target-s3-parquet - Meltano Hub

S3 Parquet

target-s3-parquet (jkausti variant)🥇

AWS S3 - Apache Parquet File Format

The target-s3-parquet loader

This plugin is deprecated and not recommended for use. Please use another variant.

sends data into S3 Parquet after it was pulled from a source using an extractor

Getting Started

Prerequisites

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

Installation and configuration

Add the target-s3-parquet loader to your project using
```
meltano add
```
:

meltano add target-s3-parquet --variant jkausti

Configure the target-s3-parquet settings using

meltano config

:

meltano config target-s3-parquet set --interactive

Next steps

Follow the remaining steps of the Getting Started guide:

Run a data integration (EL) pipeline

If you run into any issues, learn how to get help.

Capabilities

The current capabilities for target-s3-parquet may have been automatically set when originally added to the Hub. Please review the capabilities when using this loader. If you find they are out of date, please consider updating them by making a pull request to the YAML file that defines the capabilities for this loader.

This plugin has the following capabilities:

about
schema-flattening
stream-maps

You can override these capabilities or specify additional ones in your meltano.yml by adding the capabilities key.

Settings

The target-s3-parquet settings that are known to Meltano are documented below. To quickly find the setting you're looking for, click on any setting name from the list:

AWS_ACCESS_KEY_ID
AWS_SECRET_ACCESS_KEY
aws_region
filetype
folder_structure
path

Expand To Show SDK Settings

flattening_enabled
flattening_max_depth
stream_map_config
stream_maps

You can also list these settings using

meltano config

with the list subcommand:

meltano config target-s3-parquet list

You can override these settings or specify additional ones in your meltano.yml by adding the settings key.

Please consider adding any settings you have defined locally to this definition on MeltanoHub by making a pull request to the YAML file that defines the settings for this plugin.

AWS Access Key ID (AWS_ACCESS_KEY_ID)

Environment variable: TARGET_S3_PARQUET_AWS_ACCESS_KEY_ID

AWS Access Key ID used to authenticate programmatically to S3.

Configure this setting directly using the following Meltano command:

meltano config target-s3-parquet set AWS_ACCESS_KEY_ID [value]

AWS Secret Access Key (AWS_SECRET_ACCESS_KEY)

Environment variable: TARGET_S3_PARQUET_AWS_SECRET_ACCESS_KEY

AWS Secret Access Key used to authenticate programmatically to S3.

Configure this setting directly using the following Meltano command:

meltano config target-s3-parquet set AWS_SECRET_ACCESS_KEY [value]

AWS Region (aws_region)

Environment variable: TARGET_S3_PARQUET_AWS_REGION

Specfies the region in which your S3 bucket exists.

Configure this setting directly using the following Meltano command:

meltano config target-s3-parquet set aws_region [value]

Filetype (filetype)

Environment variable: TARGET_S3_PARQUET_FILETYPE
Default Value: parquet

Specifies the filetype to store the data as. Only parquet supported atm. required

Configure this setting directly using the following Meltano command:

meltano config target-s3-parquet set filetype [value]

Folder Structure (folder_structure)

Environment variable: TARGET_S3_PARQUET_FOLDER_STRUCTURE
Default Value: simple

Determines the folder-structure. Alternatives are: 'simple', 'date_hierarchy' and 'both'.

Configure this setting directly using the following Meltano command:

meltano config target-s3-parquet set folder_structure [value]

Path (path)

Environment variable: TARGET_S3_PARQUET_PATH

The path to where the data should be stored. required

Configure this setting directly using the following Meltano command:

meltano config target-s3-parquet set path [value]

Expand To Show SDK Settings

Flattening Enabled (flattening_enabled)

Environment variable: TARGET_S3_PARQUET_FLATTENING_ENABLED

'True' to enable schema flattening and automatically expand nested properties.

Configure this setting directly using the following Meltano command:

meltano config target-s3-parquet set flattening_enabled [value]

Flattening Max Depth (flattening_max_depth)

Environment variable: TARGET_S3_PARQUET_FLATTENING_MAX_DEPTH

The max depth to flatten schemas.

Configure this setting directly using the following Meltano command:

meltano config target-s3-parquet set flattening_max_depth [value]

Stream Map Config (stream_map_config)

Environment variable: TARGET_S3_PARQUET_STREAM_MAP_CONFIG

User-defined config values to be used within map expressions.

Configure this setting directly using the following Meltano command:

meltano config target-s3-parquet set stream_map_config [value]

Stream Maps (stream_maps)

Environment variable: TARGET_S3_PARQUET_STREAM_MAPS

Config object for stream maps capability. For more information check out Stream Maps.

Configure this setting directly using the following Meltano command:

meltano config target-s3-parquet set stream_maps [value]

Something missing?

This page is generated from a YAML file that you can contribute changes to.

Edit it on GitHub!

Looking for help?

If you're having trouble getting the target-s3-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.

Install

meltano add
              target-s3-parquet --variant jkausti

Maintenance Status

Repo

https://github.com/jkausti/target-s3

Maintainer

Keywords