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GunnerEP
Obsidian | Level 7

Hello All,

 

I am connecting to hadoop & writing a SAS dataset to hadoop using a libname statement.

 

libname hdptgt hadoop server=&server port=10000 schema=sample config="&hadoop_config_file"; /*parameters passed from unix*/

 

/** sas code **/

data hdptgt.main_table;

merge main_table sub_table;

by rec_id;

run;

 

Log resolution:-

NOTE: There were 290000000 observations read from the data set WORK.MAIN_TABLE.
NOTE: There were 10000000 observations read from the data set WORK.SUB_TABLE.
NOTE: The data set HDP.MAIN_TABLE has 290000000 observations and 50 variables.

 

real time           8:30:04.19

cpu time            34:31.04

 

This takes around 8 hrs 30 mins. Is there anything i could do to run this fast ? any help would be appreciated.

2 REPLIES 2
LinusH
Tourmaline | Level 20

Typically, on would use BULKLOAD to speed up RDBMS write operations.

Unfortunately, for Hive this is just a syntax support, there is the same underlying process that is used.

I would start with adding 

options msglevel=i sastrace=',,,d' sastraceloc=saslog nostsuffix;

to your program to better analyze what's going on on the Hive side.

Other than that, I think this is a matter of hdfs/Hive optimization issue (given that you can rule out network bottlenecks, or local SAS session ones during read/merge operation).

Data never sleeps

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