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Fivetran and the data.world Collector

Introduction

Note

The latest version of the Collector is 2.119. To view the release notes for this version and all previous versions, please go here.

The data.world Collector harvests metadata from your source system. Please read over the data.world Collector FAQ to familiarize yourself with the Collector.

Prerequisites

  • You must have a ddw-catalogs (or other) dataset set up to hold your catalog files when you are done running the collector.

  • The machine running the catalog collector should have connectivity to the internet or access to the source instance. For Linux- or Unix-based machines, it is recommended to have a minimum of 2G memory, and a 2Ghz processor. For Windows-based machines, it is recommended to have a minimum of 4G, and a 2Ghz processor.

  • Docker must be installed. For more information see https://docs.docker.com/get-docker/.

  • The user defined to run the data.world Collector must have read access to all resources being cataloged.

  • The computer running the data.world Collector needs a Java Runtime Environment. OpenJDK 17 is supported and available here.

Permissions

The owner of the api key is needs read access to destinations and connectors. See the Fivetran documentation for more information.

Collected from fivetran

The Fivetran collector catalogs column-level lineage relationships that exist during the load step (copy from source to destination systems). The collector catalogs both database and non-database Connection and Destination systems in Fivetran. The database systems that the collector supports include the following, and, if applicable, cloud-hosted instances on AWS and Azure:

Sources:

  • MariaDB

  • MySQL

  • Oracle

  • PostgreSQL

  • MS SQL Server

Destinations:

  • Azure SQL Data Warehouse

  • Big Query

  • MySQL

  • PostgreSQL

  • Redshift

  • Snowflake

These are the Fivetran concepts that are catalogued:

  • https://open-kos.org/ext/kos-fivetran/FivetranConnector

  • https://open-kos.org/ext/kos-fivetran/FivetranConnectorJob

  • https://open-kos.org/ext/kos-fivetran/FivetranConnectorType

  • https://open-kos.org/ext/kos-fivetran/FivetranDataSource

  • https://open-kos.org/ext/kos-fivetran/FivetranConfigurationProperty

  • https://open-kos.org/ext/kos-fivetran/FivetranDestination

  • https://open-kos.org/ext/kos-fivetran/FivetranDestinationType

  • https://open-kos.org/ext/kos-fivetran/FivetranGroup

For FivetranDestinations, we also catalog the following:

  • https://dwec.data.world/v0/DatabaseConnection

  • https://dwec.data.world/v0/DatabaseConnectionInfo

  • https://dwec.data.world/v0/Database

  • https://dwec.data.world/v0/DatabaseColumn

  • https://dwec.data.world/v0/DatabaseTable

  • https://dwec.data.world/v0/DatabaseSchema

For FivetranConnectors we collect configuration properties for the FivetranDataSource. If the FivetranDataSource connects to a database which we recognize, then we catalog the following for that database:

  • https://dwec.data.world/v0/DatabaseConnection

  • https://dwec.data.world/v0/DatabaseConnectionInfo

  • https://dwec.data.world/v0/Database

  • https://dwec.data.world/v0/DatabaseColumn

  • https://dwec.data.world/v0/DatabaseTable

  • https://dwec.data.world/v0/DatabaseSchema

Otherwise if it’s another tabular data source like a web analytics site then we catalog the data source as a https://open-kos.org/schema/TabularDataSource and generically catalog the tables and columns which fivetran retrieves from that data source as :

  • https://dwec.data.world/v0/Column

  • https://dwec.data.world/v0/Table

Lineage Fivetran

The Fivetran collector identifies the source columns that destination columns sourced their data from (via copy / load operation).

Ways to run the data.world Collector

There are a few different ways to run the data.world Collector--any of which can be combined with an automation strategy to keep your catalog up to date:

  • Create a configuration file (config.yml) - This option stores all the information needed to catalog your data sources. It is an especially valuable option if you have multiple data sources to catalog as you don't need to run multiple scripts or CLI commands separately.

  • Run the collector though a CLI - Clear-cut and efficient, but makes regular, repeating runs of the collector very laborious and time-consuming as the commands are re-entered for each run.

Writing the data.world Collector command

The easiest way to create your Collector command is to:

  1. Copy the following example command

  2. Edit it for your organization and data source

  3. Open a terminal window in any Unix environment that uses a Bash shell and paste your command into it.

The example command includes the minimal parameters required to run the collector (described below)--your instance may require more. A description of all the available parameters is available in this article. Edit the command by adding any other parameters you wish to use, and by replacing the values for all your parameters with your information as appropriate. Parameters required by the Collector are in bold.

Important

Do not forget to replace x.y in datadotworld/dwcc:x.y with the version of the Collector you want to use (e.g., datadotworld/dwcc:2.113).

Docker and the data.world Collector

Detailed information about the Docker portion of the command can be found here. When you run the command, run will attempt to find the image locally, and if it doesn't find it, it will go to Dockerhub and download it automatically:

dwcc_and_cli.png

Collector runtime and troubleshooting

The catalog collector may run in several seconds to many minutes depending on the size and complexity of the system being crawled. If the catalog collector runs without issues, you should see no output on the terminal, but a new file that matching *.dwec.ttl should be in the directory you specified for the output. If there was an issue connecting or running the catalog collector, there will be either a stack trace or a *.log file. Both of those can be sent to support to investigate if the errors are not clear. A list of common issues and problems encountered when running the collectors is available here.

Upload the .ttl file generated from running the Collector

When the data.world Collector runs successfully, it creates a .ttl file in the directory you specified as the dwcc-output directory. The automatically-generated file name is databaseName.catalogName.dwec.ttl. You can rename the file or leave the default, and then upload it to your ddw-catalogs dataset (or wherever you store your catalogs).

Caution

If there is already a .ttl catalog file with the same name in your ddw-catalogs dataset, when you add the new one it will overwrite the existing one.

Automatic updates to your metadata catalog

Keep your metadata catalog up to date using cron, your Docker container, or your automation tool of choice to run the catalog collector on a regular basis. Considerations for how often to schedule include:

  • Frequency of changes to the schema

  • Business criticality of up-to-date data

For organizations with schemas that change often and where surfacing the latest data is business critical, daily may be appropriate. For those with schemas that do not change often and which are less critical, weekly or even monthly may make sense. Consult your data.world representative for more tailored recommendations on how best to optimize your catalog collector processes.