A Spark and Hadoop Spark training will enable you to become a Data Science professional. Find out why and how to master these Big Data processing tools. Big Data processing requires new tools capable of handling vast volumes of data. Hadoop and Spark are two of the main tools used by Data Scientists and Data Engineers.
What is Apache Hadoop?
Apache Hadoop is an open source framework for storing and processing large datasets. It enables data to be analyzed in parallel on a cluster of multiple computers, rather than on a single machine. This delivers significant speed gains.
Four main modules make up Hadoop. HDFS (Hadoop Distributed File System) is a distributed file system that can be run on standard or low-end hardware. It offers higher performance and greater error tolerance than conventional file systems.
The YARN (Yet Another Resource Negotiator) is used to manage and monitor cluster nodes and resource usage. It is also used to schedule tasks and jobs.
The MapReduce framework helps programs perform parallel calculations on data. Finally, Hadoop Common provides common Java libraries that can be used with all modules.
Hadoop makes it easier to use the full storage and processing capacity of clustered servers, and to run distributed processing on large volumes of data. This framework provides the building blocks on which applications and services are constructed.
Data from different sources and in various formats can be transferred to Hadoop using an API to connect to NameNode. Chunks of each file are replicated on DataNodes. MapReduce is then applied to the data distributed between the DataNodes.
Over the years, the Hadoop ecosystem has grown to include numerous tools and applications dedicated to Big Data. These include the Presto SQL engine, the Hive analytical interface, the HBase non-relational database, the Zeppelin interactive notebook, and the Apache Spark distributed processing system.
What is Apache Spark?
Apache Spark is a distributed processing system used for Big Data workloads. It uses in-memory caching and optimized query execution to enable fast queries on data of any size. Simply put, it’s a fast engine for Big Data processing.
It offers better performance than previous Big Data tools such as MapReduce. Its secret is that it runs on RAM, offering faster processing than on hard disks. This general-purpose engine can be used for distributed SQL queries, creating data pipelines, ingesting data into a database, running Machine Learning algorithms or working with data streams and graphs.
Today, Spark is included with most Hadoop distributions. It has become the leading Big Data processing framework, thanks to a number of advantages, starting with its speed and easy-to-use API for developers.
Why take a Hadoop training and Spark training course?
To work as a Data Scientist, Data Analyst or Data Engineer, mastering Big Data tools like Apache Hadoop and Spark is essential. By following a training course, you can acquire an expertise that is highly sought-after in companies.
By 2021, Glassdoor estimates that Data Science will be the second fastest-growing job sector in the United States. Professionals are coveted in all sectors, at a time when the global volume of data is exploding along with the adoption of artificial intelligence.
In France, according to our survey of the CAC 40, a Data Scientist can earn between €35,000 and €55,000 a year as a beginner, and between €45,000 and €60,000 with a little experience. A Data Analyst earns between €35,000 and €60,000 a year. Hadoop and Spark training?
How can I take a Hadoop training and Spark training course?
To learn how to use Hadoop and Spark, you can choose DataScientest training courses. These Big Data tools are at the heart of our Data Engineer, Data Scientist and Data Analyst programs.
Through these courses, you’ll learn to use Hadoop and Spark, as well as Python programming, SQL for databases, Machine Learning, DevOps and DataViz. At the end of the course, you’ll have all the skills you need to work in the Big Data industry.
Whether you’re looking for a job or already working, you can choose between the intensive BootCamp format or Continuing Education. Our innovative Blended Learning approach combines a coached, cloud-based platform with a masterclass.
At the end of the course, you’ll receive a certificate awarded by MINES ParisTech / PSL Executive Education. This qualification is recognized by industry, and over 80% of our alumni find immediate employment.
For financing, our programs are eligible for the funding options. So make the most of it! Find out more about DataScientest training courses.
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