PySpark Certification Course

Get ready to add some Spark to your Python code with this PySpark certification training. This course gives you an overview of the Spark stack and lets you know how to leverage the functionality of Python as you deploy it in the Spark ecosystem. It helps you gain the skills required to become a PySpark developer.

Enquire Now

What will you learn

  • What is Apache Spark?
  • Why Pyspark?
  • Need for pyspark.
  • spark Python Vs Scala
  • pyspark features
  • Real-life usage of PySpark
  • PySpark Web/Application
  • PySpark - SparkSession
  • PySpark – SparkContext
  • PySpark – RDD
  • PySpark – Parallelize
  • PySpark – repartition () vs coalesce
  • PySpark – Broadcast Variables
  • PySpark – Accumulator

  • Operations on an RDD
  • Direct Acyclic Graph (DAG)
  • RDD Actions and Transformations
  • RDD computation
  • Steps in RDD computation
  • RDD persistence
  • Persistence features
  • Persistence Options:
    • - MEMORY_ONLY - MEMORY_SER_ONLY - DISK_ONLY - DISK_SER_ONLY - MEMORY_AND_DISK_ONLY

  • Fault Tolerence model in spark
  • Different ways of creating an RDD
  • Word Count Example
  • Creating spark objects (RDDs) from Scala Objects(lists).
  • Increasing the no of partitons
  • Aggregations Over Structured Data:
  • reduceByKey ()

  • i) Single Grouping and Single Aggregation
  • ii) Single Grouping and multiple Aggregation
  • iii) multi-Grouping and Single Aggregation
  • iv) Multi Grouping and Multi Aggregation
  • Differences b/w reduceByKey () and groupByKey ()
  • Process of groupByKey
  • Process of reduceByKey
  • Reduce () function.
  • Various Transformations
  • Various Built-in Functions

  • countByKey()
  • countByValue()
  • sortByKey()
  • zip()
  • Union()
  • Distinct()
  • Various count aggregation
  • Joins
    • -inner join -outer join
  • Cartesian ()
  • Cogroup ()
  • Other actions and transformations

  • Introduction
  • Making data Structured
  • Case Classes
  • ways to extract case class objects.
    • - using function - using map with multiple expressions - using map with single expression
  • SQL Context
  • Data Frames API
  • Dataset API
  • RDD vs DataFrame vs DataSet
  • PySpark – Create a DataFrame
  • PySpark – Create an empty DataFrame.
  • PySpark – Convert RDD to DataFrame
  • PySpark – Convert DataFrame to Pandas
  • PySpark – show()
  • PySpark – StructType & StructField
  • PySpark – Row Class
  • PySpark – Column Class
  • PySpark – select()
  • PySpark – collect()
  • PySpark – withColumn()
  • PySpark – withColumnRenamed()
  • PySpark – where() & filter()
  • PySpark – drop() & dropDuplicates()
  • PySpark – orderBy() and sort()
  • PySpark – groupBy()
  • PySpark – join()
  • PySpark – union() & unionAll()
  • PySpark – unionByName()
  • PySpark – UDF (User Defined Function)
  • PySpark – map()
  • PySpark – flatMap()
  • Pyspark – foreach()
  • PySpark – sample() vs sampleBy()
  • PySpark – fillna() & fill()
  • PySpark – pivot() (Row to Column)
  • PySpark – partitionBy()
  • PySpark – ArrayType Column (Array)
  • PySpark – MapType (Map/Dict)

  • PySpark – Aggregate Functions
  • PySpark – Window Functions
  • PySpark – Date and Timestamp Functions
  • PySpark – JSON Functions
  • PySpark – Read & Write JSON file

  • PySpark – when()
  • PySpark – expr()
  • PySpark – lit()
  • PySpark – split()
  • PySpark – concat_ws()
  • Pyspark – substring()
  • PySpark – translate()
  • PySpark – regexp_replace()
  • PySpark – overlay()
  • PySpark – to_timestamp()
  • PySpark – to_date()
  • PySpark – date_format()
  • PySpark – datediff()
  • PySpark – months_between()
  • PySpark – explode()
  • PySpark – array_contains()
  • PySpark – array()
  • PySpark – collect_list()
  • PySpark – collect_set()
  • PySpark – create_map()
  • PySpark – map_keys()
  • PySpark – map_values()
  • PySpark – struct()
  • PySpark – countDistinct()
  • PySpark – sum(), avg()
  • PySpark – row_number()
  • PySpark – rank()
  • PySpark – dense_rank()
  • PySpark – percent_rank()
  • PySpark – typedLit()
  • PySpark – from_json()
  • PySpark – to_json()
  • PySpark – json_tuple()
  • PySpark – get_json_object()
  • PySpark – schema_of_json()
  • Working Examples

  • Working with sql statements
  • Spark and Hive Integration
  • Spark and mysql Integration
  • Working with CSV
  • Working with JSON
  • Transformations and actions on dataframes
  • Narrow, wide transformations
  • Addition of new columns, dropping of columns ,renaming columns
  • Addition of new rows, dropping rows
  • Handling nulls
  • Joins
  • Window function
  • Writing data back to External sources
  • Creation of tables from Data frames (Internal tables, Temporary tables)

  • Local Mode
  • Cluster Modes (Standalone , YARN

  • Stages and Tasks
  • Driver and Executor
  • Building spark applications/pipelines
  • Deploying spark apps to cluster and tuning
  • Performance tuning

Frequently Asked Questions

    We have both online & offline training.

    Yes, you will get course completion certificate when course is completed.

    Basic Understanding on Python.

    Netbanking and UPI.

    We have industrial experts with professional experience.

    Big Data architects, Data scientists,

    Yes, you can get free demo before enrolling to this course.

Quick Enquiry

Please wait we are capturing your information.

Your Response was submitted. our team will contact you shortly.

Industry experts Mentored

Learning a technology with a professional who is well expertise in that to solve 80% of your needs

Hands on project based learning

We support any training with more practical classes. So, we always prefer to give hands-on training.

Flexible Timing

We started with 2+ trainers, now we have more than 15+ and it is still increasing. So we can give flexible timings to our learners.

Live interactive online learning

Our platform enables seamless interaction between instructors and learners, creating an immersive and effective online training environment.

Certification

Earn industry-recognized credentials with our rigorous certification courses, empowering your career advancement and professional growth.

Interview Preparation

Master the art of interviewing through personalized coaching, mock interviews, and strategic guidance, ensuring you stand out and secure your dream opportunity.

WHY CHOOSE US?

Take on any Challenge of the Digital World