Big Data Processing with PySpark Training
Big Data Processing with PySpark Course:
PySpark is an API developed in python for spark programming and writing spark applications in Python. PySpark allows data scientists to perform rapid distributed transformations on large sets of data. Apache Spark is open source and uses in-memory computation. It can run tasks up to 100 times faster,when it utilizes the in-memory computations and 10 times faster when it uses disk than traditional map-reduce tasks.
Big Data Processing with PySpark Course Curriculum
What is Apache Spark?
Spark Jobs and APIs
Resilient Distributed Dataset
Datasets
Project Tungsten
Unifying Datasets and DataFrames
Tungsten phase 2
Continuous applications
Internal workings of an RDD
Schema
Lambda expressions
Transformations
Transformations
Math/Statistical transformations
Data structure-based transformations
flatMap function
coalesce
Actions -reduce,count,collect,Caching
Loading data
wholeTextFiles
Saving RDD
Python to RDD communications
Speeding up PySpark with DataFrames
Generating our own JSON data
Creating a temporary table
DataFrame API query
Interoperating with RDDs
Programmatically specifying the schema
Number of rows
Querying with SQL
Running filter statements using the where Clauses
Preparing the source datasets
Visualizing our flight-performance data
Checking for duplicates, missing observations, and outliers
Missing observations
Getting familiar with your data
Correlations
Histograms
Solving cases
Overview of the package
Getting to know your data
Correlations
Creating the final dataset
Splitting into training and testing
Logistic regression in MLlib
Random forest in MLlib
Overview of the package
Estimators
Regression
Pipeline
Loading the data
Creating an estimator
Fitting the model
Saving the model
Grid search
Other features of PySpark ML in action
Discretizing continuous variables
Classification
Finding clusters in the births dataset
What is Spark Streaming?
What is the Spark Streaming application data flow?
Introducing Structured Streaming
The spark-submit command
Deploying the app programmatically
Creating SparkSession
Structure of the module
User defined functions in Spark
Monitoring execution
Frequently Asked Questions
This "Big Data Processing with PySpark" course is an instructor-led training (ILT). The trainer travels to your office location and delivers the training within your office premises. If you need training space for the training we can provide a fully-equipped lab with all the required facilities. The online instructor-led training is also available if required. Online training is live and the instructor's screen will be visible and voice will be audible. Participants screen will also be visible and participants can ask queries during the live session.
Participants will be provided "Big Data Processing with PySpark"-specific study material. Participants will have lifetime access to all the code and resources needed for this "Big Data Processing with PySpark". Our public GitHub repository and the study material will also be shared with the participants.
All the courses from zekeLabs are hands-on courses. The code/document used in the class will be provided to the participants. Cloud-lab and Virtual Machines are provided to every participant during the "Big Data Processing with PySpark" training.
The "Big Data Processing with PySpark" training varies several factors. Including the prior knowledge of the team on the subject, the objective of the team learning from the program, customization in the course is needed among others. Contact us to know more about "Big Data Processing with PySpark" course duration.
The "Big Data Processing with PySpark" training is organised at the client's premises. We have delivered and continue to deliver "Big Data Processing with PySpark" training in India, USA, Singapore, Hong Kong, and Indonesia. We also have state-of-art training facilities based on client requirement.
Our Subject matter experts (SMEs) have more than ten years of industry experience. This ensures that the learning program is a 360-degree holistic knowledge and learning experience. The course program has been designed in close collaboration with the experts working in esteemed organizations such as Google, Microsoft, Amazon, and similar others.
Yes, absolutely. For every training, we conduct a technical call with our Subject Matter Expert (SME) and the technical lead of the team that undergoes training. The course is tailored based on the current expertise of the participants, objectives of the team undergoing the training program and short term and long term objectives of the organisation.
Drop a mail to us at [email protected] or call us at +91 8041690175 and we will get back to you at the earliest for your queries on "Big Data Processing with PySpark" course.
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