Best Institutes for Apache Spark 2.4 training in Ludhiana with Course Fees
List of 2+ Apache Spark 2.4 training institutes located near to you in Ludhiana as on May 31, 2020. Get access to training curriculum, placement training, course fees, contact phone numbers and students reviews.
Apache Spark 2.4 Training Institutes in Ludhiana - by Location
Yet5.com Provides complete list of best Apache Spark 2.4 training institutes in Ludhiana and training centers with contact address, phone number, training reviews, course fees, job placement, course content, special offers and trainer profile information by area.
Learning Apache Spark 2.4 course in Ludhiana - Benefits, Advantages & Placements.
We have identified the benefits of learning apache-spark course in Ludhiana.
Apache Spark 2.4 training in Ludhiana is part of Hadoop training course class,
The largest district of Punjab and the largest city in the north of Delhi .The city resides on the banks of Sutlejs old banks. The city is populous in the harvesting season and the city provides a high quality education. There are institutions and research organisations on engineering, management , medicine etc. The city attracts a lot of students as it has a good coaching and trainers. The city has many MNCs and food industries setting up as the place is rich in agriculture and attracts a lot of students for employment. The city is affordable to live in.
You have travel connectivity to apache-spark course educational training institutes in Ludhiana. The Ludhiana junction railway station connects all the metro cities and city is connected by national and state highways through Punjab. The Ludhiana airport located near the town of Sahnewal also has connecting flights plying to Delhi and other places. The Taxis and Auto rickshaw facility inside the city helps the localities to reach nearby places.
Apache Spark 2.4 course Content / syllabus in ludhiana
Below is the Apache Spark 2.4 course content in ludhiana used by the training institutes as part of the Apache Spark 2.4 course training. The Apache Spark 2.4 course syllabus covers basic to advanced level course contents which is used by most of Apache Spark 2.4 training classes in ludhiana .
1 SCALA (Object Oriented and Functional Programming)
1.1 Getting started With Scala.
1.2 Scala Background, Scala Vs Java and Basics.
1.3 Interactive Scala – REPL, data types, variables,expressions, simple functions.
1.4 Running the program with Scala Compiler.
1.5 Explore the type lattice and use type inference
1.6 Define Methodsand Pattern Matching.
2 Scala Environment Set up.
2.1 Scala set up on Windows.
2.2 Scala set up on UNIX.
3 Functional Programming.
3.1 What is Functional Programming.
3.2 Differences between OOPS and FPP.
4 Collections (Very Important for Spark)
4.1 Iterating, mapping, filtering and counting
4.2 Regular expressions and matching with them.
4.3 Maps, Sets, group By, Options, flatten, flat Map
4.4 Word count, IO operations,file access, flatMap
5 Object Oriented Programming.
5.1 Classes and Properties.
5.2 Objects, Packaging and Imports.
5.4 Objects, classes, inheritance, Lists with multiple related types, apply
6.1 What is SBT?
6.2 Integration of Scala in Eclipse IDE.
6.3 Integration of SBT with Eclipse.
7 SPARK CORE
7.1 Batch versus real-time data processing
7.2 Introduction to Spark, Spark versus Hadoop
7.3 Architecture of Spark.
7.4 Coding Spark jobs in Scala
7.5 Exploring the Spark shell -> Creating Spark
7.6 RDD Programming
7.7 Operations on RDD.
7.10 Loading Data and Saving Data.
7.11 Key Value Pair RDD.
7.12 Broad cast variables.
8.1 Configuring and running the Spark cluster.
8.2 Exploring to Multi Node Spark Cluster.
8.3 Cluster management
8.4 Submitting Spark jobs and running in the
8.5 Developing Spark applications in Eclipse
8.6 Tuning and Debugging Spark.
9 CASSANDRA (N0SQL DATABASE)
9.1 Learning Cassandra
9.2 Getting started with architecture
9.3 Installing Cassandra.
9.4 Communicating with Cassandra.
9.5 Creating a database.
9.6 Create a table
9.7 Inserting Data
9.8 Modelling Data.
9.9 Creating an Application with Web.
9.10 Updating and Deleting Data.
10 SPARK INTEGRATION WITH NO SQL (CASSANDRA) and AMAZON EC2
10.1 Introduction to Spark and Cassandra
10.2 Spark With Cassandra -> Set up.
10.3 Creating Spark Context to connect the
10.4 Creating Spark RDD on the Cassandra Data
10.5 Performing Transformation and Actions on the
10.6 Running Spark Application in Eclipse to
access the data in the Cassandra.
10.7 Introduction to Amazon Web Services.
10.8 Building 4 Node Spark Multi Node Cluster in
Amazon Web Services.
10.9 Deploying in Production with Mesos and YARN.
11 SPARK STREAMING
11.1 Introduction of Spark Streaming.
11.2 Architecture of Spark Streaming
11.3 Processing Distributed Log Files in Real Time
11.4 Discretized streams RDD.
11.5 Applying Transformations and Actions on
11.6 Integration with Flume and Kafka.
11.7 Integration with Cassandra
11.9 Monitoring streaming jobs.
12 SPARK SQL
12.1 Introduction to Apache Spark SQL
12.2 The SQL context
12.3 Importing and saving data
12.4 Processing the Text files,JSON and Parquet
12.6 user-defined functions
12.7 Using Hive
12.8 Local Hive Metastore server
13 SPARK MLIB.
13.1 Introduction to Machine Learning
13.2 Types of Machine Learning.
13.3 Introduction to Apache Spark MLLib
13.4 Machine Learning Data Types and working with
13.5 Regression and Classification Algorithms.
13.6 Decision Trees in depth.
13.7 Classification with SVM, Naive Bayes
13.8 Clustering with K-Means
13.9 Building the Spark server