Apache Oozie
E185677
Apache Software Foundation project
Hadoop ecosystem component
open-source software
workflow scheduler system
Apache Oozie is a workflow scheduler system designed to manage and coordinate Hadoop jobs such as MapReduce, Pig, and Hive in complex data processing pipelines.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Apache Oozie canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T1647856 — 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.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Apache Oozie Context triple: [Hadoop, ecosystemIncludes, Apache Oozie]
-
A.
Hadoop
Hadoop is an open-source framework that enables distributed storage and parallel processing of large data sets across clusters of commodity hardware.
-
B.
Google Cloud Dataproc
Google Cloud Dataproc is a managed cloud service for running Apache Hadoop, Spark, and other big data workloads on scalable, automated clusters in Google Cloud.
-
C.
Apache Mesos
Apache Mesos is an open-source cluster manager that abstracts CPU, memory, storage, and other resources away from machines to enable efficient deployment and scaling of distributed applications and frameworks.
-
D.
Google Cloud Dataflow
Google Cloud Dataflow is a fully managed service for developing and executing batch and streaming data processing pipelines, based on Apache Beam, within the Google Cloud ecosystem.
-
E.
AWS Glue
AWS Glue is a fully managed extract, transform, and load (ETL) service from Amazon Web Services that simplifies data preparation and integration for analytics and data warehousing.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Apache Oozie Target entity description: Apache Oozie is a workflow scheduler system designed to manage and coordinate Hadoop jobs such as MapReduce, Pig, and Hive in complex data processing pipelines.
-
A.
Hadoop
Hadoop is an open-source framework that enables distributed storage and parallel processing of large data sets across clusters of commodity hardware.
-
B.
Google Cloud Dataproc
Google Cloud Dataproc is a managed cloud service for running Apache Hadoop, Spark, and other big data workloads on scalable, automated clusters in Google Cloud.
-
C.
Apache Mesos
Apache Mesos is an open-source cluster manager that abstracts CPU, memory, storage, and other resources away from machines to enable efficient deployment and scaling of distributed applications and frameworks.
-
D.
Google Cloud Dataflow
Google Cloud Dataflow is a fully managed service for developing and executing batch and streaming data processing pipelines, based on Apache Beam, within the Google Cloud ecosystem.
-
E.
AWS Glue
AWS Glue is a fully managed extract, transform, and load (ETL) service from Amazon Web Services that simplifies data preparation and integration for analytics and data warehousing.
- F. None of above. chosen
Statements (49)
| Predicate | Object |
|---|---|
| instanceOf |
Apache Software Foundation project
ⓘ
Hadoop ecosystem component ⓘ open-source software ⓘ workflow scheduler system ⓘ |
| configurationFormat | XML ⓘ |
| deploymentModel | server-side web application ⓘ |
| designedFor |
coordinating complex data processing pipelines
ⓘ
managing Hadoop workflows ⓘ |
| developer | Apache Software Foundation ⓘ |
| integratesWith |
Hadoop
ⓘ
surface form:
Apache Hadoop
Apache Hive ⓘ Apache Pig ⓘ Apache Sqoop ⓘ HDFS ⓘ YARN ⓘ |
| license | Apache License 2.0 ⓘ |
| partOf |
Apache ecosystem
ⓘ
surface form:
Apache Hadoop ecosystem
|
| programmingLanguage | Java ⓘ |
| provides |
REST API
ⓘ
command-line interface ⓘ web console ⓘ |
| requires |
Hadoop cluster
ⓘ
relational database for state storage ⓘ |
| supports |
Apache Hive jobs
ⓘ
Apache Pig jobs ⓘ Apache Sqoop jobs ⓘ HDFS operations ⓘ Hadoop MapReduce jobs ⓘ Java programs ⓘ SLA monitoring ⓘ bundle jobs ⓘ coordinator jobs ⓘ data-availability-based scheduling ⓘ decision control nodes ⓘ email notifications ⓘ error handling and retries ⓘ fork and join control nodes ⓘ shell scripts ⓘ sub-workflows ⓘ time-based scheduling ⓘ workflow dependency management ⓘ |
| supportsVersion |
Hadoop
ⓘ
surface form:
Hadoop 1.x
Hadoop ⓘ
surface form:
Hadoop 2.x
|
| useCase |
ETL pipelines
ⓘ
batch data processing workflows ⓘ coordinated execution of multiple Hadoop jobs ⓘ periodic data ingestion ⓘ |
| website | https://oozie.apache.org/ ⓘ |
| workflowDefinitionLanguage | XML ⓘ |
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.
Instruction
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.
Input
Subject: Apache Oozie Description of subject: Apache Oozie is a workflow scheduler system designed to manage and coordinate Hadoop jobs such as MapReduce, Pig, and Hive in complex data processing pipelines.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.