Mantis: Netflix’s Event Stream Processing System
Rx/reactive in style, autoscaling, support for queue/broker-based strong consistency as well as TCP-based lossy delivery
(tags: netflix rx reactive autoscaling mantis stream-processing)
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‘I now a man with a wooden leg named sea what was the name of the other leg SAND’
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Fergal Crehan’s new gig — good idea!
The Hit Team helps you fight back against leaked photos and videos, internet targeting and revenge porn.
(tags: revenge-porn revenge law privacy porn leaks photos videos images selfies)
F1: A Distributed SQL Database That Scales
Beyond the interesting-enough stuff about scalability in a distributed SQL store, there’s this really nifty point about avoiding the horrors of the SQL/ORM impedance mismatch:
At Google, Protocol Buffers are ubiquitous for data storage and interchange between applications. When we still had a MySQL schema, users often had to write tedious and error-prone transformations between database rows and in-memory data structures. Putting protocol buffers in the schema removes this impedance mismatch and gives users a universal data structure they can use both in the database and in application code…. Protocol Buffer columns are more natural and reduce semantic complexity for users, who can now read and write their logical business objects as atomic units, without having to think about materializing them using joins across several tables.
This is something that pretty much any store can already adopt. Go protobufs. (or Avro, etc.) Also, I find this really neat, and I hope this idea is implemented elsewhere soon: asynchronous schema updates:Schema changes are applied asynchronously on multiple F1 servers. Anomalies are prevented by the use of a schema leasing mechanism with support for only current and next schema versions; and by subdividing schema changes into multiple phases where consecutive pairs of changes are mutually compatible and cannot cause anomalies.