Ray is an open source, easy to use library for distributed computing with python. In my opinion, the biggest advantage of Ray is that python code might be parallelized as it is, so code do not have to be written in a specific way. Functions might be used as tasks …
In Big Data containers era, there is no way, that you will avoid working with cluster-computing frameworks, like Hadoop or Spark. At some point, I had to choose between those two, and as Apache spark seems to be more flexible and faster, I decided to look closer into it. Following …
“…Protocol buffers are Google’s language-neutral, platform-neutral, extensible mechanism for serializing structured data – think XML, but smaller, faster, and simpler. You define how you want your data to be structured once, then you can use special generated source code to easily write and read your structured data to and from …
