Edward, Thanks for your reply. Can you please tell me the query performance of Hive-parquet against Vertica. Can Hive -parquet match against Vertica's retrieval performance, as I have been told Vertica is also compressed columnar format and is fast? What if I query against some 50 millions of rows , which one will be faster?
And moreover is Impala open source ? In some blogs I have seen Impala as open source but in some it says Impala as Cloudera proprietary engine. Ultimately, I want to use Hive -parquet but need to show that it is better than Vertica, a few microseconds here and there would be fine. I don't have access to Vertica. Thanks shashi On Sun, Jan 4, 2015 at 1:07 AM, Edward Capriolo <edlinuxg...@gmail.com> wrote: > Hive is the only system that can store and query xml directly, with the > help of different serde's or input formats. > > Impala and Vertical have more standard schema systems that do not support > Collections like List, Map, Struct or nested collections you might need to > store and process a complex XML document. > > Parquet (A storage format that works with Hive and Impala can support > List,Map, Structs) but he the Impala engine can not access these at the > moment. Last I checked impala refuses to read tables that have one of these > elements ( instead of skipping them). > > It sounds like you want to do one of a few things: > 1) Normalize your xml into a table and then you can use Vertica, Hive, or > Imapa > 2) Write your data using using an Parquet (to handle nested objects ) and > Hive to query it.(Hopefully then when Impala adds collection support you > can switch over. > > But mostly you need to do more research. > > Edward > > On Sat, Jan 3, 2015 at 2:15 PM, Shashidhar Rao <raoshashidhar...@gmail.com > > wrote: > >> Hi, >> >> Can someone help me with insights into Hive with parquet vs Vertica >> comparison. >> >> I need to store large xml data into one these database so please help me >> with query performance. >> >> Is Impala opensource and can we use it without Cloudera license. >> >> Thanks >> Shashi >> >> >> >
