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
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On Thu, 23 Dec 2021 at 15:41, Luca Canali <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>
> *Sent:* Thursday, December 23, 2021 14:23
> *To:* bit...@bitfox.top
> *Cc:* user <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> 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.
>
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>
