Apache Spark Online Training will give you expertise to perform large-scale Data Processing using RDD, Spark Streaming, SparkSQL, MLlib, GraphX and Scala with Real Life use-cases on Banking and Telecom domain
Faculty : Real Time Expert | Duration : 20hrs | Material : Yes | Price : Rs.20,000/-
Itabhyas online training is the Best Spark Online Training in USA, UK, Australia, Canada and India.
Spark is an open source processing engine built around speed, ease of use, and analytics. If you have large amounts of data that requires low latency processing that a typical MapReduce program cannot provide, Spark is the way to go.
Apache Spark is another increasingly popular alternative to replace MapReduce with a more performant execution engine but still use Hadoop HDFS as storage engine for large data sets.
From architecture perspective Apache Spark is based on two key concepts; Resilient Distributed Datasets (RDD) and directed acyclic graph (DAG) execution engine. With regards to datasets, Spark supports two types of RDDs: parallelized collections that are based on existing Scala collections and Hadoop datasets that are created from the files stored on HDFS. RDDs support two kinds of operations: transformations and actions. Transformations create new datasets from the input (e.g. map or filter operations are transformations), whereas actions return a value after executing calculations on the dataset (e.g. reduce or count operations are actions).
The DAG engine helps to eliminate the MapReduce multi-stage execution model and offers significant performance improvements.
Spark Online Training batches will start every week. Make a call on +91-9030403937 or send a mail to firstname.lastname@example.org
1. Why Spark?
- Problems with Traditional Large-Scale Systems
- Introducing Spark
2. Spark Basics
- What is Apache Spark?
- Using the Spark Shell
- Resilient Distributed Datasets (RDDs)
- Functional Programming with Spark
3. Working with RDDs
- RDD Operations
- Key-Value Pair RDDs
- MapReduce and Pair RDD Operations
4. The Hadoop Distributed File System
- Why HDFS?
- HDFS Architecture
- Using HDFS
5. Running Spark on a Cluster
- A Spark Standalone Cluster
- The Spark Standalone Web UI
6. Parallel Programming with Spark
- RDD Partitions and HDFS Data Locality
- Working with Partitions
- Executing Parallel Operations
7. Caching and Persistence
- RDD Lineage
- Caching Overview
- Distributed Persistence
8. Writing Spark Applications
- Spark Applications vs. Spark Shell
- Creating the SparkContext
- Configuring Spark Properties
- Building and Running a Spark Application
9. Spark, Hadoop, and the Enterprise Data Center
- Spark and the Hadoop Ecosystem
- Spark and MapReduce
10. Spark Streaming
- Example: Streaming Word Count
- Other Streaming Operations
- Sliding Window Operations
- Developing Spark Streaming Applications
11. Common Spark Algorithms
- Iterative Algorithms
- Graph Analysis
- Machine Learning
- Improving Spark Performance
- Shared Variables: Broadcast Variables
- Shared Variables: Accumulators
- Common Performance Issues
- who is a trainer ?
IT Abhyas trainers are working professionals from the Industry and have 10 yrs of relevant experience.
- Will i ask for Demo session?
yes , we r conducting the demo sessions when u need.
- How i will practice ?
We will provide a software to do the practice.In case you come across any doubt, we have a 24*7 support team they will assist you.
- If I miss the session ?
Any situation you are not attend the session we will provide the Recorded session.
- What about the course Material?
We are ready to provide the course material.
- will i get the videos of course?
yes , you get the videos after completion of daily session.that access for life time.
- Will i enroll now take a sessions after?
yes you will join u take a sessions later.
- If i have any queries ?
you will send a mail or give a call to support team.