Downloaded 73 times
![Jepp
13
object TestJepp extends App {
val jep = new Jep()
jep.runScript("python_util.py")
val a = (2).asInstanceOf[AnyRef]
val b = (3).asInstanceOf[AnyRef]
val sumByPython = jep.invoke("python_add", a, b)
}
object TestJepp extends App {
val jep = new Jep()
jep.runScript("python_util.py")
val a = (2).asInstanceOf[AnyRef]
val b = (3).asInstanceOf[AnyRef]
val sumByPython = jep.invoke("python_add", a, b)
}
def python_add(a, b):
return a + b
def python_add(a, b):
return a + b
python_util.py
TestJepp.scala](https://image.slidesharecdn.com/howtointegratepythonintoascalastacktobuildrealtimepredictivemodelsv2nomanuscript-140518005621-phpapp01/75/PyCon-2014-APAC-How-to-integrate-python-into-a-scala-stack-to-build-realtime-predictive-models-13-2048.jpg)
![Jepp
13
object TestJepp extends App {
val jep = new Jep()
jep.runScript("python_util.py")
val a = (2).asInstanceOf[AnyRef]
val b = (3).asInstanceOf[AnyRef]
val sumByPython = jep.invoke("python_add", a, b)
}
object TestJepp extends App {
val jep = new Jep()
jep.runScript("python_util.py")
val a = (2).asInstanceOf[AnyRef]
val b = (3).asInstanceOf[AnyRef]
val sumByPython = jep.invoke("python_add", a, b)
}
def python_add(a, b):
return a + b
def python_add(a, b):
return a + b
python_util.py
TestJepp.scala](https://crownmelresort.com/image.slidesharecdn.com/howtointegratepythonintoascalastacktobuildrealtimepredictivemodelsv2nomanuscript-140518005621-phpapp01/75/PyCon-2014-APAC-How-to-integrate-python-into-a-scala-stack-to-build-realtime-predictive-models-13-2048.jpg)
Uploaded byJerry Chou
[PyCon 2014 APAC] How to integrate python into a scala stack to build realtime predictive models
This document discusses different tools for integrating Python into a Scala stack to enable building real-time predictive models. It covers Jython, Jepp, Thrift, and REST APIs. Jepp is identified as allowing access to high-quality Python extensions with CPython speed while avoiding the overhead of separate runtimes like Jython. Thrift and REST are also presented as language-independent options that introduce communication overhead. The document concludes by detailing Fliptop's architecture that uses multiple Python servers communicating via Bottle to handle over 4,500 requests per second for predictive modeling.
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[PyCon 2014 APAC] How to integrate python into a scala stack to build realtime predictive models
- 1. How to IntegratePython into a Scala Stack to Build Realtime Predictive Models Jerry Chou Lead Research Engineer jerry@fliptop.com
- 2. Stories Beforehand • Productpivoted • Data search => data analysis • Build on top of existing infrastructure (hosted on AWS & Azure) • Need tools for scientific computation • Mahout (Java) • Weka (Java) • Scikit-learn (Python) 2
- 3. Agenda • Requirements andhigh level concepts • Tools for calling Python from Scala • Decision making 3
- 4. High Level Concept- Before 4 Existing business logic (in both Scala & Java) Modeling Logic (in Python) Node 1 Modeling Logic (in Python) Node 2 … Modeling Logic (in Python) Node N
- 5. Requirements • APIs toexploit Python’s modeling power • Train, predict, model info query, etc • Scalability • On demand Python serving nodes 5
- 6. Tools for Scala-PythonIntegration • Reimplementation of Python • Jython (JPython) • Communication through JNI • Jepp • Communication through IPC • Thrift • Communication through REST API calls • Bottle 6
- 7. Jython (JPython) • Re-Implementationof Python in Java • Compiles to Java bytecode • either on demand or statically. • Can import and use any Java class 7
- 8.
- 9. Jython • Lacks supportfor lots of extensions for scientific computing • Numpy, Scipy, etc. • JyNI to the rescue? • Not ready yet for even Numpy 9
- 10.
- 11. Communication through JNI •Jepp(Java Embedded Python) • Embeds CPython in Java • Runs Python code in CPython • Leverages both JNI and Python/C API for integration 11
- 12. Python Interpreter Jepp 12 JVM Scala Code PythonCode JNI Jepp
- 13. Jepp 13 object TestJepp extendsApp { val jep = new Jep() jep.runScript("python_util.py") val a = (2).asInstanceOf[AnyRef] val b = (3).asInstanceOf[AnyRef] val sumByPython = jep.invoke("python_add", a, b) } object TestJepp extends App { val jep = new Jep() jep.runScript("python_util.py") val a = (2).asInstanceOf[AnyRef] val b = (3).asInstanceOf[AnyRef] val sumByPython = jep.invoke("python_add", a, b) } def python_add(a, b): return a + b def python_add(a, b): return a + b python_util.py TestJepp.scala
- 14. Communication through IPC •Thrift •Developed & open sourced by Facebook •IDL-based (Interface Definition Language) •Generates server/client code in specified languages •Take care of protocol and transport layer details •Comes with generators for Java, Python, C++, etc. • No Scala generator • Scrooge to the rescue! 14
- 15. Thrift – IDL 15 namespacejava python_service_test namespace py python_service_test service PythonAddService { i32 pythonAdd (1:i32 a, 2:i32 b), } namespace java python_service_test namespace py python_service_test service PythonAddService { i32 pythonAdd (1:i32 a, 2:i32 b), } TestThrift.thrift $ thrift --gen java --gen py TestThrift.thrift$ thrift --gen java --gen py TestThrift.thrift
- 16. Thrift – PythonServer class ExampleHandler(python_service_test.PythonAddService.Iface): def pythonAdd(self, a, b): return a + b handler = ExampleHandler() processor = Example.Processor(handler) transport = TSocket.TServerSocket(9090) tfactory = TTransport.TBufferedTransportFactory() pfactory = TBinaryProtocol.TBinaryProtocolFactory() server = TServer.TThreadedServer(processor, transport, tfactory, pfactory) server.serve() class ExampleHandler(python_service_test.PythonAddService.Iface): def pythonAdd(self, a, b): return a + b handler = ExampleHandler() processor = Example.Processor(handler) transport = TSocket.TServerSocket(9090) tfactory = TTransport.TBufferedTransportFactory() pfactory = TBinaryProtocol.TBinaryProtocolFactory() server = TServer.TThreadedServer(processor, transport, tfactory, pfactory) server.serve() PythonAddServer.py class Iface: def pythonAdd(self, a, b): pass class Iface: def pythonAdd(self, a, b): pass PythonAddService.py
- 17. Thrift – ScalaClient 17 object PythonAddClient extends App { val transport: TTransport = new TSocket("localhost", 9090) val protocol: TProtocol = new TBinaryProtocol(transport) val client = new PythonAddService.Client(protocol) transport.open() val sumByPython = client.python_add(3, 5) println("3 + 5 = " + sumByPython) transport.close() } object PythonAddClient extends App { val transport: TTransport = new TSocket("localhost", 9090) val protocol: TProtocol = new TBinaryProtocol(transport) val client = new PythonAddService.Client(protocol) transport.open() val sumByPython = client.python_add(3, 5) println("3 + 5 = " + sumByPython) transport.close() } PythonAddClient.scala
- 18. Thrift 18 JVM Scala Code Thrift PythonCode Python Interpreter Thrift Python Code Python Interpreter Thrift … Auto Balancing 、 Built-in Encryption
- 19.
- 20. REST API Architecture 20 …Bottle PythonCode Bottle Python Code Bottle Python Code JVM Scala Code Auto Balancer? Encoding?
- 21. Thrift v.s. REST ThriftRES T Load Balancer ✔ Encode / Decode ✔ Low Learning Curve ✔ No Dependency ✔ Does it matter? No (AWS & Azure) No (We’re already doing it) Maybe Yes
- 22. Fliptop’s Architecture 22 Load Balancer …Bottle PythonCode Bottle Python Code Bottle Python Code JVM Scala Code 5 Python servers ~4,500 requests/sec
- 23. Summary • Jython • (✓)Tight integration with Scala/Java • (✗) Lack support for C extensions (JyNI might help in the future) • Jepp • (✓) Access high quality Python extensions with CPython speed • (✗) Two runtime environments • Thrift, REST • (✓) Language-independent development • (✗) Bigger communication overhead 23
- 24.
- 25. Other tools • JyNI(Jython Native Interface) • A compatibility layer to enable Jython to use native CPython extensions like NumPy or SciPy • Binary compatible with existing builds • Cython • A subset of Python implementation written in Python that translates Python codes to C • JNA (Java Native Access) • JNI-based wrapper providing Java programs access to native shared libraries • JPE (Java-Python Extension) • JNI-based wrapper integrating Java and standard Python • last updated at: 2013-03-22 25