Credits
This post is nothing but reproduce of work done here at AmpLabs. If you want latest and detailed read i suggest you to go there.
Bigdata world is so beautiful , the research in this field is driving at such a fast pace that eventually BigData is no more synonymous with long running queries , its becoming LiveData everywhere.
The work compares the computation time of Redshift , Hive , Impala , Shark with different types of queries
The performance of Shark in memory has been consistent in all 4 types. It would be interesting to see the comparison when Hive 0.11 is used as it also adds few performance improvements driven by work at Hortonworks.
This post is nothing but reproduce of work done here at AmpLabs. If you want latest and detailed read i suggest you to go there.
Bigdata world is so beautiful , the research in this field is driving at such a fast pace that eventually BigData is no more synonymous with long running queries , its becoming LiveData everywhere.
The work compares the computation time of Redshift , Hive , Impala , Shark with different types of queries
The performance of Shark in memory has been consistent in all 4 types. It would be interesting to see the comparison when Hive 0.11 is used as it also adds few performance improvements driven by work at Hortonworks.
