Running an Apache Spark Artificial Neural Network as a Docker Image

Introduction There are various previous studies to run Apache Spark [1] applications in Docker. A Docker image for an earlier version (1.6.0) of Spark is available in [2], for both standalone and cluster applications. In [3], a Docker image is discussed that simplifies installing/configuring Spark and submitting Spark applications to a Spark cluster. A Docker container for running Python code to interact with Spark is discussed in [4]. A review of running Spark clusters in Docker containers is given in [5]. In this article, we will discuss how to develop a Docker image from an Apache Spark artificial neural network that solves a classification problem. The image runs in a single, non-clustered Docker host. The run-time environment for Apache Spark is also very basic, locally running non-distributed single JVM deployment mode [6]. The simple run-time environment discussed here could be beneficial for application settings with relatively small workloads that are manageable with a single client machine.

✔ Read More...

I guess you came to this post by searching similar kind of issues in any of the search engine and hope that this resolved your problem. If you find this tips useful, just drop a line below and share the link to others and who knows they might find it useful too.

Stay tuned to my blog, twitter or facebook to read more articles, tutorials, news, tips & tricks on various technology fields. Also Subscribe to our Newsletter with your Email ID to keep you updated on latest posts. We will send newsletter to your registered email address. We will not share your email address to anybody as we respect privacy.

This article is related to

big data,docker,machine learning,ai,artificial intelligence,apache spark,classification models,artificial neural network,apache spark examples java