Apache Spark Training in Tambaram Chennai

Apache Spark Training in Tambaram Chennai:

Greens Technology Tambaram is one of the best Apache Spark Training Institutes in Chennai Tambaram. We are focusing Placement based hands-on training for Apache Spark Course. Our Apache Spark course Trainers are taking the classes from basic level to Advanced Level. So, our Students can get the job easily in MNC companies in Chennai and Bangalore once complete their Apache Spark Classes. Our Apache Spark Course content and syllabus are revised monthly once by our experienced trainers. Our Apache Spark training syllabus is designed for fulfilled to our student’s needs. So, you can get the up-to-date technical knowledge in Apache Spark field. Our 6+ years of experienced trainers are working hard to improve their student knowledge and helps to attend the interviews confidently.

Our Training center offering Apache Spark Training in various places around the Tambaram Chennai. We are providing well infrastructure with fully equipped lab facilities to our students. We pay more attention to the needs of our students. Already we have trained more than 200+ Students in Chennai with placement. Apache Spark Training timing schedule on weekday classes, Weekend classes, Evening classes and Fast Track classes. Our Apache Spark Course fees is based on student’s requirement and value for money. After completing Apache Spark Classes, providing free resume building classes, Aptitude classes, Mockup Interview Sessions.

Our Apache Spark Course syllabus covering some important topics like Linux Fundamental, Boot and Package management, User Administration, Run Level, Service protocol, Introduction Cloud computing, Virtualization, Load Balancing, EBS, Storage on Cloud, cloud infront, Apache Spark real-time project and Apache Spark placement training in Tambaram Chennai.

Apache Spark Training in Tambaram Chennai syllabus:

1.1 SCALA (Object Oriented and Functional Programming)
1.2 Scala Environment Set up.
1.3 Functional Programming.
1.4 Collections (Very Important for Spark)
1.5 Object Oriented Programming.
1.6 Integrations
1.7 SPARK CORE.
1.8 Persistence.
1.9 CASSANDRA (N0SQL DATABASE)
1.10 SPARK INTEGRATION WITH NO SQL (CASSANDRA) and AMAZON EC2
1.11 SPARK STREAMING
1.12 SPARK SQL
1.13 SPARK MLIB.

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