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TechTalk #13 Grokking: Scaling and supercharging your online business models with Elasticsearch

TechTalk #13 Grokking: Scaling and supercharging your online business models with Elasticsearch

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Scaling and supercharging your online business models with Elasticsearch - Tri Tran (8Bit Rockstars)

Scaling and supercharging your online business models with Elasticsearch - Tri Tran (8Bit Rockstars)

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TechTalk #13 Grokking: Scaling and supercharging your online business models with Elasticsearch

  1. 1. • • • •
  2. 2. WILL • • • •
  3. 3. WON’T • • •
  4. 4. From: ttgtmedia.com • Large joins taking up memory • Working size exceeds the hardware limits • Full text search & NLP • Write-write conflicts • Database Replication • Full page cache
  5. 5. From: Google
  6. 6. • Shard? What is it? • Primary shard vs. Replica shard • Shard Overallocation
  7. 7. “ ” Elasticsearch provides the ability to subdivide your index into multiple pieces called shards. Each shard is in itself a fully- functional and independent "index" that can be hosted on any node in the cluster. • •
  8. 8. P1 R1 R2 • Can be stored on any node in a cluster • Independent Index • Distributed • Parallelize operations • A copy of primary shard • In case failover • Never resides on a same node as the original shard • Scaling search volume
  9. 9. https://www.youtube.com/watch?v=WLiVjAELUaU By Scott Davis
  10. 10. • Preventing to spend expensive SQL queries to a relational database with several joins and conditions. • Or using Elasticsearch as a primary data storage
  11. 11. From Spryker.com
  12. 12. From ONGR.io
  13. 13. From ONGR.io
  14. 14. • Normal Load Condition (0-5 clients per 5 minutes | 1 dyno) • Peak Load Condition (0-100 clients per 5 minutes | 1 dyno) • Extra Scaling Up Load Condition (0-600 clients per 5 minutes | 10 dyno)
  15. 15. www.8bitrockr.com Project Manager Senior Front-end Developer Senior PHP Developer 8Bit Rockstars Co., LTD. L08 – R01, Vincom Center 72 Le Thanh Ton, Ben Nghe, District 1, HCMC, VN

Editor's Notes

  • An index can potentially store a large amount of data that can exceed the hardware limits of a single node. For example, a single index of a billion documents taking up 1TB of disk space may not fit on the disk of a single node or may be too slow to serve search requests from a single node alone.
  • https://www.youtube.com/watch?v=WLiVjAELUaU

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