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From "Chaozhong Yang (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (HIVE-16972) FetchOperator: filter out inputSplits which length is zero
Date Tue, 27 Jun 2017 08:07:00 GMT

     [ https://issues.apache.org/jira/browse/HIVE-16972?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Chaozhong Yang updated HIVE-16972:
----------------------------------
    Description: 
* Background
   We can describe the basic work flow of  common HQL query as follows:
  1. compile and execute
  2. fetch results
  In many cases, we don't need to  worry about the issues fetching results from HDFS(iff there
are mapreduce jobs generated in planning step). However, the number of results files on HDFS
and data distribution will affect the final status of HQL query, especially for HiveServer2.
We have some map-only queries, e.g: 
{code:sql}
select * from myTable where date > '20170101' and date <= '20170301' and id = 88 and
type=99;
{code}
    This query will generate more than 20,000 files(look at screenshot image uploaded) on
HDFS and most of those files are empty. Of course, they are very sparse. If we send TFetchResultsRequest
from HiveServer2 client with  some parameters(timeout: 90s, maxRows: 1024) , FetchOperator
can not fetch 1024 rows in 90 seconds and our HiveServer2 client will mark this TFetchResultsRequest
as timed out failure. Why? In fact, It's expensive to fetch results from empty file. In our
HDFS cluster( 5000+ DataNodes) , reading data from an empty file will cost almost 100 ms (100ms
* 1000 ==> 100s > 90s timeout). Obviously, we can filter out those empty files or splits
to speed up the process of FetchResults. 

  

  was:
* Background
   We can describe the basic work flow of  common HQL query as follows:
  1. compile and execute
  2. fetch results
  In many cases, we don't need to  worry about the issues fetching results from HDFS(iff there
are mapreduce jobs generated in planning step). However, the number of results files on HDFS
and data distribution will affect the final status of HQL query, especially for HiveServer2.
We have some map-only queries, e.g: 
{code:sql}
select * from myTable where date > '20170201' and date <= '20170301' and id = 88;
{code}
    This query will generate more than 10,000 files on HDFS and most of those files are empty.
Of course, they are very sparse. If we send TFetchResultsRequest from HiveServer2 client with
 some parameters(timeout: 90s, maxRows: 1024) , FetchOperator can not fetch 1024 rows in 90
seconds and our HiveServer2 client will mark this TFetchResultsRequest as timed out failure.
Why? In fact, It's expensive to fetch results from empty file. In our HDFS cluster( 5000+
DataNodes) , reading data from an empty file will cost almost 100 ms (100ms * 1000 ==>
100s > 90s timeout). Obviously, we can filter out those empty files or splits to speed
up the process of FetchResults. 



> FetchOperator: filter out inputSplits which length is zero
> ----------------------------------------------------------
>
>                 Key: HIVE-16972
>                 URL: https://issues.apache.org/jira/browse/HIVE-16972
>             Project: Hive
>          Issue Type: Improvement
>          Components: HiveServer2, Physical Optimizer, Query Planning
>    Affects Versions: 2.1.0, 2.1.1
>            Reporter: Chaozhong Yang
>            Assignee: Chaozhong Yang
>             Fix For: 2.1.2
>
>         Attachments: HIVE-16972.patch, screenshot-1.png
>
>
> * Background
>    We can describe the basic work flow of  common HQL query as follows:
>   1. compile and execute
>   2. fetch results
>   In many cases, we don't need to  worry about the issues fetching results from HDFS(iff
there are mapreduce jobs generated in planning step). However, the number of results files
on HDFS and data distribution will affect the final status of HQL query, especially for HiveServer2.
We have some map-only queries, e.g: 
> {code:sql}
> select * from myTable where date > '20170101' and date <= '20170301' and id = 88
and type=99;
> {code}
>     This query will generate more than 20,000 files(look at screenshot image uploaded)
on HDFS and most of those files are empty. Of course, they are very sparse. If we send TFetchResultsRequest
from HiveServer2 client with  some parameters(timeout: 90s, maxRows: 1024) , FetchOperator
can not fetch 1024 rows in 90 seconds and our HiveServer2 client will mark this TFetchResultsRequest
as timed out failure. Why? In fact, It's expensive to fetch results from empty file. In our
HDFS cluster( 5000+ DataNodes) , reading data from an empty file will cost almost 100 ms (100ms
* 1000 ==> 100s > 90s timeout). Obviously, we can filter out those empty files or splits
to speed up the process of FetchResults. 
>   



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