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Scalable eCommerce Platform Solutions
Scalable eCommerce Platform Solutions
In-Memory Data Grids Essentials. Oracle Coherence
Vladimir Kondraschenko
Max Myslyvtsev
Scalable eCommerce Platform Solutions
About me
Vladimir Kondraschenko
• Lead Java engineer
• More than 10 years of hands on experience in
– software design and coding
– technical leadership
– development management
vkondraschenko@griddynamics.com
Scalable eCommerce Platform Solutions
Agenda
• Preconditions of using IMDG
• Architecture overview
– topology
– distributed cache layer
– local cache layer
• Cache operations
• Persistence integration
• Tips
Scalable eCommerce Platform Solutions
Different Solutions
Coherence
Scalable eCommerce Platform Solutions
Preconditions of Using IMDG
• Big amounts of data (10-100 GB)
• Low latency
• High availability
• Distributed calculations
Scalable eCommerce Platform Solutions
Transport
Local Data
Architecture Layers
Transport
Local Data
Transport
Local Data
Shared Data
Scalable eCommerce Platform SolutionsScalable eCommerce Platform Solutions
Transport Layer
Discovery and communication
Scalable eCommerce Platform Solutions
IMDG Topology
Scalable eCommerce Platform Solutions
Discovery
• Multicast
• Well-known address
Scalable eCommerce Platform Solutions
Discovery
• Multicast
• Well-known address
New
Scalable eCommerce Platform Solutions
Discovery
• Multicast
• Well-known address
WKA
WKA
New
Scalable eCommerce Platform Solutions
Communication
• Custom protocols over TCP or UDP
• Senior node
• Heartbeats
– Cluster heartbeats
– Node heartbeats
Senior
Scalable eCommerce Platform Solutions
Communication
• Custom protocols over TCP or UDP
• Senior node
• Heartbeats
– Cluster heartbeats
– Node heartbeats
Senior
Scalable eCommerce Platform Solutions
Communication
• Custom protocols over TCP or UDP
• Senior node
• Heartbeats
– Cluster heartbeats
– Node heartbeats
Senior
Scalable eCommerce Platform Solutions
Node Departure
• TCP Ring
• IP monitor
• Timeout
Scalable eCommerce Platform Solutions
Node Departure
• TCP Ring
• IP monitor
• Timeouts
Scalable eCommerce Platform Solutions
Node Departure
• TCP Ring
• IP monitor
• Timeouts
Box1: IP 177.230.14.5
IP ping
Scalable eCommerce Platform Solutions
Node Departure
• TCP Ring
• IP monitor
• Timeout
Scalable eCommerce Platform SolutionsScalable eCommerce Platform Solutions
Shared Data Layer
Cluster-wide data
Scalable eCommerce Platform Solutions
Distributed Cache
Cluster
Client Node
Cache Interface
Storage Node
Data Storage
Cache Interface
Scalable eCommerce Platform Solutions
Cache Topology
• Replicated
Storage 1
A
D
B
E
C
F
Storage 2
A
D
B
E
C
F
Storage 3
A
D
B
E
C
F
Storage 1
A
D
B
E
Storage 2
C
A
D
F
Storage 3
E
B
F
C
• Partitioned
Scalable eCommerce Platform Solutions
Storage 3
Repartitioning
Storage 1
A
D
B
E
Storage 3
E
B
F
CE
Storage 2
C
A
D
FF
FCEB
Scalable eCommerce Platform Solutions
CAP Theorem
C
A
P
Coherence Coherence
Scalable eCommerce Platform SolutionsScalable eCommerce Platform Solutions
Get/Put/Remove, Query, Invocation, Map-Reduce
Cache operations
Scalable eCommerce Platform Solutions
Key hashing
Cache Operations: Put/Get
Storage 1 Storage 2
Client
Primary A
A B C D E F
• Client knows responsible storage
– Key hash is used to find it
• Automatic backups
Backup A
Backup F Primary F
Scalable eCommerce Platform Solutions
Storage 2Storage 2Storage 1
Cache Operations: Query
• Broadcast request
– Unless Query is Key-Associated
• All entries are evaluated
– Unless Indexes are used
field1=10 or field2>70field1=10 and key=A
key:
field1:
field2:
D
70
80
key:
field1:
field2:
C
50
60
key:
field1:
field2:
B
30
40
key:
field1:
field2:
D
70
80
key:
field1:
field2:
C
50
60
key:
field1:
field2:
B
30
40
key:
field1:
field2:
A
10
20
Scalable eCommerce Platform Solutions
Cache Operations: Invocation/Entry Processor
• Task is serialized and distributed
– May contain additional data
• Configurable execution scope
– Specific nodes
– All nodes
– Nodes bound to data
Node 1 Node 2
Task Task
Client
Task
Scalable eCommerce Platform Solutions
• Data-bound mapping
– By keys
– By Query
• Parallel execution
Storage 2Storage 1
key:
field1:
field2:
A
10
20
key:
field1:
field2:
B
30
40
key:
field1:
field2:
C
50
60
key:
field1:
field2:
D
70
80
Cache Operations: Map-Reduce
sum(field2) where field1>20
40 60 80
180
key:
field1:
field2:
A
10
20
140
Scalable eCommerce Platform SolutionsScalable eCommerce Platform Solutions
Persistence integration
Scalable eCommerce Platform Solutions
Synchronous Persistence Integration
• Read-through
• Write-through
StorageClient Durable
Storage
Data Grid
Client Durable
Storage
Data Grid
Storage
Scalable eCommerce Platform Solutions
• Refresh-ahead
• Write-behind
Asynchronous Persistence Integration
Storage QueueClient Durable
Storage
Data Grid
Storage QueueClient Durable
Storage
Data Grid
Scalable eCommerce Platform SolutionsScalable eCommerce Platform Solutions
Local Data Layer
Node-specific data
Scalable eCommerce Platform Solutions
Storage Storage
Node
Near Caching
• Local access by primary key
• Lazy population
• Invalidation
– On entry change
– By timeout
Near Cache
Distributed Cache
A
A B
Scalable eCommerce Platform Solutions
Continuous Caching
• Local access by any Query
• Eager population
• Near real-time data
Storage Storage
Node
Continuous Cache
Distributed Cache
A B
A B
Scalable eCommerce Platform SolutionsScalable eCommerce Platform Solutions
Tips
Using Oracle Coherence in practice
Scalable eCommerce Platform Solutions
Before integrating Oracle Coherence
• Do I really need IMDG or just a cache?
• How large my cluster should be?
• How much heap memory should be
configured for each node?
• What GC configuration to use?
• Do I have a relevant environment
to test my application?
Scalable eCommerce Platform Solutions
Memory usage
Limit cache size
• By binary size (per node)
• By number of objects in cache (per node)
Estimate cache object memory consumption
• Use BinaryMemoryCalculator
• Remember about backup copies
• Cache listeners (near cache, custom)
Scalable eCommerce Platform Solutions
Investigation & troubleshooting
• Coherence Management Framework (JMX)
– view cluster and nodes settings
– list caches (front and back) on each node
– view cache dynamic metrics
• Coherence command-line tool
– manage cache services
– manipulate cache data
• Profiling and heap analysis
– analyze heap dump
– analyze GC logs
Scalable eCommerce Platform Solutions
Scalable eCommerce Platform Solutions
Thank you!
Questions & Answers
Scalable eCommerce Platform Solutions
References
• Workshop
– https://github.com/mmyslyvtsev/imdg-workshop
• Coherence Knowledge Base
– http://coherence.oracle.com
• Developers Guide
– http://docs.oracle.com/cd/E18686_01/coh.37/e18677/toc.htm
• Book
– http://www.amazon.com/Oracle-Coherence-3-5-Aleksandar-
Seovic/dp/1847196128

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In-Memory Data Grids Essentials. Oracle Coherence

  • 1. Scalable eCommerce Platform Solutions Scalable eCommerce Platform Solutions In-Memory Data Grids Essentials. Oracle Coherence Vladimir Kondraschenko Max Myslyvtsev
  • 2. Scalable eCommerce Platform Solutions About me Vladimir Kondraschenko • Lead Java engineer • More than 10 years of hands on experience in – software design and coding – technical leadership – development management vkondraschenko@griddynamics.com
  • 3. Scalable eCommerce Platform Solutions Agenda • Preconditions of using IMDG • Architecture overview – topology – distributed cache layer – local cache layer • Cache operations • Persistence integration • Tips
  • 4. Scalable eCommerce Platform Solutions Different Solutions Coherence
  • 5. Scalable eCommerce Platform Solutions Preconditions of Using IMDG • Big amounts of data (10-100 GB) • Low latency • High availability • Distributed calculations
  • 6. Scalable eCommerce Platform Solutions Transport Local Data Architecture Layers Transport Local Data Transport Local Data Shared Data
  • 7. Scalable eCommerce Platform SolutionsScalable eCommerce Platform Solutions Transport Layer Discovery and communication
  • 8. Scalable eCommerce Platform Solutions IMDG Topology
  • 9. Scalable eCommerce Platform Solutions Discovery • Multicast • Well-known address
  • 10. Scalable eCommerce Platform Solutions Discovery • Multicast • Well-known address New
  • 11. Scalable eCommerce Platform Solutions Discovery • Multicast • Well-known address WKA WKA New
  • 12. Scalable eCommerce Platform Solutions Communication • Custom protocols over TCP or UDP • Senior node • Heartbeats – Cluster heartbeats – Node heartbeats Senior
  • 13. Scalable eCommerce Platform Solutions Communication • Custom protocols over TCP or UDP • Senior node • Heartbeats – Cluster heartbeats – Node heartbeats Senior
  • 14. Scalable eCommerce Platform Solutions Communication • Custom protocols over TCP or UDP • Senior node • Heartbeats – Cluster heartbeats – Node heartbeats Senior
  • 15. Scalable eCommerce Platform Solutions Node Departure • TCP Ring • IP monitor • Timeout
  • 16. Scalable eCommerce Platform Solutions Node Departure • TCP Ring • IP monitor • Timeouts
  • 17. Scalable eCommerce Platform Solutions Node Departure • TCP Ring • IP monitor • Timeouts Box1: IP 177.230.14.5 IP ping
  • 18. Scalable eCommerce Platform Solutions Node Departure • TCP Ring • IP monitor • Timeout
  • 19. Scalable eCommerce Platform SolutionsScalable eCommerce Platform Solutions Shared Data Layer Cluster-wide data
  • 20. Scalable eCommerce Platform Solutions Distributed Cache Cluster Client Node Cache Interface Storage Node Data Storage Cache Interface
  • 21. Scalable eCommerce Platform Solutions Cache Topology • Replicated Storage 1 A D B E C F Storage 2 A D B E C F Storage 3 A D B E C F Storage 1 A D B E Storage 2 C A D F Storage 3 E B F C • Partitioned
  • 22. Scalable eCommerce Platform Solutions Storage 3 Repartitioning Storage 1 A D B E Storage 3 E B F CE Storage 2 C A D FF FCEB
  • 23. Scalable eCommerce Platform Solutions CAP Theorem C A P Coherence Coherence
  • 24. Scalable eCommerce Platform SolutionsScalable eCommerce Platform Solutions Get/Put/Remove, Query, Invocation, Map-Reduce Cache operations
  • 25. Scalable eCommerce Platform Solutions Key hashing Cache Operations: Put/Get Storage 1 Storage 2 Client Primary A A B C D E F • Client knows responsible storage – Key hash is used to find it • Automatic backups Backup A Backup F Primary F
  • 26. Scalable eCommerce Platform Solutions Storage 2Storage 2Storage 1 Cache Operations: Query • Broadcast request – Unless Query is Key-Associated • All entries are evaluated – Unless Indexes are used field1=10 or field2>70field1=10 and key=A key: field1: field2: D 70 80 key: field1: field2: C 50 60 key: field1: field2: B 30 40 key: field1: field2: D 70 80 key: field1: field2: C 50 60 key: field1: field2: B 30 40 key: field1: field2: A 10 20
  • 27. Scalable eCommerce Platform Solutions Cache Operations: Invocation/Entry Processor • Task is serialized and distributed – May contain additional data • Configurable execution scope – Specific nodes – All nodes – Nodes bound to data Node 1 Node 2 Task Task Client Task
  • 28. Scalable eCommerce Platform Solutions • Data-bound mapping – By keys – By Query • Parallel execution Storage 2Storage 1 key: field1: field2: A 10 20 key: field1: field2: B 30 40 key: field1: field2: C 50 60 key: field1: field2: D 70 80 Cache Operations: Map-Reduce sum(field2) where field1>20 40 60 80 180 key: field1: field2: A 10 20 140
  • 29. Scalable eCommerce Platform SolutionsScalable eCommerce Platform Solutions Persistence integration
  • 30. Scalable eCommerce Platform Solutions Synchronous Persistence Integration • Read-through • Write-through StorageClient Durable Storage Data Grid Client Durable Storage Data Grid Storage
  • 31. Scalable eCommerce Platform Solutions • Refresh-ahead • Write-behind Asynchronous Persistence Integration Storage QueueClient Durable Storage Data Grid Storage QueueClient Durable Storage Data Grid
  • 32. Scalable eCommerce Platform SolutionsScalable eCommerce Platform Solutions Local Data Layer Node-specific data
  • 33. Scalable eCommerce Platform Solutions Storage Storage Node Near Caching • Local access by primary key • Lazy population • Invalidation – On entry change – By timeout Near Cache Distributed Cache A A B
  • 34. Scalable eCommerce Platform Solutions Continuous Caching • Local access by any Query • Eager population • Near real-time data Storage Storage Node Continuous Cache Distributed Cache A B A B
  • 35. Scalable eCommerce Platform SolutionsScalable eCommerce Platform Solutions Tips Using Oracle Coherence in practice
  • 36. Scalable eCommerce Platform Solutions Before integrating Oracle Coherence • Do I really need IMDG or just a cache? • How large my cluster should be? • How much heap memory should be configured for each node? • What GC configuration to use? • Do I have a relevant environment to test my application?
  • 37. Scalable eCommerce Platform Solutions Memory usage Limit cache size • By binary size (per node) • By number of objects in cache (per node) Estimate cache object memory consumption • Use BinaryMemoryCalculator • Remember about backup copies • Cache listeners (near cache, custom)
  • 38. Scalable eCommerce Platform Solutions Investigation & troubleshooting • Coherence Management Framework (JMX) – view cluster and nodes settings – list caches (front and back) on each node – view cache dynamic metrics • Coherence command-line tool – manage cache services – manipulate cache data • Profiling and heap analysis – analyze heap dump – analyze GC logs
  • 39. Scalable eCommerce Platform Solutions Scalable eCommerce Platform Solutions Thank you! Questions & Answers
  • 40. Scalable eCommerce Platform Solutions References • Workshop – https://github.com/mmyslyvtsev/imdg-workshop • Coherence Knowledge Base – http://coherence.oracle.com • Developers Guide – http://docs.oracle.com/cd/E18686_01/coh.37/e18677/toc.htm • Book – http://www.amazon.com/Oracle-Coherence-3-5-Aleksandar- Seovic/dp/1847196128

Editor's Notes

  1. Macys: сотни тысяч продуктов Кохеренс
  2. Macys: сотни тысяч продуктов Кохеренс
  3. кох – ведущий, широкий функционал, широко применяется, я его знаю
  4. Говорить план след слайдов
  5. DHT
  6. Showcase node leave Reference to real data amount:
  7. IMDG -> Coh CA – one node leave AP – brain split
  8. Filter-Map-Reduce
  9. Write-behind batching didn’t work in 3.5