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Apache Spark & Scala Introduction
Apache Spark and Scala web based instructional class is composed by industry specialists according to market principles to make you very adept to propel your vocation in second Gen Big Data Tool as a large number of different experts have officially done by joining this course.
Gotten to be Spark and Scala master by acing the ideas of Spark and its environment, RDD, Spark Streaming, MLlib GraphX, Spark SQL and Scala. Singular themes are disclosed utilizing various workshops to give hands on information. The course additionally incorporates genuine utilize cases, various POCs and ongoing Spark venture to make you prepared to take Apache Spark occupations.
Apache Spark & Scala Online training Highlights
- Scenario Oriented Training
- Materials and Certification Guidance
- Access For Hands-On
- Live-Support During Sessions Hours
About Our Apache Spark & Scala Trainers
- More than 6 Years of experience in Apache Spark & Scala Technologies
- Has worked on multiple realtime Apache Spark & Scala projects
- Working in a top MNC company
- Trained 2000+ Students so far.
- Strong Theoretical & Practical Knowledge
- Industry certified Professionals
Apache Spark & Scala Certification Info
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
- Some experience coding in Python, Java, or Scala, plus some familiarity with Big Data issues/concepts.
Online
- It is a 12 days program and extends up to 2hrs each.
- The format is 20% theory, 80% Hands-on.
- Instructor-Led Regular Online (Limited Persons Per Group) Training.
- Instructor-Led Online On Demand Training ( 1-1 or Corporate Training ).
Corporate
- It is a 3 days program and extends up to 8hrs each.
- The format is 20% theory, 80% Hands-on.
Classroom
- Private Classroom arranged on request and minimum attendees for batch is 4.
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