Re: [VOTE] Release Apache Spark 2.3.3 (RC1)

2019-01-20 Thread Takeshi Yamamuro
Oh, sorry for that and I misunderstood the Apache release policy. Yea, its ok to keep the RC1 voting. Best, Takeshi On Mon, Jan 21, 2019 at 11:07 AM Sean Owen wrote: > OK, if it passes tests, I'm +1 on the release. > Can anyone else verify the tests pass? > > What is the reason for a new RC? I

Re: [VOTE] Release Apache Spark 2.3.3 (RC1)

2019-01-20 Thread Sean Owen
OK, if it passes tests, I'm +1 on the release. Can anyone else verify the tests pass? What is the reason for a new RC? I didn't see any other issues reported. On Sun, Jan 20, 2019 at 8:03 PM Takeshi Yamamuro wrote: > > Hi, all > > Thanks for the checks, Sean and Felix. > I'll start the next

Re: [VOTE] Release Apache Spark 2.3.3 (RC1)

2019-01-20 Thread Takeshi Yamamuro
Hi, all Thanks for the checks, Sean and Felix. I'll start the next vote as RC2 this Tuesday noon (PST). > Sean I re-run JavaTfIdfSuite on my env and it passed. I used `-Pyarn -Phadoop-2.7 -Phive -Phive-thriftserver -Pmesos -Psparkr` and run the tests on a EC2 instance below (I launched the new

Re: [VOTE] Release Apache Spark 2.3.3 (RC1)

2019-01-20 Thread Felix Cheung
+1 My focus is on R (sorry couldn’t cross validate what’s Sean is seeing) tested: reviewed doc R package test win-builder, r-hub Tarball/package signature From: Takeshi Yamamuro Sent: Thursday, January 17, 2019 6:49 PM To: Spark dev list Subject: [VOTE]

Re: [DISCUSS] Identifiers with multi-catalog support

2019-01-20 Thread Felix Cheung
+1 I like Ryan last mail. Thank you for putting it clearly (should be a spec/SPIP!) I agree and understand the need for 3 part id. However I don’t think we should make assumption that it must be or can only be as long as 3 parts. Once the catalog is identified (ie. The first part), the catalog

Re: [VOTE] Release Apache Spark 2.3.3 (RC1)

2019-01-20 Thread Sean Owen
I'm getting different errors when I run on a different machine; not quite the same. Things like: [ERROR] Errors: [ERROR] JavaTfIdfSuite.tfIdf:44 » Spark Job aborted due to stage failure: Task 0 in st... [ERROR] JavaTfIdfSuite.tfIdfMinimumDocumentFrequency:64 » Spark Job aborted due to sta...