Udemy Coupon for Master Apache Spark using Spark SQL and PySpark 3. Find Out Other Apache Spark Courses and Tutorials from Udemy Learning with Discount Coupon Codes. Master Apache Spark using Spark SQL as well as PySpark with Python3 with complementary lab access
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Master Apache Spark using Spark SQL and PySpark 3
As part of this course, you will learn all the key skills to build Data Engineering Pipelines using Spark SQL and Spark Data Frame APIs using Python as a Programming language. This Master Apache Spark using Spark SQL and PySpark 3 course used to be a CCA 175 Spark and Hadoop Developer course for the preparation for the Certification Exam. As of 10/31/2021, the exam is sunset and we have renamed it to Apache Spark 2 and Apache Spark 3 using Python 3 as it covers industry-relevant topics beyond the scope of certification.
About Data Engineering
Data Engineering is nothing but processing the data depending upon our downstream needs. We need to build different pipelines such as Batch Pipelines, Streaming Pipelines, etc as part of Data Engineering. All roles related to Data Processing are consolidated under Data Engineering. Conventionally, they are known as ETL Development, Data Warehouse Development, etc. Apache Spark is evolved as a leading technology to take care of Data Engineering at scale.
I have prepared this course for anyone who would like to transition into a Data Engineer role using Pyspark (Python + Spark). I myself am a proven Data Engineering Solution Architect with proven experience in designing solutions using Apache Spark.
Let us go through the details about what you will be learning in this course. Keep in mind that the course is created with a lot of hands-on tasks which will give you enough practice using the right tools. Also, there are tons of tasks and exercises to evaluate yourself. We will provide details about Resources or Environments to learn Spark SQL and PySpark 3 using Python 3 as well as Reference Material on GitHub to practice Spark SQL and PySpark 3 using Python 3. Keep in mind that you can either use the cluster at your workplace or set up the environment using provided instructions or use ITVersity Lab to take this course.
Setup of Single Node Big Data Cluster
Many of you would like to transition to Big Data from Conventional Technologies such as Mainframes, Oracle PL/SQL, etc and you might not have access to Big Data Clusters. It is very important for you set up the environment in the right manner. Don’t worry if you do not have the cluster handy, we will guide you through support via Udemy Q&A.
In this Apache Spark Courses you will learn?
- Setup the Single Node Hadoop and Spark using Docker locally or on AWS Cloud9
- Review ITVersity Labs (exclusively for ITVersity Lab Customers)
- All the HDFS Commands that are relevant to validate files and folders in HDFS.
- Quick recap of Python which is relevant to learn Spark
- Ability to use Spark SQL to solve the problems using SQL style syntax.
- Pyspark Dataframe APIs to solve the problems using Dataframe style APIs.
- Relevance of Spark Metastore to convert Dataframs into Temporary Views so that one can process data in Dataframes using Spark SQL.
- Apache Spark Application Development Life Cycle
- Apache Spark Application Execution Life Cycle and Spark UI
- Setup SSH Proxy to access Spark Application logs
- Deployment Modes of Spark Applications (Cluster and Client)
- Passing Application Properties Files and External Dependencies while running Spark Applications
