DynamoDB at HasOffers

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Amazon Web Services

How HasOffers uses DynamoDB

Tecnologia

• Attribution for web & mobile marketing
• Tons of data
• Ad-hoc analysis
• Near real-time

DynamoDB at HasOffers
18 months in production
207 billion items
87 TB of data

Use Cases
Tracking sessions
Deduplication
Attribution

Use Case: Tracking Sessions
Session
Data
671c6a9a-bed0-4cec-a465-613cca8c9832
• Impression
• Click

Use Case: Tracking Sessions
• Ideal for NoSQL
• KV lookups
• Scalability
• Availability

Use Case: Event Deduplication
671c6a9a-bed0-4cec-a465-613cca8c9832
ebe0efef-aa71-471c-b3f8-7b66b458bd79
ebe0efef-aa71-471c-b3f8-7b66b458bd79
d149e52c-d2b3-49bc-b6af-f304b5fab57f
DEDUPE!
(Idempotency)

Use Case: Event Deduplication
Hash uuid
Range <none>
Write capacity = X, Read capacity = 1
Conditional puts

$Use Case: Event Deduplication def is_duplicate( dynamo_tbl, uuid ): row_data = {‘host’: socket.gethostname(), ‘created’: int(time.time())} row = dynamo_tbl.new_item( hash_key=uuid, attrs=row_data ) DEDUPE! try: row.put( expected_value={‘host’: False} ) except DynamoDBConditionalCheckFailedError: return True # not a duplicate return False$

Use Case: Event Deduplication
• Real-time dedupe
• Conditional put
• Writes only; no read
• Extra debug info
{uuid: d149e52c-d2b3-49bc-b6af-f304b5fab57f,
host: server03.hasoffers.com,
created: 1398884990}
DEDUPE!

Cluster Resizing
• Upsize and downsize trivial in DynamoDB
• Infrequent on own cluster = limits operational experience

Cluster Software Updates
0.7 1.0
• Production depends on NoSQL solution
being available.
• Software version updates somewhere
between nail-biting and terrifying

DynamoDB Capacity
Per table R/W capacity
Capacity units
Exceed = throttling

DynamoDB Throttling
CloudWatch = 5 minutes
DynamoDB = 1 second

DynamoDB Throttling
• Double capacity on table
• Root cause from log analysis
– capacity usage
– key hot-spotting
• Fix root cause
• Reduce capacity on table

Closing Thoughts
• Compelling offering
• Simple operations
• Avoid hammer syndrome
• Very happy

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DynamoDB at HasOffers

1. DynamoDB at HasOffers

2. • Attribution for web & mobile marketing • Tons of data • Ad-hoc analysis • Near real-time

3. DynamoDB at HasOffers 18 months in production 207 billion items 87 TB of data

4. Use Cases Tracking sessions Deduplication Attribution

5. Tracking Sessions

6. Use Case: Tracking Sessions Session Data 671c6a9a-bed0-4cec-a465-613cca8c9832 • Impression • Click

7. Use Case: Tracking Sessions • Ideal for NoSQL • KV lookups • Scalability • Availability

8. Deduplication

9. Use Case: Event Deduplication 671c6a9a-bed0-4cec-a465-613cca8c9832 ebe0efef-aa71-471c-b3f8-7b66b458bd79 ebe0efef-aa71-471c-b3f8-7b66b458bd79 d149e52c-d2b3-49bc-b6af-f304b5fab57f DEDUPE! (Idempotency)

10. Use Case: Event Deduplication Hash uuid Range <none> Write capacity = X, Read capacity = 1 Conditional puts

11. Use Case: Event Deduplication def is_duplicate( dynamo_tbl, uuid ): row_data = {‘host’: socket.gethostname(), ‘created’: int(time.time())} row = dynamo_tbl.new_item( hash_key=uuid, attrs=row_data ) DEDUPE! try: row.put( expected_value={‘host’: False} ) except DynamoDBConditionalCheckFailedError: return True # not a duplicate return False

12. Use Case: Event Deduplication • Real-time dedupe • Conditional put • Writes only; no read • Extra debug info {uuid: d149e52c-d2b3-49bc-b6af-f304b5fab57f, host: server03.hasoffers.com, created: 1398884990} DEDUPE!

13. Why NoSQL SaaS?

14. Cluster Resizing • Upsize and downsize trivial in DynamoDB • Infrequent on own cluster = limits operational experience

15. Cluster Software Updates 0.7 1.0 • Production depends on NoSQL solution being available. • Software version updates somewhere between nail-biting and terrifying

16. Dynamo Operations

17. DynamoDB Capacity Per table R/W capacity Capacity units Exceed = throttling

18. DynamoDB Throttling CloudWatch = 5 minutes DynamoDB = 1 second

19. DynamoDB Throttling • Double capacity on table • Root cause from log analysis – capacity usage – key hot-spotting • Fix root cause • Reduce capacity on table

20. Closing Thoughts

21. Closing Thoughts • Compelling offering • Simple operations • Avoid hammer syndrome • Very happy

22. Thank you! niek@hasoffers.com

DynamoDB at HasOffers

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