Taming Your Data With Elasticsearch - Madison PHP

Are you searching unstructured data or text fields? Do you need to aggregate and summarize your geo, financial, or other numeric data? Do you want to query your structured data in new and exciting ways? If so, Elasticsearch may be right for you. Let’s explore the many ways you can ask questions of your data and have it make sense to you and your users. We’ll sort through millions of rows in milliseconds and give you the tools to take your data analysis to the next level. You will learn how to use basic RESTful API calls to store, search, and aggregate your data.

Transcript

1. Taming Your Data with Elasticsearch
2. Hello! I Am Derek Binkley Senior Engineer with TurnTo Networks Volunteer with Community Justice @DerekB_WI binkleyd@yahoo.com
3. Customer Generated Content
4. Fast Searching Scalability Finding Value within a Sea of Data
5. What is it? open-source, RESTful, distributed search and analytics engine built on Apache Lucene Elasticsearch Tool for querying and exploring data Kibana
6. How is it stored? A grouping of JSON documents with similar structure. Index Defines what is contained in a document Mapping A JSON document stores each data element. Document
7. Storing Data
8. Store new document POST
9. Specify ID to update or insert PUT
10. Created automatically or manually Updated automatically Mapping
11. Mapping
12. Define empty index Setup document structure https:/ /www.elastic.co/guide/en/ elasticsearch/reference/current/indices- put-mapping.html Put Mapping
13. Storing Data with PHP
14. Guzzle converts array to JSON body Put Mapping
15. Guzzle converts array to JSON body Post
16. Update Data
17. Automatically assigned - POST Manually assigned - PUT ID
18. Replaces document if exists Adds new if not exists PUT DOC
19. Only updates named fields Update Fields
20. Replaces document if exists Adds new if not exists Script Update
21. Searching Data
22. Define query in JSON body match_all finds everything Query Keyword
23. Looking for best results Find a Match
24. Results are scored Find a Match
25. Results are scored Search Within Text
26. Results are scored Search Within Text
27. Damereau-Levenshtein Distance Fuzziness
28. more_like_this query Similar Documents
29. Paginating Data
30. Aggregating
31. Query unique results or keywords What’s In a Field
32. Query unique results or keywords that get sorted into “buckets” What’s In a Field
33. Calculate summary values such as avg Metrics
34. Calculate summary values such as avg Metrics
35. Group documents into buckets Buckets with Metrics
36. Group documents into buckets Buckets with Metrics
37. Geo Points
38. Find results with a distance of a point Distance Search
39. Filter by geo, aggregate by term Distance Aggregation
40. Filter by geo, aggregate by term Distance Aggregation
41. Complex mapping applications can be created by using four types of queries Uses GeoJSON to define shape GeoShape Define top_left and bottom_right Geo Bounding Box Geo searches Previous example Geo Distance Define points to create a polygon Geo Polygon
42. ANY QUESTIONS? You can find me at @DerekB_WI binkleyd@yahoo.com Thanks!
43. https://www.elastic.co/blog/found-elasticsearch-from-the-bottom-up https://en.wikipedia.org/wiki/Damerau-Levenshtein_distance https://lucene.apache.org/ https://www.elastic.co/guide/en/elasticsearch/painless/current/painless-getting-started.html http://geojson.org/ Resources