Description: Apache Beam is an open-source unified programming model and set of tools for building batch and streaming data processing pipelines. It provides a high-level API that allows developers to write data processing logic once and execute it on various distributed processing backends, such as Apache Flink, Apache Spark, and Google Cloud Dataflow. Beam's model allows for both batch and streaming data processing, enabling developers to handle real-time data as well as large-scale batch data in a consistent manner.
Additional information: Apache Beam simplifies the development of data processing pipelines by providing a portable and expressive programming model. It allows developers to focus on the logic of their data transformations without worrying about the underlying execution engine. Beam's model supports a wide range of data processing patterns, including filtering, aggregating, joining, and transforming data. It also provides built-in support for windowing, allowing developers to handle time-based computations efficiently. With its ability to run on multiple execution engines, Apache Beam offers flexibility and scalability for processing data at any scale.
Example: An example of using Apache Beam is to process a stream of user activity data in real-time. The pipeline can read the incoming data, apply transformations such as filtering and aggregating, and then write the results to a database or generate alerts based on certain conditions. Another example is processing a large batch of log files to extract relevant information, perform analytics, and store the results in a data warehouse. Apache Beam's unified programming model allows developers to write these pipelines once and run them on different execution engines, making it easier to switch between batch and streaming processing or migrate to a different backend without rewriting the entire pipeline.
Publisher: Apache Beam Documentation
Source: https://beam.apache.org/documentation/
LOST view: TVA-Orchestration Enablers [Motivation]
Identifier: http://data.europa.eu/dr8/egovera/ApacheBeamApplicationService
EIRA traceability: eira:DigitalSolutionApplicationService
EIRA concept: eira:SolutionBuildingBlock
Last modification: 2023-07-20
dct:identifier: http://data.europa.eu/dr8/egovera/ApacheBeamApplicationService
dct:title: Apache Beam Application Service
|
|
eira:PURI | http://data.europa.eu/dr8/egovera/ApacheBeamApplicationService |
eira:ABB | eira:DigitalSolutionApplicationService |
dct:modified | 2023-07-20 |
dct:identifier | http://data.europa.eu/dr8/egovera/ApacheBeamApplicationService |
dct:title | Apache Beam Application Service |
skos:example | An example of using Apache Beam is to process a stream of user activity data in real-time. The pipeline can read the incoming data, apply transformations such as filtering and aggregating, and then write the results to a database or generate alerts based on certain conditions. Another example is processing a large batch of log files to extract relevant information, perform analytics, and store the results in a data warehouse. Apache Beam's unified programming model allows developers to write these pipelines once and run them on different execution engines, making it easier to switch between batch and streaming processing or migrate to a different backend without rewriting the entire pipeline. |
skos:note | Apache Beam simplifies the development of data processing pipelines by providing a portable and expressive programming model. It allows developers to focus on the logic of their data transformations without worrying about the underlying execution engine. Beam's model supports a wide range of data processing patterns, including filtering, aggregating, joining, and transforming data. It also provides built-in support for windowing, allowing developers to handle time-based computations efficiently. With its ability to run on multiple execution engines, Apache Beam offers flexibility and scalability for processing data at any scale. |
eira:concept | eira:SolutionBuildingBlock |
dct:description | Apache Beam is an open-source unified programming model and set of tools for building batch and streaming data processing pipelines. It provides a high-level API that allows developers to write data processing logic once and execute it on various distributed processing backends, such as Apache Flink, Apache Spark, and Google Cloud Dataflow. Beam's model allows for both batch and streaming data processing, enabling developers to handle real-time data as well as large-scale batch data in a consistent manner. |
dct:publisher | Apache Beam Documentation |
dct:source | https://beam.apache.org/documentation/ |
eira:view | TVA-Orchestration Enablers [Motivation] |