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Reading from Blackbaud Raiser's Edge NXT entities

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Reading from Blackbaud Raiser's Edge NXT entities - AWS Glue

Prerequisite

A Blackbaud Raiser's Edge NXT object you would like to read from. You will need the object name.

Supported entities for source:

Entity Can be filtered Supports limit Supports Order by Supports Select * Supports partitioning
Constituent Address Yes Yes No Yes Yes
Constituent Education Yes Yes No Yes Yes
Constituent Email address Yes Yes No Yes Yes
Constituent Phone Yes Yes No Yes Yes
Constituent Note Yes Yes No Yes Yes
Constituent Relationship Yes Yes No Yes Yes
Constituent Online presence Yes Yes No Yes Yes
Opportunity Yes Yes No Yes Yes
Appeal Yes Yes No Yes Yes
Campaign Yes Yes No Yes Yes
Fund Yes Yes No Yes Yes
Package Yes Yes No Yes Yes
Gift Batch Yes Yes No Yes No
Event Participant Yes Yes Yes Yes Yes
Constituent Fundraiser Assignment No No No Yes No
Gift Yes Yes Yes Yes Yes
Membership Yes Yes No Yes Yes
Action Yes Yes No Yes No
Constituent Yes Yes Yes Yes Yes
Constituent Goods Yes Yes No Yes Yes
Event Yes Yes Yes Yes Yes
Gift custom field Yes Yes No Yes Yes

Example:

blackbaud_read = glueContext.create_dynamic_frame.from_options( connection_type="BLACKBAUD", connection_options={ "connectionName": "connectionName", "ENTITY_NAME": "entityName", "API_VERSION": "v1", "SUBSCRIPTION_KEY": <Subscription key associated with one's developer account> }

Blackbaud Raiser's Edge NXT entity and field details

For more information about the entities and field details see:

Note

Struct and List data types are converted to String data type, and DateTime data type is converted to Timestamp in the response of the connectors.

Partitioning queries

Field-based partitioning:

Blackbaud Raiser's Edge NXT doesn’t support field based or record based partitioning.

Record-based partitioning:

You can provide the additional Spark option NUM_PARTITIONS if you want to utilize concurrency in Spark. With this parameter, the original query would be split into NUM_PARTITIONS number of sub-queries that can be executed by Spark tasks concurrently.

In record based partitioning, the total number of records present is queried from Blackbaud Raiser’s Edge NXT API, and it is divided by NUM_PARTITIONS number provided. The resulting number of records are then concurrently fetched by each sub-query.

  • NUM_PARTITIONS: the number of partitions.

Example:

blackbaud_read = glueContext.create_dynamic_frame.from_options( connection_type="BLACKBAUD", connection_options={ "connectionName": "connectionName", "ENTITY_NAME": "entityName", "API_VERSION": "v1", "NUM_PARTITIONS": "2", "SUBSCRIPTION_KEY": <Subscription key associated with one's developer account> }
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