[jira] [Resolved] (HIVE-10149) Shuffle Hive data before storing in Parquet

["Aihua Xu (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/HIVE-10149?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Aihua Xu resolved HIVE-10149.
-----------------------------
    Resolution: Not A Problem

 HIVE-6455 already addressed this issue. To get around the OOM, we need to set hive.optimize.sort.dynamic.partition to true so that the data is sorted by partition key and at one time only one partition needs to be accessed.  

> Shuffle Hive data before storing in Parquet
> -------------------------------------------
>
>                 Key: HIVE-10149
>                 URL: https://issues.apache.org/jira/browse/HIVE-10149
>             Project: Hive
>          Issue Type: Improvement
>    Affects Versions: 1.1.0
>            Reporter: Sergio Peña
>            Assignee: Aihua Xu
>         Attachments: data.txt, hive.log
>
>
> Hive can run into OOM (Out Of Memory) exceptions when writing many dynamic partitions to parquet because it creates too many open files at once and Parquet buffers an entire row group of data in memory for each open file. To avoid this in ORC, HIVE-6455 shuffles data for each partition so only one file is open at a time. We need to extend this support to Parquet and possibly the MR and Spark planners.
> Steps to reproduce:
> 1. Create a table and load some data that contains many many partitions (file {{data.txt}} attached on this ticket).
> {code}
> hive> create table t1_stage(id bigint, rdate string) row format delimited fields terminated by ' ';
> hive> load data local inpath 'data.txt' into table t1_stage;
> {code}
> 2. Create a Parquet table, and insert partitioned data from the t1_stage table.
> {noformat}
> hive> set hive.exec.dynamic.partition.mode=nonstrict;
> hive> create table t1_part(id bigint) partitioned by (rdate string) stored as parquet;
> hive> insert overwrite table t1_part partition(rdate) select * from t1_stage;
> Query ID = sergio_20150330163713_db3afe74-d1c7-4f0d-a8f1-f2137ddb64a4
> Total jobs = 3
> Launching Job 1 out of 3
> Number of reduce tasks is set to 0 since there's no reduce operator
> Starting Job = job_1427748520315_0006, Tracking URL = http://victory:8088/proxy/application_1427748520315_0006/
> Kill Command = /opt/local/hadoop/bin/hadoop job  -kill job_1427748520315_0006
> Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 0
> 2015-03-30 16:37:19,065 Stage-1 map = 0%,  reduce = 0%
> 2015-03-30 16:37:43,947 Stage-1 map = 100%,  reduce = 0%
> Ended Job = job_1427748520315_0006 with errors
> Error during job, obtaining debugging information...
> Examining task ID: task_1427748520315_0006_m_000000 (and more) from job job_1427748520315_0006
> Task with the most failures(4): 
> -----
> Task ID:
>   task_1427748520315_0006_m_000000
> URL:
>   http://0.0.0.0:8088/taskdetails.jsp?jobid=job_1427748520315_0006&tipid=task_1427748520315_0006_m_000000
> -----
> Diagnostic Messages for this Task:
> Error: Java heap space
> FAILED: Execution Error, return code 2 from org.apache.hadoop.hive.ql.exec.mr.MapRedTask
> MapReduce Jobs Launched: 
> Stage-Stage-1: Map: 1   HDFS Read: 0 HDFS Write: 0 FAIL
> Total MapReduce CPU Time Spent: 0 msec
> {noformat}



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