[jira] [Comment Edited] (SOLR-13047) Add facet2D Streaming Expression
[ https://issues.apache.org/jira/browse/SOLR-13047?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16863160#comment-16863160 ] Nazerke Seidan edited comment on SOLR-13047 at 6/13/19 2:56 PM: [~ctargett], closed the PR #659. was (Author: snazerke): [~ctargett], closed the PR #660. > Add facet2D Streaming Expression > > > Key: SOLR-13047 > URL: https://issues.apache.org/jira/browse/SOLR-13047 > Project: Solr > Issue Type: New Feature >Reporter: Joel Bernstein >Assignee: Joel Bernstein >Priority: Major > Fix For: 8.2 > > Time Spent: 1h > Remaining Estimate: 0h > > The current facet expression is a generic tool for creating multi-dimension > aggregations. The *facet2D* Streaming Expression has semantics specific for 2 > dimensional facets which are designed to be *pivoted* into a matrix and > operated on by *Math Expressions*. > facet2D will use the json facet API under the covers. > Proposed syntax: > {code:java} > facet2D(medrecords, q=*:*, x=diseases, y=symptoms, dimensions="300, 10", > count(*)){code} > The example above will return tuples containing the top 300 diseases and the > top ten symptoms for each disease. > Using math expression the tuples can be *pivoted* into a matrix where the > rows of the matrix are the diseases, the columns of the matrix are the > symptoms and the cells in the matrix contain the counts. This matrix can then > be *clustered* to find clusters of *diseases* that are correlated by > *symptoms*. > {code:java} > let(a=facet2D(medrecords, q=*:*, x=diseases, y=symptoms, dimensions="300, > 10", count(*)), > b=pivot(a, diseases, symptoms, count(*)), > c=kmeans(b, 10)){code} > > *Implementation Note:* > The implementation plan for this ticket is to create a new stream called > Facet2DStream. The FacetStream code is a good starting point for the new > implementation and can be adapted for the Facet2D parameters. Similar tests > to the FacetStream can be added to StreamExpressionTest > -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Commented] (SOLR-13047) Add facet2D Streaming Expression
[ https://issues.apache.org/jira/browse/SOLR-13047?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16863160#comment-16863160 ] Nazerke Seidan commented on SOLR-13047: --- [~ctargett], closed the PR #660. > Add facet2D Streaming Expression > > > Key: SOLR-13047 > URL: https://issues.apache.org/jira/browse/SOLR-13047 > Project: Solr > Issue Type: New Feature >Reporter: Joel Bernstein >Assignee: Joel Bernstein >Priority: Major > Fix For: 8.2 > > Time Spent: 1h > Remaining Estimate: 0h > > The current facet expression is a generic tool for creating multi-dimension > aggregations. The *facet2D* Streaming Expression has semantics specific for 2 > dimensional facets which are designed to be *pivoted* into a matrix and > operated on by *Math Expressions*. > facet2D will use the json facet API under the covers. > Proposed syntax: > {code:java} > facet2D(medrecords, q=*:*, x=diseases, y=symptoms, dimensions="300, 10", > count(*)){code} > The example above will return tuples containing the top 300 diseases and the > top ten symptoms for each disease. > Using math expression the tuples can be *pivoted* into a matrix where the > rows of the matrix are the diseases, the columns of the matrix are the > symptoms and the cells in the matrix contain the counts. This matrix can then > be *clustered* to find clusters of *diseases* that are correlated by > *symptoms*. > {code:java} > let(a=facet2D(medrecords, q=*:*, x=diseases, y=symptoms, dimensions="300, > 10", count(*)), > b=pivot(a, diseases, symptoms, count(*)), > c=kmeans(b, 10)){code} > > *Implementation Note:* > The implementation plan for this ticket is to create a new stream called > Facet2DStream. The FacetStream code is a good starting point for the new > implementation and can be adapted for the Facet2D parameters. Similar tests > to the FacetStream can be added to StreamExpressionTest > -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Comment Edited] (SOLR-13047) Add facet2D Streaming Expression
[ https://issues.apache.org/jira/browse/SOLR-13047?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16818793#comment-16818793 ] Nazerke Seidan edited comment on SOLR-13047 at 4/16/19 10:50 AM: - Regarding the implementation details, are the math expressions limited to metrics such as sum, count, max, min and avg? I came up with the following implementation ideas: This is a constructor how it looks like in this stream: facet2DStream(String collection, ModifiableSolrParams params, Bucket x, Bucket y, String dimensions, Metric metric). The basic idea is that first I will apply a count metric on the given buckets. Then I will internally sort the buckets in descending order. Then I will get the tuples while the x and y values are not equal in the dimensions. Any suggestions? was (Author: snazerke): Regarding the implementation details, are the math expressions limited to metrics such as sum, count, max, min and avg? > Add facet2D Streaming Expression > > > Key: SOLR-13047 > URL: https://issues.apache.org/jira/browse/SOLR-13047 > Project: Solr > Issue Type: New Feature > Security Level: Public(Default Security Level. Issues are Public) >Reporter: Joel Bernstein >Assignee: Joel Bernstein >Priority: Major > > The current facet expression is a generic tool for creating multi-dimension > aggregations. The *facet2D* Streaming Expression has semantics specific for 2 > dimensional facets which are designed to be *pivoted* into a matrix and > operated on by *Math Expressions*. > facet2D will use the json facet API under the covers. > Proposed syntax: > {code:java} > facet2D(medrecords, q=*:*, x=diseases, y=symptoms, dimensions="300, 10", > count(*)){code} > The example above will return tuples containing the top 300 diseases and the > top ten symptoms for each disease. > Using math expression the tuples can be *pivoted* into a matrix where the > rows of the matrix are the diseases, the columns of the matrix are the > symptoms and the cells in the matrix contain the counts. This matrix can then > be *clustered* to find clusters of *diseases* that are correlated by > *symptoms*. > {code:java} > let(a=facet2D(medrecords, q=*:*, x=diseases, y=symptoms, dimensions="300, > 10", count(*)), > b=pivot(a, diseases, symptoms, count(*)), > c=kmeans(b, 10)){code} > > *Implementation Note:* > The implementation plan for this ticket is to create a new stream called > Facet2DStream. The FacetStream code is a good starting point for the new > implementation and can be adapted for the Facet2D parameters. Similar tests > to the FacetStream can be added to StreamExpressionTest > -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Comment Edited] (SOLR-13047) Add facet2D Streaming Expression
[ https://issues.apache.org/jira/browse/SOLR-13047?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16818793#comment-16818793 ] Nazerke Seidan edited comment on SOLR-13047 at 4/16/19 9:00 AM: Regarding the implementation details, are the math expressions limited to metrics such as sum, count, max, min and avg? was (Author: snazerke): Regarding the math expressions, is it limited to metrics? > Add facet2D Streaming Expression > > > Key: SOLR-13047 > URL: https://issues.apache.org/jira/browse/SOLR-13047 > Project: Solr > Issue Type: New Feature > Security Level: Public(Default Security Level. Issues are Public) >Reporter: Joel Bernstein >Assignee: Joel Bernstein >Priority: Major > > The current facet expression is a generic tool for creating multi-dimension > aggregations. The *facet2D* Streaming Expression has semantics specific for 2 > dimensional facets which are designed to be *pivoted* into a matrix and > operated on by *Math Expressions*. > facet2D will use the json facet API under the covers. > Proposed syntax: > {code:java} > facet2D(medrecords, q=*:*, x=diseases, y=symptoms, dimensions="300, 10", > count(*)){code} > The example above will return tuples containing the top 300 diseases and the > top ten symptoms for each disease. > Using math expression the tuples can be *pivoted* into a matrix where the > rows of the matrix are the diseases, the columns of the matrix are the > symptoms and the cells in the matrix contain the counts. This matrix can then > be *clustered* to find clusters of *diseases* that are correlated by > *symptoms*. > {code:java} > let(a=facet2D(medrecords, q=*:*, x=diseases, y=symptoms, dimensions="300, > 10", count(*)), > b=pivot(a, diseases, symptoms, count(*)), > c=kmeans(b, 10)){code} > > *Implementation Note:* > The implementation plan for this ticket is to create a new stream called > Facet2DStream. The FacetStream code is a good starting point for the new > implementation and can be adapted for the Facet2D parameters. Similar tests > to the FacetStream can be added to StreamExpressionTest > -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Commented] (SOLR-13047) Add facet2D Streaming Expression
[ https://issues.apache.org/jira/browse/SOLR-13047?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16818793#comment-16818793 ] Nazerke Seidan commented on SOLR-13047: --- Regarding the math expressions, is it limited to metrics? > Add facet2D Streaming Expression > > > Key: SOLR-13047 > URL: https://issues.apache.org/jira/browse/SOLR-13047 > Project: Solr > Issue Type: New Feature > Security Level: Public(Default Security Level. Issues are Public) >Reporter: Joel Bernstein >Assignee: Joel Bernstein >Priority: Major > > The current facet expression is a generic tool for creating multi-dimension > aggregations. The *facet2D* Streaming Expression has semantics specific for 2 > dimensional facets which are designed to be *pivoted* into a matrix and > operated on by *Math Expressions*. > facet2D will use the json facet API under the covers. > Proposed syntax: > {code:java} > facet2D(medrecords, q=*:*, x=diseases, y=symptoms, dimensions="300, 10", > count(*)){code} > The example above will return tuples containing the top 300 diseases and the > top ten symptoms for each disease. > Using math expression the tuples can be *pivoted* into a matrix where the > rows of the matrix are the diseases, the columns of the matrix are the > symptoms and the cells in the matrix contain the counts. This matrix can then > be *clustered* to find clusters of *diseases* that are correlated by > *symptoms*. > {code:java} > let(a=facet2D(medrecords, q=*:*, x=diseases, y=symptoms, dimensions="300, > 10", count(*)), > b=pivot(a, diseases, symptoms, count(*)), > c=kmeans(b, 10)){code} > > *Implementation Note:* > The implementation plan for this ticket is to create a new stream called > Facet2DStream. The FacetStream code is a good starting point for the new > implementation and can be adapted for the Facet2D parameters. Similar tests > to the FacetStream can be added to StreamExpressionTest > -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Issue Comment Deleted] (SOLR-13047) Add facet2D Streaming Expression
[ https://issues.apache.org/jira/browse/SOLR-13047?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Nazerke Seidan updated SOLR-13047: -- Comment: was deleted (was: Regarding the implementation details, are the math expressions limited to metrics such as count(*) , sum(col), max(col), min(col) and avg(col)? Why do we need count? as a parameter in the facet2D? Obviously, we are returning 300 diseases containing 10 symptoms for each disease.) > Add facet2D Streaming Expression > > > Key: SOLR-13047 > URL: https://issues.apache.org/jira/browse/SOLR-13047 > Project: Solr > Issue Type: New Feature > Security Level: Public(Default Security Level. Issues are Public) >Reporter: Joel Bernstein >Assignee: Joel Bernstein >Priority: Major > > The current facet expression is a generic tool for creating multi-dimension > aggregations. The *facet2D* Streaming Expression has semantics specific for 2 > dimensional facets which are designed to be *pivoted* into a matrix and > operated on by *Math Expressions*. > facet2D will use the json facet API under the covers. > Proposed syntax: > {code:java} > facet2D(medrecords, q=*:*, x=diseases, y=symptoms, dimensions="300, 10", > count(*)){code} > The example above will return tuples containing the top 300 diseases and the > top ten symptoms for each disease. > Using math expression the tuples can be *pivoted* into a matrix where the > rows of the matrix are the diseases, the columns of the matrix are the > symptoms and the cells in the matrix contain the counts. This matrix can then > be *clustered* to find clusters of *diseases* that are correlated by > *symptoms*. > {code:java} > let(a=facet2D(medrecords, q=*:*, x=diseases, y=symptoms, dimensions="300, > 10", count(*)), > b=pivot(a, diseases, symptoms, count(*)), > c=kmeans(b, 10)){code} > > *Implementation Note:* > The implementation plan for this ticket is to create a new stream called > Facet2DStream. The FacetStream code is a good starting point for the new > implementation and can be adapted for the Facet2D parameters. Similar tests > to the FacetStream can be added to StreamExpressionTest > -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Comment Edited] (SOLR-13047) Add facet2D Streaming Expression
[ https://issues.apache.org/jira/browse/SOLR-13047?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16818790#comment-16818790 ] Nazerke Seidan edited comment on SOLR-13047 at 4/16/19 8:57 AM: Regarding the implementation details, are the math expressions limited to metrics such as count(*) , sum(col), max(col), min(col) and avg(col)? Why do we need count? as a parameter in the facet2D? Obviously, we are returning 300 diseases containing 10 symptoms for each disease. was (Author: snazerke): Regarding the implementation details, are the math expressions limited to metrics such as count(*), sum(col), max(col), min(col) and avg(col)? Why do we need count(*) as a parameter in the facet2D? Obviously, we are returning 300 diseases containing 10 symptoms for each disease. > Add facet2D Streaming Expression > > > Key: SOLR-13047 > URL: https://issues.apache.org/jira/browse/SOLR-13047 > Project: Solr > Issue Type: New Feature > Security Level: Public(Default Security Level. Issues are Public) >Reporter: Joel Bernstein >Assignee: Joel Bernstein >Priority: Major > > The current facet expression is a generic tool for creating multi-dimension > aggregations. The *facet2D* Streaming Expression has semantics specific for 2 > dimensional facets which are designed to be *pivoted* into a matrix and > operated on by *Math Expressions*. > facet2D will use the json facet API under the covers. > Proposed syntax: > {code:java} > facet2D(medrecords, q=*:*, x=diseases, y=symptoms, dimensions="300, 10", > count(*)){code} > The example above will return tuples containing the top 300 diseases and the > top ten symptoms for each disease. > Using math expression the tuples can be *pivoted* into a matrix where the > rows of the matrix are the diseases, the columns of the matrix are the > symptoms and the cells in the matrix contain the counts. This matrix can then > be *clustered* to find clusters of *diseases* that are correlated by > *symptoms*. > {code:java} > let(a=facet2D(medrecords, q=*:*, x=diseases, y=symptoms, dimensions="300, > 10", count(*)), > b=pivot(a, diseases, symptoms, count(*)), > c=kmeans(b, 10)){code} > > *Implementation Note:* > The implementation plan for this ticket is to create a new stream called > Facet2DStream. The FacetStream code is a good starting point for the new > implementation and can be adapted for the Facet2D parameters. Similar tests > to the FacetStream can be added to StreamExpressionTest > -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Commented] (SOLR-13047) Add facet2D Streaming Expression
[ https://issues.apache.org/jira/browse/SOLR-13047?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16818790#comment-16818790 ] Nazerke Seidan commented on SOLR-13047: --- Regarding the implementation details, are the math expressions limited to metrics such as count(*), sum(col), max(col), min(col) and avg(col)? Why do we need count(*) as a parameter in the facet2D? Obviously, we are returning 300 diseases containing 10 symptoms for each disease. > Add facet2D Streaming Expression > > > Key: SOLR-13047 > URL: https://issues.apache.org/jira/browse/SOLR-13047 > Project: Solr > Issue Type: New Feature > Security Level: Public(Default Security Level. Issues are Public) >Reporter: Joel Bernstein >Assignee: Joel Bernstein >Priority: Major > > The current facet expression is a generic tool for creating multi-dimension > aggregations. The *facet2D* Streaming Expression has semantics specific for 2 > dimensional facets which are designed to be *pivoted* into a matrix and > operated on by *Math Expressions*. > facet2D will use the json facet API under the covers. > Proposed syntax: > {code:java} > facet2D(medrecords, q=*:*, x=diseases, y=symptoms, dimensions="300, 10", > count(*)){code} > The example above will return tuples containing the top 300 diseases and the > top ten symptoms for each disease. > Using math expression the tuples can be *pivoted* into a matrix where the > rows of the matrix are the diseases, the columns of the matrix are the > symptoms and the cells in the matrix contain the counts. This matrix can then > be *clustered* to find clusters of *diseases* that are correlated by > *symptoms*. > {code:java} > let(a=facet2D(medrecords, q=*:*, x=diseases, y=symptoms, dimensions="300, > 10", count(*)), > b=pivot(a, diseases, symptoms, count(*)), > c=kmeans(b, 10)){code} > > *Implementation Note:* > The implementation plan for this ticket is to create a new stream called > Facet2DStream. The FacetStream code is a good starting point for the new > implementation and can be adapted for the Facet2D parameters. Similar tests > to the FacetStream can be added to StreamExpressionTest > -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Comment Edited] (SOLR-13047) Add facet2D Streaming Expression
[ https://issues.apache.org/jira/browse/SOLR-13047?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16818790#comment-16818790 ] Nazerke Seidan edited comment on SOLR-13047 at 4/16/19 8:56 AM: Regarding the implementation details, are the math expressions limited to metrics such as count(*), sum(col), max(col), min(col) and avg(col)? Why do we need count(*) as a parameter in the facet2D? Obviously, we are returning 300 diseases containing 10 symptoms for each disease. was (Author: snazerke): Regarding the implementation details, are the math expressions limited to metrics such as count(*), sum(col), max(col), min(col) and avg(col)? Why do we need count(*) as a parameter in the facet2D? Obviously, we are returning 300 diseases containing 10 symptoms for each disease. > Add facet2D Streaming Expression > > > Key: SOLR-13047 > URL: https://issues.apache.org/jira/browse/SOLR-13047 > Project: Solr > Issue Type: New Feature > Security Level: Public(Default Security Level. Issues are Public) >Reporter: Joel Bernstein >Assignee: Joel Bernstein >Priority: Major > > The current facet expression is a generic tool for creating multi-dimension > aggregations. The *facet2D* Streaming Expression has semantics specific for 2 > dimensional facets which are designed to be *pivoted* into a matrix and > operated on by *Math Expressions*. > facet2D will use the json facet API under the covers. > Proposed syntax: > {code:java} > facet2D(medrecords, q=*:*, x=diseases, y=symptoms, dimensions="300, 10", > count(*)){code} > The example above will return tuples containing the top 300 diseases and the > top ten symptoms for each disease. > Using math expression the tuples can be *pivoted* into a matrix where the > rows of the matrix are the diseases, the columns of the matrix are the > symptoms and the cells in the matrix contain the counts. This matrix can then > be *clustered* to find clusters of *diseases* that are correlated by > *symptoms*. > {code:java} > let(a=facet2D(medrecords, q=*:*, x=diseases, y=symptoms, dimensions="300, > 10", count(*)), > b=pivot(a, diseases, symptoms, count(*)), > c=kmeans(b, 10)){code} > > *Implementation Note:* > The implementation plan for this ticket is to create a new stream called > Facet2DStream. The FacetStream code is a good starting point for the new > implementation and can be adapted for the Facet2D parameters. Similar tests > to the FacetStream can be added to StreamExpressionTest > -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Commented] (SOLR-13391) Add variance and standard deviation stream evaluators
[ https://issues.apache.org/jira/browse/SOLR-13391?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16814745#comment-16814745 ] Nazerke Seidan commented on SOLR-13391: --- [~joel.bernstein], I have ready code on this to the pull request. What I used were StatUtils.variance(data) and Math.sqrt(StatUtils.variance(data)) instead of StatUtils.mean(data) in the MeanEvaluator.java. > Add variance and standard deviation stream evaluators > - > > Key: SOLR-13391 > URL: https://issues.apache.org/jira/browse/SOLR-13391 > Project: Solr > Issue Type: Improvement > Security Level: Public(Default Security Level. Issues are Public) > Components: streaming expressions >Reporter: Nazerke Seidan >Priority: Minor > Labels: pull-request-available > > It seems variance and standard deviation stream evaluators are not supported > by any of the solr version. For example, > let(echo="m,v,sd", arr=array(1,3,3), m=mean(a), v=var(a), > sd=stddev(a)) > So far, only the mean function is implemented. I think it is useful to have > var and sttdev functions separately as a stream evaluator. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Created] (SOLR-13391) Add variance and standard deviation stream evaluators
Nazerke Seidan created SOLR-13391: - Summary: Add variance and standard deviation stream evaluators Key: SOLR-13391 URL: https://issues.apache.org/jira/browse/SOLR-13391 Project: Solr Issue Type: Improvement Security Level: Public (Default Security Level. Issues are Public) Components: streaming expressions Reporter: Nazerke Seidan It seems variance and standard deviation stream evaluators are not supported by any of the solr version. For example, let(echo="m,v,sd", arr=array(1,3,3), m=mean(a), v=var(a), sd=stddev(a)) So far, only the mean function is implemented. I think it is useful to have var and sttdev functions separately as a stream evaluator. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Commented] (SOLR-7229) Allow DIH to handle attachments as separate documents
[ https://issues.apache.org/jira/browse/SOLR-7229?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16783547#comment-16783547 ] Nazerke Seidan commented on SOLR-7229: -- Hi Tim, I was wondering whether this project is still open or not? I would like to participate in GSoC'19 by contributing to solr community. > Allow DIH to handle attachments as separate documents > - > > Key: SOLR-7229 > URL: https://issues.apache.org/jira/browse/SOLR-7229 > Project: Solr > Issue Type: Improvement >Reporter: Tim Allison >Assignee: Alexandre Rafalovitch >Priority: Minor > Labels: gsoc2017 > > With Tika 1.7's RecursiveParserWrapper, it is possible to maintain metadata > of individual attachments/embedded documents. Tika's default handling was to > maintain the metadata of the container document and concatenate the contents > of all embedded files. With SOLR-7189, we added the legacy behavior. > It might be handy, for example, to be able to send an MSG file through DIH > and treat the container email as well each attachment as separate (child?) > documents, or send a zip of jpeg files and correctly index the geo locations > for each image file. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Commented] (SOLR-10329) Rebuild Solr examples
[ https://issues.apache.org/jira/browse/SOLR-10329?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16783533#comment-16783533 ] Nazerke Seidan commented on SOLR-10329: --- Hi Alexandre, I was wondering whether this project is still open or not? I would like to participate in GSoC'19 by contributing to solr community. Many thanks! > Rebuild Solr examples > - > > Key: SOLR-10329 > URL: https://issues.apache.org/jira/browse/SOLR-10329 > Project: Solr > Issue Type: Wish > Components: examples >Reporter: Alexandre Rafalovitch >Priority: Major > Labels: gsoc2017 > > Apache Solr ships with a number of examples. They evolved from a kitchen sync > example and are rather large. When new Solr features are added, they are > often shoehorned into the most appropriate example and sometimes are not > represented at all. > Often, for new users, it is hard to tell what part of example is relevant, > what part is default and what part is demonstrating something completely > different. > It would take significant (and very appreciated) effort to review all the > examples and rebuild them to provide clean way to showcase best practices > around base and most recent features. > Specific issues are around kitchen sync vs. minimal examples, better approach > to "schemaless" mode and creating examples and datasets that allow to create > both "hello world" and more-advanced tutorials. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org