Hi. I have been hearing a fair bit about Parquet versus ORC tables.
In a nutshell I can say that Parquet is a predecessor to ORC (both provide columnar type storage) but I notice that it is still being used especially with Spark users. In mitigation it appears that Spark users are reluctant to use ORC despite the fact that with inbuilt Store Index it offers superior optimisation with data and stats at file, stripe and row group level. Both Parquet and ORC offer SNAPPY compression as well. ORC offers ZLIB as default. There may be other than technical reasons for this adaption, for example too much reliance on Hive plus the fact that it is easier to flatten Parquet than ORC (whatever that means). I for myself use either text files or ORC with Hive and Spark and don't really see any reason why I should adopt others like Avro, Parquet etc. Appreciate any verification or experience on this. Thanks , Dr Mich Talebzadeh LinkedIn * https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw <https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw>* http://talebzadehmich.wordpress.com
