Handling SSL Certificate Verification Error and Configuring Profiling for Redshift Ingestion

ingestion
1

Original Slack Thread

<@U06TM7M40RK> when i tried redshift ingestion, always error

sqlalchemy.exc.InterfaceError: (redshift_connector.error.InterfaceError) ('communication error', SSLCertVerificationError(1, "[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: Hostname mismatch, certificate is not valid

2

The error you’re encountering indicates an SSL certificate verification failure due to a hostname mismatch. This typically occurs when the SSL certificate presented by the server does not match the expected hostname, which can happen if the certificate is self-signed or if there is a configuration issue with the server’s SSL setup.

To address this issue, you can consider the following steps:

  1. Disable SSL Verification: If you are aware of the risks and are in a controlled environment, you can disable SSL verification. According to the <https://github.com/datahub-project/datahub/blob/master/metadata-ingestion/sink_docs/datahub.md|DataHub Rest configuration guide>, you can set the disable_ssl_verification parameter to true in your configuration to bypass SSL verification.

  2. Verify SSL Certificate: Ensure that the SSL certificate used by your Redshift cluster is correctly configured and matches the hostname you are connecting to. This might involve checking the certificate’s common name (CN) and subject alternative names (SANs).

  3. Use a Valid Certificate: If possible, use a valid SSL certificate issued by a trusted certificate authority (CA) for your Redshift cluster.

  4. Update CA Certificates: Ensure that your client environment has the necessary CA certificates to verify the server’s certificate. You can specify the path to the CA certificate using the ca_certificate_path parameter if needed.

  5. Check Hostname Configuration: Verify that the hostname you are using to connect to Redshift matches the one specified in the SSL certificate.

Would you like more detailed steps on any of these potential solutions?

Sources:

3

<@U06TM7M40RK> Any options specified here will be passed to https://docs.sqlalchemy.org/en/14/core/engines.html#sqlalchemy.create_engine|SQLAlchemy.create_engine as kwargs. To set connection arguments in the URL, specify them under connect_args.

4

To pass additional options to the SQLAlchemy.create_engine function, you can use the options field in your DataHub ingestion recipe. This allows you to specify various parameters that will be passed as keyword arguments (kwargs) to the create_engine function. Additionally, connection-specific arguments can be set using the connect_args parameter.

Here’s how you can structure your recipe to include these options:

source:
  type: redshift
  config:
    host_port: "your-redshift-cluster:5439"
    database: "your_database"
    username: "your_username"
    password: "your_password"
    options:
      connect_args:
        sslmode: "verify-full"  # Example of a connection argument
        connect_timeout: 10     # Timeout in seconds
      echo: true                # Example of an SQLAlchemy engine option

Explanation:

  • connect_args: This is used to specify connection-specific arguments. For example, sslmode can be set to control SSL behavior, and connect_timeout can be used to specify the timeout duration for establishing a connection.
  • options: This field allows you to pass additional options to the create_engine function. For example, echo can be set to true to enable logging of all the SQL statements executed.

For more details on the available options, you can refer to the <Engine Configuration — SQLAlchemy 1.4 Documentation documentation>.

Would you like more details on any specific part of this configuration?

Sources:

5

<@U06TM7M40RK> for redshift, https://datahubproject.io/docs/generated/ingestion/sources/redshift/ how can i enable profiling to get numbe of columns?

6

To enable profiling in DataHub for Redshift to obtain the number of columns, you need to configure the profiling settings in your ingestion recipe. Profiling allows you to collect statistics about your tables, including the number of columns.

Here’s how you can enable profiling for Redshift:

  1. Enable Profiling: Set the profiling.enabled parameter to true in your configuration. This will enable the profiling feature.

  2. Configure Profiling Options: You can specify additional profiling options such as profile_table_level_only if you want to limit profiling to table-level statistics only.

Here is an example configuration snippet for enabling profiling in Redshift:

source:
  type: redshift
  config:
    host_port: "your-redshift-cluster:5439"
    database: "your_database"
    username: "your_username"
    password: "your_password"
    profiling:
      enabled: true
      profile_table_level_only: false  # Set to true if you only want table-level stats

Explanation:

  • profiling.enabled: This parameter enables the profiling feature.
  • profile_table_level_only: If set to true, profiling will only collect table-level statistics, not column-level. Set it to false if you want to include column-level statistics.

According to the <https://datahubproject.io/docs/generated/ingestion/sources/redshift/|DataHub Redshift documentation>, profiling is optionally enabled via configuration, and you can customize it based on your needs.

Would you like more detailed guidance on any specific part of this process?

Sources:

7

<@U06TM7M40RK> but it will profile with sample value the column as well

8

Yes, when you enable profiling in DataHub for Redshift, it can also profile sample values for each column by default. If you want to control whether sample values are included in the profiling results, you can use the include_field_sample_values parameter in your configuration.

Here’s how you can configure it:

source:
  type: redshift
  config:
    host_port: "your-redshift-cluster:5439"
    database: "your_database"
    username: "your_username"
    password: "your_password"
    profiling:
      enabled: true
      include_field_sample_values: false  # Set to false to exclude sample values

Explanation:

  • include_field_sample_values: This parameter controls whether sample values for each column are included in the profiling results. Setting it to false will exclude sample values, while setting it to true will include them.

According to the <https://datahubproject.io/docs/generated/ingestion/sources/redshift/|DataHub Redshift documentation>, you can customize profiling settings to suit your needs, including whether to include sample values.

Would you like more detailed guidance on any specific part of this configuration?

Sources:

9

Hi :slight_smile: ! Did this interaction resolve your issue or do you still require assistance ?

Please tag @ RunLLM if you still need further assistance !

Or tag @Datahub Community Support if you require a person to take a look :slight_smile:

Hope this helps ! ><