Apache Flume
E185680
Apache Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log and event data into Hadoop and other data stores.
All labels observed (2)
| Label | Occurrences |
|---|---|
| Apache Flume canonical | 1 |
| HDFS Sink | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T1647859 — 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 Flume Context triple: [Hadoop, ecosystemIncludes, Apache Flume]
-
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.
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.
-
C.
Amazon Kinesis Data Firehose
Amazon Kinesis Data Firehose is a fully managed AWS service for reliably capturing, transforming, and loading real-time streaming data into data lakes, warehouses, and analytics services.
-
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.
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.
- 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 Flume Target entity description: Apache Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log and event data into Hadoop and other data stores.
-
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.
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.
-
C.
Amazon Kinesis Data Firehose
Amazon Kinesis Data Firehose is a fully managed AWS service for reliably capturing, transforming, and loading real-time streaming data into data lakes, warehouses, and analytics services.
-
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.
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.
- F. None of above. chosen
Statements (59)
| Predicate | Object |
|---|---|
| instanceOf |
data ingestion tool
ⓘ
open-source software ⓘ software framework ⓘ |
| architectureComponent |
Agent
ⓘ
Channel ⓘ Sink ⓘ Source ⓘ |
| dataModel | Event (header and body) ⓘ |
| designedFor |
high-throughput data ingestion
ⓘ
reliable event delivery to Hadoop and other stores ⓘ scalable log collection ⓘ |
| developer | Apache Software Foundation ⓘ |
| feature |
channel selectors
ⓘ
configurable data flows ⓘ distributed architecture ⓘ failover ⓘ fan-in and fan-out flows ⓘ interceptors for event transformation ⓘ load balancing ⓘ multi-hop flows ⓘ pluggable sources channels and sinks ⓘ reliable event delivery ⓘ sink groups ⓘ transactional reliability semantics ⓘ |
| genre |
distributed data ingestion system
ⓘ
event data collection system ⓘ log collection system ⓘ |
| license | Apache License 2.0 ⓘ |
| operatingSystem | cross-platform ⓘ |
| partOf |
Apache ecosystem
ⓘ
surface form:
Apache Hadoop ecosystem
|
| programmingLanguage | Java ⓘ |
| repository | https://github.com/apache/flume ⓘ |
| supports |
Avro
ⓘ
Avro Sink ⓘ File Channel ⓘ Apache HBase ⓘ
surface form:
HBase
Apache HBase ⓘ
surface form:
HBase Sink
HDFS ⓘ Apache Flume self-linksurface differs ⓘ
surface form:
HDFS Sink
HTTP ⓘ Hadoop ⓘ JDBC Channel ⓘ JMS ⓘ Kafka (via sink or source integrations) ⓘ Logger Sink ⓘ Memory Channel ⓘ Spooling Directory Source ⓘ Taildir Source ⓘ Thrift ⓘ Apache Thrift ⓘ
surface form:
Thrift Sink
syslog ⓘ |
| useCase |
centralized logging for distributed systems
ⓘ
collecting application logs ⓘ collecting machine-generated data ⓘ collecting web server logs ⓘ event data collection ⓘ log aggregation ⓘ streaming data ingestion into Hadoop ⓘ |
| website | https://flume.apache.org/ ⓘ |
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 Flume Description of subject: Apache Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log and event data into Hadoop and other data stores.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.
this entity surface form:
HDFS Sink