Yes, that's right. On Fri, Oct 5, 2018 at 3:35 AM Gourav Sengupta <gourav.sengu...@gmail.com> wrote:
> Hi Marcelo, > it will be great if you illustrate what you mean, I will be interested to > know. > > Hi Jianshi, > so just to be sure you want to work on SPARK 2.3 while having SPARK 2.1 > installed in your cluster? > > Regards, > Gourav Sengupta > > On Thu, Oct 4, 2018 at 6:26 PM Marcelo Vanzin <van...@cloudera.com.invalid> > 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 >> >> --------------------------------------------------------------------- >> To unsubscribe e-mail: user-unsubscr...@spark.apache.org >> >> -- Jianshi Huang
