Kinesis Analytics

Kevin Feasel

2016-09-19

Cloud

Ryan Nienhuis shows how to implement Amazon Kinesis Analytics:

As I covered in the first post, streaming data is continuously generated; therefore, you need to specify bounds when processing data to make your result set deterministic. Some SQL statements operate on individual rows and have natural bounds, such as a continuous filter that evaluates each row based upon a defined SQL WHERE clause. However, SQL statements that process data across rows need to have set bounds, such as calculating the average of particular column. The mechanism that provides these bounds is a window.

Windows are important because they define the bounds for which you want your query to operate. The starting bound is usually the current row that Amazon Kinesis Analytics is processing, and the window defines the ending bound.

Windows are required with any query that works across rows, because the in-application stream is unbounded and windows provide a mechanism to bind the result set and make the query deterministic. Analytics supports three types of windows: tumbling, sliding, and custom.

The concepts here are very similar to Azure’s Stream Analytics.

Related Posts

Automating Azure SQL Database Scaling

Arun Sirpal shows how to use Azure Logic Apps to auto-scale Azure SQL Database: When I was presenting my Azure SQL Database session at DataRelay (used to be SQLRelay) I was asked (over coffee) about auto scaling capabilities. Quite simply there is nothing out of the box to achieve this. The idea of auto scaling […]

Read More

Deploying An Azure Container Within A Virtual Network

Andrew Pruski shows us that you can now deploy an Azure container running SQL Server within an Azure virtual network: Up until now Azure Container Instances only had one option to allow us to connect. That was assigning a public IP address that was directly exposed to the internet. Not really great as exposing SQL […]

Read More

Categories

September 2016
MTWTFSS
« Aug Oct »
 1234
567891011
12131415161718
19202122232425
2627282930