[jira] [Updated] (FLINK-2147) Approximate calculation of frequencies in data streams
[ https://issues.apache.org/jira/browse/FLINK-2147?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Flink Jira Bot updated FLINK-2147: -- Labels: approximate auto-deprioritized-major auto-deprioritized-minor statistics (was: approximate auto-deprioritized-major stale-minor statistics) Priority: Not a Priority (was: Minor) This issue was labeled "stale-minor" 7 days ago and has not received any updates so it is being deprioritized. If this ticket is actually Minor, please raise the priority and ask a committer to assign you the issue or revive the public discussion. > Approximate calculation of frequencies in data streams > -- > > Key: FLINK-2147 > URL: https://issues.apache.org/jira/browse/FLINK-2147 > Project: Flink > Issue Type: New Feature > Components: API / DataStream >Reporter: Gábor Gévay >Priority: Not a Priority > Labels: approximate, auto-deprioritized-major, > auto-deprioritized-minor, statistics > > Count-Min sketch is a hashing-based algorithm for approximately keeping track > of the frequencies of elements in a data stream. It is described by Cormode > et al. in the following paper: > http://dimacs.rutgers.edu/~graham/pubs/papers/cmsoft.pdf > Note that this algorithm can be conveniently implemented in a distributed > way, as described in section 3.2 of the paper. > The paper > http://www.vldb.org/conf/2002/S10P03.pdf > also describes algorithms for approximately keeping track of frequencies, but > here the user can specify a threshold below which she is not interested in > the frequency of an element. The error-bounds are also different than the > Count-min sketch algorithm. -- This message was sent by Atlassian Jira (v8.20.1#820001)
[jira] [Updated] (FLINK-2147) Approximate calculation of frequencies in data streams
[ https://issues.apache.org/jira/browse/FLINK-2147?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Flink Jira Bot updated FLINK-2147: -- Labels: approximate auto-deprioritized-major stale-minor statistics (was: approximate auto-deprioritized-major statistics) I am the [Flink Jira Bot|https://github.com/apache/flink-jira-bot/] and I help the community manage its development. I see this issues has been marked as Minor but is unassigned and neither itself nor its Sub-Tasks have been updated for 180 days. I have gone ahead and marked it "stale-minor". If this ticket is still Minor, please either assign yourself or give an update. Afterwards, please remove the label or in 7 days the issue will be deprioritized. > Approximate calculation of frequencies in data streams > -- > > Key: FLINK-2147 > URL: https://issues.apache.org/jira/browse/FLINK-2147 > Project: Flink > Issue Type: New Feature > Components: API / DataStream >Reporter: Gábor Gévay >Priority: Minor > Labels: approximate, auto-deprioritized-major, stale-minor, > statistics > > Count-Min sketch is a hashing-based algorithm for approximately keeping track > of the frequencies of elements in a data stream. It is described by Cormode > et al. in the following paper: > http://dimacs.rutgers.edu/~graham/pubs/papers/cmsoft.pdf > Note that this algorithm can be conveniently implemented in a distributed > way, as described in section 3.2 of the paper. > The paper > http://www.vldb.org/conf/2002/S10P03.pdf > also describes algorithms for approximately keeping track of frequencies, but > here the user can specify a threshold below which she is not interested in > the frequency of an element. The error-bounds are also different than the > Count-min sketch algorithm. -- This message was sent by Atlassian Jira (v8.20.1#820001)
[jira] [Updated] (FLINK-2147) Approximate calculation of frequencies in data streams
[ https://issues.apache.org/jira/browse/FLINK-2147?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Flink Jira Bot updated FLINK-2147: -- Labels: approximate auto-deprioritized-major statistics (was: approximate stale-major statistics) > Approximate calculation of frequencies in data streams > -- > > Key: FLINK-2147 > URL: https://issues.apache.org/jira/browse/FLINK-2147 > Project: Flink > Issue Type: New Feature > Components: API / DataStream >Reporter: Gábor Gévay >Priority: Major > Labels: approximate, auto-deprioritized-major, statistics > > Count-Min sketch is a hashing-based algorithm for approximately keeping track > of the frequencies of elements in a data stream. It is described by Cormode > et al. in the following paper: > http://dimacs.rutgers.edu/~graham/pubs/papers/cmsoft.pdf > Note that this algorithm can be conveniently implemented in a distributed > way, as described in section 3.2 of the paper. > The paper > http://www.vldb.org/conf/2002/S10P03.pdf > also describes algorithms for approximately keeping track of frequencies, but > here the user can specify a threshold below which she is not interested in > the frequency of an element. The error-bounds are also different than the > Count-min sketch algorithm. -- This message was sent by Atlassian Jira (v8.3.4#803005)
[jira] [Updated] (FLINK-2147) Approximate calculation of frequencies in data streams
[ https://issues.apache.org/jira/browse/FLINK-2147?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Flink Jira Bot updated FLINK-2147: -- Priority: Minor (was: Major) > Approximate calculation of frequencies in data streams > -- > > Key: FLINK-2147 > URL: https://issues.apache.org/jira/browse/FLINK-2147 > Project: Flink > Issue Type: New Feature > Components: API / DataStream >Reporter: Gábor Gévay >Priority: Minor > Labels: approximate, auto-deprioritized-major, statistics > > Count-Min sketch is a hashing-based algorithm for approximately keeping track > of the frequencies of elements in a data stream. It is described by Cormode > et al. in the following paper: > http://dimacs.rutgers.edu/~graham/pubs/papers/cmsoft.pdf > Note that this algorithm can be conveniently implemented in a distributed > way, as described in section 3.2 of the paper. > The paper > http://www.vldb.org/conf/2002/S10P03.pdf > also describes algorithms for approximately keeping track of frequencies, but > here the user can specify a threshold below which she is not interested in > the frequency of an element. The error-bounds are also different than the > Count-min sketch algorithm. -- This message was sent by Atlassian Jira (v8.3.4#803005)
[jira] [Updated] (FLINK-2147) Approximate calculation of frequencies in data streams
[ https://issues.apache.org/jira/browse/FLINK-2147?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Flink Jira Bot updated FLINK-2147: -- Labels: approximate stale-major statistics (was: approximate statistics) > Approximate calculation of frequencies in data streams > -- > > Key: FLINK-2147 > URL: https://issues.apache.org/jira/browse/FLINK-2147 > Project: Flink > Issue Type: New Feature > Components: API / DataStream >Reporter: Gábor Gévay >Priority: Major > Labels: approximate, stale-major, statistics > > Count-Min sketch is a hashing-based algorithm for approximately keeping track > of the frequencies of elements in a data stream. It is described by Cormode > et al. in the following paper: > http://dimacs.rutgers.edu/~graham/pubs/papers/cmsoft.pdf > Note that this algorithm can be conveniently implemented in a distributed > way, as described in section 3.2 of the paper. > The paper > http://www.vldb.org/conf/2002/S10P03.pdf > also describes algorithms for approximately keeping track of frequencies, but > here the user can specify a threshold below which she is not interested in > the frequency of an element. The error-bounds are also different than the > Count-min sketch algorithm. -- This message was sent by Atlassian Jira (v8.3.4#803005)
[jira] [Updated] (FLINK-2147) Approximate calculation of frequencies in data streams
[ https://issues.apache.org/jira/browse/FLINK-2147?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Aljoscha Krettek updated FLINK-2147: Component/s: (was: Streaming) DataStream API > Approximate calculation of frequencies in data streams > -- > > Key: FLINK-2147 > URL: https://issues.apache.org/jira/browse/FLINK-2147 > Project: Flink > Issue Type: New Feature > Components: DataStream API >Reporter: Gabor Gevay > Labels: approximate, statistics > > Count-Min sketch is a hashing-based algorithm for approximately keeping track > of the frequencies of elements in a data stream. It is described by Cormode > et al. in the following paper: > http://dimacs.rutgers.edu/~graham/pubs/papers/cmsoft.pdf > Note that this algorithm can be conveniently implemented in a distributed > way, as described in section 3.2 of the paper. > The paper > http://www.vldb.org/conf/2002/S10P03.pdf > also describes algorithms for approximately keeping track of frequencies, but > here the user can specify a threshold below which she is not interested in > the frequency of an element. The error-bounds are also different than the > Count-min sketch algorithm. -- This message was sent by Atlassian JIRA (v6.3.15#6346)
[jira] [Updated] (FLINK-2147) Approximate calculation of frequencies in data streams
[ https://issues.apache.org/jira/browse/FLINK-2147?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Gabor Gevay updated FLINK-2147: --- Labels: approximate statistics (was: statistics) > Approximate calculation of frequencies in data streams > -- > > Key: FLINK-2147 > URL: https://issues.apache.org/jira/browse/FLINK-2147 > Project: Flink > Issue Type: New Feature > Components: Streaming >Reporter: Gabor Gevay > Labels: approximate, statistics > > Count-Min sketch is a hashing-based algorithm for approximately keeping track > of the frequencies of elements in a data stream. It is described by Cormode > et al. in the following paper: > http://dimacs.rutgers.edu/~graham/pubs/papers/cmsoft.pdf > Note that this algorithm can be conveniently implemented in a distributed > way, as described in section 3.2 of the paper. > The paper > http://www.vldb.org/conf/2002/S10P03.pdf > also describes algorithms for approximately keeping track of frequencies, but > here the user can specify a threshold below which she is not interested in > the frequency of an element. The error-bounds are also different than the > Count-min sketch algorithm. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Updated] (FLINK-2147) Approximate calculation of frequencies in data streams
[ https://issues.apache.org/jira/browse/FLINK-2147?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Gabor Gevay updated FLINK-2147: --- Priority: Major (was: Minor) > Approximate calculation of frequencies in data streams > -- > > Key: FLINK-2147 > URL: https://issues.apache.org/jira/browse/FLINK-2147 > Project: Flink > Issue Type: New Feature > Components: Streaming >Reporter: Gabor Gevay > Labels: statistics > > Count-Min sketch is a hashing-based algorithm for approximately keeping track > of the frequencies of elements in a data stream. It is described by Cormode > et al. in the following paper: > http://dimacs.rutgers.edu/~graham/pubs/papers/cmsoft.pdf > Note that this algorithm can be conveniently implemented in a distributed > way, as described in section 3.2 of the paper. > The paper > http://www.vldb.org/conf/2002/S10P03.pdf > also describes algorithms for approximately keeping track of frequencies, but > here the user can specify a threshold below which she is not interested in > the frequency of an element. The error-bounds are also different than the > Count-min sketch algorithm. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Updated] (FLINK-2147) Approximate calculation of frequencies in data streams
[ https://issues.apache.org/jira/browse/FLINK-2147?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Gabor Gevay updated FLINK-2147: --- Issue Type: New Feature (was: Sub-task) Parent: (was: FLINK-2142) > Approximate calculation of frequencies in data streams > -- > > Key: FLINK-2147 > URL: https://issues.apache.org/jira/browse/FLINK-2147 > Project: Flink > Issue Type: New Feature > Components: Streaming >Reporter: Gabor Gevay >Priority: Minor > Labels: statistics > > Count-Min sketch is a hashing-based algorithm for approximately keeping track > of the frequencies of elements in a data stream. It is described by Cormode > et al. in the following paper: > http://dimacs.rutgers.edu/~graham/pubs/papers/cmsoft.pdf > Note that this algorithm can be conveniently implemented in a distributed > way, as described in section 3.2 of the paper. > The paper > http://www.vldb.org/conf/2002/S10P03.pdf > also describes algorithms for approximately keeping track of frequencies, but > here the user can specify a threshold below which she is not interested in > the frequency of an element. The error-bounds are also different than the > Count-min sketch algorithm. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Updated] (FLINK-2147) Approximate calculation of frequencies in data streams
[ https://issues.apache.org/jira/browse/FLINK-2147?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Gabor Gevay updated FLINK-2147: --- Labels: statistics (was: ) Approximate calculation of frequencies in data streams -- Key: FLINK-2147 URL: https://issues.apache.org/jira/browse/FLINK-2147 Project: Flink Issue Type: Sub-task Components: Streaming Reporter: Gabor Gevay Priority: Minor Labels: statistics Count-Min sketch is a hashing-based algorithm for approximately keeping track of the frequencies of elements in a data stream. It is described by Cormode et al. in the following paper: http://dimacs.rutgers.edu/~graham/pubs/papers/cmsoft.pdf Note that this algorithm can be conveniently implemented in a distributed way, as described in section 3.2 of the paper. The paper http://www.vldb.org/conf/2002/S10P03.pdf also describes algorithms for approximately keeping track of frequencies, but here the user can specify a threshold below which she is not interested in the frequency of an element. The error-bounds are also different than the Count-min sketch algorithm. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
