Real World Spark 2 – Interactive Python pyspark Core
Note : This course is built on top of the “Real World Vagrant – Build an Apache Spark Development Env! – Toyin Akin” course. So if you do not have a Spark environment already installed (within a VM or directly installed), you can take the stated course above.
Spark’s python shell provides a simple way to learn the API, as well as a powerful tool to analyze data interactively. It is available in Python. Start it by running the following anywhere within a bash terminal within the built Virtual Machine
Spark’s primary abstraction is a distributed collection of items called a Resilient Distributed Dataset (RDD). RDDs can be created from collections, Hadoop InputFormats (such as HDFS files) or by transforming other RDDs
Spark Monitoring and Instrumentation
While creating RDDs, performing transformations and executing actions, you will be working heavily within the monitoring view of the Web UI.
Every SparkContext launches a web UI, by default on port 4040, that displays useful information about the application. This includes:
A list of scheduler stages and tasks
A summary of RDD sizes and memory usage
Information about the running executors
Why Apache Spark …
Apache Spark run programs up to 100x faster than Hadoop MapReduce in memory, or 10x faster on disk. Apache Spark has an advanced DAG execution engine that supports cyclic data flow and in-memory computing. Apache Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python and R shells. Apache Spark can combine SQL, streaming, and complex analytics.
Apache Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application.
Introduction to Python, Spark Core via pyspark
A quick tour of Python pyspark
Suggested Spark Udemy curriculum courses to follow. You do not need to
take/purchase the first three courses if you already have spark
Author, Equipment and Compensation
My experience within the Enterprise
Spark job compensation for those in this field.
Recommended Hardware for Spark and Hadoop labs ...
Setup the Environment
Resource files for the course
Walking through the Base Vagrant Spark Box.
Upgrade and Package the Vagrant Box to Spark 2
Register the updated Vagrant Spark Box
Interact with Spark Core (Python)
Boot up and Walkthrough of the pyspark Python Environment
Configure and Startup a Spark Environment for Distributed Computing
Python Spark RDD, Transformations, Actions and Monitoring I
Python Spark RDD, Transformations, Actions and Monitoring II
Python Spark RDD, Transformations, Actions and Monitoring III
Python Spark RDD, Transformations, Actions and Monitoring IV
Python Spark RDD, Transformations, Actions and Monitoring V
Python Spark RDD, Transformations, Actions and Monitoring VI
Python Spark RDD, Transformations, Actions and Monitoring VII