Which alternatives to ThriftServer do we really have? If ThriftServer is not there anymore, there is no other way to connect to Spark SQL using JDBC.... and this is the primary way for connecting BI tools to Spark SQL. Do I miss something?
The question is, if Spark would like to be the tool, used for the online queries... Alternative is to process/enrich data with Spark, push it somewhere and use other tools for actual queries... Do you think, it is better to use Spark in this way ? On Fri, Oct 26, 2018 at 7:48 PM Sean Owen <sro...@gmail.com> wrote: > Maybe that's what I really mean (you can tell I don't follow the Hive part > closely) > In my travels, indeed the thrift server has been viewed as an older > solution to a problem probably better met by others. > From my perspective it's worth dropping, but, that's just anecdotal. > Any other arguments for or against the thrift server? > > On Fri, Oct 26, 2018 at 12:30 PM Marco Gaido <marcogaid...@gmail.com> > wrote: > >> Hi all, >> >> one big problem about getting rid of the Hive fork is the thriftserver, >> which relies on the HiveServer from the Hive fork. >> We might migrate to an apache/hive dependency, but not sure this would >> help that much. >> I think a broader topic would be the actual opportunity of having a >> thriftserver directly into Spark. It has many well-known limitations (not >> fault tolerant, no security/impersonation, etc.etc.) and there are other >> project which target to provide a thrift/JDBC interface to Spark. Just to >> be clear I am not proposing to remove the thriftserver in 3.0, but maybe it >> is something we could evaluate in the long term. >> >> Thanks, >> Marco >> >> >> Il giorno ven 26 ott 2018 alle ore 19:07 Sean Owen <sro...@gmail.com> ha >> scritto: >> >>> OK let's keep this about Hive. >>> >>> Right, good point, this is really about supporting metastore versions, >>> and there is a good argument for retaining backwards-compatibility with >>> older metastores. I don't know how far, but I guess, as far as is practical? >>> >>> Isn't there still a lot of Hive 0.x test code? is that something that's >>> safe to drop for 3.0? >>> >>> And, basically, what must we do to get rid of the Hive fork? that seems >>> like a must-do. >>> >>> >>> >>> On Fri, Oct 26, 2018 at 11:51 AM Dongjoon Hyun <dongjoon.h...@gmail.com> >>> wrote: >>> >>>> Hi, Sean and All. >>>> >>>> For the first question, we support only Hive Metastore from 1.x ~ 2.x. >>>> And, we can support Hive Metastore 3.0 simultaneously. Spark is designed >>>> like that. >>>> >>>> I don't think we need to drop old Hive Metastore Support. Is it >>>> for avoiding Hive Metastore sharing between Spark2 and Spark3 clusters? >>>> >>>> I think we should allow that use cases, especially for new Spark 3 >>>> clusters. How do you think so? >>>> >>>> >>>> For the second question, Apache Spark 2.x doesn't support Hive >>>> officially. It's only a best-effort approach in a boundary of Spark. >>>> >>>> >>>> http://spark.apache.org/docs/latest/sql-programming-guide.html#unsupported-hive-functionality >>>> >>>> http://spark.apache.org/docs/latest/sql-programming-guide.html#incompatible-hive-udf >>>> >>>> >>>> Not only the documented one, decimal literal(HIVE-17186) makes a query >>>> result difference even in the well-known benchmark like TPC-H. >>>> >>>> Bests, >>>> Dongjoon. >>>> >>>> PS. For Hadoop, let's have another thread if needed. I expect another >>>> long story. :) >>>> >>>> >>>> On Fri, Oct 26, 2018 at 7:11 AM Sean Owen <sro...@gmail.com> wrote: >>>> >>>>> Here's another thread to start considering, and I know it's been >>>>> raised before. >>>>> What version(s) of Hive should Spark 3 support? >>>>> >>>>> If at least we know it won't include Hive 0.x, could we go ahead and >>>>> remove those tests from master? It might significantly reduce the run time >>>>> and flakiness. >>>>> >>>>> It seems that maintaining even the Hive 1.x fork is untenable going >>>>> forward, right? does that also imply this support is almost certainly not >>>>> maintained in 3.0? >>>>> >>>>> Per below, it seems like it might even be hard to both support Hive 3 >>>>> and Hadoop 2 at the same time? >>>>> >>>>> And while we're at it, what's the + and - for simply only supporting >>>>> Hadoop 3 in Spark 3? Is the difference in client / HDFS API even that big? >>>>> Or what about focusing only on Hadoop 2.9.x support + 3.x support? >>>>> >>>>> Lots of questions, just interested now in informal reactions, not a >>>>> binding decision. >>>>> >>>>> On Thu, Oct 25, 2018 at 11:49 PM Dagang Wei <notificati...@github.com> >>>>> wrote: >>>>> >>>>>> Do we really want to switch to Hive 2.3? From this page >>>>>> https://hive.apache.org/downloads.html, Hive 2.3 works with Hadoop >>>>>> 2.x (Hive 3.x works with Hadoop 3.x). >>>>>> >>>>>> — >>>>>> You are receiving this because you were mentioned. >>>>>> Reply to this email directly, view it on GitHub >>>>>> <https://github.com/apache/spark/pull/21588#issuecomment-433285287>, >>>>>> or mute the thread >>>>>> <https://github.com/notifications/unsubscribe-auth/AAyM-sRygel3il6Ne4FafD5BQ7NDSJ7Mks5uopRlgaJpZM4Usweh> >>>>>> . >>>>>> >>>>>
