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

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 structure. 
> 
> 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: 
> https://blog.twitter.com/2013/dremel-made-simple-with-parquet 
> 
> 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 : https://groups.google.com/forum/#!topic/parquet-dev/0IdtSLdIINQ [1] 
> 
> THANKS & REGARDS,
> ABHISHEK DUBEY 
> 
> FROM: Ravi Prasad [mailto:raviprasa...@gmail.com] 
> SENT: Thursday, February 18, 2016 9:06 AM
> TO: user@hive.apache.org
> 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,
> RAVI PRASAD. T

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