1. Nam Nguyen Software Engineer Caucho Technology, Inc.
Baratine in Practice
Date:
Location: San Diego JUG
Nam Nguyen
Software Engineer
Caucho Technology, Inc.

2. Baratine in Practice
Download Install Our - Multiple counters - implement an Type of services chart Partitioning and clustering

3. Task: Baratine quick start - Download - Install - Our first service

4. public class CounterServiceImpl { private long _id; private long _counter; public long get() return _counter; public long incrementAndGet() { return ++_counter; public long decrementAndGet() { return --_counter; public long addAndGet(long value) { _counter = _counter + value;

5. jonathan hughes optiminsight
HTTP Polling
HTTP REST
WebSocket
Java
INBOX
OUTBOX
public class CounterServiceImpl { private long _id; private long _counter; public long get() return _counter; public long incrementAndGet() { return ++_counter; public long decrementAndGet() { return --_counter; public long addAndGet(long value) { _counter = _counter + value;
JOURNAL
KEY-VALUE DB
(internal)

6. What You Get + Insane low-latency concurrent performance
assign thread
1. incrementAndGet()
2. incrementAndGet()
3. addAndGet()
4. decrementAndGet()
5. incrementAndGet()
6. incrementAndGet()
7. ...
NO BLOCKING / LOCKING !
 CPU cache stays hot (for both data and instructions)
CPU core uninterrupted during batch
no context switching
no pausing
thread screams through entire batch
Batch A
Batch B
Instead of the CPU core spending time in the operating system’s scheduling code, or the queue blocking code, the core spends all its time in the code that matters the most: your service code.

7. Batch Programming
assign thread
@BeforeBatch
1 incrementAndGet()
2. addAndGet()
3. addAndGet()
4. decrementAndGet()
5. incrementAndGet()
6. incrementAndGet()
@AfterBatch
- flush writes
7. ...
 Leave expensive operations to be executed at the end of the batch.
Inbox is empty at this point

8. Performance Characteristics
Requests per Second
Baratine
Batch Size / Clients

9. Performance Characteristics
ServiceA to ServiceB within the same JVM
Batch Size / Clients
Requests per Second
Baratine
If same JVM, get a magnitude better performance. e.g. analytics or reporting service that co-hosted in the same JVM as your other services. Like deploying a job to Hadoop and letting it run among your data.

10. Reliable to Batch  Safe to process in batches. @OnCheckpoint
assign thread
@BeforeBatch
1 incrementAndGet()
2. addAndGet()
3. addAndGet()
4. decrementAndGet()
5. incrementAndGet()
6. incrementAndGet()
@AfterBatch
- flush writes
7. ...
 Safe to process in batches.
@OnCheckpoint
Journaling

11. Putting it All Together
Freed to operate
in memory safely!
▲ Operational Data
What is Operational Data?
Instead of having data stored in some external database, it is owned and stored in the service itself where it’s being used and modified. The service has ownership of its own data. The data stays with the service, within the same JVM, even within the same object instance. It’s true object-oriented programming in the finest sense where the object encapsulates both data and logic.

12. Sounds like a lot of magic is going on.
@Journal
@ResourceService(“public:///counter/{_id}”)
public class CounterServiceImpl {
private long _id;
private long _counter;
public long get()
return _counter; }
@Modify
public long incrementAndGet() {
return ++_counter;
public long decrementAndGet() {
return --_counter;
public long addAndGet(long value) {
_counter = _counter + value;
What do you get with a service so simple? Your service is operating like a database, but with logic and data working together seamlessly.
Sounds like a lot of magic is going on.

13. Warning: hardcore! @Service
Barebones service, basis Singleton, only one instance within a JVM - - No automatic restore - No automatic paging - No automatic checkpointing - No automatic query support - No automatic partitioning
Warning: hardcore!

14. @Service
Less magic: you have fine-grained control

15. Task: implement a logging service with a @Service

16. @Workers
with a thread-pool acting on the inbox. Example: hibernate, SAP, MySQL, legacy, integration
- Does not fully benefit from batching
- Not single-threaded
+ Can block
+ Multi-threaded

17. Task: implement a @Workers @Service

18. Types of Services Annotation: @ResourceService @Service @Workers
Batching ✓ ✓*
Journaling
Checkpointing
Paging
Partitioning
Resource ID’s
Search
Threaded-ness
single
multi
Can Block?
Performance
★★★☆
★★★★
★☆☆☆
(manual)

19. Partitioning and Clustering
/auction/111
/auction/444
/auction/999
/auction/222
/auction/555
/auction/888
/auction/000
/auction/333
/auction/666
/auction/777
Resources are partitioned
by its service URL and ID

20. State of Baratine
GPL Been in active development for over 2 years v0.8.3 (alpha) (alpha) Thank you!
stealth
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21. The End
Q and A