I have performed some queries using pyspark on jupyter notebook now i want the outputs to be visualized in powerbi/tableau.
How do i do it ? I'm completely new to pyspark and need help !
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In Azure Synapse Analytics, I want to keep my SQL queries separately from my PySpark notebook.
So I have created some SQL scripts. And I would like to use them in my PySpark notebook.
Is it possible ?
And what is the python code to load a SQL script into a variable ?
As I undertand the ask here , is can we read the SQL scripts which we have already created from pysprk notebook . I was looking at the storage account whiched is mapped to my synapse analytics studio ( ASA) and i do not see that the notebook or SQL scripts are stored there . So i dont think you can convert the existing SQL script to Pyspark code within the ASA . Yes if you export the SQL scripts and then upload to storage and then read the scripts from the notebook .
We are looking into using Spark as big data processing framework in Azure Synapse Analytics with notebooks. I want to set up a local development environment/sandbox on my own computer similar to that, interacting with Azure Data Lake Storage Gen 2.
For installing Spark I'm using WSL with a Ubuntu distro (Spark seems to be easier to manage in linux)
For notebooks I'm using jupyter notebook with Anaconda
Both components work fine by themself but I can't manage to connect the notebook to my local sparkcluster in WSL. I tried the following:
from pyspark.sql import SparkSession
spark = SparkSession \
.builder \
.master("local[1]") \
.appName("Python Spark SQL basic example") \
.getOrCreate()
When examining the spark object it outputs
SparkSession - in-memory
SparkContext
Spark UI
Version v3.3.0
Master local[1]
AppName Python Spark SQL basic example
The spark-ui link points to http://host.docker.internal:4040/jobs/, Also when examining the UI for spark in WSL I can't see any connection. I think there is something I'm missing or not understanding with how pyspark works. Any help would be much appreciated to clarify.
Your are connecting to local instance which is in this case native Windows running jupyter:
.master("local[1]")
Instead, you should connect to your WSL cluster:
.master("spark://localhost:7077") # assuming default port
I started working with SparkMagic lately, I was able to create notebooks on PySpark kernel which works fine.
Now when I use SparkMagic on Ipython kernel, there's a step which should be done manually (execute %manage_spark, create endpoint, create session)
I would like to know if there's away to do these steps programatically!
I am using pyspark kernel inside jupyterhub and want to connect hivellap from spark . I am able to create a spark session but when i am trying to execute
from pyspark_llap import HiveWarehouseSession it is showing error no module found pyspark_llap
The same command i am able to execute in python kernel and it successfully executed.
Kindly suggest what configuration is needed to import HiveWarehouseSession from pyspark_llap inside pyspark kernel.
I run the following code in Jupyter notebook, but get ImportError. Note that 'udf' can be imported in Jupyter.
from pyspark.sql.functions import pandas_udf
ImportError Traceback (most recent call
last) in ()
----> 1 from pyspark.sql.functions import pandas_udf
ImportError: cannot import name 'pandas_udf'
Anyone knows how to fix it? Thank you very much!
It looks like you start jupyter notebook by itself, rather than start pyspark with jupyter notebook, which is following command:
PYSPARK_DRIVER_PYTHON=jupyter PYSPARK_DRIVER_PYTHON_OPTS="notebook" pyspark
If your jupyter notebook server process are running from another machine, maybe you want to use this command to make it available to all IP addresses of your sever.
(NOTE: This could be a potential security issue if your server is on a public or untrusted network)
PYSPARK_DRIVER_PYTHON=jupyter PYSPARK_DRIVER_PYTHON_OPTS="notebook --ip=0.0.0.0 " pyspark
I will revised my answer if the problem still persist after you start jupyter notebook like that.