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In this paper, we present BlinkDB, a massively parallel, approximate query engine for running interactive SQL queries on large volumes of data. BlinkDB allows users to trade-off query accuracy for response time, enabling interactive queries over massive data by running queries on data samples and presenting results annotated with meaningful error bars. To(More)
Mining frequent itemsets from data streams has proved to be very difficult because of computational complexity and the need for real-time response. In this paper, we introduce a novel verification algorithm which we then use to improve the performance of monitoring and mining tasks for association rules. Thus, we propose a frequent itemset mining method for(More)
Much research attention has been given to delivering high-performance systems that are capable of <i>complex event processing</i> (CEP) in a wide range of applications. However, many current CEP systems focus on processing efficiently data having a simple structure, and are otherwise limited in their ability to support efficiently complex continuous queries(More)
Crowd-sourcing has become a popular means of acquiring labeled data for many tasks where humans are more accurate than computers , such as image tagging, entity resolution, and sentiment analysis. However, due to the time and cost of human labor, solutions that rely solely on crowd-sourcing are oen limited to small datasets (i.e., a few thousand items). is(More)
Database administrators of Online Transaction Processing (OLTP) systems constantly face difficult questions. For example, "What is the maximum throughput I can sustain with my current hardware?", "How much disk I/O will my system perform if the requests per second double?", or "What will happen if the ratio of transactions in my system changes?". Resource(More)
Crowd-sourcing has become a popular means of acquiring labeled data for many tasks where humans are more accurate than computers , such as image tagging, entity resolution, or sentiment analysis. However, due to the time and cost of human labor, solutions that solely rely on crowd-sourcing are often limited to small datasets (i.e., a few thousand items).(More)
While Complex Event Processing (CEP) constitutes a considerable portion of the so-called Big Data analytics, current CEP systems can only process data having a simple structure, and are otherwise limited in their ability to efficiently support complex continuous queries on structured or semistructured information. However, XML-like streams represent a very(More)
Walsh-Hadamard transform (WHT) has many applications in digital signal processing including bioinformatics. While there are efficient algorithms for implementing this transform such as fast WHT (FWHT), performing WHT continuously on a sliding window over a long sequence is time consuming. As it is not reasonable to compute a separate WHT upon arrival of(More)
Modern data analytics applications typically process massive amounts of data on clusters of tens, hundreds, or thousands of machines to support near-real-time decisions.The quantity of data and limitations of disk and memory bandwidth often make it infeasible to deliver answers at interactive speeds. However, it has been widely observed that many(More)