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Description of  Apache Spark 2 and 3 using Python 3 (Formerly CCA 175)

cca-175-spark-and-hadoop-developer-python-pysparkMP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 9.34 GB | Duration: 28h 36m Data Engineering using Apache Spark 2 or 3 using Python as Programming Language What you'll learncourse All the HDFS Commands that are relevant to validate files a2021, the exam is sunset and we have renamed it to Apache Spark 2 and 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. Course Details Here www.udemy.comis the high level outline of the topics related to this course. Quick recap of Python Data Engineering using Spark SQL Let us, deep-dive into Spark SQL to understand how it can be used to build Data Engineering Pipelines. Spark with SQL will provide us the ability to leverage distributed computing capabilities of Spark coupled with easy-to-use developer-friendly SQL-style syntax. Getting Started with Spark SQL Basic Transformations Managing Tables - Basic DDL and DML Managing Tables - DML and Partitioning Overview of Spark SQL Functions Windowing Functions Data Engineering using Spark Data Frame APIs Spark Data Frame APIs are an alternative waor Spark SQL. Apache Spark Application Development and Deployment Life Cycle professional willing to learn Data Engineering using Apache Spark Python Developers who want to learn Spark to add the key skill to be a Data Engineer Homepage https: Apache Spark Application Development Lifecycle Spark Application Execution Life Cycle and Spark UI Setup SSH Proxy to access Spark Application logs Deployment Modes of Spark Applications Passing Application Properties Files and External Dependencies All the demos are given on our state of the art Big Data cluster. You can avail one-month complimentary lab access by reaching out towith Udemy receipt. Who this course is for Any IT aspiranty of building Data Engineering applications at scale leveraging distributed computing capabilities of Spark. Data Engineers from application development backgrounds might prefer Data Frame APIs over Spark SQL to build Data Engineering applications. Data Processing Overview Processing Column Data Basic Transformations - Filtering, Aggregations, and Sorting Joining Data Sets Windowing Functions - Aggregations, Ranking, and Analytic Functions Spark Metastore Databases and TablesPlease note that the syllabus is recently changed and now the exam is primarily focused on Spark Data Frames andnd 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 Cl31ient) Passing Application Properties Files and External Dependencies while running Spark Applications Basic programming skills using any programming language Self support lab (Instructions provided) or ITVersity lab at additional cost for appropriate environment. Minimum memory required based on the environment you are using with 64 bit operating system 4 GB RAM with access to proper clusters or 16 GB RAM with virtual machines such as Cloudera QuickStart VM Description As part of this course, you will learn all the key skills to build Data Engineering Pipelines using Spark SQL and Data Frame APIs using Python as Programming language. This course used to be CCA 175 Spark and Hadoop Developer course for the preparation of Certification Exam. As of 10