Chewdata

This application is a light ETL in rust that can be used as a connector between systems

| Feature | Values | Description | | ---------------------------------------- | ----------------------------------------------------------------------- | ------------------------------------------------------------------ | | Generate data | - | Generate data for testing | | Supported formats | Json , Jsonl , CSV , Toml , XML , Yaml , Text , Parquet | Read and Write in these formats | | Multi Connectors | Mongodb , S3 , Minio , APIs | Read / Write / Clean data | | Multi Http auths | Basic , Bearer , Jwt | Read / Write / Clean data | | Transform data | tera template | Transform the data in the fly | | Multi Configuration formats | Json , Yaml | The project need a jobs configuration in input | | Read data in parallel or sequential mode | Cursor , Offset | With this type of paginator, the data can be read in different way |

More useful information:

• It need only rustup
• No garbage collector
• Parallel works
• Cross-platform
• Use async/await for concurrent threads with zero-cost
• Read multi files in parallel into the local or in a bucket
• Search data into multi csv/json/parquet files with S3 select
• Can be deployed into AWS Lambda
• The configuration easly versionable
• Can generate data in the fly for testing purpose
• Control and validate the data. Handle bad and valid data in a dedicated stream

Getting started

Setup from source code

Requirement:

• Rust
• Docker and Docker-compose for testing the code in local

Commands to execute:

Bash git clone https://github.com/jmfiaschi/chewdata.git chewdata cd chewdata cp .env.dev .env vim .env // Edit the .env file make build make unit-tests make integration-tests

If all the test pass, the project is ready. read the Makefile in order to see, what kind of shortcut you can use.

If you want some examples to discover this project, go in this section ./examples

Run the ETL

If you run the program without parameters, the application will wait until you write json data. By default, the program write json data in the output and the program stop when you enter empty value.

Bash $ cargo run $ [{"key":"value"},{"name":"test"}] $ enter [{"key":"value"},{"name":"test"}]

Another example without etl configuration and with file in input

Bash $ cat ./data/multi_lines.json | cargo run [{...}]

or

Bash $ cat ./data/multi_lines.json | make run [{...}]

Another example, With a json etl configuration in argument

Bash $ cat ./data/multi_lines.csv | cargo run '[{"type":"reader","document":{"type":"csv"}},{"type":"writer"}]' [{...}] // Will transform the csv data into json format

or

Bash $ cat ./data/multi_lines.csv | make run json='[{\"type\":\"reader\",\"document\":{\"type\":\"csv\"}},{\"type\":\"writer\"}]' [{...}] // Will transform the csv data into json format

Another example, With etl file configuration in argument

Bash $ echo '[{"type":"reader","connector":{"type":"io"},"document":{"type":"csv"}},{"type":"writer"}]' > my_etl.conf.json $ cat ./data/multi_lines.csv | cargo run -- --file my_etl.conf.json [{...}]

or

Bash $ echo '[{"type":"reader","connector":{"type":"io"},"document":{"type":"csv"}},{"type":"writer"}]' > my_etl.conf.json $ cat ./data/multi_lines.csv | make run file=my_etl.conf.json [{...}]

It is possible to use alias and default value to decrease the configuration length

Bash $ echo '[{"type":"r","doc":{"type":"csv"}},{"type":"w"}]' > my_etl.conf.json $ cat ./data/multi_lines.csv | make run file=my_etl.conf.json [{...}]

How to contribute

In progress...

After code modifications, please run all tests.

Bash make test

Useful links

• Benchmark report
• Documentation
• Package