cd /srv/jupyterhub/deploy
sudo git pull
sudo ./create_virtualenv.sh /srv/jupyterhub/venv

cd /srv/jupyterhub/deploy
for venv in $(ls -d /home/*/venv); do
    user=$(echo $venv | awk -F '/' '{print $3}')
    echo "Installing packages for $user"
    sudo -u $user $venv/bin/pip install \
        --upgrade \
        --no-index \
        --ignore-installed \
        --find-links=/srv/jupyterhub/deploy/artifacts/stretch/wheels \
        --requirement=/srv/jupyterhub/deploy/frozen-requirements.txt &
done

{
  "env": {
    "PYTHON_EXEC": "/usr/bin/python3",
    "PYSPARK_PYTHON": "/usr/bin/python3",
    "DEFAULT_INTERPRETER": "PySpark",
    "PYTHONPATH": "/usr/lib/spark2/python:/usr/lib/spark2/python/lib/py4j-0.10.6-src.zip",
    "__TOREE_OPTS__": "",
    "__TOREE_SPARK_OPTS__": "--name='Jupyter PySpark' --master=yarn --conf spark.executorEnv.PYTHONPATH=/usr/lib/spark2/python:/usr/lib/spark2/python/lib/py4j-0.10.6-src.zip",
    "SPARK_HOME": "/usr/lib/spark2"
  },
  "display_name": "Spark YARN - PySpark",
  "metadata": {},
  "language": "python",
  "interrupt_mode": "signal",
  "argv": [
    "/usr/local/share/jupyter/kernels/spark_yarn_pyspark/bin/run.sh",
    "--profile",
    "{connection_file}"
  ]
}

Reason: Container killed by YARN for exceeding memory limits. 2.1 GB of 2 GB physical memory used. Consider boosting spark.yarn.executor.memoryOverhead.

# # Counting Links in Wikipedias using a parquet DUMP


#Setup
import pandas as pd
sqlContext.sql('use wmf')


# Define UDF
from pyspark.sql.functions import udf
from pyspark.sql.types import IntegerType
import re

def getWikilinksNumber(wikitext): #UDF to get wikipedia pages titles
    links  = re.findall("\[\[(.*?)\]\]",wikitext) #get wikilinks
    if len(links) >=0:
        return len(links)
    else:
        return -1

udfGetWikilinksNumber = udf(getWikilinksNumber,IntegerType())

#Loading cawiki
df = spark.read.parquet('hdfs:///user/joal/wmf/data/wmf/mediawiki/wikitext/snapshot=2018-01/cawiki')
#Apply UDF
df2 = df.withColumn('numOfLinks',udfGetWikilinksNumber(df.revision_text))


df2.count()

#Get last revision ID until 2017/06/01 for all pages in namespace =0 , noredirect in cawiki

pages = sqlContext.sql('''SELECT page_id,MAX(revision_id) as rev_id FROM mediawiki_history  WHERE snapshot="2018-01" 
                     AND page_namespace=0 AND page_is_redirect=0 AND page_creation_timestamp < "2017-06-27" AND event_timestamp < "2017-06-27" AND  wiki_db='cawiki' GROUP BY page_id''')
pages.show()


#Join last revision with udf results

df3 = df2.select('numOfLinks','revision_id').join(pages.select('rev_id'),pages.rev_id == df2.revision_id)



df3.schema
result = df3.select('numOfLinks').toPandas()


Py4JJavaError                             Traceback (most recent call last)
<ipython-input-55-875f80eba6b8> in <module>()
      1 import pandas as pd
----> 2 d = df3.select('numOfLinks').toPandas()

/usr/lib/spark2/python/pyspark/sql/dataframe.py in toPandas(self)
   1964                 raise RuntimeError("%s\n%s" % (_exception_message(e), msg))
   1965         else:
-> 1966             pdf = pd.DataFrame.from_records(self.collect(), columns=self.columns)
   1967 
   1968             dtype = {}

/usr/lib/spark2/python/pyspark/sql/dataframe.py in collect(self)
    464         """
    465         with SCCallSiteSync(self._sc) as css:
--> 466             port = self._jdf.collectToPython()
    467         return list(_load_from_socket(port, BatchedSerializer(PickleSerializer())))
    468 

/usr/lib/spark2/python/lib/py4j-0.10.6-src.zip/py4j/java_gateway.py in __call__(self, *args)
   1158         answer = self.gateway_client.send_command(command)
   1159         return_value = get_return_value(
-> 1160             answer, self.gateway_client, self.target_id, self.name)
   1161 
   1162         for temp_arg in temp_args:

/usr/lib/spark2/python/pyspark/sql/utils.py in deco(*a, **kw)
     61     def deco(*a, **kw):
     62         try:
---> 63             return f(*a, **kw)
     64         except py4j.protocol.Py4JJavaError as e:
     65             s = e.java_exception.toString()

/usr/lib/spark2/python/lib/py4j-0.10.6-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
    318                 raise Py4JJavaError(
    319                     "An error occurred while calling {0}{1}{2}.\n".
--> 320                     format(target_id, ".", name), value)
    321             else:
    322                 raise Py4JError(

Py4JJavaError: An error occurred while calling o840.collectToPython.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 491 in stage 59.0 failed 4 times, most recent failure: Lost task 491.3 in stage 59.0 (TID 57404, analytics1051.eqiad.wmnet, executor 7274): ExecutorLostFailure (executor 7274 exited caused by one of the running tasks) Reason: Container killed by YARN for exceeding memory limits. 2.1 GB of 2 GB physical memory used. Consider boosting spark.yarn.executor.memoryOverhead.
Driver stacktrace:
	at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1599)
	at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1587)
	at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1586)
	at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
	at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
	at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1586)
	at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
	at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
	at scala.Option.foreach(Option.scala:257)
	at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:831)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1820)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1769)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1758)
	at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
	at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2027)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2048)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2067)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2092)
	at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:939)
	at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
	at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
	at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
	at org.apache.spark.rdd.RDD.collect(RDD.scala:938)
	at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:297)
	at org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply$mcI$sp(Dataset.scala:3195)
	at org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply(Dataset.scala:3192)
	at org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply(Dataset.scala:3192)
	at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77)
	at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:3225)
	at org.apache.spark.sql.Dataset.collectToPython(Dataset.scala:3192)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.lang.reflect.Method.invoke(Method.java:498)
	at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
	at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
	at py4j.Gateway.invoke(Gateway.java:282)
	at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
	at py4j.commands.CallCommand.execute(CallCommand.java:79)
	at py4j.GatewayConnection.run(GatewayConnection.java:214)
	at java.lang.Thread.run(Thread.java:748)