Hi Stephane,
I mean running spark sql job concurrently via %spark.sql just by
setting zeppelin.spark.concurrentSQL
to be true.
See the details here
http://zeppelin.apache.org/docs/0.9.0-preview1/interpreter/spark.html#sparksql
于2020年7月22日周三 上午12:21写道：
> Hi Jeff,
>
>
>
> * You can also run mult
Hi Jeff,
You can also run multiple spark sql jobs concurrently in one spark app
Can you please elaborate on this? What I see (with Zeppelin 0.8) is that with
shared interpreter, each job is ran one after one. When going to one
interpreter per user, many users can run a job at the same tim
Regarding how many spark apps, it depends on the interpreter binding mode,
you can refer to this document.
http://zeppelin.apache.org/docs/0.9.0-preview1/usage/interpreter/interpreter_binding_mode.html
Internally, each spark app run a scala shell to execute scala code and
python shell to execute py
Hello,
I'm looking for documentation to better understand pyspark/scala notebook
execution in Spark. I typically see application runtimes that can be very
long, is there always a spark "application" running for a notebook or
zeppelin session? Those that are not actually being run in zeppelin
typ
I didn't compile it myself, I just use binaries that Jeff created for
preview2. My point is that it worked out of box in preview1, and previous
versions, and should continue be the same, otherwise it's a very breaking
change that requires that people know about that...
On Tue, Jul 21, 2020 at 11:4
That's right, In that PR, I exclude hadoop jars from zeppelin distribution,
so that we can support both hadoop2 and hadoop3 (user could set
USE_HADOOP=true in zeppelin-env.sh, so that zeppelin run command `hadoop
classpath` and put all the hadoop jars in classpath of zeppelin.
But for this issue,
Hi Alex,
It seems that Hadoop classes are missing. Do you include Hadoop jars
with "-P include-hadoop"?
I think it's related to
https://github.com/apache/zeppelin/commit/6fa79a9fc743f2b4321ac9e8713b3380bb4d64c9#diff-600376dffeb79835ede4a0b285078036.
Philipp
Am 21.07.20 um 11:28 schrieb Al
Hi Jeff
I've found another issue in both rc1 & rc2 - if you don't specify the
SPARK_HOME, then the default Spark interpreter doesn't start with following
error if I execute the code for reading from Cassandra:
%spark
import org.apache.spark.sql.cassandra._
val data = spark.read.cassandraFormat("
