Database Reference
In-Depth Information
Figure 1-2. Dynamic systems such as aircraft produce a wide variety of data that can and should
be stored as a time series to reap the maximum benefit from analytics, especially if the predominant
access pattern for queries is based on a time range. The chart shows the first few minutes of alti-
tude data from the flight data systems of aircraft taking off at a busy airport in California.
To clarify the concept of a time series, let's first consider a case where a time series is not ne-
cessary. Sometimes you just want to know the value of a particular parameter
at the current
moment
. As a simple example, think about glancing at the speedometer in a car while driv-
ing. What's of interest in this situation is to know the speed at the moment, rather than hav-
ing a history of how that condition has changed with time. In this case, a time series of speed
measurements is not of interest to the driver.
Next, consider how you think about time. Going back to the analogy of a holiday flight for a
moment, sometimes you are concerned with the length of a
time interval
--how long is the
flight in hours, for instance. Once your flight arrives, your perception likely shifts to think of
