18.12.2012 Views

Roxana - Gabriela HORINCAR Refresh Strategies and Online ... - LIP6

Roxana - Gabriela HORINCAR Refresh Strategies and Online ... - LIP6

Roxana - Gabriela HORINCAR Refresh Strategies and Online ... - LIP6

SHOW MORE
SHOW LESS

Create successful ePaper yourself

Turn your PDF publications into a flip-book with our unique Google optimized e-Paper software.

eaches (<strong>and</strong> possibly exceeds) the size of its publication window:<br />

Div(s, t, Tr) ≥ Ws.<br />

In consequence, we make a distinction between the total number of items published by a<br />

source since the last refresh (stream divergence) <strong>and</strong> the number of only those available<br />

ones (window divergence).<br />

Definition 2.1.5. Stream divergence relevant to query q<br />

Let F (s, t) be the publication stream of source feed s. Let function new(F (s, t)) be the<br />

sequence of new items generated by s since its last refresh moment Tr. We define the<br />

stream divergence as:<br />

DivF (s, q, t, Tr) = |q(new(F (s, t)))|<br />

Note that the divergence function introduced before (Definition 2.1.2) corresponds to the<br />

stream divergence.<br />

Definition 2.1.6. Window divergence relevant to query q<br />

Let A(s, t) be the publication window of source feed s. Let function new(A(s, t)) return<br />

the sequence of new items published since time moment Tr <strong>and</strong> still available at source s<br />

at time moment t. We define the window divergence as:<br />

DivA(s, q, t, Tr) = |q(new(A(s, t)))|<br />

Observe that stream <strong>and</strong> window divergence functions relevant to query q are equal if the<br />

source s is not yet saturated at time moment t:<br />

if |new(A(s, t))| = |new(F (s, t))| < Ws, then DivA(s, q, t, Tr) = DivF (s, q, t, Tr)<br />

Otherwise, as source s becomes saturated, stream divergence exceeds the window divergence<br />

value:<br />

if |new(A(s, t))| = Ws, |new(F (s, t))| > Ws, then DivA(s, q, t, Tr) < DivF (s, q, t, Tr)<br />

We introduce an example in Figure 2.2 in order to better underst<strong>and</strong> the evolution in time<br />

of the stream <strong>and</strong> window divergence functions when different types of aggregation queries<br />

are used: a simple union q1, with sel(q1) = 1, <strong>and</strong> a filtering query q2, with sel(q2) < 1.<br />

We consider that source s becomes saturated at time instant Tsat. Both the stream <strong>and</strong><br />

window divergence functions relevant to query q1 reach the capacity of the publication<br />

window Ws <strong>and</strong> those relevant to query q2 reach a value estimated near sel(q2) · Ws. In<br />

Figure 2.2 the saturation point is marked by red lines.<br />

24

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!