Efficient UD(A)Fs with PySparkNowadays, Spark surely is one of the most prevalent technologies in the fields of data science and big data. Luckily, even though it is developed in Scala and runs in the Java Virtual Machine (JVM), it comes with Python bindings also known as PySpark, whose API was heavily influenced by Pandas. With respect to functionality, modern PySpark has about the same capabilities as Pandas when it comes to
Spark using PySpark read images
Running PySpark with Conda Env
Running PySpark with Virtualenv
[SPARK-16367] Wheelhouse Support for PySpark - ASF JIRA
Cloudera Blog
GitHub - adornes/spark_python_ml_examples: Spark 2.0 Python Machine Learning examples
