Reading from Asana entities - AWS Glue

Reading from Asana entities

Prerequisites

An Asana Object you would like to read from. Refer the supported entities table below to check the available entities.

Supported entities for source

Entity Can be Filtered Supports Limit Supports Order By Supports Select * Supports Partitioning

Workspace

 No Yes No Yes No
Tag No Yes No Yes No
User No Yes No Yes No

Portfolio

 No Yes No Yes No
Team No Yes No Yes No
Project Yes Yes No Yes No
Section No Yes No Yes No
Task Yes No No Yes Yes
Goal Yes Yes No Yes No

AuditLogEvent

 Yes Yes No Yes No

Status Update

 Yes Yes No Yes No

Custom Field

 No Yes No Yes No

Project Brief

 Yes No No Yes Yes

Example 

read_read = glueContext.create_dynamic_frame.from_options(
    connection_type="Asana",
    connection_options={
        "connectionName": "connectionName",
        "ENTITY_NAME": "task/workspace:xxxx",
        "API_VERSION": "1.0",
        "PARTITION_FIELD": "created_at",
        "LOWER_BOUND": "2024-02-05T14:09:30.115Z",
        "UPPER_BOUND": "2024-06-07T13:30:00.134Z",
        "NUM_PARTITIONS": "3"
    }

Asana entity and field details

Partitioning queries

Additional spark options PARTITION_FIELD, LOWER_BOUND, UPPER_BOUND, NUM_PARTITIONS can be provided if you want to utilize concurrency in Spark. With these parameters, the original query would be split into NUM_PARTITIONS number of sub-queries that can be executed by spark tasks concurrently.

  • PARTITION_FIELD: the name of the field to be used to partition query.

  • LOWER_BOUND: an inclusive lower bound value of the chosen partition field.

    For date, we accept the Spark date format used in Spark SQL queries. Example of valid values: 2024-06-07T13:30:00.134Z.

  • UPPER_BOUND: an exclusive upper bound value of the chosen partition field.

  • NUM_PARTITIONS: number of partitions.

Entity-wise partitioning field support details are captured in the following table.

Entity Name Partitioning Field Data Type
Task

created_at

 DateTime
Task

modified_at

 DateTime

Example 

read_read = glueContext.create_dynamic_frame.from_options(
    connection_type="Asana",
    connection_options={
        "connectionName": "connectionName",
        "ENTITY_NAME": "task/workspace:xxxx",
        "API_VERSION": "1.0",
        "PARTITION_FIELD": "created_at",
        "LOWER_BOUND": "2024-02-05T14:09:30.115Z",
        "UPPER_BOUND": "2024-06-07T13:30:00.134Z",
        "NUM_PARTITIONS": "3"
    }