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Databricks and the data.world Collector

Introduction

Note

The latest version of the Collector is 2.128. 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.

Permissions

The account used to authenticate needs to read the information schema of the databases about which it is collecting metadata. It does not need read access to the data within the tables.

What is cataloged

The information cataloged by the collector includes:

Preparing Databricks for collectors

  • Generate the Databricks personal access token for API authentication. (For more information, see the Databricks documentation.

Setting up 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 1.

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.



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:

  1. On the Organization profile page, go to the Settings tab > Metadata collectors section.

  2. Click the Help me set up a collector button.

  3. On the On-prem collector setup prerequisites screen, read the pre-requisites and click Next.

  4. 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.

    general_01.png
  5. On the Choose metadata collector type you would like to setup screen, select Databricks. Click Next.

  6. On the Configure a new on premises Databricks Collector screen, set the following properties and click Next.

    databricks_01.png
    Table 2.

    Field name

    Corresponding parameter name

    Description

    Required?

    data.world API token

    -t=<apiToken>

    --api-token=<apiToken>

    The data.world API token to use for authentication. Default is to use an environment variable named ${DW_AUTH_TOKEN}.

    Yes

    Output Directory

    -o=<outputDir>

    --output=<outputDir>

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

    Yes

    Collection Name

    -n=<catalogName>

    -n=<catalogName>

    The name of the collection where the collector output will be stored.

    Yes

    Automatic upload location

    --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 (ignored if --upload not specified)

    Yes

    data.world API host

    -H=<apiHost>

    --api-host=<apiHost>

    The host for the data.world API. NOTE: This parameter is required for Private instances and single-tenant installations. For example, "api.site.data.world" where "site" is the name of the single-tenant or private install.

    Yes

    (for single-tenant installations)



  7. On the next screen, set the following properties and click Next.

    databricks_02.png
    Table 3.

    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

    Private access 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

    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 private 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)



  8. On the next screen, set the following properties and click Next.

    databricks_03.png
    Table 4.

    Field name

    Corresponding parameter name

    Description

    Required?

    Databricks http path to endpoint

    --http-path=<httpPath>

    httpPath parameter for Databricks compute resources URL (see Databricks documentation for details)

    Yes

    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



  9. 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

    databricks_04.png

    Important

    You must ensure that you have set up these environment variables and directories before you run the collector.

  10. The next screen gives you an option to download the YAML configuration file or copy the CLI command. Click Done. If you are generated a YAML file, click Next.

    databricks_05.png

    Sample YAML file:

    databricks_06.png
  11. The Databricks command screen gives you the command to use for running the collector using the YAML file.

    databricks_07.png
  12. You will notice that the YAML/CLI has following additional parameters that are automatically set for you.

    Parameter name

    Details

    Required?

    -b=<base>

    --base=<base>

    The base URI to use as the namespace for any URIs generated.

    (Must use this OR --agent)

    Yes

    (If agent is not provided)

    -a=<agent>

    --agent=<agent>

    --account=<agent>

    The CLI and YAML file incudes the base parameter. If you want, you can instead use the agent parameter.

    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.

    (Must include either --agent or --base)

    Yes

    (if base parameter is not provided)

    --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)

    -L

    --no-log-upload

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

    Yes

    dwcc:<CollectorVersion>

    The version of the collector you want to use (For example, datadotworld/dwcc:2.113)

    Yes

  13. Add 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.

  14. Add the following parameter if you are using a sparql query to execute to transform the catalog graph emitted by the collector

    • -z=<postProcessSparql>--post-process-sparql=<postProcessSparql> : A file containing a sparql query to execute to transform the catalog graph emitted by the collector.

Verifying environment variables and directories

  1. Verify that you have set up all the required environment variables that were 9 before running the collector. Alternatively, you can set these credentials in a credential vault and use a script to retrieve those credentials.

  2. 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

  1. Go to the server where you have setup docker to run the collector.

  2. Make sure you have download the correct version of collectors. This version should match the version of the collector specified in the YAML/CLI generated from the collector wizard.

  3. Place the YAML file generated from the Collector wizard to the correct directory.

  4. 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.yml
  5. The 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.

  6. 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

  1. Go to the server where you have setup docker to run the collector.

  2. Make sure you have download the version of collectors from here.

  3. 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=${HOME}/dwcc datadotworld/dwcc:2.124 \
      catalog-databricks --base=https://solutions-8bank-catalog-config.app.linked.data.world/d/ddw-catalogs/ \
      --site=solutions --no-log-upload=false --upload=true --api-token=${DW_AUTH_TOKEN} \
      --output=/dwcc-output --name=8bank-catalog-config-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-path
  4. The 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.

  5. 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.

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.

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.