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ThoughtSpot and the data.world Collector

Note

The latest version of the Collector is 2.137. To view the release notes for this version and all previous versions, please go here.

About the collector

Use this collector to directly harvest metadata ThoughtSpot Answers and Liveboards into data.world

Authentication supported

The collector authenticates to ThoughtSpot using username and password. The collector will have access to all the resources that the ThoughtSpot account has access to.

What is cataloged

The collector catalogs the following information.

Table 1.

Object

Information cataloged

Answer

Title, Description, Tags, SQL query, Created by, Creation date, Last modified by, Last modified date

Liveboard

Title, Description, Tags, SQL query, Created by, Creation date, Last modified by, Last modified date

Logical Column

Title, Description, Tags, SQL query, Column Index, Column Type Name, Column Precision, Is Primary Key, Creation date, Last modified by, Last modified date

Logical table

Title, Description, Tags, Created by, Creation date, Last modified by, Last modified date

Workbook

Title, Description, Tags, Created by, Creation date, Last modified by, Last modified date

Formula

Title, Formula text, Created by, Last modified by, Last modified date

Tag

Title, Count of resources with tag, Description, Creation date, Last modified by, Last modified date



Relationships between objects

By default, the harvested metadata includes catalog pages for the following resource types. Each catalog page has a relationship to the other related resource types. If the metadata presentation for this data source has been customized with the help of the data.world Solutions team, you may see other resource pages and relationships.

Table 2.

Resource page

Relationship

Answer

  • Relationship to Liveboard that contains Answer

  • Relationship to Tags that the Answer is associated with

Liveboard

  • Relationship to Answers that are used in the Liveboard

  • Relationship to Tags that the Liveboard is associated with

Logical Column

  • Relationship to Logical Tables that the Logical Column is part of 

  • Relationship to Tags that the Logical Column is associated with

  • Relationship to Formulae that the Logical Column is associated with

Logical Table

  • Relationship to Logical Columns contained in Logical Table

  • Relationship to Tags that the Logical Table is associated with

Workbook

  • Relationship to Logical Columns contained in Workbook

  • Relationship to Tags that the Workbook is associated with

Formula

  • Relationship to the Logical Column that contains the Formula

Tag

  • Relationship to Answer, Liveboard, Logical Column, Logical Table, or Workbook resources that the Tag is associated with



Pre-requisites for running the collector

Make sure that the machine from where you are running the collector meets the following hardware and software requirements.

Table 3.

Item

Requirement

Hardware

RAM

8 GB

CPU

2 Ghz processor

Software

Docker

Click here to get Docker.

Java Runtime Environment

OpenJDK 17 is supported and available here.

data.world specific objects

Dataset

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



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 - Repeat runs of the collector requires you to re-enter the command for each run.

Note

This section walks you through the process of running the collector using CLI.

Preparing and running the command

The easiest way to create your Collector command is to:

  1. Copy the following example command in a text editor.

  2. Set the required parameters in the command. The example command includes the minimal parameters required to run the collector

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

docker run -it --rm --mount type=bind,source=/tmp,target=/dwcc-output \
--mount type=bind,source=/tmp,target=/app/log \
datadotworld/dwcc:<CollectorVersion> \
catalog-thoughtspot -a <account> \
--hostname=<hostname> --username=<username> --password=<password> \
-n <catalogName> -o "/dwcc-output"  

The following table describes the parameters for the command. Detailed information about the Docker portion of the command can be found here.

Table 1.

Parameter

Details

Required?

dwcc: <CollectorVersion>

Replace <CollectorVersion> in with the version of the collector you want to use (For example, datadotworld/dwcc:2.113)

Yes

-A, --all-schemas

Catalog all schemas to which the user has access (exclusive of --schema).

Yes

-a = <agent>

--agent= <agent>

--account= <agent>

The ID for the data.world account into which you will load this catalog. The ID is the organization name as it appears in your organization. This is used to generate the namespace for any URIs generated.

Yes

--hostname= <hostname>

The host name for the Thoughtspot account to collect. For example, instanceName.thoughtspot.cloud

Yes

--username= <username>

The username for the Thoughtspot account to collect.

Yes

--password= <password>

The password for the Thoughtspot account to collect.

Yes

--dry-run= <dryRun>

Specify this option to run the collector in dry run mode to test the connection details provided. No metadata is harvested in dry run mode.

No

-n= <catalogName>

--name= <catalogName>

The name of the catalog - this will be used to generate the ID for the catalog as well as the filename into which the catalog file will be written.

Yes

-o= <outputDir>

--output= <outputDir>

The output directory into which any catalog files should be written.

In our example we use the /dwcc -outputas it is running in a Docker container and that is what we specified in the script for a Docker mount point.

You can change this value to anything you would like as long as it matches what you use in the mount point:

-mount type=bind,source=/tmp,target=/dwcc-output ...-o /dwcc-output

In this example, the output will be written to the /tmp directory on the local machine, as indicated by the mount point directive. The log file, in addition to any catalog files, will be written to the directory specified in the mount point directive.

Yes

-L

--no-log-upload

Do not upload the log of the dwcc run to the organization account's catalogs dataset or to another location specified with --upload-location (ignored if --upload not specified)

No

--site= <site>

The slug for the data.world site into which you will load this catalog this is used to generate the namespace for any URIs generated.

No

-H= Host

--api-host= Host

The host for the data.world API.

No

-t= <apiToken>

--api-token= <apiToken>

The data.world API token to use for authentication. The default is to use an environment variable named DW_AUTH_TOKEN.

No

-U

--upload

Whether to upload the generated catalog to the organization account's catalogs dataset or to another location specified with --upload-location (This requires that the --api-token is specified.

No

--upload-location= <uploadLocation>

The dataset to which the catalog is to be uploaded, specified as a simple dataset name to upload to that dataset within the organization's account, or [account/dataset] to upload to a dataset in some other account. This parameter is ignored if --upload is not specified.

No



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.

Automating 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.