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Course Content:
SPARK - Basic & Advanced
SPARK with SCALA
* Scala overview
* Introducing Scala
* Journey – Java to Scala
* What is Scala?
* Why Scala?
* Scala Installation
* Execution Mechanisms
* Scala in interactive mode
* Scala Scripts
* Scala Advanced programming
* Defining Functions
SPARK - Python
* SPARK - Python overview
* What is Python?
* Why Python?
* How to use PYSPARK?
* Advantages of Python in SPARK
* Web scraping using Python
* Handling high volume unstructured data using Python
* Generating huge volumes (10 crore + records) using Python
SPARK
* Spark overview
* What is Spark?
* Why Spark?
* Linking with Spark
* Initializing Spark
* Using the Shell
* Spark Installation
* Resilient Distributed Datasets (RDDs)
* Parallelized Collections
* External Datasets
* RDD Operations
* Basics, Passing Functions to Spark
* Working with Key-Value Pairs
* Transformations
* RDD Persistence
* Which Storage Level to Choose?
* Removing Data
* Shared Variables
* Broadcast Variables
* Accumulators
* SPARK Streaming
* What is Spark Streaming
* Why we need Spark Streaming
* Differences between SPARK Streaming Vs Flume Vs Kafka
* Dynamic memory allocation of Streaming
* Configuration and settings for Streaming path and sources
* Spark SQL
* Why Spark SQL
* Integrating SPARK SQL with RDBMS
* Performance considerations using SPARK SQL
* Integrating unstructured sources to SPARK SQL
* RDD usage in SPARK SQL
* SPARK GRAPHX
* What is Spark GraphX
* How to create connected Data Structures
* Develop your first DATA GRAPGH
* Using RDD's and SPARK SQL as input
* Handling complex DATA GRAPHS
* SPARK R
* What is R?
* How to work on scientific calculations using SPARK R
* How to execute Statistical operations using SPARK R
Expert Faculty with 20years experience
