Name
Abstract | ||
|---|---|---|
Data market is an emerging type of cloud service that enables a data owner to sell their data sets in a public cloud. Buyers who are interested in a certain dataset can access the data in the market via a RESTful API. Accessing data in the data market may not be free. For example, it costs USD 12 per month to obtain 100 “transactions” from the WorldWide Historical Weather dataset in Windows Azure Data Marketplace, where a transaction is a unit of result size (e.g., a query result of 4400 records would consume 44 transactions as Windows Azure Data Marketplace confines one transaction to 100 records). Therefore, in this paper, we present PayLess, a system that helps data buyers to optimize their queries so that they can obtain the query results by paying less to the data sellers. Experiments over synthetic data and real data sets in Windows Azure Marketplace show that PayLess can cost-effectively handle SQL query processing over data markets. |
Year | Venue | Field |
|---|---|---|
2015 | EDBT | Query optimization,SQL,Data mining,Data set,Computer science,Synthetic data,Database transaction,Database,Cloud computing |
DocType | Citations | PageRank |
Conference | 1 | 0.34 |
References | Authors | |
21 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yu Li | 1 | 25 | 4.17 |
| Eric Lo | 2 | 813 | 51.50 |
| man lung yiu | 3 | 2436 | 109.78 |
| Wenjian Xu | 4 | 49 | 6.28 |