Couchbase ETL Target

Couchbase ETL Target allows you to emit the transformed data into your Couchbase accounts.

Target Configuration #

Configure the data emitter parameters as explained below.

Connection Name #

Connections are the service identifiers. A connection name can be selected from the list if you have created and saved connection details for Couchbase earlier. Or create one as explained in the topic - Couchbase Connection →

Use the Test Connection option to ensure that the connection with the Couchbase channel is established successfully.

A success message states that the connection is available. In case of any error in test connection, edit the connection to resolve the issue before proceeding further.

Bucket Name #

Specify the name of the Couchbase bucket where the data will be stored or retrieved.

Memory Quota #

Memory Quota in megabytes per server node. Memory quota cannot be less than 100 MB.

Replicate view indexes #

By checking the Replicate view indexes checkbox, you ensure that view indexes, as well as data, are replicated.

Flush #

When flushed, aLL items in the bucket are removed as soon as possible.

Document ID #

Unique document key for Couchbase to persist the document in Couchbase. If document id is not unique then document with same id get overridden every time

Retention Enable #

If Retention is enabled, each newly created item lives for the number of seconds specified by Retention Policy, following the document’s creation. After its expiration time is reached, the item will be deleted by Couchbase Server.

Retention Policy #

Provide the duration that each newly created item will remain in the database before being automatically deleted by Couchbase Server upon expiration.

Output Fields #

Fields in the message that needs to be a part of the output data.

Add Configuration: Additional properties can be added using this option as key-value pairs.

Schema Mapping #

In this schema, you can define the source and target column mappings.

The actions available for the schema mapping section are explained below:

• Search: Search the Column Name values to get a specific target column.

• Refresh Schema: Use this option to refresh the entire schema mapping section.

• Auto Fill: Use this option to match the source and target column names, and automatically fill the source column mapping values to the corresponding target columns.

• Auto Fill Sequentially: Use this option to sequentially fill the incoming source column mapping values to the corresponding target columns.

• Download Mapping: Use this option to download a sample schema file. Update mapping values in the downloaded file.

  In case if Gathr application does not have access to a target table, you can choose the option download schema mapping option to map the target table columns with the source columns during the design time and confirm the data type for each column.

  In such cases you can run the application in a registered environment, that has access to all the required resources. During run-time, the application will run on the registered cluster of your choice picking up the configuration values as provided during application design.

• Upload Mapping: Use this option to upload the sample schema file with updated mapping values to provide the schema mapping.

The fields visible in the schema mapping section are explained below:

• Column Name: The column names as per the target entity selected will get populated in the Schema Mapping section.

• Mapping Value: The source column should be mapped for each target column listed in the Schema Mapping section. This operation can be done individually or in bulk using the auto fill action.

• Data Type: The data type of each target column is listed, for example, INT, TIMESTAMP, BIT, VARCHAR and so on.

• Is Autogenerated: Specifies if any target column(s) are autogenerated, for example, ID column may have autogenerated values.

• Ignore None/All/Unmapped: The target columns selected here will be ignored while emitting the data. There are bulk actions available to ignore none of the columns, all the columns or only the unmapped columns.

Post Action #

To understand how to provide SQL queries or Stored Procedures that will be executed during pipeline run, see Post-Actions →

Notes #

Optionally, enter notes in the Notes → tab and save the configuration.