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https://issues.apache.org/jira/browse/SPARK-25038?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Jason Guo updated SPARK-25038:
------------------------------
Description:
When Spark SQL read large amount of data, it take a long time (more than 10
minutes) to generate physical Plan and then ActiveJob
Example:
There is a table which is partitioned by date and hour. There are more than 13
TB data each hour and 185 TB per day. When we just issue a very simple SQL, it
take a long time to generate ActiveJob
The SQL statement is
{code:java}
select count(device_id) from test_tbl where date=20180731 and hour='21';
{code}
The SQL is issued at 2018-08-07 08:43:48
!image-2018-08-07-08-48-28-753.png!
However, the job is submitted at 2018-08-07 08:46:05, which is 2minutes and 17
seconds later than the SQL issue time
!image-2018-08-07-08-47-06-321.png!
was:
When Spark SQL read large amount of data, it take a long time (more than 10
minutes) to generate physical Plan and then ActiveJob
Example:
There is a table which is partitioned by date and hour. There are more than 13
TB data each hour and 185 TB per day. When we just issue a very simple SQL, it
take a long time to generate ActiveJob
The SQL statement is
{code:java}
select count(device_id) from test_tbl where date=20180731 and hour='21';
{code}
The SQL is issued at 2018-08-05 18:33:21
!image-2018-08-07-08-38-01-984.png!
However, the job is submitted at 2018-08-05 18:34:45, which is 1minutes and 24
seconds later than the SQL issue time
> Accelerate Spark Plan generation when Spark SQL read large amount of data
> -------------------------------------------------------------------------
>
> Key: SPARK-25038
> URL: https://issues.apache.org/jira/browse/SPARK-25038
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 2.3.1
> Reporter: Jason Guo
> Priority: Critical
>
> When Spark SQL read large amount of data, it take a long time (more than 10
> minutes) to generate physical Plan and then ActiveJob
>
> Example:
> There is a table which is partitioned by date and hour. There are more than
> 13 TB data each hour and 185 TB per day. When we just issue a very simple
> SQL, it take a long time to generate ActiveJob
>
> The SQL statement is
> {code:java}
> select count(device_id) from test_tbl where date=20180731 and hour='21';
> {code}
>
> The SQL is issued at 2018-08-07 08:43:48
> !image-2018-08-07-08-48-28-753.png!
> However, the job is submitted at 2018-08-07 08:46:05, which is 2minutes and
> 17 seconds later than the SQL issue time
> !image-2018-08-07-08-47-06-321.png!
>
>
>
>
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