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From Mich Talebzadeh <>
Subject RE: Difference between RC file format & Parquet file format
Date Thu, 18 Feb 2016 16:39:01 GMT

ORC has what is called storage index built in that provide data +

It provide stats at file, stripe and rowgroup (batches of rows) levels.
In terms of efficiency, for Data warehouse applications it is best
format I believe 

On 18/02/2016 07:38, Abhishek Dubey wrote: 

> I think it's fair to say that one of the main differences is the representation of nesting
> PARQUET uses Dremel's repetition and definition levels, which is an extremely efficient
representation of nested structure that has the 
> added benefit of being easy to embed into the column data itself; 
> Julien wrote an excellent blog post that explains the details:

> ORCFILE on the other hand uses separate "counter" columns, which means that for nested
structures you need to read those counter columns in 
> addition to the data columns you care about in order to recreate the nesting structure;
this increases the required amount of random I/O. 
> Also, Parquet is natively supported in a number of popular Hadoop frameworks: Pig, Impala,
Hive, MR, Cascading. 
> Source :!topic/parquet-dev/0IdtSLdIINQ [1] 
> FROM: Ravi Prasad [] 
> SENT: Thursday, February 18, 2016 9:06 AM
> TO:
> SUBJECT: Difference between RC file format & Parquet file format 
> Hi all, 
> Can you please let me know, 
> How the RC file format is different from the Parquet file format. 
> Both are column oriented file format, then what are the difference.
> -- 
> ----------------------------------------------
> Regards,


Dr Mich Talebzadeh


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