# Reading from Okta entities
<a name="okta-reading-from-entities"></a>

 **Prerequisites** 
+  A Okta Object you would like to read from. Refer the supported entities table below to check the available entities. 

 **Supported entities** 


| Entity | Can be Filtered | Supports Limit | Supports Order By | Supports Select \$1 | Supports Partitioning | 
| --- | --- | --- | --- | --- | --- | 
| Applications | Yes | Yes | No | Yes | No | 
| Devices | Yes | Yes | No | Yes | Yes | 
| Groups | Yes | Yes | Yes | Yes | Yes | 
| Users | Yes | Yes | Yes | Yes | Yes | 
| User Types | No | No | No | Yes | No | 

 **Example** 

```
okta_read = glueContext.create_dynamic_frame.from_options(
    connection_type="Okta",
    connection_options={
        "connectionName": "connectionName",
        "ENTITY_NAME": "applications",
        "API_VERSION": "v1"
    }
```

 **Okta entity and field details** 

 Entities list: 
+  Application: [ https://developer.okta.com/docs/api/openapi/okta-management/management/tag/Application/ ](https://developer.okta.com/docs/api/openapi/okta-management/management/tag/Application/) 
+  Device: [ https://developer.okta.com/docs/api/openapi/okta-management/management/tag/Device/ ](https://developer.okta.com/docs/api/openapi/okta-management/management/tag/Device/) 
+  Group: [ https://developer.okta.com/docs/api/openapi/okta-management/management/tag/Group/ ](https://developer.okta.com/docs/api/openapi/okta-management/management/tag/Group/) 
+  User: [ https://developer.okta.com/docs/api/openapi/okta-management/management/tag/User/ ](https://developer.okta.com/docs/api/openapi/okta-management/management/tag/User/) 
+  User Type: [ https://developer.okta.com/docs/api/openapi/okta-management/management/tag/UserType/ ](https://developer.okta.com/docs/api/openapi/okta-management/management/tag/UserType/) 

 **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: `"2024-02-06"`. 
+  `UPPER_BOUND`: an exclusive upper bound value of the chosen partition field. 
+  `NUM_PARTITIONS`: number of partitions. 

 **Example** 

```
okta_read = glueContext.create_dynamic_frame.from_options(
    connection_type="okta",
    connection_options={
        "connectionName": "connectionName",
        "ENTITY_NAME": "lastUpdated",
        "API_VERSION": "v1",
        "PARTITION_FIELD": "lastMembershipUpdated"
        "LOWER_BOUND": "2022-08-10T10:28:46.000Z"
        "UPPER_BOUND": "2024-08-10T10:28:46.000Z"
        "NUM_PARTITIONS": "10"
    }
```