Apache Spark的工人python

Question

After installing Apache Spark on 3 nodes on top of Hadoop, I encountered the following problems:

I had problem with setting the python on workers. This is the setting in.bashrc file and the same setting is in the spark-env.sh file.

alias python3='/usr/bin/python3'
export PYSPARK_PYTHON=/usr/bin/python3
export PYSPARK_DRIVER_PYTHON=/usr/bin/python3

In the Spark logs (yarn logs --applicationId <app_id>) I could see that everything is as expected:

export USER="hadoop"
export LOGNAME="hadoop"
export PYSPARK_PYTHON="python3"

While I installed the pandas library (pip install pandas) on master and worker nodes and made sure it is installed, I constantly received the following message when used the command /home/hadoop/spark/bin/spark-submit --master yarn --deploy-mode cluster sparksql_recommender_system_2.py

ModuleNotFoundError: No module named 'pandas' <br>

Surprisingly this error was just in cluster mode and I didn't have that error in client deployment mode.

The command which python returns /usr/bin/python in which the library pandas exists. After 2 days I couldn't find my answer on web. By chance, I tried installing pandas using sudo and it worked:).

sudo pip install pandas

However, what I expected was that Spark is going to use the python in /usr/bin/python for the hadoop user, not the root user. How can I fix it?

I use VScode ssh addon to connect to a server on which I develop my codes. When do it from one host (PC) I can use spark-submit , but on my other PC I have to use the exact path /home/hadoop/spark/bin/spark-submit . It is strange because I use VSCode ssh to the same server and files. Any idea how I can solve it?

Answer 1

Here's a great discussion on how to package item s up so that your python environment is transferred to executor.

Create the environment

conda create -y -n pyspark_conda_env -c conda-forge pyarrow pandas conda-pack conda activate pyspark_conda_env conda pack -f -o pyspark_conda_env.tar.gz

Ship it:

 export PYSPARK_DRIVER_PYTHON=python # Do not set in cluster modes. export PYSPARK_PYTHON=./environment/bin/python spark-submit --archives pyspark_conda_env.tar.gz#environment app.py

This does have the disadvantage of having to be shipped every time but it's the safest, and least hassle way to do it. Installing everything on each node is 'faster' but comes with a higher threshold of managment and I suggest avoiding it.

All that said... get off the Pandas. Pandas does python things(small data). Spark Data Frames do Spark things(Big Data). I hope it was just an illustrative example and you aren't going to use Pandas.(It's not a bad. it's just made for small data so use it for small data,) If you "have to" use it. look into Koala's that does a translation to allow you to ask panda things of spark data frames.