LiveView 1.4 – New Continuous Queries

This is the first of three posts about the new LiveView 1.4 release.

The big innovation of StreamBase LiveView is its Continuous Query (CQ) mechanism. In many ways, a continuous query looks like a standard database query – a predicate is sent to the server, and a result set is returned. But a LiveView query is a query that keeps being answered, continuously, and automatically. The LiveView server registers queries and, after the current snapshot answer is delivered, the server pushes subsequent matches to the query to the client to provide an always-live view of the query.

So LiveView query results are never out of date – always live.

Continuous query evaluation is a new area of technology innovation, and live query processing demands special features that aren’t found in traditional query processors. In LiveView 1.4, we introduce two major enhancements to the LiveView CQ model: Top-N queries and Time-Windowed queries.

Top-N Queries

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LiveView is often used to manage customer data - for example, many brokerages on Wall Street use
LiveView to continuously understand the state of orders and trades, and to decide how to optimize trading in real-time. A common requirement is for firms to understand: “Which clients are the most at risk?” or “Who is doing the most trading?” With LiveView, it is easy to create a pre-aggregated, real-time view of hundreds of such trading risk analytics.

The problem is, most brokerages have hundreds, or thousands of clients, and the amount of data can overwhelm some user interfaces used to analyze these metrics, such as Excel, or a web client, so our clients often create complex analytics to store only the most interesting real-time metrics to display to traders.  And because LiveView query results are constantly live and updating, sometimes it’s desirable to have the CQ mechanism pre-sort the results for you.

Now, with LiveView 1.4, a continuous query can narrow the amount of data automatically for clients. The CQ can now be parameterized to only show the top values in the table according to any sort key. For example, an Excel sheet might want to display only the 10 most at-risk counterparties, or the 100 largest open orders. A Top-N querie avoids data overload, reduces data clutter on the client, and helps focus user attention on the real-time data that matters the most.

As with all LiveView queries, Top-N queries are continuous. As data goes in or out of scope, rows are added or removed from the result set displayed automatically to users. If data values change, data is re-sorted, and new results may come into the view due to growing or shrinking of the result set.

The result is a new way to explore real-time data and to focus attention on what matters most when making real-time decisions.

Time-Windowed Queries

 

Click to view full sized image on the StreamBase Facebook page.

One of the unique attributes of event processing systems is that they are designed to understand the temporal attributes of streaming data. LiveView can order a table by the event arrival, and appended at the end of a table (e.g., new client orders as they arrive), or events can replace existing fields place (e.g., applying real-time pricing updates to existing client orders).

 

So streaming data has time dimensions that can be handled in a variety of temporal ways by LiveView, allowing decision makers to evaluate data based on its relationship to time. For example, a trader might want continuously view orders from the last 5 minutes organized by size, or open orders that have not been filled that were submitted over 1 minute ago.

LiveView Time-Windowed Queries allows users to restrict a query by “when” the event happened, based on one of these time dimensions. Only data that satisfies the WHEN condition will be displayed, and, once again, due to the CQ model of LiveView, is continuously updated and live.

For example, a query for open orders older than 1 minute would have data leave the view when the order closed. The display the trader looks at will be automatically updated by LiveView. Each cell in the table would be updated in place, as soon as its value changed.

In our other example - a query for the last 5 minutes of counterparty quotes  - will continuously slide forward in time, so a trader is continuously looking at the latest and greatest prices quoted in the market, without ever re-issuing a query, or hitting the “refresh” button on the user interface.

StreamBase handles data in a variety of ways. For example, an order might carry timestamps indicating when it was sent to the market, when it was acknowledged, when it was filled, or a timestamp applied by a third-party system. All of these values are available for time-windowed querying in LiveView.

Continuous Alerting on Top-N and Time-Windowed Continuous Queries

StreamBase LiveView also has native support for alerting. Administrators and end-users alike can ask to be alerted (via SMS, email, etc.) when a continuous query predicate is matched. In LiveView 1.4, alerting has been extended to work with these two new query types, Top-N and Time-Windowed queries.

LiveView – Making Real-Time Analytics Accessible and Actionable

When working with live data, time is the biggest factor. Traditional database-driven systems aren’t designed for real-time analytics; event processing systems are. By using Time-Windowed and Top-N queries in LiveView 1.4, firms can change the way they think about data and turn real-time information into action.