I don't think we should drop support for Scala 2.10, or make it harder in
terms of operations for people to upgrade.
If there are further objections, I'm going to bump remove the 1.7 version
and retarget things to 2.0 on JIRA.
On Wed, Nov 25, 2015 at 12:54 AM, Sandy Ryza
wrote:
> I see. My co
For the 2nd use case, can you save the result for first 29 days, then just get
the last day result and add yourself ? This can be done outside of spark. Does
that work for you
Sent from my iPad
> On Nov 25, 2015, at 9:46 PM, Sachith Withana wrote:
>
> Hi folks!
>
> I'm wondering if Sparks
Hi folks!
I'm wondering if Sparks supports or hopes to support incremental data
analysis.
There are few use cases that prompted me to wonder.
ex: If we need to summarize last 30 days worth of data everyday,
1. Does Spark support time range based query execution ?
select * from foo where timesta
Spark 1.5.2.
在 2015-11-26 13:19:39,"张志强(旺轩)" 写道:
What’s your spark version?
发件人: wyphao.2007 [mailto:wyphao.2...@163.com]
发送时间: 2015年11月26日 10:04
收件人: user
抄送:dev@spark.apache.org
主题: Spark checkpoint problem
I am test checkpoint to understand how it works, My code as following:
scala> v
Hi Everyone
I noticed that spark ec2 script is outdated.
How to add 1.5.2 support to ec2/spark_ec2.py?
What else (except of updating spark version in the script) should be done
to add 1.5.2 support?
We also need to update scala to 2.10.4 (currently it's 2.10.3)
Alex
What’s your spark version?
发件人: wyphao.2007 [mailto:wyphao.2...@163.com]
发送时间: 2015年11月26日 10:04
收件人: user
抄送: dev@spark.apache.org
主题: Spark checkpoint problem
I am test checkpoint to understand how it works, My code as following:
scala> val data = sc.parallelize(List("a", "b",
I am test checkpoint to understand how it works, My code as following:
scala> val data = sc.parallelize(List("a", "b", "c"))
data: org.apache.spark.rdd.RDD[String] = ParallelCollectionRDD[0] at
parallelize at :15
scala> sc.setCheckpointDir("/tmp/checkpoint")
15/11/25 18:09:07 WARN spark.Sp
Seems to be some new thing with recent JDK updates according to the
intertubes. This patch seems to work around it:
---
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/HyperLogLogPlusPlus.scala
+++
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expr
$ java -version
java version "1.7.0_67"
Java(TM) SE Runtime Environment (build 1.7.0_67-b01)
(On Linux.) It's not that particular suite, though, it's anything I do
that touches Spark SQL...
On Wed, Nov 25, 2015 at 4:54 PM, Josh Rosen wrote:
> I think I've also seen this issue as well, but in a d
I think I've also seen this issue as well, but in a different suite. I
wasn't able to easily get to the bottom of it, though. What JDK / JRE are
you using? I'm on
Java(TM) SE Runtime Environment (build 1.7.0_65-b17)
Java HotSpot(TM) 64-Bit Server VM (build 24.65-b04, mixed mode)
on OSX.
On Wed,
I've been running into this error when running Spark SQL recently; no
matter what I try (completely clean build or anything else) doesn't
seem to fix it. Anyone has some idea of what's wrong?
[info] Exception encountered when attempting to run a suite with class
name: org.apache.spark.sql.executio
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You can even use it without spark as well (besides local). For example i
have used the following algo in some web app:
https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/mllib/classification/NaiveBayes.scala
Essentially some algorithms (i havent checked them all) the
Hi,
I am test checkpoint to understand how it works, My code as following:
scala> val data = sc.parallelize(List("a", "b", "c"))
data: org.apache.spark.rdd.RDD[String] = ParallelCollectionRDD[0] at
parallelize at :15
scala> sc.setCheckpointDir("/tmp/checkpoint")
15/11/25 18:09:07 WARN spark
I see. My concern is / was that cluster operators will be reluctant to
upgrade to 2.0, meaning that developers using those clusters need to stay
on 1.x, and, if they want to move to DataFrames, essentially need to port
their app twice.
I misunderstood and thought part of the proposal was to drop
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