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When Document Generation API launched a few months ago, we included a Microsoft Word add-in to make it simpler for folks to design their Word templates for use within the API. To use the add-in, you needed to provide data in JSON format, either pasted in or uploaded via an existing file:

This worked perfectly fine if you had your data ready to go, but that wouldn’t always be possible, especially if you’re starting a new project and need to start prototyping quickly. Luckily, our latest update adds a few features to simplify this. Let’s take a quick look at what’s changed. Note — for folks who’ve already installed the Word add-in, it should update automatically for you. Suppose you haven’t installed this add-in yet; head over to our documentation for instructions on how to do it. 

Source de l’article sur DZONE

Applications used in the field of Big Data process huge amounts of information, and this often happens in real time. Naturally, such applications must be highly reliable so that no error in the code can interfere with data processing. To achieve high reliability, one needs to keep a wary eye on the code quality of projects developed for this area. The PVS-Studio static analyzer is one of the solutions to this problem. Today, the Apache Flink project developed by the Apache Software Foundation, one of the leaders in the Big Data software market, was chosen as a test subject for the analyzer.

So, what is Apache Flink? It is an open-source framework for distributed processing of large amounts of data. It was developed as an alternative to Hadoop MapReduce in 2010 at the Technical University of Berlin. The framework is based on the distributed execution engine for batch and streaming data processing applications. This engine is written in Java and Scala. Today, Apache Flink can be used in projects written using Java, Scala, Python, and even SQL.

Source de l’article sur DZONE