Many people still wonder what is Apache Hadoop. It has to do with big data, Hortonworks is involved but what does it really consist of?? Apache Hadoop is an open source framework that enables distributed storage and processing of large data sets based on commercial hardware. In other words, Hadoop enables institutions to quickly obtain information from massive amounts of structured and unstructured data, positioning them at the level of current market demands in terms of dynamism and capacity.
The Hadoop ecosystem has solutions of all kinds to cover any need that the business may have regarding:
It is exactly these functionalities that best define what is Apache Hadoop although, to truly know the possibilities of this tool and the secret of its versatility, it is necessary to understand the origin of the benefits it brings; those that drive many corporations to opt for this alternative for their big data projects. All the benefits of Hadoop focus on some of its main qualities:
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Scalability: this tool enables you to store and distribute huge data sets on its hundreds of servers that operate in parallel, allowing you to forget the limits imposed by other alternatives.
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Speed– Ensures processing efficiency that no one can match, How else can terabytes of information be processed in minutes?
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Cost effectiveness: Data storage becomes a reality for companies as the investment required goes from tens of hundreds of euros per terabyte to hundreds of euros per terabyte.
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Flexibility: New data sources? No problem, New types of data? of course… Apache Hadoop adapts to the needs of the business and accompanies it in its expansion, providing real solutions for any initiative that arises.
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Resistance to failure: its tolerance to errors is one of its attributes best valued by users since all the information contained in each node is replicated in other nodes of the cluster. In case of failure, there will always be a copy ready to be used.
What is Apache Hadoop: enterprise Solutions
Every problem needs a solution and, therefore, get closer to discover what is Apache Hadoop implies entering the Apache Software Foundation projects. Each of them has been developed to offer an explicit function and, therefore, each has its own community of developers, as well as individual release cycles. Tools, integrate and work with Hadoop it's related to:
1. Data management: The goal is to store and process large amounts of data in a scalable storage layer and, to make it, viene el Distributed file systemA distributed file system (DFS) Allows storage and access to data on multiple servers, facilitating the management of large volumes of information. This type of system improves availability and redundancy, as files are replicated to different locations, reducing the risk of data loss. What's more, Allows users to access files from different platforms and devices, promoting collaboration and... the Hadoop (HDFSHDFS, o Hadoop Distributed File System, It is a key infrastructure for storing large volumes of data. Designed to run on common hardware, HDFS enables data distribution across multiple nodes, ensuring high availability and fault tolerance. Its architecture is based on a master-slave model, where a master node manages the system and slave nodes store the data, facilitating the efficient processing of information..). This technology, that works by means of inexpensive hardware, lays the foundation for efficient scale from the storage tier. It is also based on Apache Hadoop THREAD, Provides pluggable architecture and resource management to enable a wide variety of data access methods, which makes it feasible to operate with data stored in Hadoop at the desired performance and service levels. In short Apache Tez, what does magic do, processing big data in near real time, thanks to its generalization of the paradigm Small map that gains in efficiency.
2. Access to data: You cannot have the perspective necessary to answer the question of what Apache Hadoop is without knowing that one of its strengths is the accessibility that it guarantees, by allowing you to interact with data in a wide variety of ways and in real time. The applications that achieve this are:
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Apache HiveHive is a decentralized social media platform that allows its users to share content and connect with others without the intervention of a central authority. Uses blockchain technology to ensure data security and ownership. Unlike other social networks, Hive allows users to monetize their content through crypto rewards, which encourages the creation and active exchange of information....: the most widely adopted data access technology.
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Small map: enabling you to build applications that process large amounts of structured and unstructured data in parallel.
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Apache pig: a platform for the processing and analysis of large data sets.
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Apache HCatalog: which provides a centralized way for data processing systems that makes it possible to understand the structure and location of data stored in Apache Hadoop.
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Apache Hive: data warehouse that enables easy summarization and ad-hoc query launch via SQL-equivalent interface for large data sets stored in HDFS.
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Apache HBaseHBase is a NoSQL database designed to handle large volumes of data distributed in clusters. Based on the column model, Enables fast, scalable access to information. HBase easily integrates with Hadoop, making it a popular choice for applications that require massive data storage and processing. Its flexibility and ability to grow make it ideal for big data projects....: NoSQL column-oriented data storage system that provides access to read or write big data in real time for any application.
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Apache storm: adds reliable real-time data processing capabilities.
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Apache KafkaApache Kafka is a distributed messaging platform designed to handle real-time data streams. Originally developed by LinkedIn, Offers high availability and scalability, making it a popular choice for applications that require processing large volumes of data. Kafka allows developers to publish, Subscribe and store event logs, facilitating system integration and real-time analytics....: is a fast and scalable publish-subscribe messaging system that is often used in place of traditional message brokers due to its high performance, replication and fault tolerance.
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Apache mahout– Provides scalable machine learning algorithms for Hadoop that greatly assist data scientists in their clustering tasks, sorting and filtering.
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Apache Accumulation– A high-performance data storage device that includes recovery systems.
3. Governance and data integration: enables fast and efficient data loading based on the intervention of:
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Apache Falcon: is a data management framework that simplifies data lifecycle management and processing, which enables users to configure, manage and orchestrate data movement, parallel processing, error recovery and data retention; policy-based governance.
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Canal Apache– It enables you to move, in an aggregate and efficient way, large amounts of log data from many different sources to Hadoop.
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Apache SqoopSqoop es una herramienta de código abierto diseñada para facilitar la transferencia de datos entre bases de datos relacionales y el ecosistema Hadoop. Permite la importación de datos desde sistemas como MySQL, PostgreSQL y Oracle a HDFS, así como la exportación de datos desde Hadoop a estas bases de datos. Sqoop optimiza el proceso mediante la paralelización de las operaciones, lo que lo convierte en una solución eficiente para el...– Streamlines and facilitates the movement of data in and out of Hadoop.
4. Security: Apache Knox is responsible for providing a single point of authentication and access to the Apache Hadoop services in a group. Thus, simplicity in terms of security is ensured, tanto para los usuarios que acceden a los datos del clusterA cluster is a set of interconnected companies and organizations that operate in the same sector or geographical area, and that collaborate to improve their competitiveness. These groupings allow for the sharing of resources, Knowledge and technologies, fostering innovation and economic growth. Clusters can span a variety of industries, from technology to agriculture, and are fundamental for regional development and job creation...., as for the operators who are in charge of managing the cluster and controlling its access.
5. Operations: Apache Ambari provides the essential interface and APIs for provisioning, Hadoop cluster management and monitoring and integration with other management console software. Apache Zookeeper"Zookeeper" is a simulation video game released in 2001, where players take on the role of a zookeeper. The main mission is to manage and care for various species of animals, ensuring your well-being and the satisfaction of visitors. Throughout the game, Users can design and customize their zoo, facing challenges including food, the habitat and health of animals.... coordinates distributed processes, enabling distributed applications to store and mediate changes to important configuration information. Finally, Apache OozieOozie es un sistema de gestión de trabajos orientado a flujos de datos, diseñado para coordinar trabajos en Hadoop. Permite a los usuarios definir y programar trabajos complejos, integrando tareas de MapReduce, Pig, Hive y otros. Oozie utiliza un enfoque basado en XML para describir los flujos de trabajo y su ejecución, facilitando la orquestación de procesos en entornos de big data. Su funcionalidad mejora la eficiencia en el procesamiento... is in charge of guaranteeing the work logic in the programming tasks.
Today, with the new serverless platforms, Cloud, Spark, Kafka and the rise of data engineering, Apache Hadoop has lost some relevance. It is the logical consequence of the transition from business intelligence and big data to artificial intelligence and machine learning.. Despite this, despite the changes, this technology and its ecosystem will continue to adapt to, presumably, lead again, sometime, digital evolution, as they already did in their day.
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