A short intro about the Elasticsearch techonlogy for young programmers in Bucharest.

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!
Thursday, February 27, 14