Caching search engine results over incremental indices

Blanco, Roi; Bortnikov, Edward; Junqueira, Flavio; Lempel, Ronny; Telloli, Luca; Zaragoza, Hugo

doi:10.1145/1835449.1835466

Cited by 32 publications

(77 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Sazoglu et al [2013b] investigate hybrid strategies for setting TTL values. Other works [Alicia et al 2011;Blanco et al 2010aBlanco et al , 2010bBortnikov et al 2011; propose more sophisticated mechanisms. Herein, we do not further discuss these studies, since the cache freshness issue is not in the scope of our work.…”

Section: Search Results Cachingmentioning

confidence: 99%

Second Chance

et al. 2013

View full text Add to dashboard Cite

Web search engines are known to cache the results of previously issued queries. The stored results typically contain the document summaries and some data that is used to construct the final search result page returned to the user. An alternative strategy is to store in the cache only the result document IDs, which take much less space, allowing results of more queries to be cached. These two strategies lead to an interesting trade-off between the hit rate and the average query response latency. In this work, in order to exploit this trade-off, we propose a hybrid result caching strategy where a dynamic result cache is split into two sections: an HTML cache and a docID cache. Moreover, using a realistic cost model, we evaluate the performance of different result prefetching strategies for the proposed hybrid cache and the baseline HTML-only cache. Finally, we propose a machine learning approach to predict singleton queries, which occur only once in the query stream. We show that when the proposed hybrid result caching strategy is coupled with the singleton query predictor, the hit rate is further improved.

show abstract

Section: Search Results Cachingmentioning

confidence: 99%

Second Chance

et al. 2013

View full text Add to dashboard Cite

show abstract

“…Caching documents for popular web queries is widely employed in practice. Blanco et al [5] propose a scheme to invalidate cached results when new documents arrive. Invalidation causes re-execution of the query when it is invoked by a user.…”

Section: Real-time Tweet Indexingmentioning

confidence: 99%

“…Serving costs comparison to the pub-sub architecture. We continue by further comparing our approach with a caching scheme, along the lines proposed by Blanco et al [5], which caches the top-k updates that annotate each story, and invalidates the cached list on arrival of a tweet that could potentially annotate the story. We consider the cost of annotating the 1K most-popular stories shown on a news website in a single day, where each story is represented using its main body of text.…”

Section: Real-time Tweet Indexingmentioning

confidence: 99%

Top-k publish-subscribe for social annotation of news

et al. 2013

View full text Add to dashboard Cite

Social content, such as Twitter updates, often have the quickest first-hand reports of news events, as well as numerous commentaries that are indicative of public view of such events. As such, social updates provide a good complement to professionally written news articles. In this paper we consider the problem of automatically annotating news stories with social updates (tweets), at a news website serving high volume of pageviews. The high rate of both the pageviews (millions to billions a day) and of the incoming tweets (more than 100 millions a day) make real-time indexing of tweets ineffective, as this requires an index that is both queried and updated extremely frequently. The rate of tweet updates makes caching techniques almost unusable since the cache would become stale very quickly.We propose a novel architecture where each story is treated as a subscription for tweets relevant to the story's content, and new algorithms that efficiently match tweets to stories, proactively maintaining the top-k tweets for each story. Such top-k pub-sub consumes only a small fraction of the resource cost of alternative solutions, and can be applicable to other large scale content-based publish-subscribe problems. We demonstrate the effectiveness of our approach on realworld data: a corpus of news stories from Yahoo! News and a log of Twitter updates.

show abstract

“…The result sets for such queries should have a short time to live, whereas there are queries for which the search results change very rarely, they could be cached much longer. Making informed decisions about invalidation requires knowledge about the rate of change for particular queries [19]. Perhaps this information, or an estimate thereof, could be made an integral part of the search results, similar to the way in which Domain Name System (DNS) records work.…”

Section: We Have Explored Several Fundamental Caching Policies Showinmentioning

confidence: 99%

Search Result Caching in Peer-to-Peer Information Retrieval Networks

Tigelaar

Hiemstra

Trieschnigg

2011

Lecture Notes in Computer Science

View full text Add to dashboard Cite

For peer-to-peer web search engines it is important to quickly process queries and return search results. How to keep the perceived latency low is an open challenge. In this paper we explore the solution potential of search result caching in large-scale peer-to-peer information retrieval networks by simulating such networks with increasing levels of realism. We nd that a small bounded cache oers performance comparable to an unbounded cache. Furthermore, we explore partially centralised and fully distributed scenarios, and nd that in the most realistic distributed case caching can reduce the query load by thirty-three percent. With optimisations this can be boosted to nearly seventy percent. IntroductionIn peer-to-peer information retrieval a network of peers provide a search service collaboratively. We dene a peer as a computer system connected to the Internet.The term peer refers to the fact that in a peer-to-peer system all peers are considered equal and can both supply and consume resources. In a peer-to-peer network each additional peer adds extra processing capacity and bandwidth in contrast with typical client/server search systems where each additional client puts extra strain on the server. When such a peer-to-peer network has good load balancing properties it can scale up to handle millions of simultaneous peers.However, the performance is strongly aected by how well it can deal with the continuous rapid joining and departing of peers which is called churn.We study peer-to-peer information retrieval systems where each peer contains, and maintains an index over, a subset of all the documents in the system.Since presumably relevant search results can be located at any peer it is dicult to route a query to the right one. This problem is commonly approached using dierent network topologies and replication of index data [1,2,3].In this paper we explore search result caching. We assume that for each query there is a peer that can provide a set of original search results. If this query is posed often that peer would cripple under the demand for providing this set over and over again. Hence, we propose that each peer that obtains search results for a particular query caches those results. The eect is that search results for popular queries can be obtained from many peers: high availability, and the load on the peer that provided the original results is reduced: load balancing.

show abstract

Caching search engine results over incremental indices

Cited by 32 publications

References 19 publications

Second Chance

Second Chance

Top-k publish-subscribe for social annotation of news

Search Result Caching in Peer-to-Peer Information Retrieval Networks

Contact Info

Product

Resources

About