Spark Training in Marathahalli | Spark Training in Bangalore
Introduction to Spark
Spark Architecture explanation
Installation of Spark in different modes
Basics of Spark
Resilient Distributed Dataset (RDD)
Working with Key/Value Pairs
Loading and Saving Your Data
Broadcast and Accumulators
Working with Spark in different programming languages
Apache Spark SQL
- Spark SQL & Hive Architecture explanation Practical examples on Spark SQL
- Working with Spark SQL DataSets
- Working with Spark SQL DataFrames
- Practice on Spark SQL Context
- Integrating Spark SQL with o Hive o Phoenix o Cassandra o RDBMS
- Processing different files using Spark o Text o Json o Csv o Tsv o Parquet
- Spark SQL UDFsSpark SQL UDFs
- Spark SQL Performance Tuning Options
- JDBC/ODBC Server
Apache Spark Streaming
- Spark Streaming Architecture explanation
- Creating the Streaming Context
- Discretized Streams (DStreams)
- Transformations on Dstream
- Output Operations on DStreams
- Streaming UI explanation
- Spark Streaming Sources o Basic Sources o Advanced Sources
- Integrating Spark Streaming with o Flume o Kafka o Twitter o HDFS
- Performance Considerations
- Practical examples on Spark Streaming
Apache Spark MLib
Apache Spark Graphx
Introduction of Scala
Scala using Command Line
Basics of Scala
Scala Type Less, Do More
Expressions and Conditionals
Functional Programming in Scala
Object-Oriented Programming in Scala
Scala for Big Data
Spark with Big Data Integrations:
Real Time Big Data Projects
Spark Training in Bangalore
What is Apache spark?
Apache Spark is a lightning-fast cluster computing technology, designed for fast computation. It is based on Hadoop MapReduce and it extends the MapReduce model to efficiently use it for more types of computations, which includes interactive queries and stream processing. The main feature of Spark is its in-memory cluster computing that increases the processing speed of an application.
Spark is designed to cover a wide range of workloads such as batch applications, iterative algorithms, interactive queries and streaming. Apart from supporting all these workloads in a respective system, it reduces the management burden of maintaining separate tools. we Provide the best Spark training in Bangalore Marathahalli.
Why learn Apache spark?
Eminent It Provides the best Spark Training in Marathahalli Bangalore. Spark enables users to write applications in Java, Scala, Python, R. This helps them to create and run their applications on programming languages they are comfortable with. Spark also scores on many senses. You can write a custom Spark big data app, use Spark SQL and do data analysis using SQL, set up ETL pipelines using Spark, use Spark streaming and make it part of real-time data pipeline, use MLlib machine learning library and run Analytics… Or even do graph processing with GraphX. On top of this, Scala is supported by Java which helps write concise code. It can replace a 50 line java map-reduce code with a 2-3 line Scala Spark code.
About the course
Learn and master the art of framing data analysis problems as Spark problems through hands-on examples, and then scale them up to run on cloud computing services in this course.
Learn the concepts of Spark’s Resilient Distributed Datastores
Develop and run Spark jobs quickly using Python
Translate complex analysis problems into iterative or multi-stage Spark scripts
Scale up to larger data sets using Amazon’s Elastic MapReduce service
Understand how Hadoop YARN distributes Spark across computing clusters
Learn about other Spark technologies, like Spark SQL, Spark Streaming, and GraphX
By the end of this course, you’ll be running code that analyzes gigabytes worth of information – in the cloud – in a matter of minutes.
Apache Spark/Scala Course objective
Eminent IT is the best Apache Spark Training Institute in Bangalore and helps the students to obtain all course objectives.
- Frame big data analysis problems as Spark problems
- Use Amazon’s Elastic MapReduce service to run your job on a cluster with Hadoop YARN
- Install and run Apache Spark on a desktop computer or on a cluster
- Use Spark’s Resilient Distributed Datasets to process and analyze large data sets across many CPU’s
- Implement iterative algorithms such as breadth-first-search using Spark
- Use the MLLib machine learning library to answer common data mining questions
- Understand how Spark SQL lets you work with structured data
- Understand how Spark Streaming lets your process continuous streams of data in real time
- Tune and troubleshoot large jobs running on a cluster
- Share information between nodes on a Spark cluster using broadcast variables and accumulators
Understand how the GraphX library helps with network analysis problems
For whom it is designed
People with some software development background who want to learn the hottest technology in big data analysis will want to check this out. This course focuses on Spark from a software development standpoint; we introduce some machine learning and data mining concepts along the way, but that’s not the focus. If you want to learn how to use Spark to carve up huge datasets and extract meaning from them, then this course is for you.
If you’ve never written a computer program or a script before, this course isn’t for you – yet. I suggest starting with a Python course first if programming is new to you.
If your software development job involves, or will involve, processing large amounts of data, you need to know about Spark.
If you’re training for a new career in data science or big data, Spark is an important part of it.
Spark Future prospects
Eminent IT provides the best Apache Spark course in Bangalore. Around the globe, some large organizations have taken spark very seriously. Some popular companies like Amazon, Yahoo, Alibaba, eBay, Hitachi, Shopify, and many more. They have invested in talent around Spark. There is some ratio, in which jobs are available, such as in the batch processing of large data sets, 78% of them are engaged. Also, for event stream processing 60% required as support. Similarly, for fast, real-time data querying, around 56% are there. Moreover, at enhancing programming productivity 55% are aiming. Furthermore, there are some huge opportunities across industry segments, that includes:
Banking and Finance
Media and Entertainment
Professional scientific and technical services
- Lectures 196
- Quizzes 0
- Duration 40 hours
- Skill level All levels
- Language English
- Students 0
- Assessments Yes