sawant98d/PySpark

PySpark & AWS: Master Big Data With PySpark and AWS

Hands on Big Data course including in demand industry skills

BIG DATA

Prerequisites

Website: www.aisciences.io

Applications of Spark

Applications of Spark

• Streaming Data
• Machine Learning
• Batch Data
• ETL Pipelines
• Full load and Replication on going

What's inside

Methodology

Projects

• Student Data Analysis
• Employee Data Analysis
• Collaborative Filtering
• Spark Streaming
• ETL Pipeline
• Full Load and Replication on Going

SPARK

Why Spark?

• Speed
• Distributed
• Advanced Analytics
• Real Time
• Powerful Caching
• Fault Tolerant
• Deployment

HADOOP

Spark Architecture

Spark Ecosystem

Data Bricks

Spark Local Setup

Spark RDD's

• RDD is the spark’s core abstraction which stands for Resilient Distributed Dataset
• RDD is the immutable distributed collection of objects
• Internally spark distributes the data in RDD, to different nodes across the cluster to achieve parallelization.

Transformations and Actions

• Transformation creates new RDD from an existing one.
• Actions return a value to the driver program after running a computation on the RDD
• All transformation in Spark are lazy
• Spark only triggers the data flow when there is a action.

Creating Spark RDD

Running code locally

map()

• Map is used as a mapper of data from one state to another

• It will create a new RDD

• rdd.map(lambda x:x.split())

• Quiz

• Quiz solution : https://github.com/sawant98d/PySpark/blob/master/RDD%20Map.py

flatMap()

• Flat Map is used as a mapper of data and explodes data before final output
• It will create new RDD
• rdd.flatMap(lambda x:x.split())
• https://github.com/sawant98d/PySpark/blob/master/flat_map.py
• https://github.com/sawant98d/PySpark/blob/master/flat_map.ipynb

filter()

• Filter is used to remove the elements from the RDD

• It will create new RDD

• rdd.filter(lambda x:x!=12)

• Quiz

• Quiz solution - https://github.com/sawant98d/PySpark/blob/master/filter_quiz.py

distinct()

• Distinct is used to get the distinct elements in RDD
• It will create new RDD
• rdd.distinct()
• https://github.com/sawant98d/PySpark/blob/master/rdd_distinct.ipynb

groupByKey()

• groupByKey() is used to create group based on Keys in RDD
• For groupByKey to work properly the data must be in the format of (k,v), (k,v), (k2,v), (k2,v)
• • Example ("Apple",1), ("Ball",1), ("Apple",1)
• It will create a new RDD
• rdd.groupByKey()
• mapValues(list) are usually used to get the group data

reduceByKey()

• reduceByKey() is used to combined data based on keys in RDD
• for reduceByKey() to work properly the data must be in the format of (k,v), (k,v), (k2,v), (k2,v)
• • Example : ("Apple",1), ("Ball",1), ("Apple",1)
• It will create new RDD
• rdd.reduceByKey(lambda x,y:x+y)