Running the Databricks collector
Note
The latest version of the Collector is 2.159. To view the release notes for this version and all previous versions, please go here.
Generating the command or YAML file
This section walks you through the process of generating the command or YAML file for running the collector from Windows or Linux or MAC OS.
To generate the command or YAML file:
On the Organization profile page, go to the Settings tab > Metadata collectors section.
Click the Help me set up a collector button.
On the On-prem collector setup prerequisites screen, read the pre-requisites and click Next.
On the On which platform will this collector execute? screen, select if you will be running the collector on Windows or Mac OS or Linux. This will determine the format of the YAML and CLI that is generated in the end. Click Next.
On the Choose metadata collector type you would like to setup screen, select Databricks. Click Next.
On the Configure a new on premises Databricks Collector screen, set the following properties and click Next.
On the next screen, set the following properties and click Next.
Table 2.Field name
Corresponding parameter name
Description
Required?
Server
-s = <server>
--server= <server>
Specify the hostname of the database server.
Yes
Server port
-p= <port>
--port= <port>
The port of the database server (if not the default).
No
Database
-d= <database>
--database= <database>
The name of the database to connect to.
Yes
Database ID
-D= <databaseId>
---database-id=<databaseId>
A unique identifier for this database - will be used to generate the ID for the database (this is optional, you only need to provide this if the database name used for the connection is not sufficiently unique to completely identify the database)
No
Username
-u= <user>
--user= <user>
The username to use to make the JDBC connection. (For authentication to work with a personal access token, the user flag (
-u) must be set to token.)Yes
Password
-P= <password>
--password= <password>
The environment variable of the password used to connect to the database. Default value is set to ${DW_DATABRICKS_PASSWORD}.
Yes
Schemas to collect
Select from one of the following options:
Collect all schema, Specify which schemas to collect
Yes
Collect all schema
-A
--all-schemas
Catalog all schemas to which the user has access.
Yes
(if --schema is not set)
Specify which schemas to collect
-S= <databaseSchema>
--schema=<databaseSchema>
The name of the database schema to catalog.
In Databricks, the schema is sometimes referred to as a Database. For more information, see the Databricks schema documentation.
Yes
(if --all-schema is not set)
Include Information Schema
--include-information-schema= <true/false>
Include the database's Information Schema in catalog collection.
Yes
Databricks API token
--access-token= <token>
Databricks personal access token for API authentication (Go here for more information). Default value is set to ${DW_DATABRICKS_TOKEN}.
Yes
Databricks HttpPath
--http-path= <HTTPPath>
HTTPPath parameter for Databricks compute resources URL (see Databricks documentation for details)
Yes
On the next screen, set the following properties and click Next.
Table 3.Field name
Corresponding parameter name
Description
Required?
Disable lineage collection
--disable-lineage-collection
Skip harvesting of intra-database lineage metadata
No
Enable sample string values collection
--sample-string-values
Enable sampling and storage of sample values for string-valued columns
No
Enable column statistics collection
--enable-column-statistics
To enable harvesting of column statistics (i.e., data profiling).
No
Target sample size for column statistics
--target-sample-size
The number of rows sampled for computation of column statistics and string-value histograms
No
Disable harvesting workflows
--workflow-exclude
Skip harvesting of Databricks workflows and their lineage metadata.
No
Server environment
-e= <environment>
--environment= <environment>
If your provided server name is 'localhost' use this to give a friendly name to the environment in which your database server runs to help differentiate it from other environments
No
Database ID
-D= <databseid>
--database-id= <databaseId>
A unique identifier for this database - will be used to generate the ID for the database (this is optional, you only need to provide this if the database name used for the connection is not sufficiently unique to completely identify the database)
No
JDBC Properties
--jdbc-property= <driverProperties>
JDBC driver properties to pass through to driver connection, as name=value. Separate the name=value pairs with a semicolon (;). For example, property1=value1;property2=value2
No
On the next screen, provide the Collector configuration name. This is the name used to save the configuration details. The configuration is saved and made available on the Metadata collectors summary page from where you can edit or delete the configuration at a later point. Click Save and Continue.
On the Finalize your Databricks Collector configuration screen, you are notified about the environment variables and directories you need to setup for running the collector. Select if you want to generate a Configuration file( YAML) or Command line arguments (CLI). Click Next
Important
You must ensure that you have set up these environment variables and directories before you run the collector.
The next screen gives you an option to download the YAML configuration file or copy the CLI command. Click Done. If you are generating a YAML file, click Next.
The Databricks command screen gives you the command to use for running the collector using the YAML file.
You will notice that the YAML/CLI has following additional parameters that are automatically set for you.
Important
Except for the collector version, you should not change the values of any of the parameter listed here.
Table 4.Parameter name
Details
Required?
-a= <agent>
--agent= <agent>
--account= <agent>
The ID for the data.world account into which you will load this catalog - this is used to generate the namespace for any URIs generated.
Yes
--site= <site>
This parameter should be set only for Private instances. Do not set it for public instances and single-tenant installations. Required for private instance installations.
Yes (required for private instance installations)
-U
--upload
Whether to upload the generated catalog to the organization account's catalogs dataset.
Yes
-L
--no-log-upload
Do not upload the log of the Collector run to the organization account's catalogs dataset.
Yes
dwcc: <CollectorVersion>
The version of the collector you want to use (For example,
datadotworld/dwcc:2.113)Yes
Add the following additional parameter to test run the collector.
--dry-run If specified, the collector does not actually harvest any metadata, but just checks the database connection parameters provided by the user and reports success or failure at connecting.
You can add the following parameter to the Command/YAML file to use these additional features.
Table 5.Parameter name
Desscription
Required?
--api-max-retries= <maxRetries>
Specify the number of times to retry an API call which has failed. The default value is 5.
No
--api-retry-delay= <retryDelay>
Specify the amount of time in seconds to wait between retries of an API call which has failed. The default is to try with a delay of 2 seconds between each call.
N
Verifying environment variables and directories
Verify that you have set up all the required environment variables that were identified by the Collector Wizard before running the collector. Alternatively, you can set these credentials in a credential vault and use a script to retrieve those credentials.
Verify that you have set up all the required directories that were identified by the Collector Wizard.
Running the collector
Important
Before you begin running the collector make sure you have the correct version of collectors downloaded and available.
Running collector using YAML file
Go to the server where you have setup docker to run the collector.
Make sure you have download the correct version of collectors. This version should match the version of the collector specified in the command you are using to run the collector.
Place the YAML file generated from the Collector wizard to the correct directory.
From the command line, run the command generated from the application for executing the YAML file.
Caution
Note that is just a sample command for showing the syntax. You must generate the command specific to your setup from the application UI.
docker run -it --rm --mount type=bind,source=${HOME}/dwcc,target=/dwcc-output \ --mount type=bind,source=${HOME}/dwcc,target=${HOME}/dwcc -e DW_AUTH_TOKEN=${DW_AUTH_TOKEN} \ -e DW_DATABRICKS_TOKEN=${DW_DATABRICKS_TOKEN} -e DW_DATABRICKS_PASSWORD=${DW_DATABRICKS_PASSWORD} \ datadotworld/dwcc:2.124 --config-file=/dwcc-output/config-databricks.ymlThe collector automatically uploads the file to the specified dataset and you can also find the output at the location you specified while running the collector.
At a later point, if you download a newer version of collector from Docker, you can edit the collector version in the generated command to run the collector with the newer version.
Running collector without the YAML file
Go to the server where you have setup docker to run the collector.
Make sure you have download the version of collectors from here. This version should match the version of the collector specified in the command you are using to run the collector.
From the command line, run the command generated from the application. Here is a sample command.
Caution
Note that is just a sample command for showing the syntax. You must generate the command specific to your setup from the application UI.
docker run -it --rm --mount type=bind,source=${HOME}/dwcc,target=/dwcc-output \ --mount type=bind,source=${HOME}/dwcc,target=${HOME}/dwcc datadotworld/dwcc:2.124 \ catalog-databricks --agent=8bank-catalog-sources --site=solutions \ --no-log-upload=false --upload=true --api-token=${DW_AUTH_TOKEN} \ --output=/dwcc-output --name=8bank-catalog-sources-collection \ --upload-location=ddw-catalogs --server=8bank_server --database=8bank_DB \ --access-token=${DW_DATABRICKS_TOKEN} --user=8bank_user --password=${DW_DATABRICKS_PASSWORD} \ --all-schemas=true --http-path=http-pathThe collector automatically uploads the file to the specified dataset and you can also find the output at the location you specified while running the collector.
At a later point, if you download a newer version of collector from docker, you can edit the collector version in the generated command to run the collector with the newer version.
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.
Managing collector runs and configuration details
From the Metadata collectors summary page, view the collectors runs to ensure they are running successfully,
From the same Metadata collectors summary page you can view, edit, or delete the configuration details for the collectors.