Big Data Platform at Pinterest
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This document discusses Pinterest's data architecture and use of Pinball for workflow management. Pinterest processes 3 petabytes of data daily from their 60 billion pins and 1 billion boards across a 2000 node Hadoop cluster. They use Kafka, Secor and Singer for ingesting event data. Pinball is used for workflow management to handle their scale of hundreds of workflows, thousands of jobs and 500+ jobs in some workflows. Pinball provides simple abstractions, extensibility, reliability, debuggability and horizontal scalability for workflow execution.
Big Data Platform at Pinterest
- 1. Confidentia l Mao Ye Big Data Platform at interest 1
- 2. Data Architecture Design Choices for Hadoop Platform Pinball for Workflow Management
- 4. Data at Pinterest • 60 Billion Pins • 1 Billion boards • 100M MAU • 60 PB of data on S3 • 3 PB processed every day • 2000 node Hadoop cluster • 250 engineers
- 9. Design Choices for Hadoop Platform
- 10. • Ephemeral clusters • Access control layer • Shared data store • Easy deployment Hadoop Platform Requirements • Isolated multi-tenancy • Elasticity • Support multiple clusters
- 11. Decoupling compute & storage Hadoop Cluster 1 Transient HDFS Hadoop Cluster 2 Transient HDFS S3 Persistent Store
- 13. Multi-layered Packaging Mapreduce Jobs Hadoop Jars/Libs Job/User level Configs Software Packages/Libs Configs (OS/Hadoop) Misc Sys Admin OS Bootstrap Script Core SW Runtime Staging (on S3) Automated Configuration (Masterless Puppet) Baked AMI
- 15. • API for simplified executor abstraction • Advanced support for spot instances • Baked AMI customization Why Qubole? • Hadoop & Spark as managed services • Tight integration with Hive • Graceful cluster scaling
- 16. Confidentia l Pinball for Workflow Management
- 17. Confidentia l ● Scale: o 60 Billion Pins o Hundreds of workflows o Thousands of jobs o 500+ jobs in a workflow o 3 petabytes processed daily ● Support: o Hadoop, Cascading, Hive, Spark … Scale of Processing job workflow
- 18. Confidentia l Why Pinball? ● Requirements o Simple abstractions o Extensible in future o Reliable stateless computing o Easy to debug o Scales horizontally o Can be upgraded w/o aborting workflows o Rich features like auto-retries, per-job emails, overrun policies… ● Options o Apache Oozie, Azkaban, Luigi
- 20. Confidentia l â—Ź Workflow o A directed graph of nodes called jobs â—Ź Edge o Run after dependence â—Ź Node o Job is a node Workflow Model
- 21. Confidentia l Job State â—Ź Job state is captured in a token â—Ź Tokens are named hierarchically Master Job Token version: 123 name: /workflow/w1/job owner: worker_0 expiration: 1234567 data: JobTemplate(....)
- 23. Confidentia l â—Ź Master keeps the state â—Ź Workers claim and execute tasks â—Ź Horizontally scalable Master Worker Interaction Worker Master Persistent Store 1: request 2: update 3: ack
- 24. Confidentia l Master ● Entire state is kept in memory ● Each state update is synchronously persisted before master replies to client ● Master runs on a single thread – no concurrency issues
- 26. Confidentia l Open Source Git repo: https://github.com/pinterest/pinball Mailing list: https://groups.google.com/forum/#!forum/ pinball-users