SlideShare a Scribd company logo
Confidentia
l
Mao Ye
Big Data Platform at interest
1
Data Architecture
Design Choices for Hadoop Platform
Pinball for Workflow Management
Data Architecture
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
Pinterest Data Architecture
App
Pinterest Data Architecture
App
events
Kafka
Secor
Singer
Pinterest Data Architecture
App
events
Kafka
Secor
Singer
Pinterest Data Architecture
App
events
Kafka
Secor
Skyline
Pinball
Redshift
Pinalytics
Features
Qubole
(Hadoop)
Singer
Design Choices for Hadoop Platform
• Ephemeral clusters
• Access control layer
• Shared data store
• Easy deployment
Hadoop Platform Requirements
• Isolated multi-tenancy
• Elasticity
• Support multiple
clusters
Decoupling compute & storage
Hadoop Cluster 1
Transient
HDFS
Hadoop Cluster 2
Transient
HDFS
S3 Persistent
Store
Centralized Hive Metastore
Hive
Metastore
Pig
Cascading
Hive
HDFS/S3
DataMetadata
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
Executor Abstraction Layer
Hive
Metastore
HDFS/S3
Qubole
Managed
Hadoop
EMR
Executor
Pinball
Dev
Server
• 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
Confidentia
l
Pinball for Workflow Management
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
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
Confidentia
l
Pinball Design
Master
Worker
Scheduler
Command
Line Clients
UI
Confidentia
l
● Workflow
o A directed graph of
nodes called jobs
● Edge
o Run after
dependence
● Node
o Job is a node
Workflow Model
Confidentia
l
Job State
● Job state is captured in a token
● Tokens are named hierarchically
Master
Job Token
version: 123
name: /workflow/w1/job
owner: worker_0
expiration: 1234567
data: JobTemplate(....)
Confidentia
l
Job State Machine
RUNNABLE
RUNNINGWAITING
Confidentia
l
● Master keeps the state
● Workers claim and execute tasks
● Horizontally scalable
Master Worker Interaction
Worker Master Persistent Store
1: request 2: update
3: ack
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
Confidentia
l
Worker
Confidentia
l
Open Source
Git repo:
https://github.com/pinterest/pinball
Mailing list:
https://groups.google.com/forum/#!forum/
pinball-users
Confidentia
l
Thank You

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