Pyspark Training Certification
HKR Trainings Pyspark training certification training is gives the best knowledge to grow in Pyspark career. This Training would help you to clear the CCA Spark and Hadoop Developer (CCA175) Examination. This course will understand the bigdata and hadopp. You will learn how to spark enables in-memeory data processing and runs much faster than hadoop mapreduce.
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Discussion on overview of Hadoop & Big data(HDFS- Hadoop Distributed File System, YARN-Yet Another Resource Negotiator) Learn various tools which is related to pyspark Expore real time projects Capable of handling real time projects
Who Should Attend
• Developer • IT Professionals • Big data architects, engineers and developers • Data scientists and analytics professionals
Prerequisites For Pyspark Training Certification
Knowing of Python and SQL, but not monditory
Curriculum for Pyspark Training Certification
What is Big Data?
Big Data Customer Scenarios
The Limitations and Solutions of Existing Data Analytics Architecture with uber Use Case
How Hadoop Solves the Big Data Problem?
What is Hadoop?
Hadoop’s Key Characteristics
Hadoop Ecosystem and HDFS
Hadoop Core Components
Rack Awareness and Block Replication
YARN and its Advantage
Hadoop Cluster and its Architecture
Hadoop: Different Cluster Modes
Big Data Analytics with the Batch and Real-Time Processing
Why Spark is Needed?
What is Spark?
How Spark Differs from its Competitors?
Spark at eBay
Spark’s Place in Hadoop Ecosystem
Overview of Python
Different Applications where Python is Used
Values, Types, Variables
Operands and Expressions
Command Line Arguments
Writing to the Screen
Python files I/O Functions
Strings and related operations
Tuples and related operations
Lists and related operations
Dictionaries and related operations
Sets and related operations
Variable Scope and Returning Values
Modules Used in Python
The Import Statements
Module Search Path
Package Installation Ways
Spark Components & its Architecture
Spark Deployment Modes
Introduction to PySpark Shell
Submitting PySpark Job
Spark Web UI
Writing the first PySpark Job Using to Jupyter Notebook
Data Ingestion using Sqoop
Challenges in Existing Computing Methods
The Probable Solution & How RDD Solves the Problem
What is RDD, It’s Operations, Transformations & Actions
The Data Loading and Saving Through RDDs
The Key-Value Pair RDDs
Other Pair RDDs, Two Pair RDDs
The WordCount Program Using RDD Concepts
Partitioning RDD & How is it Helps Achieve Parallelization
Passing Functions to Spark
Need for Spark SQL
What is Spark SQL
Spark SQL Architecture
SQL Context in Spark SQL
User Defined Functions
Data Frames & Datasets
Interoperating with RDDs
JSON and Parquet File Formats
Loading Data through Different Sources
Why Machine Learning
What is Machine Learning
Where Machine Learning is used
Face Detection: USE CASE
Different Types of Machine Learning Techniques
• Introduction to MLlib • Features of MLlib and MLlib Tools • Various ML algorithms supported by MLlib
Supervised the Learning: Linear Regression, Logistic Regression, Decision Tree, Random Forest
Unsupervised the Learning: K-Means Clustering & How It Works with MLlib
The Analysis of US Election Data using to MLlib (K-Means)
Need for Kafka
What is Kafka
Core Concepts of Kafka
Where is Kafka Used
Understanding the Components of Kafka Cluster
Configuring Kafka Cluster
Kafka Producer and Consumer Java API
Need of Apache Flume
What is Apache Flume
Basic Flume Architecture
Integrating Apache Flume and Apache Kafka
Drawbacks in Existing Computing Methods
Why Streaming is Necessary
What is Spark Streaming
Spark Streaming Features
Spark Streaming Workflow
How Uber Uses Streaming Data
Streaming Context & DStreams
Transformations on DStreams
Describes Windowed Operators and Why is it Useful
Important Windowed Operators
Slice, Window and ReduceByWindow Operators
Apache Spark Streaming: Data Sources
Streaming Data Source Overview
Apache Flume and Apache Kafka Data Sources
Example: Using a Kafka Direct Data Source
Domain: Media and Entertainment
Statement: The Analyze and deduce of the best performing movies based on the customer feedback and review.
Use the two different of API's (Spark RDD and Spark DataFrame) on datasets to find the best ranking movies.
Modes of Training
Each and every class is recorded so if you missed any class you can review the recordings and clarify any doubts with the trainer in next class.
Yes, we don’t assure 100% placement assistance. We are tied up with some corporate companies so when they have a requirement we send your profiles to them.
Yes, we provide demo before starting any training in which you can clear all your doubts before starting training.
Our trainers are real time experts who are presently working on particular platform on which they are providing training.
You can call our customer care 24/7
Max of the students get satisfied with our training, if you are not then we provide a specialised training in return.
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After Completion of training you will receive a course completion certificate from HKR Trainings which adds a value to your carrier and this is the entry to build a carrier with this certificate.