Re: Welcoming some new committers and PMC members

Congratulations all. On Tue, 10 Sep 2019 at 7:27 AM, Haibo wrote: > congratulations~ > > > > 在2019年09月10日 09:30，Joseph Torres > 写道： > > congratulations! > > On Mon, Sep 9, 2019 at 6:27 PM 王 斐 wrote: > >> congratulations！ >> >> 获取 Outlook for iOS >> >>

Re: Support SqlStreaming in spark

Hi All, I think there are few more updates are added in the design document compare to last document where few folks has reviewed and provided inputs., requesting all experts to review the design document and help us to baseline the design for the SPIP 'Support SQL streaming' in spark

Re: scheduler braindump: architecture, gotchas, etc.

Thanks Li and Imran for providing us an overview about one of the complex module in spark  Excellent sharing. Regards Sujith. On Mon, 4 Feb 2019 at 10:54 PM, Xiao Li wrote: > Thank you, Imran! > > Also, I attached the slides of "Deep Dive: Scheduler of Apache Spark". > > Cheers, > > Xiao > >

Re: welcome a new batch of committers

Great news Congrats all for achieving the feat !!! On Wed, 3 Oct 2018 at 2:29 PM, Reynold Xin wrote: > Hi all, > > The Apache Spark PMC has recently voted to add several new committers to > the project, for their contributions: > > - Shane Knapp (contributor to infra) > - Dongjoon Hyun

Re: Welcome Zhenhua Wang as a Spark committer

Congratulations zhenhua for this great achievement. On Mon, 2 Apr 2018 at 11:05 AM, Denny Lee wrote: > Awesome - congrats Zhenhua! > > On Sun, Apr 1, 2018 at 10:33 PM 叶先进 wrote: > >> Big congs. >> >> > On Apr 2, 2018, at 1:28 PM, Wenchen Fan

Re: Regarding NimbusDS JOSE JWT jar 3.9 security vulnerability

Hi Steve, While we are building spark 2.1 version this particular JWT jar is getting added as part of transitive dependency of Hadoop-auth-2.7.2 project. I discussed with one of the Hadoop pmc, he will analyse the impact of this particular issue in Hadoop . Once I will get more information I

Re: sessionState could not be accessed in spark-shell command line

Hi, may I know which version of spark you are using, in 2.2 I tried with below query in spark-shell for viewing the logical plan and it's working fine spark.sql("explain extended select * from table1") The above query you can use for seeing logical plan. Thanks, Sujith On Thu, 7 Sep 2017

Limit Query Performance Suggestion

When limit is being added in the terminal of the physical plan there will be possibility of memory bottleneck if the limit value is too large and system will try to aggregate all the partition limit values as part of single partition. Description: Eg: create table src_temp as select * from src