[jira] [Updated] (HAWQ-1597) Implement Runtime Filter for Hash Join

2018-06-04 Thread Lin Wen (JIRA)


 [ 
https://issues.apache.org/jira/browse/HAWQ-1597?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Lin Wen updated HAWQ-1597:
--
Attachment: q17_modified_hawq.gif

> Implement Runtime Filter for Hash Join
> --
>
> Key: HAWQ-1597
> URL: https://issues.apache.org/jira/browse/HAWQ-1597
> Project: Apache HAWQ
>  Issue Type: New Feature
>  Components: Query Execution
>Reporter: Lin Wen
>Assignee: Lin Wen
>Priority: Major
> Fix For: 2.4.0.0-incubating
>
> Attachments: 111BA854-7318-46A7-8338-5F2993D60FA3.png, HAWQ Runtime 
> Filter Design.pdf, HAWQ Runtime Filter Design.pdf, q17_modified_hawq.gif
>
>
> Bloom filter is a space-efficient probabilistic data structure invented in 
> 1970, which is used to test whether an element is a member of a set.
> Nowdays, bloom filter is widely used in OLAP or data-intensive applications 
> to quickly filter data. It is usually implemented in OLAP systems for hash 
> join. The basic idea is, when hash join two tables, during the build phase, 
> build a bloomfilter information for the inner table, then push down this 
> bloomfilter information to the scan of the outer table, so that, less tuples 
> from the outer table will be returned to hash join node and joined with hash 
> table. It can greatly improment the hash join performance if the selectivity 
> is high.



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[jira] [Updated] (HAWQ-1597) Implement Runtime Filter for Hash Join

2018-06-04 Thread Lin Wen (JIRA)


 [ 
https://issues.apache.org/jira/browse/HAWQ-1597?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Lin Wen updated HAWQ-1597:
--
Attachment: 111BA854-7318-46A7-8338-5F2993D60FA3.png

> Implement Runtime Filter for Hash Join
> --
>
> Key: HAWQ-1597
> URL: https://issues.apache.org/jira/browse/HAWQ-1597
> Project: Apache HAWQ
>  Issue Type: New Feature
>  Components: Query Execution
>Reporter: Lin Wen
>Assignee: Lin Wen
>Priority: Major
> Fix For: 2.4.0.0-incubating
>
> Attachments: 111BA854-7318-46A7-8338-5F2993D60FA3.png, HAWQ Runtime 
> Filter Design.pdf, HAWQ Runtime Filter Design.pdf
>
>
> Bloom filter is a space-efficient probabilistic data structure invented in 
> 1970, which is used to test whether an element is a member of a set.
> Nowdays, bloom filter is widely used in OLAP or data-intensive applications 
> to quickly filter data. It is usually implemented in OLAP systems for hash 
> join. The basic idea is, when hash join two tables, during the build phase, 
> build a bloomfilter information for the inner table, then push down this 
> bloomfilter information to the scan of the outer table, so that, less tuples 
> from the outer table will be returned to hash join node and joined with hash 
> table. It can greatly improment the hash join performance if the selectivity 
> is high.



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[jira] [Updated] (HAWQ-1597) Implement Runtime Filter for Hash Join

2018-05-15 Thread Lin Wen (JIRA)

 [ 
https://issues.apache.org/jira/browse/HAWQ-1597?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Lin Wen updated HAWQ-1597:
--
Attachment: HAWQ Runtime Filter Design.pdf

> Implement Runtime Filter for Hash Join
> --
>
> Key: HAWQ-1597
> URL: https://issues.apache.org/jira/browse/HAWQ-1597
> Project: Apache HAWQ
>  Issue Type: New Feature
>  Components: Query Execution
>Reporter: Lin Wen
>Assignee: Lin Wen
>Priority: Major
> Fix For: 2.4.0.0-incubating
>
> Attachments: HAWQ Runtime Filter Design.pdf, HAWQ Runtime Filter 
> Design.pdf
>
>
> Bloom filter is a space-efficient probabilistic data structure invented in 
> 1970, which is used to test whether an element is a member of a set.
> Nowdays, bloom filter is widely used in OLAP or data-intensive applications 
> to quickly filter data. It is usually implemented in OLAP systems for hash 
> join. The basic idea is, when hash join two tables, during the build phase, 
> build a bloomfilter information for the inner table, then push down this 
> bloomfilter information to the scan of the outer table, so that, less tuples 
> from the outer table will be returned to hash join node and joined with hash 
> table. It can greatly improment the hash join performance if the selectivity 
> is high.



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[jira] [Updated] (HAWQ-1597) Implement Runtime Filter for Hash Join

2018-04-09 Thread Radar Lei (JIRA)

 [ 
https://issues.apache.org/jira/browse/HAWQ-1597?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Radar Lei updated HAWQ-1597:

Fix Version/s: 2.4.0.0-incubating

> Implement Runtime Filter for Hash Join
> --
>
> Key: HAWQ-1597
> URL: https://issues.apache.org/jira/browse/HAWQ-1597
> Project: Apache HAWQ
>  Issue Type: New Feature
>  Components: Query Execution
>Reporter: Lin Wen
>Assignee: Lin Wen
>Priority: Major
> Fix For: 2.4.0.0-incubating
>
> Attachments: HAWQ Runtime Filter Design.pdf
>
>
> Bloom filter is a space-efficient probabilistic data structure invented in 
> 1970, which is used to test whether an element is a member of a set.
> Nowdays, bloom filter is widely used in OLAP or data-intensive applications 
> to quickly filter data. It is usually implemented in OLAP systems for hash 
> join. The basic idea is, when hash join two tables, during the build phase, 
> build a bloomfilter information for the inner table, then push down this 
> bloomfilter information to the scan of the outer table, so that, less tuples 
> from the outer table will be returned to hash join node and joined with hash 
> table. It can greatly improment the hash join performance if the selectivity 
> is high.



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[jira] [Updated] (HAWQ-1597) Implement Runtime Filter for Hash Join

2018-03-25 Thread Lin Wen (JIRA)

 [ 
https://issues.apache.org/jira/browse/HAWQ-1597?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Lin Wen updated HAWQ-1597:
--
Attachment: HAWQ Runtime Filter Design.pdf

> Implement Runtime Filter for Hash Join
> --
>
> Key: HAWQ-1597
> URL: https://issues.apache.org/jira/browse/HAWQ-1597
> Project: Apache HAWQ
>  Issue Type: New Feature
>  Components: Query Execution
>Reporter: Lin Wen
>Assignee: Lei Chang
>Priority: Major
> Attachments: HAWQ Runtime Filter Design.pdf
>
>
> Bloom filter is a space-efficient probabilistic data structure invented in 
> 1970, which is used to test whether an element is a member of a set.
> Nowdays, bloom filter is widely used in OLAP or data-intensive applications 
> to quickly filter data. It is usually implemented in OLAP systems for hash 
> join. The basic idea is, when hash join two tables, during the build phase, 
> build a bloomfilter information for the inner table, then push down this 
> bloomfilter information to the scan of the outer table, so that, less tuples 
> from the outer table will be returned to hash join node and joined with hash 
> table. It can greatly improment the hash join performance if the selectivity 
> is high.



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