Posts Tagged ‘dataweave’

Json Data Processing with Mule Transformers and Dataweave

As REST APIs are taking over the world, json has stood out and become the de facto data format for APIs. It’s important that developers are familiar with json data processing. A couple of years ago I wrote a blog post discussing Mule Json transformers. Since then, I have seen many new nuances dealing with […]

MuleSoft – Correlating Array and HashMap with Dataweave

In data processing, two of the most common collection data types are array (list) and map (HashMap). The key difference between a list and a map is how they are accessed. A list is accessed by an integer positional index, such as list. However, map is accessed by a key, such as map.getValue(“key1”) or simply […]

Mule Flat File and Cobol Copybook Processing

A few months back, I worked on a project that involves flat file handling. I thought it was such an odd thing that people still use flat file in the 21st century. Ironically, I’m now on my 3rd project which involves flat file processing. It is not just flat file; I am actually dealing with […]

Liferay Reference Architecture on AWS

Processing JSON with Mule Transformers

To see more on Mule Json data processing, please follow this newer blog post: https://blogs.perficient.com/integrate/2018/03/02/json-data-processing-mule-transformers-dataweave/ When a JSON object comes into Mule application, it’s very common it’s represented as a JSON formatted string. For example, when it’s part of HTTP post string or part of the message received from an Amazon SQS queue. In order to process the JSON formatted […]

MuleSoft Salesforce Connector Release 7.2.0.201608251058 and fieldsToNull

Hot off the press, MuleSoft just released a new Salesforce connector “7.2.0.201608251058”. If you read carefully, that’s about 5 days ago. Normally, I’m not in a hurry to update new connector release. However, this time it may be worthwhile to get the new version if you need to use a particular feature: setting SFDC fields to […]