Re: bug: can not run Ipython notebook on cluster
What a BEAR! The following recipe worked for me. (took a couple of days
hacking).
I hope this improves the out of the box experience for others
Andy
My test program is now
In [1]:
from pyspark import SparkContext
textFile = sc.textFile("file:///home/ec2-user/dataScience/readme.md")
In [2]:
print("hello world²)
hello world
In [3]:
textFile.take(3)
Out[3]:
[' hello world', '']
Installation instructions
1. Ssh to cluster master
2. Sudo su
3. install python3.4 on all machines
```
yum install -y python34
bash-4.2# which python3
/usr/bin/python3
pssh -h /root/spark-ec2/slaves yum install -y python34
```
4. Install pip on all machines
```
yum list available |grep pip
yum install -y python34-pip
find /usr/bin -name "*pip*" -print
/usr/bin/pip-3.4
pssh -h /root/spark-ec2/slaves yum install -y python34-pip
```
5. install python on master
```
/usr/bin/pip-3.4 install ipython
pssh -h /root/spark-ec2/slaves /usr/bin/pip-3.4 install python
```
6. Install python develop stuff and jupiter on master
```
yum install -y python34-devel
/usr/bin/pip-3.4 install jupyter
```
7. Set up update spark-env.sh on all machine so by default we use python3.4
```
cd /root/spark/conf
printf "\n# Set Spark Python version\nexport PYSPARK_PYTHON=python3.4\n" >>
/root/spark/conf/spark-env.sh
for i in `cat slaves` ; do scp spark-env.sh
root@$i:/root/spark/conf/spark-env.sh; done
```
8. Restart cluster
```
/root/spark/sbin/stop-all.sh
/root/spark/sbin/start-all.sh
```
Running ipython notebook
1. set up an ssh tunnel on your local machine
ssh -i $KEY_FILE -N -f -L localhost::localhost:7000
ec2-user@$SPARK_MASTER
2. Log on to cluster master and start ipython notebook server
```
export PYSPARK_PYTHON=python3.4
export PYSPARK_DRIVER_PYTHON=python3.4
export IPYTHON_OPTS="notebook --no-browser --port=7000"
$SPARK_ROOT/bin/pyspark --master local[2]
```
3. On your local machine open http://localhost:
From: Andrew Davidson <a...@santacruzintegration.com>
Date: Friday, November 6, 2015 at 2:18 PM
To: "user @spark" <user@spark.apache.org>
Subject: bug: can not run Ipython notebook on cluster
> Does anyone use iPython notebooks?
>
> I am able to use it on my local machine with spark how ever I can not get it
> work on my cluster.
>
>
> For unknown reason on my cluster I have to manually create the spark context.
> My test code generated this exception
>
> Exception: Python in worker has different version 2.7 than that in driver 2.6,
> PySpark cannot run with different minor versions
>
> On my mac I can solve the exception problem by setting
>
> export PYSPARK_PYTHON=python3
>
> export PYSPARK_DRIVER_PYTHON=python3
>
> IPYTHON_OPTS=notebook $SPARK_ROOT/bin/pyspark
>
>
>
> On my cluster I set the values to python2.7. And PYTHON_OPTS=³notebook
> no-browser port=7000² . I connect using a ssh tunnel from my local machine.
>
>
>
> I also tried installing python 3 , pip, ipython, and jupyter in/on my cluster
>
>
>
> I tried adding export PYSPARK_PYTHON=python2.7 to the
> /root/spark/conf/spark-env.sh on all my machines
>
>
> from pyspark import SparkContext
> textFile = sc.textFile("file:///home/ec2-user/dataScience/readme.md")
> textFile.take(3
>
>
> In [1]:
> from pyspark import SparkContext
> sc = SparkContext("local", "Simple App")
> textFile = sc.textFile("file:///home/ec2-user/dataScience/readme.md")
> textFile.take(3)
> ---Py4
> JJavaError Traceback (most recent call last)
> in () 2 sc = SparkContext("local",
> "Simple App") 3 textFile =
> sc.textFile("file:///home/ec2-user/dataScience/readme.md")> 4
> textFile.take(3)/root/spark/python/pyspark/rdd.py in take(self, num) 1297
> 1298 p = range(partsScanned, min(partsScanned + numPartsToTry,
> totalParts))-> 1299 res = self.context.runJob(self,
> takeUpToNumLeft, p) 13001301 items +=
> res/root/spark/python/pyspark/context.py in runJob(self, rdd, partitionFunc,
> partitions, allowLocal)914 # SparkContext#runJob.915
> mappedRDD = rdd.mapPartitions(partitionFunc)--> 916 port =
> self._jvm.PythonRDD.runJob(self._jsc.sc(), mappedRDD._jrdd, partitions)917
> return list(_load_from_socket(port, mappedRDD._jrdd_deserializer))918
> /root/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py in
> __call__(self, *args)536 answer =
> self.gateway_client.send_command(command)537 return_value =
> get_return_value(answer, self.gateway_client,
> --> 538 self.target_id, self.n
bug: can not run Ipython notebook on cluster
Does anyone use iPython notebooks?
I am able to use it on my local machine with spark how ever I can not get it
work on my cluster.
For unknown reason on my cluster I have to manually create the spark
context. My test code generated this exception
Exception: Python in worker has different version 2.7 than that in driver
2.6, PySpark cannot run with different minor versions
On my mac I can solve the exception problem by setting
export PYSPARK_PYTHON=python3
export PYSPARK_DRIVER_PYTHON=python3
IPYTHON_OPTS=notebook $SPARK_ROOT/bin/pyspark
On my cluster I set the values to python2.7. And PYTHON_OPTS=³notebook
no-browser port=7000² . I connect using a ssh tunnel from my local
machine.
I also tried installing python 3 , pip, ipython, and jupyter in/on my
cluster
I tried adding export PYSPARK_PYTHON=python2.7 to the
/root/spark/conf/spark-env.sh on all my machines
from pyspark import SparkContext
textFile = sc.textFile("file:///home/ec2-user/dataScience/readme.md")
textFile.take(3
In [1]:
from pyspark import SparkContext
sc = SparkContext("local", "Simple App")
textFile = sc.textFile("file:///home/ec2-user/dataScience/readme.md")
textFile.take(3)
---
Py4JJavaError Traceback (most recent call last)
in ()
2 sc = SparkContext("local", "Simple App")
3 textFile =
sc.textFile("file:///home/ec2-user/dataScience/readme.md")
> 4 textFile.take(3)
/root/spark/python/pyspark/rdd.py in take(self, num)
1297
1298 p = range(partsScanned, min(partsScanned +
numPartsToTry, totalParts))
-> 1299 res = self.context.runJob(self, takeUpToNumLeft, p)
1300
1301 items += res
/root/spark/python/pyspark/context.py in runJob(self, rdd, partitionFunc,
partitions, allowLocal)
914 # SparkContext#runJob.
915 mappedRDD = rdd.mapPartitions(partitionFunc)
--> 916 port = self._jvm.PythonRDD.runJob(self._jsc.sc(),
mappedRDD._jrdd, partitions)
917 return list(_load_from_socket(port,
mappedRDD._jrdd_deserializer))
918
/root/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py in
__call__(self, *args)
536 answer = self.gateway_client.send_command(command)
537 return_value = get_return_value(answer, self.gateway_client,
--> 538 self.target_id, self.name)
539
540 for temp_arg in temp_args:
/root/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py in
get_return_value(answer, gateway_client, target_id, name)
298 raise Py4JJavaError(
299 'An error occurred while calling {0}{1}{2}.\n'.
--> 300 format(target_id, '.', name), value)
301 else:
302 raise Py4JError(
Py4JJavaError: An error occurred while calling
z:org.apache.spark.api.python.PythonRDD.runJob.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0
in stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0
(TID 0, localhost): org.apache.spark.api.python.PythonException: Traceback
(most recent call last):
File "/root/spark/python/lib/pyspark.zip/pyspark/worker.py", line 64, in
main
("%d.%d" % sys.version_info[:2], version))
Exception: Python in worker has different version 2.7 than that in driver
2.6, PySpark cannot run with different minor versions
at
org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:166)
at
org.apache.spark.api.python.PythonRunner$$anon$1.(PythonRDD.scala:207)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:88)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:11
42)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:6
17)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at
org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGSchedu
ler$$failJobAndIndependentStages(DAGScheduler.scala:1283)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGSched
uler.scala:1271)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGSched
uler.scala:1270)
at
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:5
9)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at
