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What (who) is yarn - definition

DISTRIBUTED DATA PROCESSING FRAMEWORK

HDFS; Hadoop Distributed Filesystem; Hadoop Distributed File System; Hadoop; Amazon Elastic MapReduce; Hadoop distributed file system; Hadoop YARN; YARN

Yarn

·noun One of the threads of which the strands of a rope are composed.

II. Yarn ·noun A story told by a sailor for the amusement of his companions; a story or tale; as, to spin a yarn.

III. Yarn ·noun Spun wool; woolen thread; also, thread of other material, as of cotton, flax, hemp, or silk; material spun and prepared for use in weaving, knitting, manufacturing sewing thread, or the like.

yarn

¦ noun

1. spun thread used for knitting, weaving, or sewing.

2. informal a long or rambling story, especially one that is implausible.

Austral./NZ a chat.

¦ verb informal tell a yarn.

?Austral./NZ chat; talk.

Origin

OE gearn; of Gmc origin.

yarn

(yarns)

1.

Yarn is thread used for knitting or making cloth.

She still spins the yarn and knits sweaters for her family.

...vegetable-dyed yarns.

N-MASS

2.

A yarn is a story that someone tells, often a true story with invented details which make it more interesting.

Doug has a yarn or two to tell me about his trips into the bush.

N-COUNT

Wikipedia

Apache Hadoop

Apache Hadoop ( ) is a collection of open-source software utilities that facilitates using a network of many computers to solve problems involving massive amounts of data and computation. It provides a software framework for distributed storage and processing of big data using the MapReduce programming model. Hadoop was originally designed for computer clusters built from commodity hardware, which is still the common use. It has since also found use on clusters of higher-end hardware. All the modules in Hadoop are designed with a fundamental assumption that hardware failures are common occurrences and should be automatically handled by the framework.

The core of Apache Hadoop consists of a storage part, known as Hadoop Distributed File System (HDFS), and a processing part which is a MapReduce programming model. Hadoop splits files into large blocks and distributes them across nodes in a cluster. It then transfers packaged code into nodes to process the data in parallel. This approach takes advantage of data locality, where nodes manipulate the data they have access to. This allows the dataset to be processed faster and more efficiently than it would be in a more conventional supercomputer architecture that relies on a parallel file system where computation and data are distributed via high-speed networking.

The base Apache Hadoop framework is composed of the following modules:

Hadoop Common – contains libraries and utilities needed by other Hadoop modules;
Hadoop Distributed File System (HDFS) – a distributed file-system that stores data on commodity machines, providing very high aggregate bandwidth across the cluster;
Hadoop YARN – (introduced in 2012) a platform responsible for managing computing resources in clusters and using them for scheduling users' applications;
Hadoop MapReduce – an implementation of the MapReduce programming model for large-scale data processing.
Hadoop Ozone – (introduced in 2020) An object store for Hadoop

The term Hadoop is often used for both base modules and sub-modules and also the ecosystem, or collection of additional software packages that can be installed on top of or alongside Hadoop, such as Apache Pig, Apache Hive, Apache HBase, Apache Phoenix, Apache Spark, Apache ZooKeeper, Apache Impala, Apache Flume, Apache Sqoop, Apache Oozie, and Apache Storm.

Apache Hadoop's MapReduce and HDFS components were inspired by Google papers on MapReduce and Google File System.

The Hadoop framework itself is mostly written in the Java programming language, with some native code in C and command line utilities written as shell scripts. Though MapReduce Java code is common, any programming language can be used with Hadoop Streaming to implement the map and reduce parts of the user's program. Other projects in the Hadoop ecosystem expose richer user interfaces.

https://en.wikipedia.org/wiki/Apache Hadoop

Examples of use of yarn

1. Cotton textile production declined by 0.88 percent and cotton yarn was down 0.55 percent.

2. This year‘s scariest yarn was given credence by O Globo, one of neighboring Brazil‘s largest newspapers.

3. Its main industries are construction, the manufacture of synthetic fibers, woolen yarn, and knitted goods.

4. Washington has put emergency import curbs on trousers, shirts, underwear and cotton yarn from China.

5. Increases were seen in the imports of materials for production of petroleum, plastics, paper and yarn.