Elasticsearch is a scalable full-text search engine that allows users to search content and metadata and perform analytics. It features complex query options, attribute and geo filtering, and built-in analytics and tag clouds. Elasticsearch is special because it is distributed, allowing easy clustering of data across multiple servers. It can also scale performance independently for indexing and searching, and handle complex queries on billions of documents even with just a few nodes. Elasticsearch also has an easy built-in backup solution.

1. Elasticsearch
Scalable Full-Text Search Engine
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2. Goals for this talk
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3. Outline
• What’s full text search and why do we use
it?
• What can you do with Elasticsearch?
• Why is Elasticsearch different?
• DEMO TIME!
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4. Text Search
do I really need to explain it?
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5. %LIKE%
• In the beginning there was:
SELECT * FROM tweets WHERE content
LIKE ‘%zuckerberg%’
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6. But that’s not what you usually search for!
• You want:
Search by author
Search by time
Search by sentiment
Search by location
Search by everything!
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7. That’s a lot of metadata!
• You can’t search through all that on the fly
if you want realtime results
• You need to index it first!
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8. Inverted Index
• Some documents:sells Facebook’ [Monday]
1: ‘Mark Zuckerberg
2: ‘Facebook buys WhatsApp’ [Tuesday]
3: ‘Mark’s Facebook buys Instagram’[Monday]
• Inverted index for them:{ 1, 2, 3}
Facebook:
Mark: {1, 3}
Instagram: {2}
WhatsApp: {2}
[Monday]: {1, 3}
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9. Ok, now that we have data, we also want some
numbers behind it!
• In our previous example:
• Facebook is mentioned 3 times
• There are 2 posts on [Monday]
• The most frequent words are
Facebook and Mark
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10. All 3 put together
Elasticsearch
=
Search(Content & Metadata) + Analytics
(oversimplified)
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11. Let’s look at some
search features of
Elasticsearch
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12. Features: Complex Queries
• Boolean Operators:
(apple OR pumpkin) AND pie
• Wildcards:
app*: apple, apples, appliance
appl?: apple, apply
• Fuzzy:
back~: back, pack, black, bank
• Ranged:
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13. Features: Complex Queries
• Attribute filtering:
apple AND pie AND location:california
• Range filtering:
apple AND published:[1393100055 TO 1393427055]
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14. Features:Geo Queries
Bounding Box Queries
Queries
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Distance Range

15. Feature: built in analytics
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16. Feature: Built in tagcloud
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17. What’s special about
Elasticsearch?
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18. Distributed
• Clustering data into multiple servers is easy
and abstracted away from the developer
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19. Performance/Scalability
• Add and take nodes on the fly without ever
stopping the search service
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20. Performance/Scalability
• Can scale independently both indexing and
searching
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21. Performance/Scalability
• With few nodes you can do complex
queries on billions of documents
• 3 nodes: 20 mil documents with 2 replicas
each
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22. Easy to back up
• Elasticsearch has a built in backup solution
so that you don’t have to worry about
implementing one
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23. Demo time!
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