Spark Training
Spark online training course is designed to build complete, unified Big Data applications combining batch, streaming, and interactive analytics of data.
Instructor-Led Live Online Training
- Hands On Experience
- Certified & Industry Experts Trainers
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- Customize Course Curriculum
- Schedule: 24 Nov 2018 - 23 Dec 2018
- Schedule: 01 Dec 2018 - 31 Dec 2018
- Schedule: 15 Dec 2018 - 14 Jan 2019
- Contact Us for Flexible Timings
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- Learning through Videos
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Course Details
What is Apache Spark?
Apache Spark is a collection platform designed to be general purpose and fast. Spark is created to be highly accessible, offering simple APIs in Scala, SQL, Python, and Java and rich built-in libraries.
Apache Spark is developed as the next generation big data processing engine, and is being applied throughout the industry faster than ever. Apache Spark improves over Hadoop Map Reduce, which helped ignite the big data revolution, in several key dimensions: it is faster, much easier to use due to its rich API’s and its goes far above batch applications to support a variety of including interactive queries, workloads, machine learning, graph processing, and streaming.
Why to attend Tekslate Online Training ?
Classes are conducted by Certified Spark Working Professionals with 100 % Quality Assurance.
With an experienced Certified practitioner who will teach you the essentials you need to know to kick-start your career on Spark. Our training make you more productive with your Spark Training Online. Our training style is entirely hands-on. We will provide access to our desktop screen and will be actively conducting hands-on labs with real-time projects.
Spark Training Course Curriculum
Introduction To Big Data and Spark
Introduction to Big Data, Challenges with Big Data, Batch Vs. Real Time Big Data Analytics, Batch Analytics – Hadoop Ecosystem Overview, Real Time Analytics Options, Streaming Data – Storm, In Memory Data – Spark, What is Spark?, Modes of Spark, Spark Installation Demo, Overview of Spark on a cluster, Spark Standalone Cluster
Spark Baby Steps
Invoking Spark Shell, Creating the SparkContext, Loading a File in Shell, Performing Some Basic Operations on Files in Spark Shell, Building a Spark Project with sbt, Running Spark Project with sbt, Caching Overview, Distributed Persistence, Spark Streaming Overview, Example: Streaming Word Count
Playing With RDDs In Spark
RDDs, Spark Transformations in RDD, Actions in RDD, Loading Data in RDD, Saving Data through RDD, Spark Key-Value Pair RDD, Map Reduce and Pair RDD Operations in Spark, Scala and Hadoop Integration Hands on
Shark – When Spark Meets Hive
Why Shark?, Installing Shark, Running Shark, Loading of Data, Hive Queries through Spark, Testing Tips in Scala, Performance Tuning Tips in Spark, Shared Variables: Broadcast Variables, Shared Variables: Accumulators
Spark Overview
Apache Spark is an exciting new technology that is rapidly superseding Hadoop as the preferred Big Data processing platform. Its unique design, which allows for keeping large parts of data in memory, offers tremendous performance improvements. Spark programs can be even 100 times faster than their Hadoop counterparts. Spark’s elegant API and runtime architecture allow you to write distributed programs in a manner similar to writing the local ones, using functional programming methods, which are very appropriate for data processing. By supporting Python, Java and Scala, Spark is open to a wide range of users: to the science community traditionally favoring Python, to the still widespread Java community and to people using the ever more popular Scala, offering functional programming on the JVM. Finally, Spark combines MapReduce-like capabilities for batch programming, real-time data processing functions, SQL-like handling of structured data, graph algorithms, and machine learning, all in a single framework. This makes it a one-stop-shop for all your BigData crunching needs.
Features of Spark
Fast: Data processing up to 100x faster than MapReduce, both in-memory and on disk
Powerful: Write sophisticated parallel applications quickly in Java, Scala, or Python without having to think in terms of only “map” and “reduce” operators
Integrated: Spark is deeply integrated with CDH, able to read any data in HDFS and deployed through Cloudera Manager
Advantages of Spark
In practice, it is said that Spark is 10x faster than Hadoop on average.
Agility compared to the monolithic aspect of Hadoop: Spark allows rapid changes, thanks to loading the data into memory and interacting with it in a rapid manner. The shell (REPL) is great to test things out.
Data scientists & non-data engineers can use Spark through Python.
Newer platform with multiple tools like Machine learning, Graph and streaming included, with strong community support.
Scala is superior for data processing thanks to its higher level of abstraction. Although Spark supports Java, it is recommended to use Scala in Spark as a non-functional programming will make coding less intuitive and lower level. Also using Scala will make debugging will be easier. A combination of using an IDE (for API auto completion and data typing) and REPL (interactive shell) s actually best for efficiency.
SPARK’S Performance
Spark’s core concept is an in-memory execution model which enables caching of job data in memory, instead of fetching it from disk every time, like MapReduce does. This can speed up the execution of jobs up to 100 times, compared to the same jobs in Hadoop. This has the biggest effect on iterative algorithms, like machine learning, graph algorithms and other types of workloads that need to reuse data and it is a huge performance improvement over classic MapReduce jobs.
Spark Components
Spark Core is the basic component on which the other four components depend. Also pictured are various storage systems where Spark can access data from: distributed storage systems like HDFS, GlusterFS, S3 and similar; distributed databases like Cassandra, Impala, Hive, HBase, Hypertable, and others; but also classic relational databases, such as Oracle, PostgreSQL or DB2.
Spark Core
Spark Core contains basic Spark functionalities required for running jobs and needed by other components. The most important of these is the RDD concept, or resilient distributed dataset, which is the main element of Spark API. It is an abstraction of a distributed collection of items with operations and transformations applicable to the dataset. It is resilient because it is capable of rebuilding datasets in case of node failures. Spark Core also provides means of information sharing between computing nodes with broadcast variables and accumulators. Other fundamental functions, like networking, security, scheduling and data shuffling, are also part of the Spark Core.
Spark SQL
Spark SQL is the newest Spark component, but very actively developed. It provides functions for manipulating large sets of distributed, structured data using SQL (actually, an SQL subset supported by Spark) and Hive SQL language (HQL). Spark SQL can also be used for querying JSON data as well as for writing and reading Parquet files, which is an increasingly popular file format that allows for storing schema along with the data. It provides a query optimization framework called Catalyst that can be extended by custom optimization rules and includes a Thrift server, which can be used by external systems, such as BI tools, to query data through Spark SQL using classic JDBC and ODBC protocols.
Spark Streaming
Spark Streaming is a framework for ingestion of real-time streaming data from various sources. The supported sources include HDFS, Kafka, Flume, Twitter, ZeroMQ and custom ones. Its operations recover from failure automatically which is, of course, very important for online data processing. Spark Streaming can be combined with other Spark components in a single program unifying real-time processing with machine learning, SQL and graph operations, which is something not seen in the Hadoop ecosystem.
Spark GraphX
Graphs are data structures comprised of vertices and edges connecting them. GraphX provides functions for building graphs and implementations of the most important algorithms of the graph theory, like page rank, connected components, shortest paths, SVD++ and others. It also provides Pregel message-passing API, the same API for large scale graph processing implemented by Apache Giraph, a project with implementations of graph algorithms and running on Hadoop.
Spark MLlib
Spark MLlib is a library of machine learning algorithms grown from MLbase project at UC Berkeley. Supported algorithms include logistic regression, naive Bayes classification, SVM, decision trees, random forests, linear regression, k-means clustering and others.
Salary Trends
Average Spark Salary in USA is increasing and is much better than other products.
Ref: Indeed.com
Average Spark Salary in India.
Ref: Glassdoor.com
Spark Certification
Spark Developer credential is designed for Engineers, Programmers, and Developers who prepare and process large amounts of data using Spark.
- Having Spark certification distinguishes you as an expert.
- For Spark certification, you need not go to a test center, as the certification is available online.
- You need to register yourself at https://www.mapr.com/services/mapr-academy/mapr-certified-spark-developer to give your Spark Exam.
Exam Details: http://learn.mapr.com/mcsd-mapr-certified-spark-developer
Benefits to our Global Learners
- Tekslate services are Student-centered learning.
- Qualitative & cost effective learning at your pace.
- Geographical access to learn from any part of the world.
Apache Spark Certification Training in Your City
Apache Spark Training United States
Our trainers in US are certified and have in-depth knowledge regarding Apache Spark Concepts. Tekslate superior quality training is what makes us stand apart from others. Case studies are included in the curriculum of training programs irrespective of the mode you chose. You can avail training in your cities like New York, Los Angeles, Chicago, Houston, and more.
Apache Spark Training United Kingdom
For experienced professionals in UK, special batches are conducted in different timings. Customized approach to imparting training has made us different from others. You can clarify your doubts after completing the class. You can avail training in your cities like London, Birmingham, Leeds, Glasgow and more.
Apache Spark Training Canada
There are many companies that offer Apache Spark training in Canada. Our Apache Spark course provides basic understanding about the introduction and overview. It is the course that can be educate right from the beginner to the intermediate and advanced level. Apache Spark Training is provided by Real Time Industry Experts who has huge subject knowledge, skills and enhances the skills of students in the best way. You can avail training in your cities like Montreal, Winnipeg, Mississauga, Ottawa and more.
Apache Spark Training India
Tekslate provides instructor-led live online training and corporate training. Apache Spark Training provides you hands on real-time project experience. Our Apache Spark trainers are certified industry experts and work professionals. We provide customized training for beginners as well working professionals.
- Apache Spark Training in Hyderabad – We at TekSlate offer interactively designed Apache Spark Certification training. The Apache Spark Training course design in Hyderabad aims not only imparting theoretical concepts, but also aid students explore and experiment the subject. By the end of our training program, students can confidently update their profiles with knowledge and Hands on experience.
- Apache Spark Training in Bangalore – TekSlate masters in IT Online Training services. We are aware of industry needs and we are offering Apache Spark Training in Bangalore in a more practical way. We guarantee efficient training offered by real-time experts in the industry.
- Apache Spark Training in Chennai – TekSlate is one of the top-ranked Institute in Apache Spark training in Chennai. We provide best quality training for Apache Spark online with well-experienced professionals. Our unique blend of hands-on training enables students with the productive skills to improve their performance.
- Apache Spark Training in Pune – TekSlate offers Instructor-led online training by Top-Notch Trainers in Pune. Every session will be recorded and provided to you for future reference. Good quality Material will help students explore the subject confidently.
- Apache Spark Training in Mumbai – TekSlate offers best Apache Spark Training in Mumbai with most experienced professionals. Our Instructors are working professionals in the related technologies. Our team of trainers provides training services in a practical way with a framed syllabus to match with the real world requirements for both beginner level to advanced level.
- Apache Spark Training in Delhi – Apache Spark Training helps you to develop your IT skills through our wide variant training curricula. TekSlate in Delhi has immense experienced real-time professionals having years of experience. Our training program is very much mixed with both practical and interview point of questions to achieve the expertise in the subject.
Faq's
Tekslate basically offers the online instructor-led training. Apart from that we also provide corporate training for enterprises.
Our trainers have relevant experience in implementing real-time solutions on different queries related to different topics of Spark Training. Tekslate also verifies their technical background and expertise.
As we are one of the leading providers of Training in Spark , We have customers from: Popular cities of USA, like: The City of New York, often called New York City (NYC) or simply New York, is the most populous city in the United States.New York City is also the most densely populated major city in the United States. Located at the southern tip of the state of New York, the city is the center of the New York metropolitan area, the largest metropolitan area in the world by urban landmass and one of the world’s most populous mega cities. Silicon Alley, centered in Manhattan, has evolved into a metonym for the sphere encompassing the New York City metropolitan region’s high technology industries involving the Internet, new media, telecommunications, digital media, software development, biotechnology, game design, financial technology (“FinTech”), and other fields within information technology that are supported by its entrepreneurship ecosystem and venture capital investments. Houston is the most populous city in the U.S. state of Texas and the fourth most populous city in the United States. Houston is recognized worldwide for its energy industry—particularly for oil and natural gas—as well as for biomedical research and aeronautics. Renewable energy sources—wind and solar—are also growing economic bases in the city. The Chicago metropolitan area, often referred to as “Chicagoland”, has nearly 10 million people and is the third-largest in the United States and fourth largest in North America. Positioned along Lake Michigan, the city is an international hub for finance, commerce, industry, technology, telecommunications, and transportation. The city claims two Dow 30 companies: aerospace giant Boeing, which moved its headquarters from Seattle to the Chicago Loop in 2001 and Kraft Heinz. Dallas is the most populous city in the Dallas–Fort Worth metroplex, which is the fourth most populous metropolitan area in the United States. The economy of Dallas is considered diverse, with dominant sectors including defense, financial services, information technology, telecommunications and transportation. It serves as the headquarters for 9 Fortune 500 companies within the city limits. San Jose officially the City of San Jose is an economic, cultural and political center of Silicon Valley and the largest city in Northern California. San Jose is a global city, notable as a center of innovation, for its affluence,weather, and high cost of living. San Jose’s location within the booming high tech industry, as a cultural, political, and economic center has earned the city the nickname “Capital of Silicon Valley”.Spark Training in New York
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TekSlate is the leading training provider in Hyderabad. Hyderabad popularly known as the City of Pearls & is the capital city of Andhra Pradesh. The city popular for its Film City and Charminar, Hyderabad is also a growing metropolitan area of the South. The city has been a prosperous pear and diamond trading center for the nation from years. Alongside, many manufacturing and financial institutions entered the city with industrialization. Also the flourishing pharmaceutical and biotechnology industries in Hyderabad earned it the title of India& pharmaceutical capital. The city is home to more than 1300 IT firms including Google, IBM, Yahoo, Dell, Facebook, Infosys, TCS, Wipro and more. TekSlate is the leading training provider in Bangalore. It is the capital of the Indian state of Karnataka. It has a population of over ten million, making it a megacity and the third most populous city and fifth most populous urban agglomeration in India. Bangalore is sometimes referred to as the “Silicon Valley of India” (or “IT capital of India”) because of its role as the nation’s leading information technology (IT) exporter. Indian technological organisations ISRO, Infosys, Wipro and HAL are headquartered in the city. Madras is divided into four broad regions: North, Central, South and West. North Madras is primarily an industrial area. South Madras and West Madras, previously mostly residential, are fast becoming commercial, home to a growing number of information technology firms, financial companies and call centers. Pune is known as “Oxford of the East” due to the presence of several well-known educational institutions. The city has emerged as a major educational hub in recent decades, with nearly half of the total international students in the country studying in Pune. Research institutes of information technology (IT), education, management and training in the region attract students and professionals from India and overseas. Several colleges in Pune have student-exchange programs with colleges in Europe. Along with it, we also prevail our valuable online training in the places of UK, Australia, and other parts of the world.Spark Training in Hyderabad
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Spark Training in Chennai
Spark Training in Pune
We record each LIVE class session you undergo through and we will share the recordings of each session/class.
If you have any queries you can contact our 24/7 dedicated support to raise a ticket. We provide you email support and solution to your queries. If the query is not resolved by email we can arrange for a one-on-one session with our trainers.
You will work on real world Best Spark Online Training projects wherein you can apply your knowledge and skills that you acquired through our training. We have multiple projects that thoroughly test your skills and knowledge of various aspect and components making you perfectly industry-ready.
Our Trainers will provide the Environment/Server Access to the students and we ensure practical real-time experience Spark Online training by providing all the utilities required for the in-depth understanding of the course.
If you are enrolled in classes and/or have paid fees, but want to cancel the registration for certain reason, it can be attained within 48 hours of initial registration. Please make a note that refunds will be processed within 30 days of prior request.
The Training itself is Real-time Project Oriented.
Yes. All the training sessions are LIVE Online Streaming using either through WebEx or GoToMeeting, thus promoting one-on-one trainer student Interaction.
There are some Group discounts available if the participants are more than 2.
As we are one of the leading providers of Online training, We have customers from: Popular cities of USA, like: Popular cities of Canada, like: Popular cities of India, like: Along with it, we also prevail our valuable online training in the places of UK, Australia, India and other parts of the world
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