Do the permissions on the hive table files on HDFS correspond with what the spark user is able to read? This might arise from spark being run as different users.
On Wed, Aug 7, 2019 at 3:15 PM Rishikesh Gawade <rishikeshg1...@gmail.com> wrote: > Hi, > I did not explicitly create a Hive Context. I have been using the > spark.sqlContext that gets created upon launching the spark-shell. > Isn't this sqlContext same as the hiveContext? > Thanks, > Rishikesh > > On Wed, Aug 7, 2019 at 12:43 PM Jörn Franke <jornfra...@gmail.com> wrote: > >> Do you use the HiveContext in Spark? Do you configure the same options >> there? Can you share some code? >> >> Am 07.08.2019 um 08:50 schrieb Rishikesh Gawade <rishikeshg1...@gmail.com >> >: >> >> Hi. >> I am using Spark 2.3.2 and Hive 3.1.0. >> Even if i use parquet files the result would be same, because after all >> sparkSQL isn't able to descend into the subdirectories over which the table >> is created. Could there be any other way? >> Thanks, >> Rishikesh >> >> On Tue, Aug 6, 2019, 1:03 PM Mich Talebzadeh <mich.talebza...@gmail.com> >> wrote: >> >>> which versions of Spark and Hive are you using. >>> >>> what will happen if you use parquet tables instead? >>> >>> HTH >>> >>> Dr Mich Talebzadeh >>> >>> >>> >>> LinkedIn * >>> https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw >>> <https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw>* >>> >>> >>> >>> http://talebzadehmich.wordpress.com >>> >>> >>> *Disclaimer:* Use it at your own risk. Any and all responsibility for >>> any loss, damage or destruction of data or any other property which may >>> arise from relying on this email's technical content is explicitly >>> disclaimed. The author will in no case be liable for any monetary damages >>> arising from such loss, damage or destruction. >>> >>> >>> >>> >>> On Tue, 6 Aug 2019 at 07:58, Rishikesh Gawade <rishikeshg1...@gmail.com> >>> wrote: >>> >>>> Hi. >>>> I have built a Hive external table on top of a directory 'A' which has >>>> data stored in ORC format. This directory has several subdirectories inside >>>> it, each of which contains the actual ORC files. >>>> These subdirectories are actually created by spark jobs which ingest >>>> data from other sources and write it into this directory. >>>> I tried creating a table and setting the table properties of the same >>>> as *hive.mapred.supports.subdirectories=TRUE* and >>>> *mapred.input.dir.recursive**=TRUE*. >>>> As a result of this, when i fire the simplest query of *select >>>> count(*) from ExtTable* via the Hive CLI, it successfully gives me the >>>> expected count of records in the table. >>>> However, when i fire the same query via sparkSQL, i get count = 0. >>>> >>>> I think the sparkSQL isn't able to descend into the subdirectories for >>>> getting the data while hive is able to do so. >>>> Are there any configurations needed to be set on the spark side so that >>>> this works as it does via hive cli? >>>> I am using Spark on YARN. >>>> >>>> Thanks, >>>> Rishikesh >>>> >>>> Tags: subdirectories, subdirectory, recursive, recursion, hive external >>>> table, orc, sparksql, yarn >>>> >>> -- *Patrick McCarthy * Senior Data Scientist, Machine Learning Engineering Dstillery 470 Park Ave South, 17th Floor, NYC 10016
