Tag: JSON

Feed: Featured Blog Posts - Data Science Central. Author: Vibhor Nigam. This post is a token of appreciation for the amazing open source community of Data Science, to which I owe a lot of what I have learned. For last few months, I have been working on a side project of mine to develop machine learning application on streaming data. It was a great learning experience with numerous challenges and lots of learning, some of which I have tried to share in here. This post is focused on how to deploy machine learning models on streaming data and covers all ... Read More

Feed: AWS Compute Blog. Author: Rachel Richardson. This post is courtesy of Otavio Ferreira, Manager, Amazon SNS, AWS Messaging.Amazon SNS is a fully managed pub/sub messaging and event-driven computing service that can decouple distributed systems and microservices. By default, when your publisher system posts a message to an Amazon SNS topic, all systems subscribed to the topic receive a copy of the message. By using Amazon SNS subscription attributes, you can customize this default behavior and make Amazon SNS fit your use cases even more naturally. The available set of Amazon SNS subscription attributes includes FilterPolicy, DeliveryPolicy, and RawMessageDelivery. You ... Read More

Feed: Microsoft Azure Blog. Author: Ashish Thapliyal. Fast Interactive BI, data security and end user adoption are three critical challenges for successful big data analytics implementations. Without right architecture and tools, many big data and analytics projects fail to catch on with common BI users and enterprise security architects. In this blog we will discuss architectural approaches that will help you architect big data solution for fast interactive queries, simplified security model and improved user adoption with BI users. Traditional approach to fast interactive BI Deep analytical queries processed on Hadoop systems have traditionally been slow. MapReduce jobs or hive ... Read More

Feed: Microsoft Azure Blog. Author: Ashish Thapliyal. The HDInsight team is excited to announce Apache Zeppelin Support for Apache Phoenix Phoenix in Azure HDInsight Apache Phoenix is an open source, massively parallel relational database layer built on HBase. Phoenix allows you to use SQL like queries over HBase. Phoenix uses JDBC drivers underneath to enable users to create, delete, alter SQL tables, indexes, views and sequences, upset rows individually and in bulk. Phoenix uses NOSQL native compilation rather than using MapReduce to compile queries, enabling the creation of low-latency applications on top of HBase. Apache Phoenix enables OLTP and operational ... Read More

Feed: All - O'Reilly Media. Author: Rohit Jain. Compass (source: Pixabay) Check out the "Data Engineering & Architecture" sessions at the Strata Data Conference in New York, September 11-13, 2018. Technologies for streaming, storing, and querying big data have matured to the point where the computer industry can usefully establish standards. As in other areas of engineering, standardization allows practitioners to port their learnings across a multitude of solutions, and to more easily employ different technologies together; standardization also allows solution providers to take advantage of sub-components to expeditiously build more compelling solutions with broader applicability. Unfortunately, little has been ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Packt Publishing. With the rise of IoT devices (Internet of Things), being able to analyze and visualize live streams of data is becoming more and more important. For example, you could have sensors like thermometers in machines or portable medical devices like pacemakers, continuously streaming data to a streaming service like Kafka. PixieDust makes it easier to work with live data inside Jupyter Notebooks by providing simple integration APIs to both the PixieApp and display() framework.   On the visualization level, PixieDust uses Bokeh support for efficient data source update to plot streaming ... Read More

Feed: Planet MySQL; Author: Severalnines; Monitoring is a concern for containers, as the infrastructure is dynamic. Containers can be routinely created and destroyed, and are ephemeral. So how do you keep track of your MySQL instances running on Docker? As with any software component, there are many options out there that can be used. We’ll look at Prometheus as a solution built for distributed infrastructure, and works very well with Docker. This is a two-part blog. In this part 1 blog, we are going to cover the deployment aspect of our MySQL containers with Prometheus and its components, running as ... Read More

Feed: Microsoft Power BI Blog | Microsoft Power BI. Author: . Today, we’re pleased to announce the August update of Power BI Report Server!  This release contains several new features, including some highly anticipated items like report theming, conditional formatting improvements, and report page tooltips. Read on to learn more about these and many other new capabilities we’ve added in this release.  Please note: For those users who are upgrading their report server from a previous version, we recommend clearing your browser cache before viewing your reports. Reporting Analytics Modeling We are very excited to announce we’ve added report theming to ... Read More

Feed: R-bloggers. Author: rOpenSci - open tools for open science. This week version 2.0 of the mongolite package has been released to CRAN. Major new features in this release include support for MongoDB 4.0, GridFS, running database commands, and connection pooling. Mongolite is primarily an easy-to-use client to get data in and out of MongoDB. However it supports increasingly many advanced features like aggregation, indexing, map-reduce, streaming, encryption, and enterprise authentication. The mongolite user manual provides a great introduction with details and worked examples. GridFS Support! New in version 2.0 is support for the MongoDB GridFS system. A GridFS is ... Read More

Feed: AWS Compute Blog. Author: Nathan Taber. This post contributed by Subhrangshu Kumar Sarkar, Sr. Technical Account Manager at AWSThe Amazon ECS–optimized Amazon Machine Image (AMI) comes prepackaged with the Amazon Elastic Container Service (ECS) container agent, Docker, and the ecs-init service. When updates to these components are released, try to integrate them as quickly as possible. Doing so helps you maintain a safe, secure, and reliable environment for running your containers. Each release of the ECS–optimized AMI includes bug fixes and feature updates. AWS recommends refreshing your container instance fleet with the latest AMI whenever possible, rather than trying ... Read More