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%               Thrift whitepaper

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% Name:         thrift.tex

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% Authors:      Mark Slee (mcslee@facebook.com)

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% Created:      05 March 2007

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\title{Thrift: Scalable Cross-Language Services Implementation}

\subtitle{}

\authorinfo{Mark Slee, Aditya Agarwal and Marc Kwiatkowski}

           {Facebook, 156 University Ave, Palo Alto, CA}

           {\{mcslee,aditya,marc\}@facebook.com}

\maketitle

\begin{abstract}

Thrift is a software library and set of code-generation tools developed at

Facebook to expedite development and implementation of efficient and scalable

backend services. Its primary goal is to enable efficient and reliable

communication across programming languages by abstracting the portions of each

language that tend to require the most customization into a common library

that is implemented in each language. Specifically, Thrift allows developers to

define datatypes and service interfaces in a single language-neutral file

and generate all the necessary code to build RPC clients and servers.

This paper details the motivations and design choices we made in Thrift, as

well as some of the more interesting implementation details. It is not

intended to be taken as research, but rather it is an exposition on what we did

and why.

\end{abstract}

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%Languages, serialization, remote procedure call

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%Data description language, interface definition language, remote procedure call

\section{Introduction}

As Facebook's traffic and network structure have scaled, the resource

demands of many operations on the site (i.e. search,

ad selection and delivery, event logging) have presented technical requirements

drastically outside the scope of the LAMP framework. In our implementation of

these services, various programming languages have been selected to

optimize for the right combination of performance, ease and speed of

development, availability of existing libraries, etc. By and large,

Facebook's engineering culture has tended towards choosing the best

tools and implementations available over standardizing on any one

programming language and begrudgingly accepting its inherent limitations.

Given this design choice, we were presented with the challenge of building

a transparent, high-performance bridge across many programming languages.

We found that most available solutions were either too limited, did not offer

sufficient datatype freedom, or suffered from subpar performance.

\footnote{See Appendix A for a discussion of alternative systems.}

The solution that we have implemented combines a language-neutral software

stack implemented across numerous programming languages and an associated code

generation engine that transforms a simple interface and data definition

language into client and server remote procedure call libraries.

Choosing static code generation over a dynamic system allows us to create

validated code that can be run without the need for

any advanced introspective run-time type checking. It is also designed to

be as simple as possible for the developer, who can typically define all

the necessary data structures and interfaces for a complex service in a single

short file.

Surprised that a robust open solution to these relatively common problems

did not yet exist, we committed early on to making the Thrift implementation

open source.

In evaluating the challenges of cross-language interaction in a networked

environment, some key components were identified:

\textit{Types.} A common type system must exist across programming languages

without requiring that the application developer use custom Thrift datatypes

or write their own serialization code. That is,

a C++ programmer should be able to transparently exchange a strongly typed

STL map for a dynamic Python dictionary. Neither

programmer should be forced to write any code below the application layer

to achieve this. Section 2 details the Thrift type system.

\textit{Transport.} Each language must have a common interface to

bidirectional raw data transport. The specifics of how a given

transport is implemented should not matter to the service developer.

The same application code should be able to run against TCP stream sockets,

raw data in memory, or files on disk. Section 3 details the Thrift Transport

layer.

\textit{Protocol.} Datatypes must have some way of using the Transport

layer to encode and decode themselves. Again, the application

developer need not be concerned by this layer. Whether the service uses

an XML or binary protocol is immaterial to the application code.

All that matters is that the data can be read and written in a consistent,

deterministic matter. Section 4 details the Thrift Protocol layer.

\textit{Versioning.} For robust services, the involved datatypes must

provide a mechanism for versioning themselves. Specifically,

it should be possible to add or remove fields in an object or alter the

argument list of a function without any interruption in service (or,

worse yet, nasty segmentation faults). Section 5 details Thrift's versioning

system.

\textit{Processors.} Finally, we generate code capable of processing data

streams to accomplish remote procedure calls. Section 6 details the generated

code and TProcessor paradigm.

Section 7 discusses implementation details, and Section 8 describes

our conclusions.

\section{Types}

The goal of the Thrift type system is to enable programmers to develop using

completely natively defined types, no matter what programming language they

use. By design, the Thrift type system does not introduce any special dynamic

types or wrapper objects. It also does not require that the developer write

any code for object serialization or transport. The Thrift IDL (Interface

Definition Language) file is

logically a way for developers to annotate their data structures with the

minimal amount of extra information necessary to tell a code generator

how to safely transport the objects across languages.

\subsection{Base Types}

The type system rests upon a few base types. In considering which types to

support, we aimed for clarity and simplicity over abundance, focusing

on the key types available in all programming languages, ommitting any

niche types available only in specific languages.

The base types supported by Thrift are:

\begin{itemize}

\item \texttt{bool} A boolean value, true or false

\item \texttt{byte} A signed byte

\item \texttt{i16} A 16-bit signed integer

\item \texttt{i32} A 32-bit signed integer

\item \texttt{i64} A 64-bit signed integer

\item \texttt{double} A 64-bit floating point number

\item \texttt{string} An encoding-agnostic text or binary string

\item \texttt{binary} A byte array representation for blobs

\end{itemize}

Of particular note is the absence of unsigned integer types. Because these

types have no direct translation to native primitive types in many languages,

the advantages they afford are lost. Further, there is no way to prevent the

application developer in a language like Python from assigning a negative value

to an integer variable, leading to unpredictable behavior. From a design

standpoint, we observed that unsigned integers were very rarely, if ever, used

for arithmetic purposes, but in practice were much more often used as keys or

identifiers. In this case, the sign is irrelevant. Signed integers serve this

same purpose and can be safely cast to their unsigned counterparts (most

commonly in C++) when absolutely necessary.

\subsection{Structs}

A Thrift struct defines a common object to be used across languages. A struct

is essentially equivalent to a class in object oriented programming

languages. A struct has a set of strongly typed fields, each with a unique

name identifier. The basic syntax for defining a Thrift struct looks very

similar to a C struct definition. Fields may be annotated with an integer field

identifier (unique to the scope of that struct) and optional default values.

Field identifiers will be automatically assigned if omitted, though they are

strongly encouraged for versioning reasons discussed later.

\subsection{Containers}

Thrift containers are strongly typed containers that map to the most commonly

used containers in common programming languages. They are annotated using

the C++ template (or Java Generics) style. There are three types available:

\begin{itemize}

\item \texttt{list<type>} An ordered list of elements. Translates directly into

an STL \texttt{vector}, Java \texttt{ArrayList}, or native array in scripting languages. May

contain duplicates.

\item \texttt{set<type>} An unordered set of unique elements. Translates into

an STL \texttt{set}, Java \texttt{HashSet}, \texttt{set} in Python, or native

dictionary in PHP/Ruby.

\item \texttt{map<type1,type2>} A map of strictly unique keys to values

Translates into an STL \texttt{map}, Java \texttt{HashMap}, PHP associative

array, or Python/Ruby dictionary.

\end{itemize}

While defaults are provided, the type mappings are not explicitly fixed. Custom

code generator directives have been added to substitute custom types in

destination languages (i.e.

\texttt{hash\_map} or Google's sparse hash map can be used in C++). The

only requirement is that the custom types support all the necessary iteration

primitives. Container elements may be of any valid Thrift type, including other

containers or structs.

\begin{verbatim}

struct Example {

  1:i32 number=10,

  2:i64 bigNumber,

  3:double decimals,

  4:string name="thrifty"

}\end{verbatim}

In the target language, each definition generates a type with two methods,

\texttt{read} and \texttt{write}, which perform serialization and transport

of the objects using a Thrift TProtocol object.

\subsection{Exceptions}

Exceptions are syntactically and functionally equivalent to structs except

that they are declared using the \texttt{exception} keyword instead of the

\texttt{struct} keyword.

The generated objects inherit from an exception base class as appropriate

in each target programming language, in order to seamlessly

integrate with native exception handling in any given

language. Again, the design emphasis is on making the code familiar to the

application developer.

\subsection{Services}

Services are defined using Thrift types. Definition of a service is

semantically equivalent to defining an interface (or a pure virtual abstract

class) in object oriented

programming. The Thrift compiler generates fully functional client and

server stubs that implement the interface. Services are defined as follows:

\begin{verbatim}

service <name> {

  <returntype> <name>(<arguments>)

    [throws (<exceptions>)]

  ...

}\end{verbatim}

An example:

\begin{verbatim}

service StringCache {

  void set(1:i32 key, 2:string value),

  string get(1:i32 key) throws (1:KeyNotFound knf),

  void delete(1:i32 key)

}

\end{verbatim}

Note that \texttt{void} is a valid type for a function return, in addition to

all other defined Thrift types. Additionally, an \texttt{async} modifier

keyword may be added to a \texttt{void} function, which will generate code that does

not wait for a response from the server. Note that a pure \texttt{void}

function will return a response to the client which guarantees that the

operation has completed on the server side. With \texttt{async} method calls

the client will only be guaranteed that the request succeeded at the

transport layer. (In many transport scenarios this is inherently unreliable

due to the Byzantine Generals' Problem. Therefore, application developers

should take care only to use the async optimization in cases where dropped

method calls are acceptable or the transport is known to be reliable.)

Also of note is the fact that argument lists and exception lists for functions

are implemented as Thrift structs. All three constructs are identical in both

notation and behavior.

\section{Transport}

The transport layer is used by the generated code to facilitate data transfer.

\subsection{Interface}

A key design choice in the implementation of Thrift was to decouple the

transport layer from the code generation layer. Though Thrift is typically

used on top of the TCP/IP stack with streaming sockets as the base layer of

communication, there was no compelling reason to build that constraint into

the system. The performance tradeoff incurred by an abstracted I/O layer

(roughly one virtual method lookup / function call per operation) was

immaterial compared to the cost of actual I/O operations (typically invoking

system calls).

Fundamentally, generated Thrift code only needs to know how to read and

write data. The origin and destination of the data are irrelevant; it may be a

socket, a segment of shared memory, or a file on the local disk. The Thrift

transport interface supports the following methods:

\begin{itemize}

\item \texttt{open} Opens the tranpsort

\item \texttt{close} Closes the tranport

\item \texttt{isOpen} Indicates whether the transport is open

\item \texttt{read} Reads from the transport

\item \texttt{write} Writes to the transport

\item \texttt{flush} Forces any pending writes

\end{itemize}

There are a few additional methods not documented here which are used to aid

in batching reads and optionally signaling the completion of a read or

write operation from the generated code.

In addition to the above

\texttt{TTransport} interface, there is a\\

\texttt{TServerTransport} interface

used to accept or create primitive transport objects. Its interface is as

follows:

\begin{itemize}

\item \texttt{open} Opens the transport

\item \texttt{listen} Begins listening for connections

\item \texttt{accept} Returns a new client transport

\item \texttt{close} Closes the transport

\end{itemize}

\subsection{Implementation}

The transport interface is designed for simple implementation in any

programming language. New transport mechanisms can be easily defined as needed

by application developers.

\subsubsection{TSocket}

The \texttt{TSocket} class is implemented across all target languages. It

provides a common, simple interface to a TCP/IP stream socket.

\subsubsection{TFileTransport}

The \texttt{TFileTransport} is an abstraction of an on-disk file to a data

stream. It can be used to write out a set of incoming Thrift requests to a file

on disk. The on-disk data can then be replayed from the log, either for

post-processing or for reproduction and/or simulation of past events.

\subsubsection{Utilities}

The Transport interface is designed to support easy extension using common

OOP techniques, such as composition. Some simple utilites include the

\texttt{TBufferedTransport}, which buffers the writes and reads on an

underlying transport, the \texttt{TFramedTransport}, which transmits data with frame

size headers for chunking optimization or nonblocking operation, and the

\texttt{TMemoryBuffer}, which allows reading and writing directly from the heap

or stack memory owned by the process.

\section{Protocol}

A second major abstraction in Thrift is the separation of data structure from

transport representation. Thrift enforces a certain messaging structure when

transporting data, but it is agnostic to the protocol encoding in use. That is,

it does not matter whether data is encoded as XML, human-readable ASCII, or a

dense binary format as long as the data supports a fixed set of operations

that allow it to be deterministically read and written by generated code.

\subsection{Interface}

The Thrift Protocol interface is very straightforward. It fundamentally

supports two things: 1) bidirectional sequenced messaging, and

2) encoding of base types, containers, and structs.

\begin{verbatim}

writeMessageBegin(name, type, seq)

writeMessageEnd()

writeStructBegin(name)

writeStructEnd()

writeFieldBegin(name, type, id)

writeFieldEnd()

writeFieldStop()

writeMapBegin(ktype, vtype, size)

writeMapEnd()

writeListBegin(etype, size)

writeListEnd()

writeSetBegin(etype, size)

writeSetEnd()

writeBool(bool)

writeByte(byte)

writeI16(i16)

writeI32(i32)

writeI64(i64)

writeDouble(double)

writeString(string)

name, type, seq = readMessageBegin()

                  readMessageEnd()

name =            readStructBegin()

                  readStructEnd()

name, type, id =  readFieldBegin()

                  readFieldEnd()

k, v, size =      readMapBegin()

                  readMapEnd()

etype, size =     readListBegin()

                  readListEnd()

etype, size =     readSetBegin()

                  readSetEnd()

bool =            readBool()

byte =            readByte()

i16 =             readI16()

i32 =             readI32()

i64 =             readI64()

double =          readDouble()

string =          readString()

\end{verbatim}

Note that every \texttt{write} function has exactly one \texttt{read} counterpart, with

the exception of \texttt{writeFieldStop()}. This is a special method

that signals the end of a struct. The procedure for reading a struct is to

\texttt{readFieldBegin()} until the stop field is encountered, and then to

\texttt{readStructEnd()}.  The

generated code relies upon this call sequence to ensure that everything written by

a protocol encoder can be read by a matching protocol decoder. Further note

that this set of functions is by design more robust than necessary.

For example, \texttt{writeStructEnd()} is not strictly necessary, as the end of

a struct may be implied by the stop field. This method is a convenience for

verbose protocols in which it is cleaner to separate these calls (e.g. a closing

\texttt{</struct>} tag in XML).

\subsection{Structure}

Thrift structures are designed to support encoding into a streaming

protocol. The implementation should never need to frame or compute the

entire data length of a structure prior to encoding it. This is critical to

performance in many scenarios. Consider a long list of relatively large

strings. If the protocol interface required reading or writing a list to be an

atomic operation, then the implementation would need to perform a linear pass over the

entire list before encoding any data. However, if the list can be written

as iteration is performed, the corresponding read may begin in parallel,

theoretically offering an end-to-end speedup of $(kN - C)$, where $N$ is the size

of the list, $k$ the cost factor associated with serializing a single

element, and $C$ is fixed offset for the delay between data being written

and becoming available to read.

Similarly, structs do not encode their data lengths a priori. Instead, they are

encoded as a sequence of fields, with each field having a type specifier and a

unique field identifier. Note that the inclusion of type specifiers allows

the protocol to be safely parsed and decoded without any generated code

or access to the original IDL file. Structs are terminated by a field header

with a special \texttt{STOP} type. Because all the basic types can be read

deterministically, all structs (even those containing other structs) can be

read deterministically. The Thrift protocol is self-delimiting without any

framing and regardless of the encoding format.

In situations where streaming is unnecessary or framing is advantageous, it

can be very simply added into the transport layer, using the

\texttt{TFramedTransport} abstraction.

\subsection{Implementation}

Facebook has implemented and deployed a space-efficient binary protocol which

is used by most backend services. Essentially, it writes all data

in a flat binary format. Integer types are converted to network byte order,

strings are prepended with their byte length, and all message and field headers

are written using the primitive integer serialization constructs. String names

for fields are omitted - when using generated code, field identifiers are

sufficient.

We decided against some extreme storage optimizations (i.e. packing

small integers into ASCII or using a 7-bit continuation format) for the sake

of simplicity and clarity in the code. These alterations can easily be made

if and when we encounter a performance-critical use case that demands them.

\section{Versioning}

Thrift is robust in the face of versioning and data definition changes. This

is critical to enable staged rollouts of changes to deployed services. The

system must be able to support reading of old data from log files, as well as

requests from out-of-date clients to new servers, and vice versa.

\subsection{Field Identifiers}

Versioning in Thrift is implemented via field identifiers. The field header

for every member of a struct in Thrift is encoded with a unique field

identifier. The combination of this field identifier and its type specifier

is used to uniquely identify the field. The Thrift definition language

supports automatic assignment of field identifiers, but it is good

programming practice to always explicitly specify field identifiers.

Identifiers are specified as follows:

\begin{verbatim}

struct Example {

  1:i32 number=10,

  2:i64 bigNumber,

  3:double decimals,

  4:string name="thrifty"

}\end{verbatim}

To avoid conflicts between manually and automatically assigned identifiers,

fields with identifiers omitted are assigned identifiers

decrementing from -1, and the language only supports the manual assignment of

positive identifiers.

When data is being deserialized, the generated code can use these identifiers

to properly identify the field and determine whether it aligns with a field in

its definition file. If a field identifier is not recognized, the generated

code can use the type specifier to skip the unknown field without any error.

Again, this is possible due to the fact that all datatypes are self

delimiting.

Field identifiers can (and should) also be specified in function argument

lists. In fact, argument lists are not only represented as structs on the

backend, but actually share the same code in the compiler frontend. This

allows for version-safe modification of method parameters

\begin{verbatim}

service StringCache {

  void set(1:i32 key, 2:string value),

  string get(1:i32 key) throws (1:KeyNotFound knf),

  void delete(1:i32 key)

}

\end{verbatim}

The syntax for specifying field identifiers was chosen to echo their structure.

Structs can be thought of as a dictionary where the identifiers are keys, and

the values are strongly-typed named fields.

Field identifiers internally use the \texttt{i16} Thrift type. Note, however,

that the \texttt{TProtocol} abstraction may encode identifiers in any format.

\subsection{Isset}

When an unexpected field is encountered, it can be safely ignored and

discarded. When an expected field is not found, there must be some way to

signal to the developer that it was not present. This is implemented via an

inner \texttt{isset} structure inside the defined objects. (Isset functionality

is implicit with a \texttt{null} value in PHP, \texttt{None} in Python

and \texttt{nil} in Ruby.) Essentially,

the inner \texttt{isset} object of each Thrift struct contains a boolean value

for each field which denotes whether or not that field is present in the

struct. When a reader receives a struct, it should check for a field being set

before operating directly on it.

\begin{verbatim}

class Example {

 public:

  Example() :

    number(10),

    bigNumber(0),

    decimals(0),

    name("thrifty") {}

  int32_t number;

  int64_t bigNumber;

  double decimals;

  std::string name;

  struct __isset {

    __isset() :

      number(false),

      bigNumber(false),

      decimals(false),

      name(false) {}

    bool number;

    bool bigNumber;

    bool decimals;

    bool name;

  } __isset;

...

}

\end{verbatim}

\subsection{Case Analysis}

There are four cases in which version mismatches may occur.

\begin{enumerate}

\item \textit{Added field, old client, new server.} In this case, the old

client does not send the new field. The new server recognizes that the field

is not set, and implements default behavior for out-of-date requests.

\item \textit{Removed field, old client, new server.} In this case, the old

client sends the removed field. The new server simply ignores it.

\item \textit{Added field, new client, old server.} The new client sends a

field that the old server does not recognize. The old server simply ignores

it and processes as normal.

\item \textit{Removed field, new client, old server.} This is the most

dangerous case, as the old server is unlikely to have suitable default

behavior implemented for the missing field. It is recommended that in this

situation the new server be rolled out prior to the new clients.

\end{enumerate}

\subsection{Protocol/Transport Versioning}

The \texttt{TProtocol} abstractions are also designed to give protocol

implementations the freedom to version themselves in whatever manner they

see fit. Specifically, any protocol implementation is free to send whatever

it likes in the \texttt{writeMessageBegin()} call. It is entirely up to the

implementor how to handle versioning at the protocol level. The key point is

that protocol encoding changes are safely isolated from interface definition

version changes.

Note that the exact same is true of the \texttt{TTransport} interface. For

example, if we wished to add some new checksumming or error detection to the

\texttt{TFileTransport}, we could simply add a version header into the

data it writes to the file in such a way that it would still accept old

log files without the given header.

\section{RPC Implementation}

\subsection{TProcessor}

The last core interface in the Thrift design is the \texttt{TProcessor},

perhaps the most simple of the constructs. The interface is as follows:

\begin{verbatim}

interface TProcessor {

  bool process(TProtocol in, TProtocol out)

    throws TException

}

\end{verbatim}

The key design idea here is that the complex systems we build can fundamentally

be broken down into agents or services that operate on inputs and outputs. In

most cases, there is actually just one input and output (an RPC client) that

needs handling.

\subsection{Generated Code}

When a service is defined, we generate a

\texttt{TProcessor} instance capable of handling RPC requests to that service,

using a few helpers. The fundamental structure (illustrated in pseudo-C++) is

as follows:

\begin{verbatim}

Service.thrift

 => Service.cpp

     interface ServiceIf

     class ServiceClient : virtual ServiceIf

       TProtocol in

       TProtocol out

     class ServiceProcessor : TProcessor

       ServiceIf handler

ServiceHandler.cpp

 class ServiceHandler : virtual ServiceIf

TServer.cpp

 TServer(TProcessor processor,

         TServerTransport transport,

         TTransportFactory tfactory,

         TProtocolFactory pfactory)

 serve()

\end{verbatim}

From the Thrift definition file, we generate the virtual service interface.

A client class is generated, which implements the interface and

uses two \texttt{TProtocol} instances to perform the I/O operations. The

generated processor implements the \texttt{TProcessor} interface. The generated

code has all the logic to handle RPC invocations via the \texttt{process()}

call, and takes as a parameter an instance of the service interface, as

implemented by the application developer.

The user provides an implementation of the application interface in separate,

non-generated source code.

\subsection{TServer}

Finally, the Thrift core libraries provide a \texttt{TServer} abstraction.

The \texttt{TServer} object generally works as follows.

\begin{itemize}

\item Use the \texttt{TServerTransport} to get a \texttt{TTransport}

\item Use the \texttt{TTransportFactory} to optionally convert the primitive

transport into a suitable application transport (typically the

\texttt{TBufferedTransportFactory} is used here)

\item Use the \texttt{TProtocolFactory} to create an input and output protocol

for the \texttt{TTransport}

\item Invoke the \texttt{process()} method of the \texttt{TProcessor} object

\end{itemize}

The layers are appropriately separated such that the server code needs to know

nothing about any of the transports, encodings, or applications in play. The

server encapsulates the logic around connection handling, threading, etc.

while the processor deals with RPC. The only code written by the application

developer lives in the definitional Thrift file and the interface

implementation.

Facebook has deployed multiple \texttt{TServer} implementations, including

the single-threaded \texttt{TSimpleServer}, thread-per-connection

\texttt{TThreadedServer}, and thread-pooling \texttt{TThreadPoolServer}.

The \texttt{TProcessor} interface is very general by design. There is no

requirement that a \texttt{TServer} take a generated \texttt{TProcessor}

object. Thrift allows the application developer to easily write any type of

server that operates on \texttt{TProtocol} objects (for instance, a server

could simply stream a certain type of object without any actual RPC method

invocation).

\section{Implementation Details}

\subsection{Target Languages}

Thrift currently supports five target languages: C++, Java, Python, Ruby, and

PHP. At Facebook, we have deployed servers predominantly in C++, Java, and

Python. Thrift services implemented in PHP have also been embedded into the

Apache web server, providing transparent backend access to many of our

frontend constructs using a \texttt{THttpClient} implementation of the

\texttt{TTransport} interface.

Though Thrift was explicitly designed to be much more efficient and robust

than typical web technologies, as we were designing our XML-based REST web

services API we noticed that Thrift could be easily used to define our

service interface. Though we do not currently employ SOAP envelopes (in the

authors' opinions there is already far too much repetitive enterprise Java

software to do that sort of thing), we were able to quickly extend Thrift to

generate XML Schema Definition files for our service, as well as a framework

for versioning different implementations of our web service. Though public

web services are admittedly tangential to Thrift's core use case and design,

Thrift facilitated rapid iteration and affords us the ability to quickly

migrate our entire XML-based web service onto a higher performance system

should the need arise.

\subsection{Generated Structs}

We made a conscious decision to make our generated structs as transparent as

possible. All fields are publicly accessible; there are no \texttt{set()} and

\texttt{get()} methods. Similarly, use of the \texttt{isset} object is not

enforced. We do not include any \texttt{FieldNotSetException} construct.

Developers have the option to use these fields to write more robust code, but

the system is robust to the developer ignoring the \texttt{isset} construct

entirely and will provide suitable default behavior in all cases.

This choice was motivated by the desire to ease application development. Our stated

goal is not to make developers learn a rich new library in their language of

choice, but rather to generate code that allow them to work with the constructs

that are most familiar in each language.

We also made the \texttt{read()} and \texttt{write()} methods of the generated

objects public so that the objects can be used outside of the context

of RPC clients and servers. Thrift is a useful tool simply for generating

objects that are easily serializable across programming languages.

\subsection{RPC Method Identification}

Method calls in RPC are implemented by sending the method name as a string. One

issue with this approach is that longer method names require more bandwidth.

We experimented with using fixed-size hashes to identify methods, but in the

end concluded that the savings were not worth the headaches incurred. Reliably

dealing with conflicts across versions of an interface definition file is

impossible without a meta-storage system (i.e. to generate non-conflicting

hashes for the current version of a file, we would have to know about all

conflicts that ever existed in any previous version of the file).

We wanted to avoid too many unnecessary string comparisons upon

method invocation. To deal with this, we generate maps from strings to function

pointers, so that invocation is effectively accomplished via a constant-time

hash lookup in the common case. This requires the use of a couple interesting

code constructs. Because Java does not have function pointers, process

functions are all private member classes implementing a common interface.

\begin{verbatim}

private class ping implements ProcessFunction {

  public void process(int seqid,

                      TProtocol iprot,

                      TProtocol oprot)

    throws TException

  { ...}

}

HashMap<String,ProcessFunction> processMap_ =

  new HashMap<String,ProcessFunction>();

\end{verbatim}

In C++, we use a relatively esoteric language construct: member function

pointers.

\begin{verbatim}

std::map<std::string,

  void (ExampleServiceProcessor::*)(int32_t,

  facebook::thrift::protocol::TProtocol*,

  facebook::thrift::protocol::TProtocol*)>

 processMap_;

\end{verbatim}

Using these techniques, the cost of string processing is minimized, and we

reap the benefit of being able to easily debug corrupt or misunderstood data by

inspecting it for known string method names.

\subsection{Servers and Multithreading}

Thrift services require basic multithreading to handle simultaneous

requests from multiple clients. For the Python and Java implementations of

Thrift server logic, the standard threading libraries distributed with the

languages provide adequate support. For the C++ implementation, no standard multithread runtime

library exists. Specifically, robust, lightweight, and portable

thread manager and timer class implementations do not exist. We investigated

existing implementations, namely \texttt{boost::thread},

\texttt{boost::threadpool}, \texttt{ACE\_Thread\_Manager} and

\texttt{ACE\_Timer}.

While \texttt{boost::threads}\cite{boost.threads}  provides clean,

lightweight and robust implementations of multi-thread primitives (mutexes,

conditions, threads) it does not provide a thread manager or timer

implementation.

\texttt{boost::threadpool}\cite{boost.threadpool} also looked promising but

was not far enough along for our purposes. We wanted to limit the dependency on

third-party libraries as much as possible. Because\\

\texttt{boost::threadpool} is

not a pure template library and requires runtime libraries and because it is

not yet part of the official Boost distribution we felt it was not ready for

use in Thrift. As \texttt{boost::threadpool} evolves and especially if it is

added to the Boost distribution we may reconsider our decision to not use it.

ACE has both a thread manager and timer class in addition to multi-thread

primitives. The biggest problem with ACE is that it is ACE. Unlike Boost, ACE

API quality is poor. Everything in ACE has large numbers of dependencies on

everything else in ACE - thus forcing developers to throw out standard

classes, such as STL collections, in favor of ACE's homebrewed implementations. In

addition, unlike Boost, ACE implementations demonstrate little understanding

of the power and pitfalls of C++ programming and take no advantage of modern

templating techniques to ensure compile time safety and reasonable compiler

error messages. For all these reasons, ACE was rejected. Instead, we chose

to implement our own library, described in the following sections.

\subsection{Thread Primitives}

The Thrift thread libraries are implemented in the namespace\\

\texttt{facebook::thrift::concurrency} and have three components:

\begin{itemize}

\item primitives

\item thread pool manager

\item timer manager

\end{itemize}

As mentioned above, we were hesitant to introduce any additional dependencies

on Thrift. We decided to use \texttt{boost::shared\_ptr} because it is so

useful for multithreaded application, it requires no link-time or

runtime libraries (i.e. it is a pure template library) and it is due

to become part of the C++0x standard.

We implement standard \texttt{Mutex} and \texttt{Condition} classes, and a

 \texttt{Monitor} class. The latter is simply a combination of a mutex and

condition variable and is analogous to the \texttt{Monitor} implementation provided for

the Java \texttt{Object} class. This is also sometimes referred to as a barrier. We

provide a \texttt{Synchronized} guard class to allow Java-like synchronized blocks.

This is just a bit of syntactic sugar, but, like its Java counterpart, clearly

delimits critical sections of code. Unlike its Java counterpart, we still

have the ability to programmatically lock, unlock, block, and signal monitors.

\begin{verbatim}

void run() {

 {Synchronized s(manager->monitor);

  if (manager->state == TimerManager::STARTING) {

    manager->state = TimerManager::STARTED;

    manager->monitor.notifyAll();

  }

 }

}

\end{verbatim}

We again borrowed from Java the distinction between a thread and a runnable

class. A \texttt{Thread} is the actual schedulable object. The

\texttt{Runnable} is the logic to execute within the thread.

The \texttt{Thread} implementation deals with all the platform-specific thread

creation and destruction issues, while the \texttt{Runnable} implementation deals

with the application-specific per-thread logic. The benefit of this approach

is that developers can easily subclass the Runnable class without pulling in

platform-specific super-classes.

\subsection{Thread, Runnable, and shared\_ptr}

We use \texttt{boost::shared\_ptr} throughout the \texttt{ThreadManager} and

\texttt{TimerManager} implementations to guarantee cleanup of dead objects that can

be accessed by multiple threads. For \texttt{Thread} class implementations,

\texttt{boost::shared\_ptr} usage requires particular attention to make sure

\texttt{Thread} objects are neither leaked nor dereferenced prematurely while

creating and shutting down threads.

Thread creation requires calling into a C library. (In our case the POSIX

thread library, \texttt{libpthread}, but the same would be true for WIN32 threads).

Typically, the OS makes few, if any, guarantees about when \texttt{ThreadMain}, a C thread's entry-point function, will be called. Therefore, it is

possible that our thread create call,

\texttt{ThreadFactory::newThread()} could return to the caller

well before that time. To ensure that the returned \texttt{Thread} object is not

prematurely cleaned up if the caller gives up its reference prior to the

\texttt{ThreadMain} call, the \texttt{Thread} object makes a weak referenence to

itself in its \texttt{start} method.

With the weak reference in hand the \texttt{ThreadMain} function can attempt to get

a strong reference before entering the \texttt{Runnable::run} method of the

\texttt{Runnable} object bound to the \texttt{Thread}. If no strong references to the

thread are obtained between exiting \texttt{Thread::start} and entering \texttt{ThreadMain}, the weak reference returns \texttt{null} and the function

exits immediately.

The need for the \texttt{Thread} to make a weak reference to itself has a

significant impact on the API. Since references are managed through the

\texttt{boost::shared\_ptr} templates, the \texttt{Thread} object must have a reference

to itself wrapped by the same \texttt{boost::shared\_ptr} envelope that is returned

to the caller. This necessitated the use of the factory pattern.

\texttt{ThreadFactory} creates the raw \texttt{Thread} object and a

\texttt{boost::shared\_ptr} wrapper, and calls a private helper method of the class

implementing the \texttt{Thread} interface (in this case, \texttt{PosixThread::weakRef})

 to allow it to make add weak reference to itself through the

 \texttt{boost::shared\_ptr} envelope.

\texttt{Thread} and \texttt{Runnable} objects reference each other. A \texttt{Runnable}

object may need to know about the thread in which it is executing, and a Thread, obviously,

needs to know what \texttt{Runnable} object it is hosting. This interdependency is

further complicated because the lifecycle of each object is independent of the

other. An application may create a set of \texttt{Runnable} object to be reused in different threads, or it may create and forget a \texttt{Runnable} object

once a thread has been created and started for it.

The \texttt{Thread} class takes a \texttt{boost::shared\_ptr} reference to the hosted

\texttt{Runnable} object in its constructor, while the \texttt{Runnable} class has an

explicit \texttt{thread} method to allow explicit binding of the hosted thread.

\texttt{ThreadFactory::newThread} binds the objects to each other.

\subsection{ThreadManager}

\texttt{ThreadManager} creates a pool of worker threads and

allows applications to schedule tasks for execution as free worker threads

become available. The \texttt{ThreadManager} does not implement dynamic

thread pool resizing, but provides primitives so that applications can add

and remove threads based on load. This approach was chosen because

implementing load metrics and thread pool size is very application

specific. For example some applications may want to adjust pool size based

on running-average of work arrival rates that are measured via polled

samples. Others may simply wish to react immediately to work-queue

depth high and low water marks. Rather than trying to create a complex

API abstract enough to capture these different approaches, we

simply leave it up to the particular application and provide the

primitives to enact the desired policy and sample current status.

\subsection{TimerManager}

\texttt{TimerManager} allows applications to schedule

 \texttt{Runnable} objects for execution at some point in the future. Its specific task

is to allows applications to sample \texttt{ThreadManager} load at regular

intervals and make changes to the thread pool size based on application policy.

Of course, it can be used to generate any number of timer or alarm events.

The default implementation of \texttt{TimerManager} uses a single thread to

execute expired \texttt{Runnable} objects. Thus, if a timer operation needs to

do a large amount of work and especially if it needs to do blocking I/O,

that should be done in a separate thread.

\subsection{Nonblocking Operation}

Though the Thrift transport interfaces map more directly to a blocking I/O

model, we have implemented a high performance \texttt{TNonBlockingServer}

in C++ based on \texttt{libevent} and the \texttt{TFramedTransport}. We

implemented this by moving all I/O into one tight event loop using a

state machine. Essentially, the event loop reads framed requests into

\texttt{TMemoryBuffer} objects. Once entire requests are ready, they are

dispatched to the \texttt{TProcessor} object which can read directly from

the data in memory.

\subsection{Compiler}

The Thrift compiler is implemented in C++ using standard \texttt{lex}/\texttt{yacc}

lexing and parsing. Though it could have been implemented with fewer

lines of code in another language (i.e. Python Lex-Yacc (PLY) or \texttt{ocamlyacc}), using C++

forces explicit definition of the language constructs. Strongly typing the

parse tree elements (debatably) makes the code more approachable for new

developers.

Code generation is done using two passes. The first pass looks only for

include files and type definitions. Type definitions are not checked during

this phase, since they may depend upon include files. All included files

are sequentially scanned in a first pass. Once the include tree has been

resolved, a second pass over all files is taken that inserts type definitions

into the parse tree and raises an error on any undefined types. The program is

then generated against the parse tree.

Due to inherent complexities and potential for circular dependencies,

we explicitly disallow forward declaration. Two Thrift structs cannot

each contain an instance of the other. (Since we do not allow \texttt{null}

struct instances in the generated C++ code, this would actually be impossible.)

\subsection{TFileTransport}

The \texttt{TFileTransport} logs Thrift requests/structs by

framing incoming data with its length and writing it out to disk.

Using a framed on-disk format allows for better error checking and

helps with the processing of a finite number of discrete events. The\\

\texttt{TFileWriterTransport} uses a system of swapping in-memory buffers

to ensure good performance while logging large amounts of data.

A Thrift log file is split up into chunks of a specified size; logged messages

are not allowed to cross chunk boundaries. A message that would cross a chunk

boundary will cause padding to be added until the end of the chunk and the

first byte of the message are aligned to the beginning of the next chunk.

Partitioning the file into chunks makes it possible to read and interpret data

from a particular point in the file.

\section{Facebook Thrift Services}

Thrift has been employed in a large number of applications at Facebook, including

search, logging, mobile, ads and the developer platform. Two specific usages are discussed below.

\subsection{Search}

Thrift is used as the underlying protocol and transport layer for the Facebook Search service.

The multi-language code generation is well suited for search because it allows for application

development in an efficient server side language (C++) and allows the Facebook PHP-based web application

to make calls to the search service using Thrift PHP libraries. There is also a large

variety of search stats, deployment and testing functionality that is built on top

of generated Python code. Additionally, the Thrift log file format is

used as a redo log for providing real-time search index updates. Thrift has allowed the

search team to leverage each language for its strengths and to develop code at a rapid pace.

\subsection{Logging}

The Thrift \texttt{TFileTransport} functionality is used for structured logging. Each

service function definition along with its parameters can be considered to be

a structured log entry identified by the function name. This log can then be used for

a variety of purposes, including inline and offline processing, stats aggregation and as a redo log.

\section{Conclusions}

Thrift has enabled Facebook to build scalable backend

services efficiently by enabling engineers to divide and conquer. Application

developers can focus on application code without worrying about the

sockets layer. We avoid duplicated work by writing buffering and I/O logic

in one place, rather than interspersing it in each application.