Hadoop
E35621
Hadoop is an open-source framework that enables distributed storage and parallel processing of large data sets across clusters of commodity hardware.
All labels observed (11)
| Label | Occurrences |
|---|---|
| Apache Hadoop | 16 |
| Apache Hadoop ecosystem | 5 |
| Hadoop canonical | 4 |
| Apache Hadoop MapReduce | 2 |
| Hadoop 2.x | 2 |
| Hadoop ecosystem | 2 |
| Apache Hadoop 2.x | 1 |
| Apache Hadoop project | 1 |
| Hadoop 1.x | 1 |
| Hadoop Common | 1 |
| Hadoop Distributed File System | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T277419 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
Target entity: Hadoop Context triple: [SAS, supportsIntegrationWith, Hadoop]
-
A.
Amazon Redshift
Amazon Redshift is a fully managed, cloud-based data warehousing service from Amazon Web Services designed for fast querying and analysis of large datasets using SQL.
-
B.
Tableau
Tableau is a widely used data visualization and business intelligence software platform that enables users to analyze, explore, and present data through interactive dashboards and reports.
-
C.
Google BigQuery
Google BigQuery is a fully managed, serverless cloud data warehouse from Google Cloud designed for fast SQL-based analytics on large-scale datasets.
-
D.
yarn
Yarn is a fast, reliable JavaScript package manager that serves as an alternative to npm for managing project dependencies.
-
E.
Google Cloud
Google Cloud is Alphabet Inc.'s cloud computing platform offering infrastructure, platform, and software services for building, deploying, and scaling applications and data solutions.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Target entity: Hadoop Target entity description: Hadoop is an open-source framework that enables distributed storage and parallel processing of large data sets across clusters of commodity hardware.
-
A.
Amazon Redshift
Amazon Redshift is a fully managed, cloud-based data warehousing service from Amazon Web Services designed for fast querying and analysis of large datasets using SQL.
-
B.
Tableau
Tableau is a widely used data visualization and business intelligence software platform that enables users to analyze, explore, and present data through interactive dashboards and reports.
-
C.
Google BigQuery
Google BigQuery is a fully managed, serverless cloud data warehouse from Google Cloud designed for fast SQL-based analytics on large-scale datasets.
-
D.
yarn
Yarn is a fast, reliable JavaScript package manager that serves as an alternative to npm for managing project dependencies.
-
E.
Google Cloud
Google Cloud is Alphabet Inc.'s cloud computing platform offering infrastructure, platform, and software services for building, deploying, and scaling applications and data solutions.
- F. None of above. chosen
Statements (60)
| Predicate | Object |
|---|---|
| instanceOf |
big data framework
ⓘ
distributed computing framework ⓘ open-source software framework ⓘ |
| developer | Apache Software Foundation ⓘ |
| domain | big data ⓘ |
| ecosystemIncludes |
Apache Flume
ⓘ
Apache HBase ⓘ Apache Hive ⓘ Apache Mahout ⓘ Apache Oozie ⓘ Apache Pig ⓘ Apache Sqoop ⓘ Apache ZooKeeper ⓘ |
| hasComponent |
HDFS
ⓘ
Hadoop self-linksurface differs ⓘ
surface form:
Hadoop Common
Hadoop self-linksurface differs ⓘ
surface form:
Hadoop Distributed File System
MapReduce ⓘ YARN ⓘ Yet Another Resource Negotiator ⓘ |
| influenced |
Apache Flink
ⓘ
Apache Spark ⓘ Apache Storm ⓘ |
| initiallyInspiredBy |
Google File System
ⓘ
Google MapReduce ⓘ |
| license | Apache License 2.0 ⓘ |
| operatingSystem | Cross-platform ⓘ |
| partOf | Apache Hadoop ecosystem ⓘ |
| processingLayer | MapReduce ⓘ |
| programmingLanguage | Java ⓘ |
| resourceManagementLayer | YARN ⓘ |
| runsOn | clusters of commodity hardware ⓘ |
| storageLayer | HDFS ⓘ |
| supportsArchitecture | master-slave architecture ⓘ |
| supportsDataReplicationFactor | configurable replication factor ⓘ |
| supportsFeature |
batch processing
ⓘ
data replication ⓘ distributed storage ⓘ fault tolerance ⓘ horizontal scalability ⓘ parallel processing ⓘ |
| supportsHighAvailability | NameNode high availability ⓘ |
| supportsModel | MapReduce programming model ⓘ |
| supportsOperatingSystem |
Linux
ⓘ
Windows ⓘ macOS ⓘ |
| supportsProgrammingLanguage |
C++
ⓘ
Java ⓘ Python ⓘ R ⓘ Scala ⓘ |
| supportsSecurity | Kerberos-based authentication ⓘ |
| useCase |
ETL workloads
ⓘ
data warehousing ⓘ large-scale data processing ⓘ log processing ⓘ machine learning at scale ⓘ |
| writtenIn |
C
ⓘ
Java ⓘ Python ⓘ Unix shell ⓘ
surface form:
Shell
|
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Subject: Hadoop Description of subject: Hadoop is an open-source framework that enables distributed storage and parallel processing of large data sets across clusters of commodity hardware.
Referenced by (36)
Full triples — surface form annotated when it differs from this entity's canonical label.