por A drivers in Apache Spark It is one of the alternatives that is part of the wide variety of tools created for the proper management of Big Data from the Apache Spark system. In fact, this system in recent years has established itself as one of the most used computing systems by large companies to manipulate their big data.
Remember that big data or Big Data refers to a large volume of data; in fact, annually there is an increase of 12% in the data generated. Therefore, this field requires the multiplicity of tools it has.
Likewise, a factor such as drivers in Apache Spark it is a controller spark.driver.host that will make it easier for you to process big data; however, for this you must identify how they work together The other factors, such as WorkerNode and the Executors in Apache Spark. For this reason, in this post, we present to you what a drivers in Apache Spark and how it develops in its environment from the architecture of this computing system.
What is Apache Spark?
First of all, it is necessary to remember that Apache Spark is a computing system based on Hadoop Map Reduce. In effect, this system consists of allowing the division and parallelization of jobsso they work with data in a distributed way.
On the other hand, one of the most important aspects of what Apache Spark is is that provides different APIs (Application Programming Interface) to function, such as Core, SQL, streaming, Graph either Machine Learning. Similarly, Spark is a multilanguage that can be developed in systems like Scala, Java, JVM (Java Virtual Machine) Language, Python or R.
Apache Spark architecture
On the other hand, a drivers In Apache Spark it is part of the architecture that is composed through concepts such as SparkStack and Spark Corewithin which are the frameworks from spark-shell, RDD (Resilient Distributed Datasets o Distributed and flexible data sets) o Core API (Application Interface).
Besides, Apache Spark provides several ways to deploy. Below, we share the options in which you can carry out the deployment:
Local: could be deployed from the desktop.Standalone Data Manager: in Spanish, independent data loggers. It is an in-memory data system without the use of a local.Hadoop YARN (Yet Another Resource Negotiator): deployment in one of the control layers that is established over the applications or commands that run on Hadoop.Apache Mesos: This allows information to be extracted from local systems and developed in distributed systems.Kubernetes: You will also be able to deploy it in this open source container application system.
What is a driver in Apache Spark?
Well then, he drivers in Apache Spark it is the main processsince it controls the entire application and executes the SparkContext.
Besides, a drivers In Apache Spark it is a process that requires other components to be carried out. In fact, you can count on the cluster managerwhich is the communication of drivers with the backend for acquire physical resources and be able to execute the executors.
Later, from there, is in charge WorkerNode o Worker Nodewhich refers to machines that depend on the backend and who takes care of execute the processes of the executors.
Finally, as you have noticed, a drivers in Apache Spark it finishes its work by designating executors. Therefore, the executors they get their assignments from the drivers to carry out data loading, transformation and storage.
Next, We show you a graph that shows how the data flow works in the internal architecture of the Apache Spark system. In this example you can notice How these tools work together.
so that The Driver Program is the one that has the SparkContextthat is, who is in charge of the data under the concept RDD (Resilient Distributed Datasets) o Resilient distributed data sets, in Spanish. In sum, This connects to the Cluster Manager as an intermediary with the worker Nodes which designate the work of executors in Apache Spark.
Nevertheless, the Driver Program can communicate with the worker nodes (Worker Node) without the need for the Cluster Manager, since it is supplied by the controller spark.driver.host.
What is the next Big Data step?
Know What is it and how does it work? drivers in Apache Spark It has been established as a great pillar to understand the development of the data flow created by this computing system. Now that you recognize the theory about this factor, We advise you to continue with the next step, which consists of putting it into practice.
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