The target-parquet Meltano loader sends data into Parquet after it was pulled from a source using an extractor.

Alternative variants #

Multiple variants of target-parquet are available. This document describes the default estrategiahq variant, which is recommended for new users.

Alternative variants are:

Getting Started #

Prerequisites #

If you haven't already, follow the initial steps of the Getting Started guide:

  1. Install Meltano
  2. Create your Meltano project
  3. Add an extractor to pull data from a source

Installation and configuration #

  1. Add the target-parquet loader to your project using meltano add : 

    meltano add loader target-parquet
  2. Configure the settings below using meltano config .

Next steps #

Follow the remaining steps of the Getting Started guide:

  1. Run a data integration (EL) pipeline
If you run into any issues, learn how to get help.

Capabilities #

target-parquet does not have any capabilities defined in its metadata. Please consider adding them by making a pull request to the YAML file that defines the capabilities for this loader.

Settings #

The settings for loader target-parquet that are known to Meltano are documented below. To quickly find the setting you're looking for, use the Table of Contents at the top of the page.

Disable Collection (disable_collection) #

A boolean of whether to disable Singer anonymous tracking.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-parquet set disable_collection true

export TARGET_PARQUET_DISABLE_COLLECTION=true

Logging Level (logging_level) #

(Default - INFO) The log level. Can also be set using environment variables.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-parquet set logging_level <logging_level>

export TARGET_PARQUET_LOGGING_LEVEL=<logging_level>

Destination Path (destination_path) #

(Default - ‘.’) The path to write files out to.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-parquet set destination_path <destination_path>

export TARGET_PARQUET_DESTINATION_PATH=<destination_path>

Compression Method (compression_method) #

Compression methods have to be supported by Pyarrow, and currently the compression modes available are - snappy (recommended), zstd, brotli and gzip.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-parquet set compression_method <compression_method>

export TARGET_PARQUET_COMPRESSION_METHOD=<compression_method>

Streams In Separate Folder (streams_in_separate_folder) #

(Default - False) The option to create each stream in a different folder, as these are expected to come in different schema.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-parquet set streams_in_separate_folder true

export TARGET_PARQUET_STREAMS_IN_SEPARATE_FOLDER=true

File Size (file_size) #

The number of rows to write per file. The default is to write to a single file.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-parquet set file_size 1234

export TARGET_PARQUET_FILE_SIZE=1234

Looking for help? #

If you're having trouble getting the target-parquet loader to work, look for an existing issue in its repository, file a new issue, or join the Meltano Slack community and ask for help in the #plugins-general channel.

Found an issue on this page? #

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