Apache Spark Scala Training In Bangalore & Pune
22nd July35 Hrs.Weekend - Sat10:00 AM IST
18th July35 Hrs.Weekdays - Mon10:00 AM IST
29th July35 Hrs.Weekend Sat-Sun12:30 PM IST
1st Aug35 Hrs.Weekdays - Mon11:30 AM IST
Introduction of Spark & Scala
Apache Spark is an in-memory cluster computing, processing engine built for speed and accurate analytics. This engine provides an opportunity to process Big Data which is coupled with low latency and cannot be handled with Map Reduce programs. Spark is 100 times faster and user friendly when compared to Map Reduce and ensures fast speed and also supports Java, Scala and Python APIs.
About The Apache Spark Scala Training Course:
If you are looking for course to learn the concepts of Scala, RDD, OOPS, Traits, Spark SQL and MLib enroll yourself at PrwaTech for the Best Apache Spark Scala Training course. This training course will help the participants to learn various concepts of large-scale data processing. This online course is a part of Developer’s learning path.
Apache Spark is quickly gaining momentum not only in the headlines but also in real world adoption. Today, it has grown to the extent that, customers from all the industries are using it to improve their businesses with the HDP.
Learning Objectives: At the end of Spark Training course at PrwaTech, you will be able to:
- Learn Storm Architecture and basic distributed concepts.
- Learn Big Data features
- Understand Legacy architecture of real time systems
- Understand Logic Dynamics and Components in Storm
- Learn the difference between Hadoop and Apache Spark
- Learn Scala and the programming implementation in Scala
- Build Spark Applications using Java, Python and Scala
- Implement Spark on cluster
- Gain insight into functioning of Scala
- Develop Real-life Storm Projects
- Basic knowledge of Java basics is required.
- Prior knowledge of Hadoop is not mandatory.
Recommended AudienceFor Apache Spark Training:
Anyone aiming to build a career in real-time Data Analytics.
Software Engineers who are eager to learn concepts of Big Data processing.
Software Architects, ETL Developers, Data Scientists and Project Managers.
For Best Apache Spark Training course in Pune come and visit our Apache Spark training Pune institute, we also have presence in other cities if you are looking for Spark Training in Bangalore you can visit our Spark Training in Marathalli institute for best in class Apache Spark training in Bangalore. Visit our Spark training academy Pune to learn from one another as well as get educated through research updates and guest lectures.
Who should go for this course?
- Big Data Buffs
- Software Engineers, Architects and Developers
- Analytics Professionals
- Data Scientists
Introduction to Spark & Scala
In this module, will discuss about Big Data. How Big Data impact in our social life & its important role. How Hadoop is helpful to manage & process Big Data. What is problem with MapReduce and why spark came?
1.Big Data Problems
2. What is Hadoop?
3. Introduction to HDFS
4. Introduction to MapReduce with Example.
5. What is problem with Map reduce?
6. Why Apache Spark?
7. What is Apache Spark?
8. MapReduce vs Apache Spark
Apache Spark Installations & Its basics
In this module, we will learn about RDD creations and RDD operations.
- Apache Spark installations in local machine.
- Apache Spark Conf and spark context.
- RDD creations
- Operations on RDD
- RDD transformations functions
- Map & Flat Map difference
- Actions on RDD
Introductions to Scala
In this module, we will learn about Scala programing language.
1. Why Scala ?
4. Basic oops concepts.
5. Scala Flow Control.
7. Anonymous Functions.
8. Curried functions.
12. Abstract Classes.
Spark Advance Operations:
In this module, will learn more operations on apache spark transformation and actions.
- Working with RDD key-value
- RDD joins
- Shared Variables
- Broadcast variables
Apache Spark Architecture
In this Module we will discuss a Spark Internals execution details
1. Apache Spark Cluster Details.
2. Apache Spark Standalone Mode cluster.
3. Running Spark application in Standalone mode cluster.
4. Summary of RDD sizes and memory usage.
5. Spark web UI.
6. Apache Spark internals.
7. Apache spark execution flow.
6. DAG: Logical graph of RDD operations
7. RDD Physical Plan.
11. Types of RDD transformations
In this module, will learn about SQL operations in Spark.
1. SQL Context.
2. Data Frame Creations.
3. Creating temporary tables
4. Parquet tables.
5. Loading and processing csv file.
6. Loading and processing json File.
7. Writing data to local file system.
1. What is streaming?
2. Why streaming?
3. Discretized Streams.
4. Transformations on DStreams
5. Streaming Example
Machine learning using Spark
1. What is machine learning?
2. Machine learning current use cases.
3. Type of machine learnings.
5. Problem with traditional analytics tools
6. Supervised learning using Spark with examples.
7. Unsupervised learning using Spark with Examples