Category: GLOSSARY

Hadoop YARN is the architectural center of Hadoop that allows multiple data processing engines such as interactive SQL, real-time streaming, data science and batch processing to handle data stored on a single platform, unlocking an entirely new approach to analytics. YARN is the foundation of the new generation of Hadoop and is enabling organizations everywhere to realize a modern data architecture. YARN also extends the…

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Hadoop Flume was created in the course of incubator Apache project to allow you to flow data from a source into your Hadoop environment. In Flume, the entities you work with are called sources, decorators, and sinks. A source can be any data source, and Flume has many predefined source adapters. A sink is the target of a specific operation (and in Flume, among other…

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Apache Kafka is an open-source stream processing platform developed by the Apache Software Foundation written in Scala and Java. The project aims to provide a unified, high-throughput, low-latency platform for handling real-time data feeds. Its storage layer is essentially a “massively scalable pub/sub message queue architected as a distributed transaction log, making it highly valuable for enterprise infrastructures to process streaming data. Additionally, Kafka connects…

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Hadoop Zookeeper is an open source Apacheā„¢ project that provides a centralized infrastructure and services that enable synchronization across a cluster. ZooKeeper maintains common objects needed in large cluster environments. Examples of these objects include configuration information, hierarchical naming space, etc. Applications can leverage these services to coordinate distributed processing across large clusters. Name services, group services, synchronization services, configuration management, and more, are available…

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Hadoop Hbase is a column-oriented database management system that runs on top of HDFS. It is well suited for sparse data sets, which are common in many big data use cases. An HBase system comprises a set of tables. Each table contains rows and columns, much like a traditional database. Each table must have an element defined as a Primary Key, and all access attempts…

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Hadoop Sqoop efficiently transfers bulk data between Apache Hadoop and structured datastores such as relational databases. Sqoop helps offload certain tasks (such as ETL processing) from the EDW to Hadoop for efficient execution at a much lower cost. Sqoop can also be used to extract data from Hadoop and export it into external structured datastores. Sqoop works with relational databases such as Teradata, Netezza, Oracle,…

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Hadoop Hive is a runtime Hadoop support structure that allows anyone who is already fluent with SQL (which is commonplace for relational data-base developers) to leverage the Hadoop platform right out of the gate. Hive allows SQL developers to write Hive Query Language (HQL) statements that are similar to standard SQL statements. HQL is limited in the commands it understands, but it is still useful….

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Hadoop Pig was initially developed at Yahoo to allow people using Hadoop to focus more on analyzing large datasets and spend less time writing mappers and reduce programs. This would allow people to do what they want to do instead of thinking about mapper and reducer tasks. Name Pig was given to the programming language with a hint on it being designed to handle any…

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Z-Score or Standard Score in statistics is the signed number of standard deviations by which the value of an observation or data point is above the mean value of what is being observed or measured. Observed values above the mean have positive standard scores, while values below the mean have negative standard scores. The standard score is a dimensionless quantity obtained by subtracting the population…

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Unsupervised Learning is a type of machine learning algorithm used to draw inferences from datasets consisting of input data without labelled responses. The most common unsupervised learning method is cluster analysis, which is used for exploratory data analysis to find hidden patterns or grouping in data. The clusters are modelled using a measure of similarity which is defined upon metrics such as Euclidean or probabilistic…

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