Storm: Distributed and fault-tolerant realtime

computationFerran Galí i Reniu

@ferrangali

19/06/2014

Ferran Galí i Reniu

● UPC - FIB● Trovit

○ Hadoop○ Lucene/Solr○ Storm

Big Data

● Too much data○ Store○ Compute○ Analyse

● Distributed systems○ Provide horizontal scalability

● Hadoop

Distributed Systems

HDFS HDFS HDFS

File

● Hadoop

Distributed Systems

HDFS

MapReduce

HDFS

MapReduce

HDFS

MapReduce

File

Distributed Systems

● Hadoop○ Huge files○ Useful for batch○ High latency○ No real time

Storm

“Storm is a distributed realtime computation system. Storm provides a set of general primitives for doing realtime computation. Storm is simple, can be used with any programming language, is used by many companies, and is a lot of fun to use!”

http://storm.incubator.apache.org/

Storm

● Who’s using it?

● Tuple○ Ordered list of elements○ Any type

Storm

String Integer SerializedObject ...

Storm

● Stream○ Unbounded sequence of tuples

Tuple Tuple Tuple Tuple Tuple Tuple Tuple

Storm

● Spout○ Source of streams

○ From data sources: Queues, API...

Tuple Tuple Tuple Tuple Tuple

Storm

● Bolt○ Consumes streams○ Does some processing (transform, join,...)○ Emits streams

Tuple Tuple Tuple

TupleTuple

Tuple

Tuple Tuple Tuple

Storm

● Topology○ Graph of spouts & bolts○ Runs forever

Architecture

Nimbus

Zookeeper

Zookeeper

Zookeeper

Master

Worker

Worker

Coordinator

Supervisor

Slot

Slot

Slot

Slot

Supervisor

Slot

Slot

Slot

Slot

Architecture

Supervisor

Slot

Slot

Slot

SlotWorker process

Single JVM

Tasks - Threads

parallelism hint = 4

parallelism hint = 1

parallelism hint = 2

parallelism hint = 2

parallelism hint = 3

parallelism hint = 4

Supervisor

Slot

Slot

Slot

Slot

Supervisor

Slot

Slot

Slot

Slot

Worker processes = 8

parallelism hint = 4

parallelism hint = 1

parallelism hint = 2

parallelism hint = 2

parallelism hint = 3

parallelism hint = 4

Worker processes = 8

combined parallelism = 4 + 1 + 2 + 2 + 3 + 4 = 16

Tasks per worker = 16 / 8 = 2

Supervisor

Supervisor

Example: Word Count

line line line word word wordFile

FileSpout SplitterBolt CounterBoltparallelism hint = 2 parallelism hint = 3 parallelism hint = 2

SplitterBoltFileSpout

Example: Word Count

CounterBolt

Storm is a distributed realtime computation

system. Storm provides a set of general primitives

for doing realtime computation. Storm is

simple, can be used with any programming

language, is used by many companies, and is

a lot of fun to use!

SplitterBoltFileSpout

Example: Word Count

CounterBolt

Storm is a distributed

Storm is a distributed realtime computation

system. Storm provides a set of general primitives

for doing realtime computation. Storm is

simple, can be used with any programming

language, is used by many companies, and is

a lot of fun to use!

SplitterBoltFileSpout

Example: Word Count

CounterBolt

Storm is a distributed

Storm is a distributed realtime computation

system. Storm provides a set of general primitives

for doing realtime computation. Storm is

simple, can be used with any programming

language, is used by many companies, and is

a lot of fun to use!

realtime computationsystem. Storm provides a

SplitterBoltFileSpout

Example: Word Count

CounterBolt

Storm is a distributed

Storm is a distributed realtime computation

system. Storm provides a set of general primitives

for doing realtime computation. Storm is

simple, can be used with any programming

language, is used by many companies, and is

a lot of fun to use!

realtime computationsystem. Storm provides a

shuffle grouping

SplitterBoltFileSpout

Example: Word Count

CounterBolt

Storm is a distributed

Storm is a distributed realtime computation

system. Storm provides a set of general primitives

for doing realtime computation. Storm is

simple, can be used with any programming

language, is used by many companies, and is

a lot of fun to use!

realtime computationsystem. Storm provides a

Storm a

isdistributed

realtime

computationsystem

provides

Storm a

shuffle grouping

SplitterBoltFileSpout

Example: Word Count

CounterBolt

Storm is a distributed

Storm is a distributed realtime computation

system. Storm provides a set of general primitives

for doing realtime computation. Storm is

simple, can be used with any programming

language, is used by many companies, and is

a lot of fun to use!

realtime computationsystem. Storm provides a

Storm a

isdistributed

realtime

computationsystem

provides

Storm a

Storm

a

is

distributed

realtime

computation

system

provides

Storm

a

x1

x1

x1

x1

x1

x1

x1

x1

x1

x1

shuffle grouping

SplitterBoltFileSpout

Example: Word Count

CounterBolt

Storm is a distributed

Storm is a distributed realtime computation

system. Storm provides a set of general primitives

for doing realtime computation. Storm is

simple, can be used with any programming

language, is used by many companies, and is

a lot of fun to use!

realtime computationsystem. Storm provides a

shuffle grouping

ais

Storm distributed

provides a

Storm

is

distributed

realtime

computation

system

a

x2

x1

x1

x1

x2

x1

x1

x1

realtime

computation

provides

fields grouping

systemStorm

Groupings

● Shuffle grouping● Fields grouping● All grouping● Global grouping● Direct grouping● Local or shuffle grouping

Fault-tolerance

Nimbus

Zookeeper

Zookeeper

Zookeeper

Supervisor

Supervisor

● Worker dies○ Supervisor will restart it

● Worker dies too many times○ Nimbus will reassign it to another node

● Node dies○ Nimbus will reassign task to another node

● Nimbus is not a SPOF● Nimbus & Supervisors are fail-fast

Fault-tolerance

Guaranteeing message processing

● Through API○ ack○ fail

● Manual tuple replay○ e.g: Spout emits again message with specific id

Guaranteeing message processing

● When is a message “fully processed”?

● Solutions○ Transactional Topologies○ Trident framework

Storm is a distributed

Storm

is

distributed

a

Ok

Fail

Ok

Ok

Yet another example

tweet tweet tweet

wordword

word

TwitterSpout SplitterBolt

CounterBolt

CommitBolt

signalsignal

signal

DB

shuffle groupingfields grouping

all grouping

https://github.com/ferrangali/betabeers-storm

Batch + Real time

● Lambda architecture

Serving

Batch layer

● High latency● Reprocesses all data

New data

Batch + Real time

● Lambda architecture

Speed layer

Serving

Batch layer

● Low latency● Fast & incremental algorithms● Eventually overridden by batch layer

● High latency● Reprocesses all data

New data

Storm

● Who’s using it?

Trovit

● 40 countries● 5 verticals● Hundreds of millions of ads

Trovit

● Batch layer:○ MapReduce pipeline over HDFS

HDFS

Filter Enrich Dedup Index

kafka

xml

Trovit

● Speed layer○ Storm topology

adad

ad

adad

adrich ad rich ad rich ad

Feeds Spout

Kafka Spout

Processor Bolt Indexer Bolt

Group by index

Commit in batch every 5 minutes

kafka

xml

Trovit

HDFS

Filter Enrich Dedup Index

adad

ad

adad

adrichad richad richad

HBaseZookeeper

kafka

xml

Questions?Ferran Galí i Reniu

@ferrangali

19/06/2014