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Joydeep Sen Sarma commented on HIVE-1721: ----------------------------------------- @Siyin - that's a good question. I don't know statistically how common it is - but we have heard requests along these lines. for example one use case is that one project wants to get some data for a reasonably large subset of the users. one use case we have seen was where 0.2% of users were interesting - but even 0.2% is very large for us. people also use semi-joins and that pretty much says that people want to filter rows out. > use bloom filters to improve the performance of joins > ----------------------------------------------------- > > Key: HIVE-1721 > URL: https://issues.apache.org/jira/browse/HIVE-1721 > Project: Hive > Issue Type: New Feature > Components: Query Processor > Reporter: Namit Jain > Assignee: Siying Dong > > In case of map-joins, it is likely that the big table will not find many > matching rows from the small table. > Currently, we perform a hash-map lookup for every row in the big table, which > can be pretty expensive. > It might be useful to try out a bloom-filter containing all the elements in > the small table. > Each element from the big table is first searched in the bloom filter, and > only in case of a positive match, > the small table hash table is explored. -- This message is automatically generated by JIRA. - You can reply to this email to add a comment to the issue online.