Apache Spark Key Highlights
Overview of Apache Spark Course in Chennai
Apache Spark Course in Chennai at BTree, you may deepen your understanding of the Big Data Hadoop Ecosystem. You get an essential, in-demand Apache Spark skills from this course, giving you a competitive edge as you pursue a rewarding career as a Spark Developer. A high-level API is provided by Apache Spark, a quick general-purpose computing system such as Python, R, Scala, and Java.
What is Apache Spark?
Apache Spark is a cluster computing tool that was primarily created for quick calculation. Spark is based on MapReduce and used for more complex computations, including stream processing and more queries. Spark is a memory cluster computing system that accelerates the processing of Hadoop applications.
Why do we need Apache Spark?
Apache Spark has gained popularity among most technology-based businesses worldwide. They quickly learned about the true benefits of Sparks, such as machine learning and interactive querying. Apache Spark has already been embraced by leading companies in the industry like Amazon, Huawei, and IBM. Initially built on Hadoop, companies like Hortonworks, Cloudera, and MapR have switched to Apache Spark. Furthermore, ETL professionals, SQL professionals, and Project Managers can all benefit greatly from learning Apache Spark.
Data Scientists are likely to work in the Machine Learning domain, making them ideal candidates for Apache Spark training. Those with a strong willingness to understand the latest developing technologies can also benefit from this Apache Spark training.
Why are we using Hadoop and Spark together?
The majority of people mistakenly believe that Spark replace Hadoop; nevertheless, Spark can act as a binding technology for Hadoop. However, Spark may operate independently of Hadoop and can run on a single cluster. On the top, Spark can use Hadoop’s storage and cluster management. We can use the capabilities of Hadoop to create a strong production environment. For simple resource management, Spark can alternatively use YARN Resource Manager.
Hadoop’s disaster recovery features can also be used by Apache Spark. To have better cluster administration and data management, we can use Spark with Hadoop. Better data security is provided by Spark and Hadoop combined.
Why Apache Spark course at BTree Systems?
With industry-leading facilities and 15 years of training experience, Btree System provides more than 60 IT training courses across more than ten locations in Chennai.
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Apache Spark Career Transition
60%
Avg Salary Hike
40 LPA
Highest Salary
500+
Career Transitions
300+
Hiring Partners
Apache Spark Skills Covered
Analysis and Exploration
Oozie Fundamentals and workflow creations
Deploying Kafka
Persistence Storage Levels
Sorting data using sortByKey
Access Modifier
Spark SQL
YARN
Sqoop
Apache Spark Course Fees
16
Sep
SAT - SUN
08:00 PM TO 11:00 PM IST (GMT +5:30)
23
Sep
SAT - SUN
08:00 PM TO 11:00 PM IST (GMT +5:30)
30
Sep
SAT - SUN
08:00 PM TO 11:00 PM IST (GMT +5:30)
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Curriculum for Apache Spark Course in Chennai
What is Spark
- Philosophy History
- Present & Future
Introduction to Spark
- Architecture Language APIs Spark Session Data Frames Lazy Evaluation
- Actions
- Spark UI
Spark Setup / Installation
- Setup Spark
Spark Components
- Structured API Spark Streaming MLib
- GraphX
Structured API Overview
- Data Frames Datasets Schemas Columns Rows Spark Types Execution
- Logical Plan
- Physical Plan Data Frame Operations
- Create
- Select
- Sorting
- Repartition, Coalesce etc. Aggregations
- Joins
- Working with different datatypes Working with complex data types Working with JSON.
- File formats
Spark SQL
- Hive
- Spark & Hive Relationship Run SparkSQL Queries Catalog
- Types of Tables
Spark internal working
- How Spark Works internally Lifecycle of Spark Application
Development Process of Spark Applications
- Write a sample Pyspark application
Deploying Spark Applications
- Modes of cluster deployments Standalone Mode
- Spark on Mesos
- Spark on YARN
Monitoring & Debugging
- Driver & Executor Processes Queries, Jobs, Stages and Tasks Spark Logs
- Spark UI
Performance Tuning
- Parallelism
- Filtering
- Repartition & Coalescing Caching
- Joins
- Aggregations
- Broadcast Variables
Sqoop
- Introduction Architecture
- Import / Export Data
“Accelerate Your Career Growth: Empowering You to Reach New Heights in Apache Spark”
Apache Spark Training Options
Apache Spark Classroom Training
- 50+ hours of live classroom training
- Real-Time trainer assistance
- Cutting-Edge on Apache Spark tools
- Non-Crowded training batches
- Work on real-time projects
- Flexible timings for sessions
Apache Spark online training
- 50+ Hours of online Apache Spark Training
- 1:1 personalised assistance
- Practical knowledge
- Chat and discussion panel for assistance
- Work on live projects with virtual assistance
- 24/7 support through email, chat, and social media.
Apache Spark Certification
This certificate shows that the learner has acquired the necessary coveted skills to work as an Apache Spark Developer due to the real-time exposure and project experience provided in the Spark course.
At BTree Systems, Apache Spark training is provided by Spark professionals with a minimum of 8+ years of experience working with the Big Data platform.
At BTree, the Apache Spark Mentors are professionally trained in the Big Data industry’s trends and practices.
Having an Apache Spark achievement certificate with your resume enhances your profile among your peers at the time of the interview and provides access to wider job possibilities.
Knowledge Hub with Additional Information of Apache Spark Training
Apache Hadoop vs Apache Spark
There are some significant differences between the open-source large data processing frameworks Apache Hadoop and Apache Spark. Spark uses robust distributed datasets while Hadoop uses the MapReduce method to process data (RDDs). Data files can be saved across numerous workstations thanks to Hadoop’s distributed file system (HDFS). The file system is expandable because more computers and servers may be added to handle growing data volumes. As a result, Spark is mostly utilized for computation on top of Hadoop because it does not offer a distributed file storage system. Spark can be used with Hadoop even if it doesn’t require it because it can build distributed datasets from HDFS files.
Benefits of Apache Spark
Speed: Spark, which was built from the ground up for performance, can be 100 times quicker than Hadoop for large-scale data processing by leveraging in-memory computation and other enhancements. The world record for large-scale on-disk sorting is presently held by Spark, which is also quick when data is kept on a disc.
Ease of Use: Spark features simple-to-use APIs for working with huge datasets. This consists of a set of more than 100 data transformation operators as well as well-known data frame APIs for working with semi-structured data. Higher-level libraries, including support for SQL queries, streaming data, machine learning, and graph processing, are packed with a Unified Engine Spark. These industry-recognized libraries boost developer efficiency and may be seamlessly coupled to build intricate processes.
Future scope of Apache Spark
• Spark has a promising future. Apache Spark is used in real-time use cases by anyone using Hadoop in any industry or field.
• Due to the reasons below, Apache Spark is preferred by 99% of industries across all sectors. Really important MapReduce is much easier to implement in Apache Spark.
• Spark is independent-running. In addition, it can read any existing Hadoop data and run on Hadoop 2’s YARN cluster manager. A wide range of tools is available to work with real-time data if you look at the Apache Spark ecosystem.
• Importantly Cluster management is a laborious chore for businesses, but Apache Mesos excels at handling clusters with little effort. Overall, Apache Spark has a bright future and is already being used by many different businesses.
Apache Spark PayScale
The average yearly income for a spark developer in India is 6.8 lakhs, with salaries ranging from 4.4 lakhs to 16.5 lakhs. The 133 salaries that Spark Developers have provided as a basis for their salary estimates.
With less than two years of experience to eight years of experience, a Spark Developer’s compensation in India can range from 4.4 lakhs to 16.5 lakhs, with an average yearly salary of 6.8 lakhs based on 133 salaries.
The typical annual compensation for an Apache Spark Developer in Chennai is from 12.2 to 15.5 lakhs. This is an estimation based on compensation paid to a small number of Apache Spark developers.
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FAQ on Apache Spark Course
What are the prerequisites for learning Apache Spark?
Hadoop file system fundamentals
knowledge of SQL principles
And any distributed database’s fundamentals (HBase, Cassandra)
Is Apache Spark hard to learn?
Apache Spark is not difficult to understand; Scala is the programming language used to create Apache Spark. Scala is a programming language that is new, powerful, and fast increasing. SQL knowledge is necessary to implement Spark real-time projects. Basic programming knowledge is required to understand Scala.
Are you looking for an existing offer?
Call now at +91 7397396665 to learn about the great offers that are currently available.
Does BTree Systems placement assistance after the course completion?
100% placement support is offered to our students by our extremely active placement cell. Even after the training is completed, the team continues to assist students by coaching them in mock interviews and conversations.
What are the advantages of joining at BTree Systems?
BTree Systems is a leading provider of IT training in Chennai. Over the years, we have taught students from a wide range of backgrounds. There are various advantages to using BTree Systems’ WBS, Activities, EPS, OBS, Roles, and Resources. Using a real-time project management platform, you may monitor and report on project performance.
Classrooms that are well-equipped
Providing hands-on training
Experts devised the curriculum.
Instructors who are knowledgeable and have flexible batch times
Exposure by Industry
Assistance with placement and reasonable rates
Where can I book a free demo session?
You can reach us at +91-7397396665, and we get back to you as soon as possible.
What if I miss the sessions?
Before the next session, you can examine the recordings of each Apache Spark course that BTree Systems offers. You can take as many lessons as you like for 60 days. Our Combi is now available.
What are the different modes of training that BTree Systems provide?
BTree Systems provide various modes of training to the student like
Classroom training
One-to-one training
Live instructor Online training
Customized training
What kind of certification do I get after finishing the course?
You receive BTree Systems globally recognized course completion certification.
What are the available payment options?
Payments can be made in any of the ways indicated below, and a receipt emailed to you instantly for both classroom and online training. We recently added EMI options to all of our courses.
EMI Visa Debit/Credit Card
The MasterCard.
Internet Banking /PayPal
Google Pay, PhonePe and Paytm
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