nosql rollercoaster

A NoSQL Rollercoaster

Saturday, November 6, 2010

IMSThe Hierarchical

Database

(1966)

Vern WattsSaturday, November 6, 2010

“A Relational Model for Large

Shared Databanks”

(1970)

Ted CoddSaturday, November 6, 2010

“"SEQUEL: A Structured

English Query Language"

Don Chamberlin & Ray Boyce

(1974)

Don ChamberlinSaturday, November 6, 2010

(late 1970’s)

Jim GraySaturday, November 6, 2010

“NoSQL” coined

(1998)

Carlo StrozziSaturday, November 6, 2010

“NoSQL” Reintroduced(2008)

Eric Evans

select fun, profit from real_world where relational=false?

“In striving to make every user happy, a technology an actually leave the majority

unhappy.”

“Every good idea is generalized to its level of

inapplicability.”

(Peter Principle)

Internet Scale

• Massive data collections

• Huge number of requests

• Coming from geographic areas across the globe

• 24/7

Total Cost of Ownership

• The price of a license

• The price of support

• The price of hardware

Availability

Data Models

Column Oriented

key namedcolumn

namedcolumn

Column Family ≈ Table

Empty cells are cheap (sparse

table)

Can grow “indefinitely”

Schemaless No secundary

indexes

Column Oriented + Super Columns

key namedcolumn

namedcolumn

Super Columns

Key Value Store

•Schemaless•Versioning

10110110

Graph Database

SPARQL?

Document Store

Improved Indexing

<persons><person><name>Wilfred</name><surname>Springer</person>…</persons>

[{ "Name" : "Wilfred", "Surname" : "Springer"}, …]

Serverside Processing

Challenges

CAP Theorem

Eric Brewer

Availability Consistency

PartitionTolerance

Pick two

ConsistencyConsistency

Strong Consistency

Weak Consistency

Eventual Consistency Other

Causal Consistency

Read-your-writes

ConsistencySession

ConsistencyMonotonic Read

ConsistencyMonotonic Write

Consistency

Strong Consistency

0 value = "foo"

value = "bar"

value = "bar" value = "bar"

value = "bar"

After the update, any subsequent access will return the updated value.

Weak Consistency

1 value = "bar"

value = "bar" /"foo"

value = "bar" / "foo"

0 value = "foo"

The system does not guarantee that at any given point in the future subsequent access will return the updated value

Eventual Consistency

If no updates are made to the object, eventually all accesses will return the last updated value.

1 value = "bar"

value = "bar" value = "bar"

value = "bar"

0 value = "foo"

t ≥ 1

Session Consistency

Within the “session”, the system guarantees read-your-writes consistency

2 value = "foo"

Session 1

Session 2

1 value = "bar"

0 value = "foo"

2 value = "bar"

Partition Tolerance

Awrites new value

replicates new value

reads new value

Partition Tolerance

Awrites new value

replicates new value

reads new value

Partition Tolerance

Awrites new value

fails to replicate

new value

reads old value

Partition Tolerance

failing attempt to write a new

fails to replicate

new value

Byzantine Failures

Faults that might occur in a

distributed system

•Lying

•Fabrication of messages

•Collisions

•Selective non-participation

Byzantine Generals Problem

Solution Strategies

Strong Consistency

Παξοί

Leader Proposer

Acceptor Learner

Four Roles

Paxos in a Nutshell

RequestPropose

Promise

AcceptAcceptedResponse

Processors combine various

Consensus based on

majority vote

Paxos guarantees progress for 2F + 1

processors in face of failure of F processors

“Either Paxos, Paxos with

cruft, or broken”

Mike Burrows

(Google Chubby)

Partitioning2

Consistent HashingKey KA

High Availability

ReplicationA

N = 4R = 2

Replication Factor

N = 4R = 2

Reconciliation during reads

Reconciliation

Handling Temporary

Failures

ProblemReconcilation

Alice Ben CathyDave

Wednesday?

Thursday

Tuesday

What's it gonna be?

Tuesday ThursdayX? ? ?

Vector Clocksdate = Wednesdayvclock = Alice:1

date = Tuesdayvclock = Alice:1, Ben:1

date = Tuesdayvclock = Alice:1, Ben:1, Dave:1

date = Tuesdayvclock = Alice:1, Cathy:1

date = Thursdayvclock = Alice:1, Ben:1, Cathy:1, Dave:2

Conflict Resolution

date = Tuesdayvclock = Alice:1, Ben:1, Dave:1

date = Thursdayvclock = Alice:1, Ben:1, Cathy:1, Dave:2

Recovering from permanent

failures

What if nodes die permantly?A

Merkle Trees

Enough is enough!!!

Conclusions

Scale!!!

Conclusions

Scale!!!No free ride

Conclusions

You gain some

Conclusions

You gain some

You lose some

Conclusions

You gain some

You lose someChoice

Conclusions

You gain some

You lose someChoice

Control

Conclusions

You gain some

You lose someChoice

ControlTake control

Conclusions

You gain some

You lose someChoice

ControlTake control

Understand your options

Conclusions

You gain some

You lose someChoice

ControlTake control

Fun!!!

Conclusions

You gain some

You lose someChoice

ControlTake control

Fun!!!

Changes your way of thinking

Conclusions

You gain some

You lose someChoice

ControlTake control

Fun!!!

Changes your way of thinking

No SQL!!!

wilfredspringer@gmail.com

• Basically Available

• Soft State

• Eventually Consistent

nosql rollercoaster

bar value

bar foo value

updated value

old value

causal consistency

column column family

super columns key named

column super columns

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