$batch requests - do they provide a client performance speedup compared to requests executed one by one

The $batch requests in xrm are supposed to be used for number of operations that either succeed or fail as a group.

https://docs.microsoft.com/en-us/powerapps/developer/common-data-service/webapi/execute-batch-operations-using-web-api

I.E. instead of

POST [Organization URI]/api/data/v9.0/tasks
{ ...payload for task1.. }
POST [Organization URI]/api/data/v9.0/tasks
{ ...payload for task2.. }

You create request

POST [Organization URI]/api/data/v9.0/$batch
{ .... shared payload ... }

Now my question is are they supposed to provide performance speedup for the client loading as well ? I.E. when I'll user $batch is the overall client performance supposed to be better ?

EDIT

Test snippet I've used:

syncTest = function() {
  var now = Date.now();
  var count = 0;
  var done = function() {
    count++;
    if (count === 2) {
      console.log("Sync: " + (Date.now() - now) + " ms");
    }
  };

  $.ajax({method:"GET",url:"/api/data/v9.0/contacts(53c4918e-5367-e911-a83b-000d3a31329f)", success: function() { done(); }});
  $.ajax({method:"GET",url:"/api/data/v9.0/contacts(50b297c5-4867-e911-a843-000d3a3130ea)", success: function() { done(); }});
};

asyncTest = function() {
  var now = Date.now();
  var done = function() {
    console.log("Async: " + (Date.now() - now) + " ms");
  };

  var headers = {
    'Content-Type': 'multipart/mixed;boundary=batch_123456',
    'Accept': 'application/json',
    'Odata-MaxVersion': '4.0',
    'Odata-Version': '4.0'
  };

  var data = [];
  data.push('--batch_123456');
  data.push("Content-Type: application/http");
  data.push("Content-Transfer-Encoding:binary");
  data.push('');
  data.push('GET /api/data/v9.0/contacts(53c4918e-5367-e911-a83b-000d3a31329f) HTTP/1.1');
  data.push('Content-Type:application/json;type=entry');
  data.push('');
  data.push('{}');

  data.push('--batch_123456');  
  data.push("Content-Type: application/http");
  data.push("Content-Transfer-Encoding:binary");
  data.push('');
  data.push('GET /api/data/v9.0/contacts(50b297c5-4867-e911-a843-000d3a3130ea) HTTP/1.1');
  data.push('Content-Type:application/json;type=entry');
  data.push('');
  data.push('{}');  
  data.push('--batch_123456');
  var payload = data.join('\r\n');

  $.ajax({method:"POST",url:"/api/data/v9.0/$batch", data:payload, headers: headers, success: function() { done(); }});
};

Test method - flush browser cache execute snippet; times (average for five retries):

$batch                 - 242ms per combined request (average for 5x)
one by one in parallel - 195ms per combined request (average for 5x)

So it seems $batch is actually adding some overhead.

Improve performance | Google Drive API, This document covers some techniques you can use to improve the If, instead, you're using a Google client library to make a batch request, see the client A batch request consists of multiple API calls combined into one HTTP If you provide an Authorization header for the outer request, then that� Some of our clients have low Batch Requests/sec, under 1,000. Drop a comment with the Batch Requests/sec value on your busiest server during the busiest time of the busiest day. Brent says: if I know a server well, this is the first place I look when someone says queries are slow.

For your requests, since they are running async, both requests will be sent to the server, and will be processed asynchronously vs, the batch, which will process them one at a time. So I would imagine that total execution time would be less for the two async, vs the one async, but because of server processing, not client side issues. You could change your calls to by sync instead and see if there is a difference.

Batching Requests | Classroom API, Global HTTP Batch Endpoints ( www.googleapis.com/batch ) will cease to If, instead, you're using a Google client library to make a batch request, see A batch request consists of multiple API calls combined into one HTTP For example, if you provide an Authorization header for a specific call, then batch. execute(); Note: A set of n requests batched together counts toward your usage limit as n requests, not as one request. The batch request is taken apart into a set of requests before processing. Format of a batch request. A batch request is a single standard HTTP request containing multiple Classroom API calls, using the multipart/mixed content type

Batch Request will save Round Trip times. That the Main Performance Advantage. Sending out 2x Requests sequentially, is way slower then sending out only 1 Request. As stated by Daryl, your 2 Request are send out Async (which more or less means parallel). That the reason why you see a difference. So you basically compare Parallel Processing with Single Threading.

Performance Guide | TFX, Please use the Profile Inference Requests with TensorBoard guide to When fine-tuning TensorFlow Serving's performance, there are usually 2 You may configure your clients to send batched requests to TensorFlow Serving, or you may inference on all requests that arrive in that period in one batch. The DownloadAndProcessUrl call would do steps 2 & 3 and return a Technology. (in my example I called the output a Thing). Inside a web server, each incoming request uses a thread from the thread pool. Each parallel thread you use also comes from the pool. The more of one impacts the other's performance. – Negative Eddy Jun 29 '16 at 14:48

DynamoDB: Guidelines for faster reads and writes, If you haven't read the earlier posts, you can find them here. some of the key factors that affect the performance/cost of read/write operations. DynamoDB batches are not atomic (i.e.) if one of the reads/writes in a batch fails, a single batch at the client, DynamoDB receives 100 individual read requests. In the case of backends that map to protocols curl supports, the handler needs to 1) convert a simple path request to a full curl request, and 2) handle responses coming back from curl. Non-curl protocols will additionally require an integration with the curl_multi loop, which is fairly straightforward if they provide a non-blocking 'do some

Article: Process Performance Guidelines, The process logs will give you more accompanying details. versus when it is queued up on the platform, then adding an atom worker will clear up that delay you see. If you find the need to make multiple connector calls to get the same Process performance is not usually a one size fits all solution. As for all other points from the book, the developers really look for performance as the bottom line. Some rely on external means (outside of the application) for performance enhancements such as using a fast disk, get more CPUs/Cores, tuning the storage engine, and tuning the configuration file. Others will buckle down and write better code.

[PDF] All about Eve: Execute-Verify Replication for Multi-Core Servers, then verify that they can reach agreement on a state and a replica finishes executing one request before beginning to execute the next [7, 27, 31 cas to execute requests within each batch in parallel, are live,. i.e. provide a response to client requests, despite a to- How does Eve's performance compare to an unrepli-. On the server side, the database environment must be properly configured to respond to clients' requests in the fastest way possible, while making optimum use of existing resources. The activities required to achieve this goal are commonly referred to as _____ tuning. 1) client and server 2) database SQL 3) SQL performance 4) DBMS performance

Comments
  • My guess is that because $batch is transactional, that is the cause of the overhead