Abhilash L L created KYLIN-1844:
---
Summary: High cardinality dimensions in memory
Key: KYLIN-1844
URL: https://issues.apache.org/jira/browse/KYLIN-1844
Project: Kylin
Issue Type: Improvement
Abhilash L L created KYLIN-1843:
---
Summary: LRU cache for in memory dimensions
Key: KYLIN-1843
URL: https://issues.apache.org/jira/browse/KYLIN-1843
Project: Kylin
Issue Type: Improvement
大家好
在刷kylin的时候报NaN错误。
相关错误和日志请见附件。
我们用的hdp版本是2.4.0.0-169，hbase是1.1的。kylin1.5
根据提示我在kylin_job_conf.xml和kylin_hive_conf.xml都配置了相关信息。重启后继续刷还是报同样的错误。
请大家帮忙看看有什么好建议吗？
what is the kylin version being used?
On Thu, Jun 30, 2016 at 5:43 PM, 移动苏州研发中心-陈雷雷 <775620...@qq.com> wrote:
> you can backup the metadata, delete the cube meta you dropped, reset the
> metadata, and restore the metadata.
> it is very dangerous, so I recommend that you backup twice, edit and
>
besides the measure part, you need SITE_EXTENDED_1 and SITE_EXTENDED_2
added in "hbase_mapping" as well
On Fri, Jul 1, 2016 at 1:59 PM, hongbin ma wrote:
> Unfortunately, there's no webUI for extended column yet. we're still
> working on it.
>
> You can edit the cube desc json directly, refer t
Unfortunately, there's no webUI for extended column yet. we're still
working on it.
You can edit the cube desc json directly, refer to
KYLIN_HOME/examples/test_case_data/localmeta/cube_desc/test_kylin_cube_without_slr_desc.json
as an example, we have two extended column measure there: SITE_EXTEND
"derived" need post aggregation as we know; from Day to Month, it need
aggregate 30 times data in memory to result set; For Quarter it need more;
So when the measure is "memory-hungry" measure (like distinct count, raw,
top-n), it is likely to get the out of memory error; you can try to define
"mon
raphael5200 created KYLIN-1842:
--
Summary: java.lang.NoClassDefFoundError:
org/apache/hive/hcatalog/mapreduce/HCatInputFormat
Key: KYLIN-1842
URL: https://issues.apache.org/jira/browse/KYLIN-1842
Project:
Yang Liu created KYLIN-1841:
---
Summary: Refresh or build different segments of one cube
simultaneously
Key: KYLIN-1841
URL: https://issues.apache.org/jira/browse/KYLIN-1841
Project: Kylin
Issue Typ
Hi Abhilash, welcome back;
Kylin 1.5 delivers a new plugable architecture, with many enhancements
especially on performance, like fast cubing algorithm, sharded storage
engine, etc. The facts 1) to 4) are unchanged in between I think; For the
issues like memory usage, you can open JIRA to us or su
少峰，您好：
two "distinct count" measures, are HyperLogLog counter。
一、 group by b.dim_month_name 这个是derived measure。
测试了下，如果where 条件是月，group by 周 查询时间是66秒， where 条件是周，group by 日，查询时间是9秒
如果where 条件是年，group by 月 ；where 条件是上半年，group by 季度或者月 都会内存溢出错误。
Hbase的heap si
hi tongxing,
The root cause is OutOfMemory:
Caused by: java.lang.OutOfMemoryError
at
java.io.ByteArrayOutputStream.hugeCapacity(ByteArrayOutputStream.java:123)
at
java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:117)
at
java.io.ByteArrayOutputStream.ensure
fengYu created KYLIN-1840:
-
Summary: project admin should has right to load table
Key: KYLIN-1840
URL: https://issues.apache.org/jira/browse/KYLIN-1840
Project: Kylin
Issue Type: Bug
Compon
大家好：
Kylin查询时报超时异常,sql是：
select b.dim_month_name,sum(a.ordr_amt) as 订单金额,
sum(a.pay_amt) as 支付金额,count(*) as 订单数,
count(distinct a.user_pin)as 用户数,count(distinct a.is_new) as 新用户数
from dmt.dmt_mem_vip_tx_ordr_det_i_d a
left join dim.dim_day b on a.pay_time=b.dim_day_txdate
left join dim.
you can backup the metadata, delete the cube meta you dropped, reset the
metadata, and restore the metadata.
it is very dangerous, so I recommend that you backup twice, edit and restore
one of the metadata.
http://kylin.apache.org/docs15/howto/howto_backup_metadata.html
./bin/metastore.sh backu
大家好：
Kylin查询时报超时异常,sql是：
select b.dim_month_name,sum(a.ordr_amt) as 订单金额,
sum(a.pay_amt) as 支付金额,count(*) as 订单数,
count(distinct a.user_pin)as 用户数,count(distinct a.is_new) as 新用户数
from dmt.dmt_mem_vip_tx_ordr_det_i_d a
left join dim.dim_day b on a.pay_time=b.dim_day_txdate
left join dim.
大家好：
Kylin查询时报超时异常,sql是：
select b.dim_month_name,sum(a.ordr_amt) as 订单金额,
sum(a.pay_amt) as 支付金额,count(*) as 订单数,
count(distinct a.user_pin)as 用户数,count(distinct a.is_new) as 新用户数
from dmt.dmt_mem_vip_tx_ordr_det_i_d a
left join dim.dim_day b on a.pay_time=b.dim_day_txdate
left join dim.
17 matches
Mail list logo
