Hi,
In this case it's much easier and faster to merge all files using this
command:
cat *.csv > output.csv
hive -e "load data local inpath 'output.csv' into table $table"
On 07.12.2011 07:00, Vikas Srivastava wrote:
hey if u having the same col of all the files then you can easily merge by
shell script
list=`*.csv`
$table=yourtable
for file in $list
do
cat $file>>new_file.csv
done
hive -e "load data local inpath '$file' into table $table"
it will merge all the files in single file then you can upload it in the
same query
On Tue, Dec 6, 2011 at 8:16 PM, Mohit Gupta
<success.mohit.gu...@gmail.com>wrote:
Hi Paul,
I am having the same problem. Do you know any efficient way of merging the
files?
-Mohit
On Tue, Dec 6, 2011 at 8:14 PM, Paul Mackles<pmack...@adobe.com> wrote:
How much time is it spending in the map/reduce phases, respectively? The
large number of files could be creating a lot of mappers which create a lot
of overhead. What happens if you merge the 2624 files into a smaller number
like 24 or 48. That should speed up the mapper phase significantly.****
** **
*From:* Savant, Keshav [mailto:keshav.c.sav...@fisglobal.com]
*Sent:* Tuesday, December 06, 2011 6:01 AM
*To:* user@hive.apache.org
*Subject:* Hive query taking too much time****
** **
Hi All,****
** **
My setup is ****
hadoop-0.20.203.0****
hive-0.7.1****
** **
I am having a total of 5 node cluster: 4 data nodes, 1 namenode (it is
also acting as secondary name node). On namenode I have setup hive with
HiveDerbyServerMode to support multiple hive server connection.****
** **
I have inserted plain text CSV files in HDFS using ‘LOAD DATA’ hive query
statements, total number of files is 2624 an their combined size is only
713 MB, which is very less from Hadoop perspective that can handle TBs of
data very easily.****
** **
The problem is, when I run a simple count query (i.e. *select count(*)
from a_table*), it takes too much time in executing the query.****
** **
For instance it takes almost 17 minutes to execute the said query if the
table has 950,000 rows, I understand that time is too much for executing a
query with only such small data. ****
This is only a dev environment and in production environment the number
of files and their combined size will move into millions and GBs
respectively.****
** **
On analyzing the logs on all the datanodes and namenode/secondary
namenode I do not find any error in them.****
** **
I have tried setting mapred.reduce.tasks to a fixed number also, but
number of reduce always remains 1 while number of maps is determined by
hive only.****
** **
Any suggestion what I am doing wrong, or how can I improve the
performance of hive queries? Any suggestion or pointer is highly
appreciated. ****
** **
Keshav****
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Best Regards,
Mohit Gupta
Software Engineer at Vdopia Inc.
