Input 

Document

• Min: 1

• Max: 2

• Redshift - Select

• Mapper

• JSON Generator

A JSON document containing the key-value pairs indicating the columns and values for the new rows to insert in the DLP table.

• If a second input view is configured for the Snap and it contains a document with schema (metadata) of the source table, the Snap creates the new (target) table using the same schema (metadata). However, if the schema comes from a different database, the Snap might fail with Unable to create table: "<table_name>" error due to data type incompatibility.

• In the absence of a second input view (the schema/metadata document), the Snap creates a table based on the data types of the columns generated from the first row of the input document (first input view).

Output

Document

• Min: 0

• Max: 1

• Databricks - Select

• Databricks - Unload

• Databricks - Delete

A JSON document with the details of the new rows inserted in the DLP table.

Error

Error handling is a generic way to handle errors without losing data or failing the Snap execution. You can handle the errors that the Snap might encounter while running the Pipeline by choosing one of the following options from the When errors occur list under the Views tab. The available options are:

• Stop Pipeline Execution: Stops the current pipeline execution when the Snap encounters an error.

• Discard Error Data and Continue: Ignores the error, discards that record, and continues with the rest of the records.

• Route Error Data to Error View: Routes the error data to an error view without stopping the Snap execution.

Learn more about Error handling in Pipelines.

Label*

Default Value: Databricks - Insert
Example: Db_Insert_Customer

String

The name for the Snap. You can modify this to be more specific, especially if you have more than one of the same Snap in your Pipeline.

Database name

Default Value: None.
Example: Cust_DB

String/Expression/Suggestion

Enter your corresponding DLP database name for the INSERT statement to add new rows in the table.

Table name*

Default Value: None.
Example: Cust_List

String/Expression/Suggestion

Enter your table name for the INSERT statement to add new rows.

Number of Retries

Example: 3

Minimum value: 0

Default value: 0

Integer

Specifies the maximum number of retry attempts when the Snap fails to write.

Retry Interval (seconds)

Example: 3

Minimum value: 1

Default value: 1

Integer

Specifies the minimum number of seconds the Snap must wait before each retry attempt.

Manage Queued Queries

Default value: Continue to execute queued queries when pipeline is stopped or if it fails.

Example: Cancel queued queries when pipeline is stopped or if it fails

Dropdown list

Select this property to determine whether the Snap should continue or cancel the execution of the queued Databricks SQL queries when you stop the Pipeline.

Snap Execution

Default Value: Execute only
Example: Validate & Execute

Dropdown list

Select one of the three modes in which the Snap executes. Available options are:

• Validate & Execute: Performs limited execution of the Snap, and generates a data preview during Pipeline validation. Subsequently, performs full execution of the Snap (unlimited records) during Pipeline runtime.

• Execute only: Performs full execution of the Snap during Pipeline execution without generating preview data.

• Disabled: Disables the Snap and all Snaps that are downstream from it.

Missing property value

You have not specified a value for the required field where this message appears.

Ensure that you specify valid values for all required fields.

Account Settings for Snowflake - Select Snap

Notes

We configure the Snap to fetch the table schema (output1) and the table data (rows) from the example_company_employees2 table in the Snowflake instance.

The Snap uses a Snowflake JDBC driver and the corresponding basic auth credentials to connect to the Snowflake instance hosted on the AWS cloud.

Account Settings for Databricks - Insert Snap

Notes

We configure the Snap to consume the table schema (output1) and the table data (rows) from the example_company_employees table in the Snowflake instance.

The Snap uses a Databricks JDBC driver and the corresponding basic auth credentials to connect to the DLP (target) instance hosted on the AWS cloud.

The Snap is configured to perform the Insert operation only during Pipeline execution and hence, it does not display any results during validation. Upon Pipeline Execution, the Snap creates a new table example_company_employees2 in the specified DLP database using the schema from the Snowflake - Select Snap and populates the retrieved rows data in this new table.