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From Debarshi Basak <>
Subject Re: Compressed data storage in HDFS - Error
Date Wed, 06 Jun 2012 09:15:15 GMT
<font face="Default Sans Serif,Verdana,Arial,Helvetica,sans-serif" size="2">Yes performance
is better because your IO is less when your data is less<BR><BR><BR>Debarshi
Basak<BR>Tata Consultancy Services<BR>Mailto:<BR>Website:<BR>____________________________________________<BR>Experience
certainty. IT Services<BR>Business Solutions<BR>Outsourcing<BR>____________________________________________<BR><BR><FONT
color=#990099>-----Sreenath Menon <SREENATHMENON5@GMAIL.COM>wrote: -----</FONT>

black 2px solid; MARGIN-RIGHT: 0px">To:<BR>From: Sreenath Menon
&lt;;<BR>Date: 06/06/2012 02:20PM<BR>Subject:
Compressed data storage in HDFS - Error<BR><BR>I would like to compress my data
in the HDFS using some Hive commands.<BR>Step followed: (data already residing in table
sample)<BR><BR>create table rc_lzo like sample;<BR>SET hive.exec.compress.output=true;<BR>SET
mapred.output.compression.codec=com.hadoop.compression.lzo.LzoCodec;<BR>insert overwrite
table rc_lzo select * from sample;<BR><BR>Error:<BR>Compression codec com\.hadoop\.compression\.lzo\.LzoCodec
was not found<BR><BR>1)What do I need to do to use Lzo as well as other compression
methods?<BR><BR>2)Heard somewhere that :Using compressed data will produce better
results than uncompressed data in some cases. How can this be, as there is always a compression
and decompression time allotted with compression methods. Any truth in this, if so how ? Can
understand how there are better results when using compression between mappers-to-reducers
and in between map-reduce jobs.<BR><BR>Thanks and Regards<BR>Sreenath Mullassery<BR></BLOCKQUOTE></DIV>
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