Download as PDF, PPTX
![Adding a widget life cycle
Query part 1
facet.range={!ex=bytes}bytes&f.bytes.facet.range.start=0&f.bytes.facet.range.end=9000000&
f.bytes.facet.range.gap=900000&f.bytes.facet.mincount=0&f.bytes.facet.limit=10
Query Part 2
q=Chrome&fq={!tag=bytes}bytes:[900000+TO+1800000]
Augment Solr response
{ !
'facet_counts':{ !
'facet_ranges':{ !
'bytes':{ !
'start':10000,!
'counts':[ !
'900000',!
3423,!
'1800000',!
339,!
! ! ...!
]!
}!
}!
}!
{!
...,!
'normalized_facets':[ !
{ !
'extraSeries':[ !
!
],!
'label':'bytes',!
'field':'bytes',!
'counts':[ !
{ !
'from’:'900000',!
'to':'1800000',!
'selected':True,!
'value':3423,!
'field’:'bytes',!
'exclude':False!
}!
], ...!
}!
}!
}!](https://image.slidesharecdn.com/lw14revolutionromain-141113145620-conversion-gate02/75/Interactively-Search-and-Visualize-Your-Big-Data-14-2048.jpg)
![JSON to Widget
{ !
"field":"rate_code",!
"counts":[ !
{ !
"count":97797,!
"exclude":true,!
"selected":false,!
"value":"1",!
"cat":"rate_code"!
} ...!
{ !
"field":"medallion",!
"counts":[ !
{ !
"count":159,!
"exclude":true,!
"selected":false,!
"value":"6CA28FC49A4C49A9A96",!
"cat":"medallion"!
} ….!
{ !
"extraSeries":[ !
!
],!
"label":"trip_time_in_secs",!
"field":"trip_time_in_secs",!
"counts":[ !
{ !
"from":"0",!
"to":"10",!
"selected":false,!
"value":527,!
"field":"trip_time_in_secs",!
"exclude":true!
} ...!
{ !
"field":"passenger_count",!
"counts":[ !
{ !
"count":74766,!
"exclude":true,!
"selected":false,!
"value":"1",!
"cat":"passenger_count"!
} ...!](https://image.slidesharecdn.com/lw14revolutionromain-141113145620-conversion-gate02/75/Interactively-Search-and-Visualize-Your-Big-Data-15-2048.jpg)
![Demo
Index and Visualize Taxi data
http://chriswhong.com/open-data/foil_nyc_taxi/
https://archive.org/details/nycTaxiTripData2013 [torrent better]](https://image.slidesharecdn.com/lw14revolutionromain-141113145620-conversion-gate02/75/Interactively-Search-and-Visualize-Your-Big-Data-18-2048.jpg)
Uploaded bygethue
Interactively Search and Visualize Your Big Data
The document outlines goals for enhancing user interaction with Solr and Hadoop through a web application, focusing on a user-friendly interface for data visualization and querying. It discusses various features like drag-and-drop dashboards, widget life cycles, and adding configurable components to the search application. Additional topics include enterprise features such as security, indexing capabilities, and future development plans for improved functionality.
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Interactively Search and Visualize Your Big Data
- 2. Interactively search and visualize your data Romain Rigaux
- 3. Goals Hue: makeSolr / Hadoop easier to use + Build a Web app Quickly explore data … with Solr
- 4. Architecture “Just aview” on top of the standard Solr API REST
- 5.
- 6.
- 7. Architecture: Next! Lotof learning, UX Boost needed Simple, don’t know it is Solr
- 8.
- 9.
- 10. Architecture REST AJAX /select /admin/collections /get /luke... /add_widget /zoom_in /select_facet /select_range... www…. Templates + JS Model
- 11. Architecture: UI forFacets Layout Collection Query All the 2D positioning (cell ids), visual, drag&drop Dashboard, fields, template, widgets (ids) Search terms, selected facets (q, fqs)
- 12. Adding a widgetlife cycle Load the initial page Edit mode and Drag&Drop /solr/zookeeper/clusterstate.json /solr/admin/luke… /get_collection
- 13. Adding a widgetlife cycle Select the field Guess ranges (number or dates) Rounding (number or dates) /solr/select?stats=true /new_facet
- 14. Adding a widgetlife cycle Query part 1 facet.range={!ex=bytes}bytes&f.bytes.facet.range.start=0&f.bytes.facet.range.end=9000000& f.bytes.facet.range.gap=900000&f.bytes.facet.mincount=0&f.bytes.facet.limit=10 Query Part 2 q=Chrome&fq={!tag=bytes}bytes:[900000+TO+1800000] Augment Solr response { ! 'facet_counts':{ ! 'facet_ranges':{ ! 'bytes':{ ! 'start':10000,! 'counts':[ ! '900000',! 3423,! '1800000',! 339,! ! ! ...! ]! }! }! }! {! ...,! 'normalized_facets':[ ! { ! 'extraSeries':[ ! ! ],! 'label':'bytes',! 'field':'bytes',! 'counts':[ ! { ! 'from’:'900000',! 'to':'1800000',! 'selected':True,! 'value':3423,! 'field’:'bytes',! 'exclude':False! }! ], ...! }! }! }!
- 15. JSON to Widget { ! "field":"rate_code",! "counts":[ ! { ! "count":97797,! "exclude":true,! "selected":false,! "value":"1",! "cat":"rate_code"! } ...! { ! "field":"medallion",! "counts":[ ! { ! "count":159,! "exclude":true,! "selected":false,! "value":"6CA28FC49A4C49A9A96",! "cat":"medallion"! } ….! { ! "extraSeries":[ ! ! ],! "label":"trip_time_in_secs",! "field":"trip_time_in_secs",! "counts":[ ! { ! "from":"0",! "to":"10",! "selected":false,! "value":527,! "field":"trip_time_in_secs",! "exclude":true! } ...! { ! "field":"passenger_count",! "counts":[ ! { ! "count":74766,! "exclude":true,! "selected":false,! "value":"1",! "cat":"passenger_count"! } ...!
- 16.
- 17. Enterprise features -Access to Search App configurable, LDAP/SAML auths - Share by link - Solr Cloud (or non Cloud) - Proxy user /solr/jobs_demo/select?user.name=hue&doAs=romain&q= - Security Kerberos - Sentry Collection level, Solr calls like /admin, /query, Solr UI, ZooKeeper
- 18. Demo Index andVisualize Taxi data http://chriswhong.com/open-data/foil_nyc_taxi/ https://archive.org/details/nycTaxiTripData2013 [torrent better]
- 19.
- 20. What’s next? -Map Pivot Facets - Autocomplete - Analytics range facets - Easier Indexing - … ?
- 21. Thank you! http://gethue.com/blog/search https://github.com/cloudera/hue