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MGMA connexion, 2016
Closer integration of machine learning (ML) with data processing is a booming area in both the data management industry and academia. Almost all ML toolkits assume that the input is a single table, but many datasets are not stored as single tables due to normalization.
Arun Kumar 0001 +3 more
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Closer integration of machine learning (ML) with data processing is a booming area in both the data management industry and academia. Almost all ML toolkits assume that the input is a single table, but many datasets are not stored as single tables due to normalization.
Arun Kumar 0001 +3 more
openaire +3 more sources
Join Reordering by Join Simulation
2009 IEEE 25th International Conference on Data Engineering, 2009We introduce a framework for reordering join pipelines at runtime in a database system. This framework incorporates novel techniques for simulating the execution of a join pipeline using random samples and statistical summaries. Our simulation techniques provide accurate runtime cardinality estimates along all alternative execution paths of a join ...
Chaitanya Mishra, Nick Koudas
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Proceedings of the 8th ACM international symposium on Advances in geographic information systems, 2000
Spatial applications frequently need to join two data sets based on some spatial relationship between objects in the two data sets. This operation, called a spatial join, is an expensive operation and in the past many algorithms have been proposed for evaluating the spatial join operation on a single processor system.
Jignesh M. Patel, David J. DeWitt
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Spatial applications frequently need to join two data sets based on some spatial relationship between objects in the two data sets. This operation, called a spatial join, is an expensive operation and in the past many algorithms have been proposed for evaluating the spatial join operation on a single processor system.
Jignesh M. Patel, David J. DeWitt
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ACM Transactions on Database Systems, 1991
CITATO ANCHE IN COMPUTING REVIEWS ...
NEGRI, MAURO, PELAGATTI, GIUSEPPE
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CITATO ANCHE IN COMPUTING REVIEWS ...
NEGRI, MAURO, PELAGATTI, GIUSEPPE
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Understanding Joining — And Not Joining
2007Following the discussion of the growing professionalization in groups, this chapter presents two new sorts of evidence from surveys. First, it documents responses from group managers giving a top—down insider perspective on joining. Secondly, it reports on a survey of (environmental) non-members.
Grant Jordan, William A. Maloney
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ACM SIGMOD Record
Over the last decade, worst-case optimal join (WCOJ) algorithms have emerged as a new paradigm for one of the most fundamental challenges in query processing: computing joins efficiently. Such an algorithm can be asymptotically faster than traditional binary joins, all the while remaining simple to understand and implement.
Yisu Remy Wang, Max Willsey, Dan Suciu
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Over the last decade, worst-case optimal join (WCOJ) algorithms have emerged as a new paradigm for one of the most fundamental challenges in query processing: computing joins efficiently. Such an algorithm can be asymptotically faster than traditional binary joins, all the while remaining simple to understand and implement.
Yisu Remy Wang, Max Willsey, Dan Suciu
openaire +1 more source