target-parquet

A Singer target that writes data to parquet files. This target is based on [target-csv] Targetcsv and the code was adapted to generate parquet files instead of csv files.

How to use it

target-parquet works with a Singer Tap in order to move data ingested by the tap into parquet files. Note that the parquet file will be written once all the data is imported from the tap.

Install

We will use tap-exchangeratesapi to pull currency exchange rate data from a public data set as an example.

First, make sure Python 3 is installed on your system or follow these installation instructions for Linux or Mac.

It is recommended to install each Tap and Target in a separate Python virtual environment to avoid conflicting dependencies between any Taps and Targets.

 # Install tap-exchangeratesapi in its own virtualenv
python3 -m venv ~/.virtualenvs/tap-exchangeratesapi
source ~/.virtualenvs/tap-exchangeratesapi/bin/activate
pip3 install tap-exchangeratesapi
deactivate

# Install target-parquet in its own virtualenv
python3 -m venv ~/.virtualenvs/target-parquet
source ~/.virtualenvs/target-parquet/bin/activate
pip3 install target-parquet
deactivate

Run

We can now run tap-exchangeratesapi and pipe the output to target-parquet.

~/.virtualenvs/tap-exchangeratesapi/bin/tap-exchangeratesapi | ~/.virtualenvs/target-parquet/bin/target-parquet

By default, the data will be written into a file called exchange_rate-{timestamp}.parquet in your working directory.

Optional Configuration

If you want to save the file in a specific location and not the working directory, then, you need to create a configuration file, in which you specify the path to the directory you are interested in and pass the -c argument to the target. Also, you can compress the parquet file by passing the compression_method argument in the configuration file. Note that, these compression methods have to be supported by Pyarrow, and at the moment (October, 2020), the only compression modes available are: snappy (recommended), zstd, brotli and gzip. The library will check these, and default to None if something else is provided. For an example of the configuration file, see config.sample.json. There is also an streams_in_separate_folder option to create each stream in a different folder, as these are expected to come in different schema. To run target-parquet with the configuration file, use this command:

~/.virtualenvs/tap-exchangeratesapi/bin/tap-exchangeratesapi | ~/.virtualenvs/target-parquet/bin/target-parquet -c config.json

Setting the Logging Level

There are two ways to set the logging level. If both are set, the config file has higher priority. The default value is INFO.

• LOGGER_LEVEL Enviroment variable. Set it to INFO, DEBUG or any other valid value
• config file. Set the same values in the logging_level key.

Development

To install development required packages run

pip install -e ".[dev]"

In order to run all tests run

pytest