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Real Time Data in
Superset
ARUP MALAKAR / 2018-07-17 / AMALAKAR@LYFT.COM
Use Cases
● Real time operational insight
○ Supply / Demand
○ App Open / Ride Requested / Rides in progress
● Service Diagnosis/debugging
○ HTTP access logs (aka envoy access logs)
○ Logging Summary
Earlier
Now
Architecture Choices
● Kinesis
○ Existing infrastructure for batch pipeline
● Flink
○ Scalable/performant distributed stream processor
○ SQL & Stream apis
● Druid
○ Scalable in-memory columnar database
○ Support for geospatial data
○ Extensible
○ Native integration with superset
Flink Streaming SQL
● Familiarity with SQL
● Powerful semantics for data manipulation
● Streaming and batch mode
UDFs
● Geohash
● Geo region extraction
● URL cardinality reduction/normalization
○ /users/d9cca721a735d/location -> /users/{hash}/location
○ /v1//api// -> /v1/api
● User agent parsing
○ OS name / version
○ App Name / version
SQL
Superset
Thank you!

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Superset druid realtime

  • 1. Real Time Data in Superset ARUP MALAKAR / 2018-07-17 / AMALAKAR@LYFT.COM
  • 2. Use Cases ● Real time operational insight ○ Supply / Demand ○ App Open / Ride Requested / Rides in progress ● Service Diagnosis/debugging ○ HTTP access logs (aka envoy access logs) ○ Logging Summary
  • 4. Now
  • 5. Architecture Choices ● Kinesis ○ Existing infrastructure for batch pipeline ● Flink ○ Scalable/performant distributed stream processor ○ SQL & Stream apis ● Druid ○ Scalable in-memory columnar database ○ Support for geospatial data ○ Extensible ○ Native integration with superset
  • 6. Flink Streaming SQL ● Familiarity with SQL ● Powerful semantics for data manipulation ● Streaming and batch mode
  • 7. UDFs ● Geohash ● Geo region extraction ● URL cardinality reduction/normalization ○ /users/d9cca721a735d/location -> /users/{hash}/location ○ /v1//api// -> /v1/api ● User agent parsing ○ OS name / version ○ App Name / version
  • 8. SQL