building)consistentand)highly)available)distributed ... ·...

Apache®, Apache Ignite, Ignite®, and the Apache Ignite logo are either registered trademarks or trademarks of the Apache So8ware Founda<on in the United States and/or other countries.

Valen<n Kulichenko GridGain Lead Architect Apache Ignite PMC

Building Consistent and Highly Available Distributed Systems with Apache IgniteTM and GridGain


Agenda •  What is Ignite and GridGain •  Ignite and CAP Theorem •  High Availability in Ignite

–  Cache Backups –  Persistence –  Data Center Replica<on –  Data Snapshots (+ Demo)

•  Q&A


What is Ignite?

•  A memory-‐centric data plaUorm

•  that is strongly consistent •  and highly available •  with powerful SQL, •  key-‐value and processing APIs


•  In-‐Memory Key-‐Value Store •  ACID Compliant •  Collocated Processing •  Persistence

–  Na<ve Ignite persistence –  Pluggable 3rd party persistence

• Usage –  Database Caching –  Web Session Clustering

Key-‐Value Data Grid


•  Both In-‐Memory and On-‐Disk •  Full SQL Support

–  SELECT, UPDATE, DELETE, INSERT •  Data Defini<on Language

–  Configure schema and caches

Distributed SQL Database


•  CAP –  Consistency (C) –  Availability (A) –  Network Par<<on Tolerance (P) –  Most of distributed systems are CP or AP –  Impossible: CAP

•  Ignite –  Strongly CP –  But s<ll highly available?

Ignite and CAP Theorem


Cache Backups: ParHHon vs. Replicated


Cache Backups and Network SegmentaHon

Rack 1

Switch

Node 1

Node 2

Node 3

Clients

Rack 2

Switch

Node 4

Node 5

Node 6

1

2

3

4

5

6

5

3

1

6

2

4

Lost partitions 1 and 3!


Cache Backups and Network SegmentaHon: SoluHon

•  Assign a^ribute to each node:

•  Implement backup filter:

<property name="userAttributes"> <map> <entry key="rack" value="rack-1"/> </map> </property>

public class RackFilter implements IgniteBiPredicate<ClusterNode, List<ClusterNode>> { @Override public boolean apply(ClusterNode candidate, List<ClusterNode> assigned) { String candidateRack = candidate.attribute("rack"); String primaryRack = assigned.get(0).attribute("rack"); return !Objects.equals(candidateRack, primaryRack); } }


Cache Backups and Network SegmentaHon: Solved!

Rack 1

Switch

Node 1

Node 2

Node 3

Clients

Rack 2

Switch

Node 4

Node 5

Node 6

1

2

3

4

5

6

5

4

6

3

1

2

No partitions lost!


Persistence

Ignite Persistent Store

•  Addi<onal Disk Tier •  SQL & key-‐value over both

memory and disk •  Memory warmup never

required •  Distributed disk storage •  Reads/writes are distributed

3rd Party Store

•  RDBMS, MongoDB, etc. •  Key-‐value over both memory

and disk •  Memory warmup might be

required (SQL usage) •  Single point of failure (RDBMS) •  Bo^leneck for writes (RDBMS)


Ignite Persistence Store: Per-‐Node Architecture


Ignite Persistence Store: Consistency and Durability

•  Write-‐Ahead Log (WAL) –  Append only file –  Propagates updates to disk –  Provides recovery mechanism

•  Checkpoin<ng –  Triggered periodically –  Copies actual data from RAM to disk –  Reduces WAL size


•  Mul<ple (up to 32) Data Centers •  Ac<ve-‐Ac<ve & Ac<ve-‐Passive •  Smart Conflict Resolu<on •  Durable Persistent Queues •  Automa<c Thro^ling

Data Center ReplicaHon

GridGain Enterprise Edition Only!


Data Snapshots •  Full snapshots

–  Full state –  May take long <me

•  Incremental snapshots –  Par<al state –  Only delta since last full snapshot

•  Scheduled snapshots •  Restore on different clusters •  Fully managed

GridGain Ultimate Edition Only!


ANY QUESTIONS? Thank you for joining us. Follow the conversa<on.

h^p://ignite.apache.org

#apacheignite

building)consistentand)highly)available)distributed ... ·...

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