.apache.hadoop.hive.contrib.serde2.RegexSerDe'
WITH SERDEPROPERTIES (
"input.regex" ="([0-9-]+) ([^ ]*) ([^ ]*) ([^ ]*) ([^ ]*) ([^ ]*) ([^ ]*) ([^ ]*) (\".*\"|[^ ]*) ([^ ]*) ([^ ]*) ([^ ]*) ([^ ]*) ([^ ]*) (\".*\"|[^ ]*) ([^ ]*) ([^ ]*) ([^ ]*) ([^ ]*) ([^ ]*) ([^ ]*) ([^ ]*) (\".*\"|[^ ]*) ([^ ]*) ([^ ]*) ([^ ]*) ([^ ]*) ([0-9-]+ [0-9:.]+) ([^ ]*) ([^ ]*) (\".*\"|[^ ]*) ([0-9-]+ [0-9:.]+)",
"output.format.string"="%1$s %2$s %3$s %4$s %5$s %6$s %7$s %8$s %9$s %10$s %11$s %12$s %13$s %14$s %15$s %16$s %17$s %18$s %19$s %20$s %21$s %22$s %23$s %24$s %25$s %26$s %27$s %28$s %29$s %30$s %31$s %32$s")
location 's3://*******';