Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

https://github.com/raystack/dagger

Dagger is an easy-to-use, configuration over code, cloud-native framework built on top of Apache Flink for stateful processing of real-time streaming data.
https://github.com/raystack/dagger

apache-flink apache-kafka dataops framework influxdb prometheus real-time-analytics real-time-processing stream-processing

Last synced: 4 months ago
JSON representation

Dagger is an easy-to-use, configuration over code, cloud-native framework built on top of Apache Flink for stateful processing of real-time streaming data.

Lists

README 

        
# Dagger



![build workflow](https://github.com/raystack/dagger/actions/workflows/build.yml/badge.svg)

![package workflow](https://github.com/raystack/dagger/actions/workflows/package.yml/badge.svg)

[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg?logo=apache)](LICENSE)

[![Version](https://img.shields.io/github/v/release/raystack/dagger?logo=semantic-release)](https://github.com/raystack/dagger/releases/latest)



Dagger or Data Aggregator is an easy-to-use, configuration over code, cloud-native framework built on top of Apache Flink

for stateful processing of data. With Dagger, you don't need to write custom applications or complicated code to process

data as a stream. Instead, you can write SQL queries and UDFs to do the processing and analysis on streaming data.



![](docs/static/img/overview/dagger_overview.png)



## Key Features



Discover why to use Dagger



- **Processing:** Dagger can transform, aggregate, join and enrich streaming data, both real-time and historical.

- **Scale:** Dagger scales in an instant, both vertically and horizontally for high performance streaming sink and zero data drops.

- **Extensibility:** Add your own sink to dagger with a clearly defined interface or choose from already provided ones. Use Kafka and/or Parquet Files as stream sources.

- **Flexibility:** Add custom business logic in form of plugins \(UDFs, Transformers, Preprocessors and Post Processors\) independent of the core logic.

- **Metrics:** Always know what’s going on with your deployment with built-in [monitoring](https://raystack.github.io/dagger/docs/reference/metrics) of throughput, response times, errors and more.



## What problems Dagger solves?



- Map reduce -> [SQL](https://ci.apache.org/projects/flink/flink-docs-release-1.9/dev/table/sql.html)

- Enrichment -> [Post Processors](https://raystack.github.io/dagger/docs/advance/post_processor)

- Aggregation -> [SQL](https://ci.apache.org/projects/flink/flink-docs-release-1.9/dev/table/sql.html), [UDFs](https://raystack.github.io/dagger/docs/guides/use_udf)

- Masking -> [Hash Transformer](https://raystack.github.io/dagger/docs/reference/transformers#HashTransformer)

- Deduplication -> [Deduplication Transformer](https://raystack.github.io/dagger/docs/reference/transformers#DeDuplicationTransformer)

- Realtime long window processing -> [Longbow](https://raystack.github.io/dagger/docs/advance/longbow)



To know more, follow the detailed [documentation](https://raystack.github.io/dagger/).



## Usage



Explore the following resources to get started with Dagger:



- [Guides](https://raystack.github.io/dagger/docs/guides/overview) provides guidance on [creating Dagger](https://raystack.github.io/dagger/docs/guides/create_dagger) with different sinks.

- [Concepts](https://raystack.github.io/dagger/docs/concepts/overview) describes all important Dagger concepts.

- [Advance](https://raystack.github.io/dagger/docs/advance/overview) contains details regarding advance features of Dagger.

- [Reference](https://raystack.github.io/dagger/docs/reference/overview) contains details about configurations, metrics and other aspects of Dagger.

- [Contribute](https://raystack.github.io/dagger/docs/contribute/contribution) contains resources for anyone who wants to contribute to Dagger.

- [Usecase](https://raystack.github.io/dagger/docs/usecase/overview) describes examples use cases which can be solved via Dagger.

- [Examples](https://raystack.github.io/dagger/docs/examples/overview) contains tutorials to try out some of Dagger's features with real-world usecases



## Running locally



Please follow this [Dagger Quickstart Guide](https://raystack.github.io/dagger/docs/guides/quickstart) for setting up a local running Dagger consuming from Kafka or to set up a Docker Compose for Dagger.



**Note:** Sample configuration for running a basic dagger can be found [here](https://raystack.github.io/dagger/docs/guides/create_dagger#common-configurations). For detailed configurations, refer [here](https://raystack.github.io/dagger/docs/reference/configuration).



Find more detailed steps on local setup [here](https://raystack.github.io/dagger/docs/guides/create_dagger).



## Running on cluster



Refer [here](https://raystack.github.io/dagger/docs/guides/deployment) for details regarding Dagger deployment.



## Running tests



```sh

# Running unit tests

$ ./gradlew clean test



# Run code quality checks

$ ./gradlew checkstyleMain checkstyleTest



# Cleaning the build

$ ./gradlew clean

```



## Contribute



Development of Dagger happens in the open on GitHub, and we are grateful to the community for contributing bug fixes and improvements. Read below to learn how you can take part in improving Dagger.



Read our [contributing guide](https://raystack.github.io/dagger/docs/contribute/contribution) to learn about our development process, how to propose bug fixes and improvements, and how to build and test your changes to Dagger.



To help you get your feet wet and get you familiar with our contribution process, we have a list of [good first issues](https://github.com/raystack/dagger/labels/good%20first%20issue) that contain bugs which have a relatively limited scope. This is a great place to get started.



## Credits



This project exists thanks to all the [contributors](https://github.com/raystack/dagger/graphs/contributors).



## License



Dagger is [Apache 2.0](LICENSE) licensed.