Hi Marcelo, I see what you mean. Tried it but still got same error message.
Error from python worker: > Traceback (most recent call last): > File "/usr/local/Python-3.6.4/lib/python3.6/runpy.py", line 183, in > _run_module_as_main > mod_name, mod_spec, code = _get_module_details(mod_name, _Error) > File "/usr/local/Python-3.6.4/lib/python3.6/runpy.py", line 109, in > _get_module_details > __import__(pkg_name) > File "/usr/lib/spark-current/python/lib/pyspark.zip/pyspark/__init__.py", > line 46, in <module> > File "/usr/lib/spark-current/python/lib/pyspark.zip/pyspark/context.py", > line 29, in <module> > ModuleNotFoundError: No module named 'py4j' > PYTHONPATH was: > > /usr/lib/spark-current/python/lib/pyspark.zip:/usr/lib/spark-current/python/lib/py4j-0.10.7-src.zip:/mnt/disk3/yarn/usercache/jianshi.huang/filecache/134/__spark_libs__8468485589501316413.zip/spark-core_2.11-2.3.2.jar > > On Fri, Oct 5, 2018 at 1:25 AM Marcelo Vanzin <van...@cloudera.com> wrote: > Try "spark.executorEnv.SPARK_HOME=$PWD" (in quotes so it does not get > expanded by the shell). > > But it's really weird to be setting SPARK_HOME in the environment of > your node managers. YARN shouldn't need to know about that. > On Thu, Oct 4, 2018 at 10:22 AM Jianshi Huang <jianshi.hu...@gmail.com> > wrote: > > > > > https://github.com/apache/spark/blob/88e7e87bd5c052e10f52d4bb97a9d78f5b524128/core/src/main/scala/org/apache/spark/api/python/PythonUtils.scala#L31 > > > > The code shows Spark will try to find the path if SPARK_HOME is > specified. And on my worker node, SPARK_HOME is specified in .bashrc , for > the pre-installed 2.2.1 path. > > > > I don't want to make any changes to worker node configuration, so any > way to override the order? > > > > Jianshi > > > > On Fri, Oct 5, 2018 at 12:11 AM Marcelo Vanzin <van...@cloudera.com> > wrote: > >> > >> Normally the version of Spark installed on the cluster does not > >> matter, since Spark is uploaded from your gateway machine to YARN by > >> default. > >> > >> You probably have some configuration (in spark-defaults.conf) that > >> tells YARN to use a cached copy. Get rid of that configuration, and > >> you can use whatever version you like. > >> On Thu, Oct 4, 2018 at 2:19 AM Jianshi Huang <jianshi.hu...@gmail.com> > wrote: > >> > > >> > Hi, > >> > > >> > I have a problem using multiple versions of Pyspark on YARN, the > driver and worker nodes are all preinstalled with Spark 2.2.1, for > production tasks. And I want to use 2.3.2 for my personal EDA. > >> > > >> > I've tried both 'pyFiles=' option and sparkContext.addPyFiles(), > however on the worker node, the PYTHONPATH still uses the system SPARK_HOME. > >> > > >> > Anyone knows how to override the PYTHONPATH on worker nodes? > >> > > >> > Here's the error message, > >> >> > >> >> > >> >> Py4JJavaError: An error occurred while calling o75.collectToPython. > >> >> : org.apache.spark.SparkException: Job aborted due to stage failure: > Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in > stage 0.0 (TID 3, emr-worker-8.cluster-68492, executor 2): > org.apache.spark.SparkException: > >> >> Error from python worker: > >> >> Traceback (most recent call last): > >> >> File "/usr/local/Python-3.6.4/lib/python3.6/runpy.py", line 183, in > _run_module_as_main > >> >> mod_name, mod_spec, code = _get_module_details(mod_name, _Error) > >> >> File "/usr/local/Python-3.6.4/lib/python3.6/runpy.py", line 109, in > _get_module_details > >> >> __import__(pkg_name) > >> >> File > "/usr/lib/spark-current/python/lib/pyspark.zip/pyspark/__init__.py", line > 46, in <module> > >> >> File > "/usr/lib/spark-current/python/lib/pyspark.zip/pyspark/context.py", line > 29, in <module> > >> >> ModuleNotFoundError: No module named 'py4j' > >> >> PYTHONPATH was: > >> >> > /usr/lib/spark-current/python/lib/pyspark.zip:/usr/lib/spark-current/python/lib/py4j-0.10.7-src.zip:/mnt/disk1/yarn/usercache/jianshi.huang/filecache/130/__spark_libs__5227988272944669714.zip/spark-core_2.11-2.3.2.jar > >> > > >> > > >> > And here's how I started Pyspark session in Jupyter. > >> >> > >> >> > >> >> %env SPARK_HOME=/opt/apps/ecm/service/spark/2.3.2-bin-hadoop2.7 > >> >> %env PYSPARK_PYTHON=/usr/bin/python3 > >> >> import findspark > >> >> findspark.init() > >> >> import pyspark > >> >> sparkConf = pyspark.SparkConf() > >> >> sparkConf.setAll([ > >> >> ('spark.cores.max', '96') > >> >> ,('spark.driver.memory', '2g') > >> >> ,('spark.executor.cores', '4') > >> >> ,('spark.executor.instances', '2') > >> >> ,('spark.executor.memory', '4g') > >> >> ,('spark.network.timeout', '800') > >> >> ,('spark.scheduler.mode', 'FAIR') > >> >> ,('spark.shuffle.service.enabled', 'true') > >> >> ,('spark.dynamicAllocation.enabled', 'true') > >> >> ]) > >> >> py_files = > ['hdfs://emr-header-1.cluster-68492:9000/lib/py4j-0.10.7-src.zip'] > >> >> sc = pyspark.SparkContext(appName="Jianshi", master="yarn-client", > conf=sparkConf, pyFiles=py_files) > >> >> > >> > > >> > > >> > Thanks, > >> > -- > >> > Jianshi Huang > >> > > >> > >> > >> -- > >> Marcelo > > > > > > > > -- > > Jianshi Huang > > > > LinkedIn: jianshi > > Twitter: @jshuang > > Github & Blog: http://huangjs.github.com/ > > > > -- > Marcelo > -- Jianshi Huang
