[jira] [Updated] (HIVE-8920) IOContext problem with multiple MapWorks cloned for multi-insert [Spark Branch]
[
https://issues.apache.org/jira/browse/HIVE-8920?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Xuefu Zhang updated HIVE-8920:
--
Attachment: HIVE-8920.4-spark.patch
IOContext problem with multiple MapWorks cloned for multi-insert [Spark
Branch]
---
Key: HIVE-8920
URL: https://issues.apache.org/jira/browse/HIVE-8920
Project: Hive
Issue Type: Sub-task
Components: Spark
Affects Versions: spark-branch
Reporter: Chao
Assignee: Xuefu Zhang
Attachments: HIVE-8920.1-spark.patch, HIVE-8920.2-spark.patch,
HIVE-8920.3-spark.patch, HIVE-8920.4-spark.patch
The following query will not work:
{code}
from (select * from table0 union all select * from table1) s
insert overwrite table table3 select s.x, count(1) group by s.x
insert overwrite table table4 select s.y, count(1) group by s.y;
{code}
Currently, the plan for this query, before SplitSparkWorkResolver, looks like
below:
{noformat}
M1M2
\ / \
U3 R5
|
R4
{noformat}
In {{SplitSparkWorkResolver#splitBaseWork}}, it assumes that the
{{childWork}} is a ReduceWork, but for this case, you can see that for M2 the
childWork could be UnionWork U3. Thus, the code will fail.
HIVE-9041 addressed partially addressed the problem by removing union task.
However, it's still necessary to cloning M1 and M2 to support multi-insert.
Because M1 and M2 can run in a single JVM, the original solution of storing a
global IOContext will not work because M1 and M2 have different io contexts,
both needing to be stored.
--
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[jira] [Updated] (HIVE-8920) IOContext problem with multiple MapWorks cloned for multi-insert [Spark Branch]
[
https://issues.apache.org/jira/browse/HIVE-8920?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Xuefu Zhang updated HIVE-8920:
--
Resolution: Fixed
Fix Version/s: spark-branch
Status: Resolved (was: Patch Available)
Patch #3 is committed to Spark branch.
IOContext problem with multiple MapWorks cloned for multi-insert [Spark
Branch]
---
Key: HIVE-8920
URL: https://issues.apache.org/jira/browse/HIVE-8920
Project: Hive
Issue Type: Sub-task
Components: Spark
Affects Versions: spark-branch
Reporter: Chao
Assignee: Xuefu Zhang
Fix For: spark-branch
Attachments: HIVE-8920.1-spark.patch, HIVE-8920.2-spark.patch,
HIVE-8920.3-spark.patch, HIVE-8920.4-spark.patch
The following query will not work:
{code}
from (select * from table0 union all select * from table1) s
insert overwrite table table3 select s.x, count(1) group by s.x
insert overwrite table table4 select s.y, count(1) group by s.y;
{code}
Currently, the plan for this query, before SplitSparkWorkResolver, looks like
below:
{noformat}
M1M2
\ / \
U3 R5
|
R4
{noformat}
In {{SplitSparkWorkResolver#splitBaseWork}}, it assumes that the
{{childWork}} is a ReduceWork, but for this case, you can see that for M2 the
childWork could be UnionWork U3. Thus, the code will fail.
HIVE-9041 addressed partially addressed the problem by removing union task.
However, it's still necessary to cloning M1 and M2 to support multi-insert.
Because M1 and M2 can run in a single JVM, the original solution of storing a
global IOContext will not work because M1 and M2 have different io contexts,
both needing to be stored.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
[jira] [Updated] (HIVE-8920) IOContext problem with multiple MapWorks cloned for multi-insert [Spark Branch]
[
https://issues.apache.org/jira/browse/HIVE-8920?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Xuefu Zhang updated HIVE-8920:
--
Attachment: HIVE-8920.3-spark.patch
We have to disable caching for MapInput because of IOContext initialization
problem. This would have performance impact, but only for multi-insert cases.
Regardless, correctness goes above performance.
Patch #3 includes a fix as such.
IOContext problem with multiple MapWorks cloned for multi-insert [Spark
Branch]
---
Key: HIVE-8920
URL: https://issues.apache.org/jira/browse/HIVE-8920
Project: Hive
Issue Type: Sub-task
Components: Spark
Affects Versions: spark-branch
Reporter: Chao
Assignee: Xuefu Zhang
Attachments: HIVE-8920.1-spark.patch, HIVE-8920.2-spark.patch,
HIVE-8920.3-spark.patch
The following query will not work:
{code}
from (select * from table0 union all select * from table1) s
insert overwrite table table3 select s.x, count(1) group by s.x
insert overwrite table table4 select s.y, count(1) group by s.y;
{code}
Currently, the plan for this query, before SplitSparkWorkResolver, looks like
below:
{noformat}
M1M2
\ / \
U3 R5
|
R4
{noformat}
In {{SplitSparkWorkResolver#splitBaseWork}}, it assumes that the
{{childWork}} is a ReduceWork, but for this case, you can see that for M2 the
childWork could be UnionWork U3. Thus, the code will fail.
HIVE-9041 addressed partially addressed the problem by removing union task.
However, it's still necessary to cloning M1 and M2 to support multi-insert.
Because M1 and M2 can run in a single JVM, the original solution of storing a
global IOContext will not work because M1 and M2 have different io contexts,
both needing to be stored.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
[jira] [Updated] (HIVE-8920) IOContext problem with multiple MapWorks cloned for multi-insert [Spark Branch]
[
https://issues.apache.org/jira/browse/HIVE-8920?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Xuefu Zhang updated HIVE-8920:
--
Summary: IOContext problem with multiple MapWorks cloned for multi-insert
[Spark Branch] (was: SplitSparkWorkResolver doesn't work with UnionWork [Spark
Branch])
IOContext problem with multiple MapWorks cloned for multi-insert [Spark
Branch]
---
Key: HIVE-8920
URL: https://issues.apache.org/jira/browse/HIVE-8920
Project: Hive
Issue Type: Sub-task
Components: Spark
Affects Versions: spark-branch
Reporter: Chao
Assignee: Xuefu Zhang
Attachments: HIVE-8920.1-spark.patch
The following query will not work:
{code}
from (select * from table0 union all select * from table1) s
insert overwrite table table3 select s.x, count(1) group by s.x
insert overwrite table table4 select s.y, count(1) group by s.y;
{code}
Currently, the plan for this query, before SplitSparkWorkResolver, looks like
below:
{noformat}
M1M2
\ / \
U3 R5
|
R4
{noformat}
In {{SplitSparkWorkResolver#splitBaseWork}}, it assumes that the
{{childWork}} is a ReduceWork, but for this case, you can see that for M2 the
childWork could be UnionWork U3. Thus, the code will fail.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
[jira] [Updated] (HIVE-8920) IOContext problem with multiple MapWorks cloned for multi-insert [Spark Branch]
[
https://issues.apache.org/jira/browse/HIVE-8920?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Xuefu Zhang updated HIVE-8920:
--
Description:
The following query will not work:
{code}
from (select * from table0 union all select * from table1) s
insert overwrite table table3 select s.x, count(1) group by s.x
insert overwrite table table4 select s.y, count(1) group by s.y;
{code}
Currently, the plan for this query, before SplitSparkWorkResolver, looks like
below:
{noformat}
M1M2
\ / \
U3 R5
|
R4
{noformat}
In {{SplitSparkWorkResolver#splitBaseWork}}, it assumes that the {{childWork}}
is a ReduceWork, but for this case, you can see that for M2 the childWork could
be UnionWork U3. Thus, the code will fail.
HIVE-9041 addressed partially addressed the problem by removing union task.
However, it's still necessary to cloning M1 and M2 to support multi-insert.
Because M1 and M2 can run in a single JVM, the original solution of storing a
global IOContext will not work because M1 and M2 have different io contexts,
both needing to be stored.
was:
The following query will not work:
{code}
from (select * from table0 union all select * from table1) s
insert overwrite table table3 select s.x, count(1) group by s.x
insert overwrite table table4 select s.y, count(1) group by s.y;
{code}
Currently, the plan for this query, before SplitSparkWorkResolver, looks like
below:
{noformat}
M1M2
\ / \
U3 R5
|
R4
{noformat}
In {{SplitSparkWorkResolver#splitBaseWork}}, it assumes that the {{childWork}}
is a ReduceWork, but for this case, you can see that for M2 the childWork could
be UnionWork U3. Thus, the code will fail.
IOContext problem with multiple MapWorks cloned for multi-insert [Spark
Branch]
---
Key: HIVE-8920
URL: https://issues.apache.org/jira/browse/HIVE-8920
Project: Hive
Issue Type: Sub-task
Components: Spark
Affects Versions: spark-branch
Reporter: Chao
Assignee: Xuefu Zhang
Attachments: HIVE-8920.1-spark.patch
The following query will not work:
{code}
from (select * from table0 union all select * from table1) s
insert overwrite table table3 select s.x, count(1) group by s.x
insert overwrite table table4 select s.y, count(1) group by s.y;
{code}
Currently, the plan for this query, before SplitSparkWorkResolver, looks like
below:
{noformat}
M1M2
\ / \
U3 R5
|
R4
{noformat}
In {{SplitSparkWorkResolver#splitBaseWork}}, it assumes that the
{{childWork}} is a ReduceWork, but for this case, you can see that for M2 the
childWork could be UnionWork U3. Thus, the code will fail.
HIVE-9041 addressed partially addressed the problem by removing union task.
However, it's still necessary to cloning M1 and M2 to support multi-insert.
Because M1 and M2 can run in a single JVM, the original solution of storing a
global IOContext will not work because M1 and M2 have different io contexts,
both needing to be stored.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
[jira] [Updated] (HIVE-8920) IOContext problem with multiple MapWorks cloned for multi-insert [Spark Branch]
[
https://issues.apache.org/jira/browse/HIVE-8920?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Xuefu Zhang updated HIVE-8920:
--
Attachment: HIVE-8920.2-spark.patch
Patch #2 correct some code styling issue.
IOContext problem with multiple MapWorks cloned for multi-insert [Spark
Branch]
---
Key: HIVE-8920
URL: https://issues.apache.org/jira/browse/HIVE-8920
Project: Hive
Issue Type: Sub-task
Components: Spark
Affects Versions: spark-branch
Reporter: Chao
Assignee: Xuefu Zhang
Attachments: HIVE-8920.1-spark.patch, HIVE-8920.2-spark.patch
The following query will not work:
{code}
from (select * from table0 union all select * from table1) s
insert overwrite table table3 select s.x, count(1) group by s.x
insert overwrite table table4 select s.y, count(1) group by s.y;
{code}
Currently, the plan for this query, before SplitSparkWorkResolver, looks like
below:
{noformat}
M1M2
\ / \
U3 R5
|
R4
{noformat}
In {{SplitSparkWorkResolver#splitBaseWork}}, it assumes that the
{{childWork}} is a ReduceWork, but for this case, you can see that for M2 the
childWork could be UnionWork U3. Thus, the code will fail.
HIVE-9041 addressed partially addressed the problem by removing union task.
However, it's still necessary to cloning M1 and M2 to support multi-insert.
Because M1 and M2 can run in a single JVM, the original solution of storing a
global IOContext will not work because M1 and M2 have different io contexts,
both needing to be stored.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
