Optimal sampling from sliding windows

APPEARED IN ACM PODS-2009. A sliding windows model is an important case of the streaming model, where only the most "recent" elements remain active and the rest are discarded in a stream. The sliding windows model is important for many applications (see, e.g., Babcock, Babu, Datar, Motwani and Widom (PODS 02); and Datar, Gionis, Indyk and Motwani (SODA 02)). There are two equally important types of the sliding windows model ? windows with fixed size, (e.g., where items arrive one at a time, and only the most recent n items remain active for some fixed parameter n), and bursty windows (e.g., where many items can arrive in "bursts" at a single step and where only items from the last t steps remain active, again for some fixed parameter t). Random sampling is a fundamental tool for data streams, as numerous algorithms operate on the sampled data instead of on the entire stream. Effective sampling from sliding windows is a nontrivial problem, as elements eventually exp...

• Type: Conference
• Year: 2009
• Where: PODS
• Authors: Vladimir Braverman, Rafail Ostrovsky, Carlo Zaniolo
• Keywords: Database, Explicit Deletions, Implicit Deletions, PODS 2009, Windows Model