I have installed PySpark standalone/locally (on Windows) using
pip install pyspark
I was a bit surprised I can already run pyspark
in command line or use it in Jupyter Notebooks and that it does not need a proper Spark installation (e.g. I did not have to do most of the steps in this tutorial https://medium.com/@GalarnykMichael/install-spark-on-windows-pyspark-4498a5d8d66c ).
Most of the tutorials that I run into say one needs to "install Spark before installing PySpark". That would agree with my view of PySpark being basically a wrapper over Spark. But maybe I am wrong here - can someone explain:
sbin
folder which contains e.g. script to start history server)PySpark has been released in order to support the collaboration of Apache Spark and Python, it actually is a Python API for Spark. In addition, PySpark, helps you interface with Resilient Distributed Datasets (RDDs) in Apache Spark and Python programming language.
1. Step 1. PySpark requires Java version 7 or later and Python version 2.6 or later.
To run PySpark application, you would need Java 8 or later version hence download the Java version from Oracle and install it on your system. Post installation, set JAVA_HOME and PATH variable.
PySpark is the Python API for Apache Spark, an open source, distributed computing framework and set of libraries for real-time, large-scale data processing. If you're already familiar with Python and libraries such as Pandas, then PySpark is a good language to learn to create more scalable analyses and pipelines.
As of v2.2, executing pip install pyspark
will install Spark.
If you're going to use Pyspark it's clearly the simplest way to get started.
On my system Spark is installed inside my virtual environment (miniconda) at lib/python3.6/site-packages/pyspark/jars
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