REST is an API design architecture, which, in the last few years, has become the norm for implementing web services. It uses HTTP to get data and perform various operations (POST, GET, PUT, and DELETE) in JSON format, allowing better and faster parsing of data.
However, like all great technologies, REST API comes with some downsides. Here are some of the most common ones:
Within the scope of this article, the Batch Ab Initio graph will be triggered via the scheduler and the files in the destination folder will be retrieved and the data in it will be parsed according to certain criteria.
The parsed data will be written to the database.
Events are messages that are sent by a system to notify operators or other systems about a change in its domain. With event-driven architectures powered by systems like Apache Kafka becoming more prominent, there are now many applications in the modern software stack that make use of events and messages to operate effectively. In this blog, we will examine the use of three different data backends for event data – Apache Druid, Elasticsearch, and Rockset.
Events are commonly used by systems in the following ways:
This blog introduces Wormhole, an open-source Dockerized solution for deploying Presto and Alluxio clusters for blazing-fast analytics on file system (we use S3, GCS, OSS). When it comes to analytics, generally people are hands-on in writing SQL queries and love to analyze data that resides in a warehouse (e.g. MySQL database). But as data grows, these stores start failing and there arises a need for getting the faster results in the same or a shorter time frame. This can be solved by distributed computing and Presto is designed for that. When attached to Alluxio, it works even more, faster. That’s what Wormhole is all about.
You may also enjoy: Alluxio Cluster Setup Using Docker
Here is the high-level architecture diagram of solution:
It’s a common practice to encrypt the secrets/credentials we use in our code and then save it in some secure place. We have a number of options to achieve this, with tools like Vault, Git-crypt, and more. However, git-secret is one simple awesome tool that we can use to store our secrets in our Git repo. Git secret uses gpg for encryption and decryption of secrets.
Here’s how git-secret works. Go to the folder in your repo in which you have files to encrypt. Then, run git init && git secret init. This would initialize your .gitsecret folder. Then you run git secret tell $email , and if you want other users to decrypt the secrets file you have to import their gpg public key and again run git secret tell $otheruseremailid . Now you can run git secret add $secretfilename and git secret hide,which creates $yoursecretfile.secret file, which is an encrypted secret file.
Apache Spark supports many different data formats, such as the ubiquitous CSV format and web-friendly JSON format. Common formats used primarily for big data analytical purposes are Apache Parquet and Apache Avro.
In this post, we’re going to cover the properties of these four formats — CSV, JSON, Parquet, and Avro with Apache Spark.
I am very excited to share my experiences building Continuous Integration/Continuous Delivery (CI/CD) into Spring-Boot-based Java applications. First, let’s establish everything we will learn in this tutorial:
Step 1) Create a Spring Boot Java App using Spring Initializr
I thought my first ASP.NET Core edition of Hello, Blinky would be my last, at least for a long time. But then something reminded me of Blazor, and I thought why not build a Blazor edition of Hello, Blinky for Windows IoT Core and Raspberry Pi? After some hacking, I made it work. Here’s my Hello, Blinky for Blazor.
You may also like: Building an ASP.NET Core »Hello, Blinky » IoT Application
Hello, Blinky is sort of like the "Hello, World" from Raspberry Pi and other microboards. While it’s possible to do a "Hello, World" with these boards, why not do something more interesting with connected electronics? Isn’t that what those boards were made for anyway?
Internet of Things (IoT) has transformed the way businesses work, and the industry has seen a massive shift from on-premise software to cloud computing. IoT has sprawled across several industries catering to consumers at a global level.
From smart voice assistants to smart homes, brands are expanding their range of services and experimenting with different ideas to enhance the customer experience. Data on customer behavior is now collected through diverse and innovative ways.
The Couchbase CTO, Ravi Mayuram, announced the Beta of Distributed Multi-document ACID Transactions in Couchbase Server 6.5. I highly recommend reading Ravi’s blog, which highlights how Couchbase transactions are an innovative union of ACID guarantees with scale, high-availability, performance, and flexibility.
In this article, I will dive deeper into our distributed ACID transactions functionality.
