Scala/Spark

apachescala

SCALA (Object Oriented and Functional Programming)

  • Getting started With Scala.
  • Scala Background, Scala Vs Java and Basics.
  • Interactive Scala – REPL, data types, variables,expressions, simple functions.
  • Running the program with Scala Compiler.
  • Explore the type lattice and use type inference
  • Define Methodsand Pattern Matching.

Scala Environment Set up.

  • Scala set up on Windows.
  • Scala set up on UNIX.

Functional Programming.

  • What is Functional Programming.
  • Differences between OOPS and FPP.

Collections (Very Important for Spark)

  • Iterating, mapping, filtering and counting
  • Regular expressions and matching with them.
  • Maps, Sets, group By, Options, flatten, flat Map
  • Word count, IO operations,file access, flatMap

Object Oriented Programming.

  • Classes and Properties.
  • Objects, Packaging and Imports.
  • Traits.
  • Objects, classes, inheritance, Lists with multiple related types, apply

Integrations

  • What is SBT?
  • Integration of Scala in Eclipse IDE.
  • Integration of SBT with Eclipse.

SPARK CORE.

  • Batch versus real-time data processing
  • Introduction to Spark, Spark versus Hadoop
  • Architecture of Spark.
  • Coding Spark jobs in Scala
  • Exploring the Spark shell -> Creating Spark Context.
  • RDD Programming
  • Operations on RDD.
  • Transformations
  • Actions
  • Loading Data and Saving Data.
  • Key Value Pair RDD.
  • Broad cast variables.

Persistence.

  • Configuring and running the Spark cluster.
  • Exploring to Multi Node Spark Cluster.
  • Cluster management
  • Submitting Spark jobs and running in the cluster mode.
  • Developing Spark applications in Eclipse
  • Tuning and Debugging Spark.

CASSANDRA (N0SQL DATABASE)

  • Learning Cassandra
  • Getting started with architecture
  • Installing Cassandra.
  • Communicating with Cassandra.
  • Creating a database.
  • Create a table
  • Inserting Data
  • Modelling Data.
  • Creating an Application with Web.
  • Updating and Deleting Data.

SPARK INTEGRATION WITH NO SQL (CASSANDRA) and AMAZON EC2

  • Introduction to Spark and Cassandra Connectors.
  • Spark With Cassandra -> Set up.
  • Creating Spark Context to connect the Cassandra.
  • Creating Spark RDD on the Cassandra Data base.
  • Performing Transformation and Actions on the Cassandra RDD.
  • Running Spark Application in Eclipse to access the data in the Cassandra.
  • Introduction to Amazon Web Services.
  • Building 4 Node Spark Multi Node Cluster in Amazon Web Services.
  • Deploying in Production with Mesos and YARN.

SPARK STREAMING

  • Introduction of Spark Streaming.
  • Architecture of Spark Streaming
  • Processing Distributed Log Files in Real Time
  • Discretized streams RDD.
  • Applying Transformations and Actions on Streaming Data
  • Integration with Flume and Kafka.
  • Integration with Cassandra
  • Monitoring streaming jobs.

SPARK SQL

  • Introduction to Apache Spark SQL
  • The SQL context
  • Importing and saving data
  • Processing the Text files,JSON and Parquet Files
  • DataFrames
  • user-defined functions
  • Using Hive
  • Local Hive Metastore server

SPARK MLIB.

  • Introduction to Machine Learning
    Types of Machine Learning.
  • Introduction to Apache Spark MLLib Algorithms.
  • Machine Learning Data Types and working with MLLib.
  • Regression and Classification Algorithms.
  • Decision Trees in depth.
  • Classification with SVM, Naive Bayes
  • Clustering with K-Means
  • Building the Spark server

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