DRUPAL AND ELASTICSEARCH
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The document provides an overview of Elasticsearch, a powerful, open-source search and analytics engine. It outlines its features, such as RESTful API, scalability, and ease of use, along with various commands for indexing, retrieving, updating, and deleting data. Additionally, it discusses querying capabilities, pagination, and the integration of Elasticsearch with Drupal via available modules like search API and elasticsearch_connector.
![and Facets
"aggregations" : {
"<aggregation_name>" : {
"<aggregation_type>" : {
<aggregation_body>
}
[,"meta" : { [<meta_data_body>] } ]?
[,"aggregations" : { [<sub_aggregation>]+ } ]?
}
[,"<aggregation_name_2>" : { ... } ]*
}](https://image.slidesharecdn.com/drupalcamp2019-190530152429/85/DRUPAL-AND-ELASTICSEARCH-45-320.jpg)
DRUPAL AND ELASTICSEARCH
- 1. Drupal And ElasticsearchAlex Goja
- 2. Flexible and powerful open source, distributed real-time search and analytics engine for the cloud Elasticsearch
- 3. Flexible and powerful open source, distributed real-time search and analytics engine for the cloud Elasticsearch RESTful API on top of Lucene library
- 5. Why use Elasticsearch? ● RESTful API ● Open Source ● JSON over HTTP ● based on Lucene ● distributed ● highly available ● schema free ● massively scalable
- 7. How to use it?
- 8. How to use it? > curl -XGET localhost:9200/?pretty
- 9. How to use it? > curl -XGET localhost:9200/?pretty { "ok" : true, "status" : 200, "name" : "Infinity", "version" : { "number" : "0.90.1", "snapshot_build" : false, "lucene_version" : "4.3" }, "tagline" : "You Know, for Search" }
- 10. How to use it? > curl -XGET localhost:9200/?pretty action
- 11. How to use it? > curl -XGET localhost:9200/?pretty node + port
- 12. How to use it? > curl -XGET localhost:9200/?pretty path
- 13. How to use it? > curl -XGET localhost:9200/?pretty query string
- 14. Let's index some data
- 15. Let's index some data > PUT /index/type/id Where? It's very similar to database in SQL
- 16. Let's index some data > PUT /index/type/id What? Table Content type, Entity type, any kind of type you decide
- 17. Let's index some data > PUT /index/type/id Which? Node ID, Entity ID, any kind of serial ID
- 18. Let's index some data > PUT /mysite/node/1 { "nid": "1", "status": "1", "title": "Hello elasticsearch", "body": "First elasticsearch document" }
- 19. Let's index some data > PUT /mysite/node/1 -d { "nid": "1", "status": "1", "title": "Hello elasticsearch", "body": "First elasticsearch document" } { "ok":true, "_index":"mysite", "_type":"node", "_id":"1", "_version":1 }
- 20. Let's GET some data
- 21. Let's GET some data > GET /mysite/node/1 { "_index" : "mysite", "_type" : "node", "_id" : "1", "_version" : 1, "exists" : true, "_source" : { "nid":"1", "status":"1", "title":"Hello elasticsearch”, "body":"First elasticsearch document" } }
- 22. Let's GET some data Get specific fields > GET /mysite/node/1?fields=title,body Get source only > GET /mysite/node/1/_source
- 23. Let's UPDATE some data > PUT /mysite/node/1 { “status":"0" }
- 24. Let's UPDATE some data > PUT /mysite/node/1 { "status":"0" } { "ok":true, "_index":"mysite", "_type":"node", "_id":"1", "_version":2 }
- 26. Let's DELETE some data > DELETE /mysite/node/1
- 27. Let's DELETE some data > DELETE /mysite/node/1 { "ok":true, "found":true, "_index":"mysite", "_type":"node", "_id":"1", “_version":3 }
- 29. Let's SEARCH for something > GET /_search { "took" : 32, "timed_out" : false, "_shards" : { "total" : 20, "successful" : 20, "failed" : 0 }, "hits" : { results... } }
- 30. Let's SEARCH in multiple indices and types
- 31. Let's SEARCH in multiple indices and types > GET /index/_search > GET /index1,index2/_search > GET /index/type/_search > GET /myapp_*/type, entity_*/_search
- 33. Let's PAGINATE results > GET /_search?size=10&from=20 size = results per page from = starting from
- 35. Let's search oldschool > GET /_search?q=title:elasticsearch > GET /_search?q=nid:60
- 36. Query DSL style
- 37. Query DSL style > GET /_search?size=10&from=20 { "query": { “match": "awesome" } }
- 38. Query DSL style > GET /_search?size=10&from=20 { "query": { "field" : { "title" : { “query" : "+awesome -poor", "boost" : 2.0, } } } }
- 40. Queries & Filters full text search exact match relevance score show or hide heavy lightning fast not cacheable cacheable
- 42. Combine Filters & Queries { "query": { "filtered": { "query": { "match": { "title": "awesome" } }, "filter": { "term": { "type": "article" } } } } } > GET /_search
- 43. Sorting
- 44. Sorting { "query": { "filtered": { "query": { “match": { "title": "awesome" } }, "filter": { "term": { "type": "article" } } } } "sort": {"date":"desc"} } > GET /_search
- 45. and Facets "aggregations" : { "<aggregation_name>" : { "<aggregation_type>" : { <aggregation_body> } [,"meta" : { [<meta_data_body>] } ]? [,"aggregations" : { [<sub_aggregation>]+ } ]? } [,"<aggregation_name_2>" : { ... } ]* }
- 46. and Facets > GET /_search { "aggregations": { "home_team": { "terms": { "field": “field_home_team" } } } }
- 47. and Facets > GET /_search { "aggregations": { "home_team": { "terms": { "field": “field_home_team" } } } } Give your facet a name
- 48. and Facets > GET /_search { "aggregations": { "home_team": { "terms": { "field": “field_home_team" } } } } Your facet filter can be: ● Terms ● Range ● Histogram ● Date Histogram ● Filter ● Query ● Statistical ● Terms Stats ● Geo Distance ● Cardinality ● Nested
- 49. and Facets "aggregations" : { "home_team" : { "_type" : "terms", "missing" : 203, "total" : 100, "other" : 42, "terms" : [ { "term" : "hou", "count" : 8 }, { "term" : "sln", "count" : 6 }, ...
- 50. STOP! I want this in Drupal
- 51. STOP! I want this in Drupal Available modules: Search API + elasticsearch_connector
- 52. Let the Search be with you