3. Tonight
3
• Membase Overview
• Use Cases and Customer Examples
• Zynga and Membase
• Membase Architecture
• Demo!
• Developing with Membase
• A Glimpse into the Future
5. Membase is a distributed database
5
Membase Servers
In the data center
Web application server
Application user
On the administrator console
Web application serverWeb application server
6. Five minutes or less to a working
cluster
• Downloads for Linux and Windows
• Start with a single node
• One button press joins nodes to a cluster
Easy to develop against
• Just SET and GET – no schema required
• Drop it in. 10,000+ existing applications
already “speak membase” (via memcached)
• Practically every language and application
framework is supported, out of the box
Easy to manage
• One-click failover and cluster rebalancing
• Graphical and programmatic interfaces
• Configurable alerting
Membase is Simple, Fast, Elastic
6
7. Membase is Simple, Fast, Elastic
7
Predictable
• “Never keep an application waiting”
• Quasi-deterministic latency and throughput
Low latency
• Built-in Memcached technology
High throughput
• Multi-threaded
• Low lock contention
• Asynchronous wherever possible
• Automatic write de-duplication
8. Membase is Simple, Fast, Elastic
8
Zero-downtime elasticity
• Spread I/O and data across commodity
servers (or VMs)
• Consistent performance with linear cost
• Dynamic rebalancing of a live cluster
All nodes are created equal
• No special case nodes
• Any node can replace any other node, online
• Clone to grow
Extensible
• Filtered TAP interface provides hook points
for external systems (e.g. full-text search,
backup, warehouse)
• Data bucket – engine API for specialized
container types
9. Built-in Memcached Caching Layer
9
Memcached
Membase Database
Membase Cache
Membase Database
Memcached Mode Membase Mode
Fact: Membase development team has also contributed over
half of the code to the Memcached project.
15. Clustering
• Underlying cluster
functionality based on
erlang OTP
• Have a custom, vector
clock based way of storing
and propagating...
– Cluster topology
– vBucket mapping
• Collect statistics from many
nodes of the cluster
– Identify hot keys, resource
utilization
15
16.
17.
18.
19.
20. TAP
• A generic, scalable method of streaming mutations
from a given server
– As data operations arrive, they can be sent to arbitrary TAP
receivers
• Leverages the existing memcached engine interface,
and the non-blocking IO interfaces to send data
• Three modes of operation
Working set
Data
Mutations
Working set
Data
Mutations
Working set
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21. Membase data flow – under the hood
18
SET request arrives at
KEY’s master server
Listener-Sender
Master server for KEY Replica Server 2 for KEYReplica Server 1 for KEY
3 3
1
SET acknowledgement
returned to application2
DiskDisk Disk
RAM
membasestorageengine
DiskDisk Disk
4
22. ns_server
membase
(memcached + membase engine)
moxi ns_server
vbucketmigrator
TAP
memcached operations
with tap commands
memcached operations
Client
port 11211
memcached operations
moxi + Client
port 11210
memcached operations REST/comet
cluster topology
and vbucket map
Clients, nodes and other nodes
19
23. Data buckets are secure membase “slices”
20
Membase data servers
In the data center
Web application server
Application user
On the administrator console
Bucket 1
Bucket 2
Aggregate Cluster Memory and Disk Capacity
25. Disk > Memory
BucketConfiguration
mem_high_wat
mem_low_wat
memory quota
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Dataset may have many
items infrequently accessed.
However, memcached has
different behavior (LRU) than
wanted with membase.
Still, traditional (most)
RDBMS implementations are
not 100% correct for us
either. The speed of a miss
is very, very important.
34. Membase Datatypes
• byte[]
– Does your data have
1s and 0s?
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“Any customer can have
a car painted any colour
that he wants so long as
it is black.”
35. Membase Datatypes
• byte[]
– Does your data have
1s and 0s?
26
“Any customer can have
a car painted any colour
that he wants so long as
it is black.”
• Items do have flags
– Many clients use flags
–Data type options
• Google protobuf
• Thrift
• Avro
36. Transactions
• Lock == slow me down
• CAS operations
– Optimistic locking
• Very useful with complex
datatypes
– Imagine two clients trying to
update a complex item
• You’re likely using CAS
already... if you use a CPU
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User 1
Fail!
User 2
Success
37. Common Use: Sessions
• Web user sessions
– Highly read, less writes in many case
– Protocol advantage of memcached
• Options already for PHP, Ruby and Java
• Application state
– Not necessarily “entity” style things
– May be appropriate for a “cache” pool
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38. Common Use (cache): Rate Limiting
• Want to provide API calls
into the system
– Twitter search
– Google search services
• Use the atomic increment
– Set an item with a unique ID
– Upon API request,
increment and check
• HTTP 420: go away and come
back later
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Your Users
Your App
¡Ouch!
40. Beyond key-value
• Indexing/Range Queries
• Advanced Data Structures
• Sub-object direct manipulation
Validation and In-flight transformation
• Block mutations failing validation
• Enrich or transform objects
Connectors (Integrate easily with other systems)
• Solr
• Hadoop
• MySQL
NodeCode – Motivation
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41. NodeCode - What is it?
Method for extending & customizing Membase
Separate code modules
Defined interface to datapath and cluster manager
Notification on events
• Synchronous
• Asynchronous
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42. Simple
• Packaged modules for easy install and enable
• Library of “off the shelf” modules
• Module monitoring
• Straight forward development and debugging
Fast
• Low latency/high-throughput
• Per-bucket process isolation
• Don’t break data manager performance/correctness
Elastic
• Automatically migrate and instantiate on rebalance
• Provide support for migration of internal data
• Leverage native Membase engine for internal data storage
NodeCode – Drivers
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