Hi Mich,
With Spark 3.1.1 you need to use spark-measure built with Scala 2.12: bin/pyspark --packages ch.cern.sparkmeasure:spark-measure_2.12:0.17 Best, Luca From: Mich Talebzadeh <mich.talebza...@gmail.com> Sent: Thursday, December 23, 2021 19:59 To: Luca Canali <luca.can...@cern.ch> Cc: user <user@spark.apache.org> Subject: Re: measure running time Hi Luca, Have you tested this link https://github.com/LucaCanali/sparkMeasure With Spark 3.1.1/PySpark, I am getting this error pyspark --packages ch.cern.sparkmeasure:spark-measure_2.11:0.17 :: problems summary :: :::: ERRORS unknown resolver null SERVER ERROR: Bad Gateway url=https://dl.bintray.com/spark-packages/maven/com/fasterxml/jackson/jackson-bom/2.9.9/jackson-bom-2.9.9.jar SERVER ERROR: Bad Gateway url=https://dl.bintray.com/spark-packages/maven/com/fasterxml/jackson/jackson-base/2.9.9/jackson-base-2.9.9.jar Using Python version 3.7.3 (default, Mar 27 2019 22:11:17) Spark context Web UI available at http://rhes76:4040 Spark context available as 'sc' (master = local[*], app id = local-1640285629478). SparkSession available as 'spark'. >>> from sparkmeasure import StageMetrics >>> stagemetrics = StageMetrics(spark) Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/hduser/anaconda3/envs/pyspark_venv/lib/python3.7/site-packages/sparkmeasure/stagemetrics.py", line 15, in __init__ self.stagemetrics = self.sc._jvm.ch.cern.sparkmeasure.StageMetrics(self.sparksession._jsparkSession) File "/opt/spark/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py", line 1569, in __call__ File "/opt/spark/python/pyspark/sql/utils.py", line 111, in deco return f(*a, **kw) File "/opt/spark/python/lib/py4j-0.10.9-src.zip/py4j/protocol.py", line 328, in get_return_value py4j.protocol.Py4JJavaError: An error occurred while calling None.ch.cern.sparkmeasure.StageMetrics. : java.lang.NoClassDefFoundError: scala/Product$class at ch.cern.sparkmeasure.StageMetrics.<init>(stagemetrics.scala:111) at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method) at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62) at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45) at java.lang.reflect.Constructor.newInstance(Constructor.java:423) at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:247) at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) at py4j.Gateway.invoke(Gateway.java:238) at py4j.commands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:80) at py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:69) at py4j.GatewayConnection.run(GatewayConnection.java:238) at java.lang.Thread.run(Thread.java:748) Caused by: java.lang.ClassNotFoundException: scala.Product$class at java.net.URLClassLoader.findClass(URLClassLoader.java:382) at java.lang.ClassLoader.loadClass(ClassLoader.java:424) at java.lang.ClassLoader.loadClass(ClassLoader.java:357) ... 12 more Thanks view my Linkedin profile <https://www.linkedin.com/in/mich-talebzadeh-ph-d-5205b2/> Disclaimer: Use it at your own risk. Any and all responsibility for any loss, damage or destruction of data or any other property which may arise from relying on this email's technical content is explicitly disclaimed. The author will in no case be liable for any monetary damages arising from such loss, damage or destruction. On Thu, 23 Dec 2021 at 15:41, Luca Canali <luca.can...@cern.ch <mailto:luca.can...@cern.ch> > wrote: Hi, I agree with Gourav that just measuring execution time is a simplistic approach that may lead you to miss important details, in particular when running distributed computations. WebUI, REST API, and metrics instrumentation in Spark can be quite useful for further drill down. See https://spark.apache.org/docs/latest/monitoring.html You can also have a look at this tool that takes care of automating collecting and aggregating some executor task metrics: https://github.com/LucaCanali/sparkMeasure Best, Luca From: Gourav Sengupta <gourav.sengu...@gmail.com <mailto:gourav.sengu...@gmail.com> > Sent: Thursday, December 23, 2021 14:23 To: bit...@bitfox.top Cc: user <user@spark.apache.org <mailto:user@spark.apache.org> > Subject: Re: measure running time Hi, I do not think that such time comparisons make any sense at all in distributed computation. Just saying that an operation in RDD and Dataframe can be compared based on their start and stop time may not provide any valid information. You will have to look into the details of timing and the steps. For example, please look at the SPARK UI to see how timings are calculated in distributed computing mode, there are several well written papers on this. Thanks and Regards, Gourav Sengupta On Thu, Dec 23, 2021 at 10:57 AM <bit...@bitfox.top <mailto:bit...@bitfox.top> > wrote: hello community, In pyspark how can I measure the running time to the command? I just want to compare the running time of the RDD API and dataframe API, in my this blog: https://bitfoxtop.wordpress.com/2021/12/23/count-email-addresses-using-sparks-rdd-and-dataframe/ I tried spark.time() it doesn't work. Thank you. --------------------------------------------------------------------- To unsubscribe e-mail: user-unsubscr...@spark.apache.org <mailto:user-unsubscr...@spark.apache.org>
