target-s3-parquet - Meltano Hub

S3 Parquet

target-s3-parquet (gupy-io variant)🥇

AWS S3 - Apache Parquet File Format

The target-s3-parquet loader 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 loader target-s3-parquet

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 If you find they are out of date, please consider updating them by making a pull request to the YAML file that defines the capabilities for this loader.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:

athena_database
aws_access_key_id
aws_secret_access_key
s3_path
stringify_schema

Expand To Show SDK Settings

add_record_metadata
flattening_enabled
flattening_max_depth
load_method
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.

Athena Database (athena_database)

Environment variable: TARGET_S3_PARQUET_ATHENA_DATABASE

The Athena database.

Configure this setting directly using the following Meltano command:

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

AWS Access Key ID (aws_access_key_id)

Environment variable: TARGET_S3_PARQUET_AWS_ACCESS_KEY_ID

Your AWS access key ID.

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

Your AWS secret access key.

Configure this setting directly using the following Meltano command:

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

S3 Path (s3_path)

Environment variable: TARGET_S3_PARQUET_S3_PATH

The s3 path to the target output file

Configure this setting directly using the following Meltano command:

meltano config target-s3-parquet set s3_path [value]

Stringify Schema (stringify_schema)

Environment variable: TARGET_S3_PARQUET_STRINGIFY_SCHEMA

A boolean whether to stringify Schema

Configure this setting directly using the following Meltano command:

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

Expand To Show SDK Settings

Add Record Metadata (add_record_metadata)

Environment variable: TARGET_S3_PARQUET_ADD_RECORD_METADATA

A boolean whether to add record metadata

Configure this setting directly using the following Meltano command:

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

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]

Load Method (load_method)

Environment variable: TARGET_S3_PARQUET_LOAD_METHOD
Default Value: append-only

The method to use when loading data into the destination. append-only will always write all input records whether that records already exists or not. upsert will update existing records and insert new records. overwrite will delete all existing records and insert all input records.

Configure this setting directly using the following Meltano command:

meltano config target-s3-parquet set load_method [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 loader target-s3-parquet

Maintenance Status

Repo

https://github.com/gupy-io/target-s3-parquet

Maintainer

Meltano Stats

Keywords