:50, Margus Roo wrote:
Hi
I tested |spark.streaming.receiver.maxRate and
||spark.streaming.backpressure.enabled settings using socketStream and
it works.|
|But if I am using nifi-spark-receiver
(https://mvnrepository.com/artifact/org.apache.nifi/nifi-spark-receiver)
then it does not using
|
||spark.streaming.receiver.maxRate
||
||any workaround?
||
||
Margus (margusja) Roo
http://margus.roo.ee
skype: margusja
https://www.facebook.com/allan.tuuring
+372 51 48 780
On 14/09/2017 09:57, Margus Roo wrote:
Hi
Using Spark 2.1.1.2.6-1.0-129 (from Hortonworks distro) and Scala
2.11.8 and Java 1.8.0_60
I
Hi
Using Spark 2.1.1.2.6-1.0-129 (from Hortonworks distro) and Scala 2.11.8
and Java 1.8.0_60
I have Nifi flow produces more records than Spark stream can work in
batch time. To avoid spark queue overflow I wanted to try spark
streaming backpressure (did not work for my) so back to the more
Hi
In example I submited python code to cluster:
in/spark-submit --master spark://nn1:7077 SocketListen.py
Now I discovered that I have to change something in SocketListen.py.
One way is stop older work and submit new one.
Is there way to change code in workers machines so that there no need to
Tnx for the workaround.
Margus (margusja) Roo
http://margus.roo.ee
skype: margusja
+372 51 480
On 16/03/15 06:20, Jeremy Freeman wrote:
Hi Margus, thanks for reporting this, I’ve been able to reproduce and
there does indeed appear to be a bug. I’ve created a JIRA and have a
fix ready, can hope
http://margus.roo.ee
skype: margusja
+372 51 480
On 14/03/15 09:05, Margus Roo wrote:
Hi
I try to understand example provided in
https://spark.apache.org/docs/1.2.1/mllib-linear-methods.html -
Streaming linear regression
Code:
import org.apache.spark._
import org.apache.spark.streaming._
i
Hi
I try to understand example provided in
https://spark.apache.org/docs/1.2.1/mllib-linear-methods.html -
Streaming linear regression
Code:
import org.apache.spark._
import org.apache.spark.streaming._
import org.apache.spark.mllib.linalg.Vectors
import org.apache.spark.mllib.regression.Labe
