FTN12: FutoIn Async API Version: 1.1 Date: 2014-09-07 Copyright: 2014 FutoIn Project (http://futoin.org) Authors: Andrey Galkin
This interface was born as a secondary option for executor concept. However, it quickly became clear that async/reactor/proactor/light threads/etc. should be base for scalable high performance server implementations, even though it is more difficult for understanding and/or debugging. Traditional synchronous program flow becomes an addon on top of asynchronous base for legacy code and/or too complex logic.
Program flow is split into non-blocking execution steps, represented with execution callback function. Processing Unit (eg. CPU) halting/ spinning/switching-to-another-task is seen as a blocking action in program flow.
Any step must not call any of blocking functions, except for synchronization with guaranteed minimal period of lock acquisition. Note: under minimal period, it is assumed that any acquired lock is immediately released after action with O(1) complexity and no delay caused by programmatic suspension/locking of executing task
Every step is executed sequentially. Success result of any step becomes input for the following step.
Each step can have own error handler. Error handler is called, if AsyncSteps.error() is called within step execution or any of its sub-steps. Typical behavior is to ignore error and continue or to make cleanup actions and complete job with error.
Each step can have own sequence of sub-steps. Sub-steps can be added only during that step execution. Sub-step sequence is executed after current step execution is finished.
If there are any sub-steps added then current step must not call AsyncSteps.success() or AsyncSteps.error(). Otherwise, InternalError is raised.
It is possible to create a special "parallel" sub-step and add independent sub-steps to it. Execution of each parallel sub-step is started all together. Parallel step completes with success when all sub-steps complete with success. If error is raised in any sub-step of parallel step then all other sub-steps are canceled.
Out-of-order cancel of execution can occur by timeout, execution control engine decision (e.g. Invoker disconnect) or failure of sibling parallel step. Each step can install custom on-cancel handler to free resources and/or cancel external jobs. After cancel, it must be safe to destroy AsyncSteps object.
AsyncSteps must be used in Executor request processing. The same [root] AsyncSteps object must be used for all asynchronous tasks within given request processing.
AsyncSteps may be used by Invoker implementation.
AsyncSteps must support derived classes in implementation-defined way. Typical use case: functionality extension (e.g. request processing API).
For performance reasons, it is not economical to initialize AsyncSteps with business logic every time. Every implementation must support platform-specific AsyncSteps cloning/duplicating.
When AsyncSteps (or derived) object is created all steps are added sequentially in Level 0 through add() and/or parallel(). Note: each parallel() is seen as a step.
After AsyncSteps execution is initiated, each step of Level 0 is executed. All sub-steps are added in Level n+1. Example:
add() -> Level 0 #1
add() -> Level 1 #1
add() -> Level 2 #1
parallel() -> Level 2 #2
add() -> Level 2 #3
parallel() -> Level 1 #2
add() -> Level 1 #3
parallel() -> Level 0 #2
add() -> Level 0 #3
Execution cannot continue to the next step of current Level until all steps of higher Level are executed.
The execution sequence would be:
Level 0 add #1
Level 1 add #1
Level 2 add #1
Level 2 parallel #2
Level 2 add #3
Level 1 parallel #2
Level 1 add #3
Level 0 parallel #2
Level 0 add #3
Due to not linear programming, classic try/catch blocks are converted into execute/onerror. Each added step may have custom error handler. If error handler is not specified then control passed to lower Level error handler. If non is defined then execution is aborted.
Example:
add( -> Level 0
func( as ){
print( "Level 0 func" )
add( -> Level 1
func( as ){
print( "Level 1 func" )
as.error( "myerror" )
},
onerror( as, error ){
print( "Level 1 onerror: " + error )
as.error( "newerror" )
}
)
},
onerror( as, error ){
print( "Level 0 onerror: " + error )
as.success( "Prm" )
}
)
add( -> Level 0
func( as, param ){
print( "Level 0 func2: " + param )
as.success()
}
)
Output would be:
Level 0 func
Level 1 func
Level 1 onerror: myerror
Level 0 onerror: newerror
Level 0 func2: Prm
In synchronous way, it would look like:
variable = null
try
{
print( "Level 0 func" )
try
{
print( "Level 1 func" )
throw "myerror"
}
catch ( error )
{
print( "Level 1 onerror: " + error )
throw "newerror"
}
}
catch( error )
{
print( "Level 0 onerror: " + error )
variable = "Prm"
}
print( "Level 0 func2: " + variable )
Very often, execution of step cannot continue without waiting for external event like input from network or disk. It is forbidden to block execution in event waiting. As a solution, there are special setTimeout() and setCancel() methods.
Example:
add(
func( as ){
socket.read( function( data ){
as.success( data )
} )
as.setCancel( function(){
socket.cancel_read()
} )
as.setTimeout( 30_000 ) // 30 seconds
},
onerror( as, error ){
if ( error == timeout ) {
print( "Timeout" )
}
else
{
print( "Read Error" )
}
}
)
Definition of parallel steps makes no sense to continue execution if any of steps fails. To avoid excessive time and resources spent on other steps, there is a concept of canceling execution similar to timeout above.
Example:
as.parallel()
.add(
func( as ){
as.setCancel( function(){ ... } )
// do parallel job #1
as.state()->result1 = ...;
}
)
.add(
func( as ){
as.setCancel( function(){ ... } )
// do parallel job #1
as.state()->result2 = ...;
}
)
.add(
func( as ){
as.error( "Some Error" )
}
)
as.add(
func( as ){
print( as.state()->result1 + as.state->result2 )
as.success()
}
)
In long living applications the same business logic may be re-used multiple times during execution.
In a REST API server example, complex business logic can be defined only once and stored in a kind of AsyncSteps object repository. On each request, a reference object from the repository would be copied for actual processing with minimal overhead.
However, there would be no performance difference in sub-step definition unless its callback function is also created at initialization time, but not at parent step execution time (the default concept). So, it should be possible to predefine those as well and copy/inherit during step execution. Copying steps must also involve copying of state variables.
Example:
AsyncSteps req_repo_common;
req_repo_common.add(func( as ){
as.add( func( as ){ ... } );
as.copyFrom( as.state().business_logic );
as.add( func( as ){ ... } );
});
AsyncSteps req_repo_buslog1;
req_repo_buslog1
.add(func( as ){ ... })
.add(func( as ){ ... });
AsyncSteps actual_exec = copy req_repo_common;
actual_exec.state().business_logic = req_repo_buslog1;
actual_exec.execute();
However, this approach only make sense for deep performance optimizations.
In pseudo-code.
AsyncStepsImpl as;
as.add(
function( inner_as ){
if ( something )
inner_as.success( 1, 2 )
else
inner_as.error( NotImplemented )
},
function( inner_as, error ){
externalError( error );
}
).add(
function( inner_as, res1, res2 ){
externalSuccess( res1, res2 );
inner_as.success()
},
)
AsyncStepsImpl as;
as.add(
function( inner_as ){
inner_as.add(
function( inner2_as ){
if ( something )
inner2_as.success( 1 )
else
inner2_as.error( NotImplemented )
},
function( inner2_as, error )
{
log( "Spotted error " + error )
// continue with higher level error handlers
}
)
inner_as.add(
function( inner2_as, res1 ){
inner2_as.success( res1, 2 )
}
)
},
function( inner_as, error ){
externalError( error );
}
).add(
function( inner_as, res1, res2 ){
externalSuccess( res1, res2 );
inner_as.success()
},
)
AsyncStepsImpl as;
as.add(
function( inner_as ){
inner_as.parallel().add(
function( inner2_as ){
inner2_as.state().parallel_1 = 1;
inner2_as.success()
},
function( inner2_as, error )
{
log( "Spotted error " + error )
// continue with higher level error handlers
}
).add(
function( inner2_as ){
inner2_as.state().parallel_2 = 2;
inner2_as.success()
},
function( inner2_as, error )
{
inner2_as.state().parallel_2 = 0;
inner2_as.success()
// ignore error
}
)
},
function( inner_as, error ){
externalError( error );
}
).add(
function( inner_as, res1, res2 ){
externalSuccess(
as.state().parallel_1,
as.state().parallel_2
);
inner_as.success()
},
)