Cells Get Data

Get Data using Cells API. You're only able to retrieve 10,000 fields at a time. When working with large data sets, it's best to have a Partition function that can create large batches (example below). You can also run these batches concurrently(example below).

Swagger

Params

name	Parameter type	Data Type	Values	Description
resolveReferenceUrl	query	bool	false	if you want to return the URL for entry
fillExtendedData	query	bool	false	Appends modified DataTime and Modified By to entry data
wrapIntoArrays	query	bool	true	ensures consistency for multi-value fields

Body

When requesting data, entryId and fieldId are always required. If currency field, you can optionally pass a currency value. Passing RC will return the value in the recorded currency. Passing a valid currency string will convert the stored value into the currency specified in the response.

[
  {
    "entryId": 0, (required)
    "fieldId": 0, (required)
    "currencyCode": "string" (optional)
  }
]

Regular Request

Request

POST {{host}}/api/rest/v4/data/entrydata/get HTTP/1.1
?wrapIntoArrays=true
Content-Type: application/json
Authorization: {{auth}}
 
[
  {
    "entryId": 2772624,
    "fieldId": 2211
  },
  {
    "entryId": 2772624,
    "fieldId": 2212
  }
]

Response

HTTP/1.1 200 OK
[
  {
    "entryId": 2772624,
    "fieldId": 2211,
    "isNoData": false,
    "value": {
      "id": 2772624,
      "name": "Test Interactions",
      "entryListId": 2013
    },
    "requestedCurrencyCode": "RC"
  },
  {
    "entryId": 2772624,
    "fieldId": 2212,
    "rowId": 23555389,
    "isNoData": false,
    "value": [
      {
        "id": 3043023,
        "name": "REST API Guide_20201009.docx",
        "entryListId": 2010
      }
    ],
    "requestedCurrencyCode": "RC"
  }
]

Extended Request

Request

POST {{host}}/api/rest/v4/data/entrydata/get HTTP/1.1
  ?wrapIntoArrays=true
  &resolveReferenceUrl=true
  &fillExtendedData=true
Content-Type: application/json
Authorization: {{auth}}
 
[
  {
    "entryId": 2772624,
    "fieldId": 2211
  },
  {
    "entryId": 2772624,
    "fieldId": 2212
  }
]

Response

HTTP/1.1 200 OK
{
    "entryId": 2772624,
    "fieldId": 2211,
    "isNoData": false,
    "value": {
      "url": "{{host}}/portal/pages/4/reports/146/entries/2772624",
      "id": 2772624,
      "name": "Test Interactions",
      "entryListId": 2013
    },
    "requestedCurrencyCode": "RC",
    "modified": "2020-12-31T01:18:13.517",
    "modifiedBy": 8278
  }

Errors

HTTP/1.1 400 Bad Request
{
  "message": "Field with Id \"2302\" does not exist"
}

Working with large data sets

When working with large data sets, it's best to have a Partition function that can create large batches max size 10_000 (example below). You can also run these batches concurrently, max consistency limited to 5(example below).

C# Partition Example

DefaultBatchSize should = 10000

public static IEnumerable<List<T>> Partition<T>(this IEnumerable<T> sequence, int partitionSize = DefaultBatchSize) 
{ 
    List<T> partition = new List<T>(partitionSize); 
 
    foreach (T item in sequence) 
 
    { 
        partition.Add(item); 
 
        if (partition.Count == partitionSize) 
        { 
            yield return partition; 
            partition = new List<T>(partitionSize); 
        } 
    } 
 
    if (partition.Count > 0) 
    { 
        yield return partition; 
    } 
}

C# Concurrent Calls

public static async Task<DataResponseSchema> ChunkProcessBulkDataReadRequestsAsync(this IntappAPIClient intappClient,
    List<DataReadRequest> pullRequests,
    bool includeAuditData = false)
{
  // Partition data into large batch sizes not to exceed 10000
  IEnumerable<List<DataReadRequest>> batchedRequests = pullRequests.Partition();
  // Set max concurrent calls
  List<Task<DataRequestSchema>> tasks = new List<Task<DataRequestSchema>>(intappClient.MaxConcurrentAPICalls + 1);
  // Crate a place to store the expected response
  List<DataRequestSchema> pullResults = new List<DataRequestSchema>(batchedRequests.Count());
  
  // Use async method to fetch results while we are making new requests
  foreach (List<DataReadRequest> batch in batchedRequests)
  {
      while (tasks.Count >= intappClient.MaxConcurrentAPICalls)
      {
          Task<DataRequestSchema> completedTask = await Task.WhenAny(tasks);
          pullResults.Add(await completedTask);
          tasks.Remove(completedTask);
      }
 
      Task<DataRequestSchema> task = intappClient.ProcessBulkDataReadRequestAsync(batch, false, includeAuditData);
      tasks.Add(task);
  }
 
  await Task.WhenAll(tasks);
  pullResults.AddRange(tasks.Select(x => x.Result));
  return new DataResponseSchema(pullResults);
}

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