RunFuzzyMatchPLINQ(
string[] wordsLookup,
IEnumerable<string> files)
{
var matchSet = await (
from contentFile in files.Traverse(f => File.ReadAllTextAsync(f))
from words in contentFile.Traverse(text =>
WordRegex.Value.Split(text).Where(w => !IgnoreWords.Contains(w)))
let wordSet = words.Flatten().AsSet()
from bestMatch in wordsLookup.Traverse(wl => JaroWinklerModule.bestMatchTask(wordSet, wl, threshold))
select bestMatch.Flatten());
// NOTES
// Here the code that leverages the "ReadFileLinesAndFlatten" method
//var matchSet = await (
// from contentFile in files.Traverse(f => ReadFileLinesAndFlatten(f))
// let wordSet = contentFile.Flatten().AsSet()
// from bestMatch in wordsLookup.Traverse(wl => JaroWinklerModule.bestMatchTask(wordSet, wl, threshold))
// select bestMatch.Flatten());
return PrintSummary(matchSet.AsSet());
}
RunFuzzyMatchSequential(
string[] wordsLookup,
IEnumerable<string> files)
{
// Sequential workflow -> how can we parallelize this work?
// The collection 'matchSet' cannot be shared among threads
var matchSet = new HashSet<WordDistanceStruct>();
foreach (var file in files)
{
string readText = File.ReadAllText(file);
var words = readText.Split(punctuation.Value)
.Where(w => !IgnoreWords.Contains(w))
.AsSet();
foreach (var wl in wordsLookup)
{
var bestMatch = JaroWinklerModule.bestMatch(words, wl, threshold);
matchSet.AddRange(bestMatch);
}
}
return PrintSummary(matchSet);
}
RunFuzzyMatchTaskProcessAsCompleteAbstracted(
string[] wordsLookup,
IEnumerable <string> files)
{
var matchSet = new HashSet <WordDistanceStruct>();
// TODO (4) : Implement a resuable function called "ContinueAsComplete" to abstract the implementation of the
// previous method "RunFuzzyMatchTaskProcessAsCompleteBasic".
// The function "ContinueAsComplete" should sattisfy the following signatue:
// Signature :
// Enumerable<Task<R>> ContinueAsComplete<T, R>(this IEnumerable<T> input, Func<T, Task<R>> selector)
//
// C# : go to "Module 2\TaskAsComplete.cs" and add the missing code (4)
// F# : go to the FSharp project "Module 2\TaskAsComplete.fs" and add the missing code (4)
foreach (var textTask in files.ContinueAsComplete(file => File.ReadAllTextAsync(file)))
{
var text = await textTask;
var words = WordRegex.Value
.Split(text)
.Where(w => !IgnoreWords.Contains(w))
.AsSet();
foreach (var matchTask in wordsLookup.ContinueAsComplete(
wl => JaroWinklerModule.bestMatchTask(words, wl, threshold)))
{
matchSet.AddRange(await matchTask);
}
}
return(PrintSummary(matchSet));
}
RunFuzzyMatchTaskContinuation(
string[] wordsLookup,
IEnumerable <string> files)
{
// Let's start by converting the I/O operation to be asynchronous
// The continuation passing style avoids to block any threads
//
// What about the error handlimg ? and cancellation (if any) ?
var matchSet = new HashSet <WordDistanceStruct>();
foreach (var file in files)
{
var readFileTask = File.ReadAllTextAsync(file);
IEnumerable <WordDistanceStruct[]> bestMatches =
await readFileTask
.ContinueWith(readText =>
{
return(WordRegex.Value.Split(readText.Result)
.Where(w => !IgnoreWords.Contains(w)));
})
.ContinueWith(words =>
{
var tasks = (from wl in wordsLookup
select JaroWinklerModule.bestMatchTask(words.Result, wl, threshold)).ToList();
return(Task.WhenAll(tasks));
}).Unwrap();
matchSet.AddRange(bestMatches.Flatten());
}
return(PrintSummary(matchSet));
}
public static void RunFuzzyMatchPipeline(
string[] wordsLookup,
IList <string> files)
{
var pipeline = Pipeline <string, string[]> .Create(file => File.ReadAllLinesAsync(file));
pipeline
.Then(lines =>
lines.SelectMany(l => l.Split(punctuation.Value)
.Where(w => !IgnoreWords.Contains(w))).AsSet()
)
.Then(wordSet =>
wordsLookup.Traverse(wl => JaroWinklerModule.bestMatchTask(wordSet, wl, threshold))
)
.Then(matcheSet =>
PrintSummary(matcheSet.Flatten().AsSet())
);
foreach (var file in files)
{
Console.WriteLine($"analyzing file {file}");
pipeline.Enqueue(file);
}
// End C# Pipeline
}
public static void RunFuzzyMatchPipelineFSharp(
string[] wordsLookup,
IList <string> files)
{
// TODO (3) : In the previous example you have implemented the Monadic operator SelectMany (usually called Bind)
// This operator enables the compiler to understand the monadic (LINQ) pattern, which allows you to write
// expressive/declarative code in LINQ style
// Let's implement a parallel Pipeline that allows you to keep the continuation semantic,
// with the advantage of running
// the transoramations in parallel
//
// Implement the "Then" operator (instance method) that can be used to create and fluently compose a pipeline
// for example:
// pipeline.Then( .... ).Then(...)
//
// Also implement the logic in the "Enqueue" method
//
// F# : go to the FSharp project "Module 2\Pipeline.fs" and add the missing code (3.a and 3.b)
//
// To be bale to handle correctly a Multi-Producer/Multi-Consumer scenario,
// take look to these oprions
// BlockingCollection<TInput>.TryAddToAny
// BlockingCollection<TInput>.TryTakeFromAny
//
// When you are complete, uncomment the code and run it
// TODO (3) Start F# Pipeline
var pipelineFSharp =
Pipeline.Pipeline <string, string[]>
.Create(file => File.ReadAllLinesAsync(file))
.Then(lines =>
lines.SelectMany(l => l.Split(punctuation.Value)
.Where(w => !IgnoreWords.Contains(w))).AsSet()
)
.Then(wordSet =>
wordsLookup.Traverse(wl => JaroWinklerModule.bestMatchTask(wordSet, wl, threshold))
)
.Then(matcheSet =>
matcheSet.Flatten().AsSet()
);
pipelineFSharp.Execute(4, CancellationToken.None);
var unit = (Unit)Activator.CreateInstance(typeof(Unit), true);
foreach (var file in files)
{
pipelineFSharp.Enqueue(file,
(tup =>
{
Console.WriteLine($"analyzing file {file}");
PrintSummary(tup.Item2);
return(unit);
}));
}
// End F# Pipeline
}
RunFuzzyMatchBetterTaskContinuation(
string[] wordsLookup,
IEnumerable<string> files)
{
// Ideally, we should handle potential errors or cancellations
// This is a lot of code which goes against the DRY principal
var matchSet = new HashSet<WordDistanceStruct>();
foreach (var file in files)
{
var readFileTask = File.ReadAllTextAsync(file);
var bestMatches = await readFileTask
.ContinueWith(readText =>
{
switch (readText.Status)
{
case TaskStatus.Faulted:
Exception ex = readText.Exception;
while (ex is AggregateException && ex.InnerException != null)
ex = ex.InnerException;
// do something with ex
return null;
case TaskStatus.Canceled:
// do something because Task cancelled
return null;
default:
return WordRegex.Value.Split(readText.Result)
.Where(w => !IgnoreWords.Contains(w));
}
})
.ContinueWith(words =>
{
switch (words.Status)
{
case TaskStatus.Faulted:
Exception ex = words.Exception;
while (ex is AggregateException && ex.InnerException != null)
ex = ex.InnerException;
// do something with ex
return null;
case TaskStatus.Canceled:
// do something because Task cancelled
return null;
default:
return wordsLookup.Traverse(wl =>
JaroWinklerModule.bestMatchTask(words.Result, wl, threshold));
}
}).Unwrap();
matchSet.AddRange(bestMatches.Flatten());
}
return PrintSummary(matchSet);
}
// Listing 2.23 Fast Fuzzy Match using precomputation
public static Func <string, string> PartialFuzzyMatch(List <string> words) //#A
{
var wordSet = new HashSet <string>(words); //#B
return(word =>
(from w in wordSet.AsParallel()
select JaroWinklerModule.Match(w, word))
.OrderByDescending(w => w.Distance)
.Select(w => w.Word)
.FirstOrDefault()); //#C
}
RunFuzzyMatchTaskProcessAsCompleteBasic(
string[] wordsLookup,
IEnumerable <string> files)
{
// An alternative pattern to parallize the FuzzyMatch is the "Procces as complete"
// The idea of this pattern is to start the execution of all the operations (tasks)
// at the same time, and then proccess them as they complete instead of waiting for all the operations
// to be completed before continuing.
// In other words, this pattern returns a sequence of tasks which will be observed to complete with the same set
// of results as the given input tasks, but in the order in which the original tasks complete.
//
// Here a simple implementation ::
var matchSet = new HashSet <WordDistanceStruct>();
var readFileTasks =
(from file in files
select File.ReadAllTextAsync(file)
).ToList();
while (readFileTasks.Count > 0)
{
await Task.WhenAny(readFileTasks)
.ContinueWith(async readTask =>
{
var finishedReadTask = readTask.Result;
readFileTasks.Remove(finishedReadTask);
var words = WordRegex.Value
.Split(finishedReadTask.Result)
.Where(w => !IgnoreWords.Contains(w));
var matchTasks =
(from wl in wordsLookup
select JaroWinklerModule.bestMatchTask(words, wl, threshold)
).ToList();
while (matchTasks.Count > 0)
{
await Task.WhenAny(matchTasks)
.ContinueWith(matchTask =>
{
var finishedMatchTask = matchTask.Result;
matchTasks.Remove(finishedMatchTask);
matchSet.AddRange(finishedMatchTask.Result);
});
}
});
}
return(PrintSummary(matchSet));
}
RunFuzzyMatchTaskComposition(
string[] wordsLookup,
IEnumerable <string> files)
{
// A better apporach is to create a custom operator that preserves
// the continuation semantic, while handling cases of error, exception and transformation
// Signatures :
// Task<TOut> Then<TIn, TOut>(this Task<TIn> task, Func<TIn, TOut> next) : Functor
// Task<TOut> Then<TIn, TOut>(this Task<TIn> task, Func<TIn, Task<TOut>> next) : Bind
// Traverese the given files in parallel
// TODO (1) : Implement a reusable and optimizied fucntion called "Then" that satisfied the previous signature
// C# : go to the "Module 1\TaskCompoistion.cs" and add the missing code in TODO (1)
// F# : go to the FSharp project "Module 1\TaskCompoistion.fs" and add the missing code
//
// Optional/bonus function to implement with signature :
// Task<TOut> SelectMany<TIn, TMid, TOut>(this Task<TIn> input, Func<TIn, Task<TMid>> f, Func<TIn, TMid, TOut> projection)
return
(files.Traverse(file => File.ReadAllTextAsync(file))
.Then(fileContent =>
fileContent
.SelectMany(text => WordRegex.Value.Split(text))
.Where(w => !IgnoreWords.Contains(w))
.AsSet()
)
.Then(wordsSplit =>
wordsLookup.Traverse(wl => JaroWinklerModule.bestMatchTask(wordsSplit, wl, threshold))
)
.Then(matcheSet => PrintSummary(matcheSet.Flatten().AsSet())));
// NOTES
// In this scenario, and only for demo purposes, we are reading the text asynchronously
// in one operation, and then we are treating the text as a unique string.
// In the case that the text is a large string, there are some performance penalties especially
// during the Regex Split. A better approach is to read text files in line and run the Regex against
// chunks of strings.
// One solution is to create a Task that reads, splits and flattens the input text
// in one operation. The method "ReadFileLinesAndFlatten" ( in the "TaskEx" static class )
// implements this design.
// Feel free to check the method and use it if you would like.
// Here is the code that replaces the previus code.
//return
// files.Traverse(file => ReadFileLinesAndFlatten(file))
// .Then(wordsSplit =>
// {
// var words = wordsSplit.Flatten();
// return wordsLookup.Traverse(wl => JaroWinklerModule.bestMatchTask(words, wl, threshold));
// })
// .Then(matcheSet => PrintSummary(matcheSet.Flatten().AsSet()));
}
// Listing 2.22 A fuzzy match
public static string FuzzyMatch(List <string> words, string word)
{
var wordSet = new HashSet <string>(words); //#A
string bestMatch =
(from w in wordSet.AsParallel() //#B
select JaroWinklerModule.Match(w, word))
.OrderByDescending(w => w.Distance)
.Select(w => w.Word)
.FirstOrDefault();
return(bestMatch); //#C
}
RunFuzzyMatchTaskComposition(
string[] wordsLookup,
IEnumerable<string> files)
{
return
files.Traverse(file => File.ReadAllTextAsync(file))
.Then(fileContent =>
fileContent
.SelectMany(text => WordRegex.Value.Split(text))
.Where(w => !IgnoreWords.Contains(w))
.AsSet()
)
.Then(wordsSplit =>
wordsLookup.Traverse(wl => JaroWinklerModule.bestMatchTask(wordsSplit, wl, threshold))
)
.Then(matcheSet => PrintSummary(matcheSet.Flatten().AsSet()));
// NOTES
// In this scenario, and only for demo purposes, we are reading the text asynchronously
// in one operation, and then we are treating the text as a unique string.
// In the case that the text is a large string, there are some performance penalties especially
// during the Regex Split. A better approach is to read text files in line and run the Regex against
// chunks of strings.
// One solution is to create a Task that reads, splits and flattens the input text
// in one operation. The method "ReadFileLinesAndFlatten" ( in the "TaskEx" static class )
// implements this design.
// Feel free to check the method and use it if you would like.
// Here is the code that replaces the previus code.
//return
// files.Traverse(file => ReadFileLinesAndFlatten(file))
// .Then(wordsSplit =>
// {
// var words = wordsSplit.Flatten();
// return wordsLookup.Traverse(wl => JaroWinklerModule.bestMatchTask(words, wl, threshold));
// })
// .Then(matcheSet => PrintSummary(matcheSet.Flatten().AsSet()));
}
RunFuzzyMatchTaskProcessAsCompleteAbstracted(
string[] wordsLookup,
IEnumerable <string> files)
{
var matchSet = new HashSet <WordDistanceStruct>();
foreach (var textTask in files.ContinueAsComplete(file => File.ReadAllTextAsync(file)))
{
var text = await textTask;
var words = WordRegex.Value
.Split(text)
.Where(w => !IgnoreWords.Contains(w))
.AsSet();
foreach (var matchTask in wordsLookup.ContinueAsComplete(
wl => JaroWinklerModule.bestMatchTask(words, wl, threshold)))
{
matchSet.AddRange(await matchTask);
}
}
return(PrintSummary(matchSet));
}
RunFuzzyMatchPLINQ(
string[] wordsLookup,
IEnumerable <string> files)
{
// TODO (2) : After have copmletd TODO (1), we should be able to implement
// effortlessly a LINQ pattern using the Task.
// Rename the "Then" function implemented with the name SelectMany, such that these three followig signatures
// are sattisfied :
//
// Task<TOut> SelectMany<TIn, TMid, TOut>(this Task<TIn> input, Func<TIn, Task<TMid>> f, Func<TIn, TMid, TOut> projection)
// Task<TOut> SelectMany<TIn, TOut>(this Task<TIn> first, Func<TIn, Task<TOut>> next)
// Task<TOut> Select<TIn, TOut>(this Task<TIn> task, Func<TIn, TOut> projection)
//
// Then uncomment the following code, add the missing code and run it
var matchSet = await(
from contentFile in files.Traverse(f => File.ReadAllTextAsync(f))
from words in contentFile.Traverse(text =>
WordRegex.Value.Split(text).Where(w => !IgnoreWords.Contains(w)))
let wordSet = words.Flatten().AsSet()
// TODO (2)
from bestMatch in wordsLookup.Traverse(wl => JaroWinklerModule.bestMatchTask(wordSet, wl, threshold))
select bestMatch.Flatten());
// NOTES
// Here the code that leverages the "ReadFileLinesAndFlatten" method
//var matchSet = await (
// from contentFile in files.Traverse(f => ReadFileLinesAndFlatten(f))
// let wordSet = contentFile.Flatten().AsSet()
// from bestMatch in wordsLookup.Traverse(wl => JaroWinklerModule.bestMatchTask(wordSet, wl, threshold))
// select bestMatch.Flatten());
return(PrintSummary(matchSet.AsSet()));
}
// Example F#
public static async Task RunFuzzyMatchAgentFSharp(string[] wordsLookup, IList <string> files)
{
var cts = new CancellationTokenSource();
var opt = new ExecutionDataflowBlockOptions
{
BoundedCapacity = 10,
MaxDegreeOfParallelism = 4,
CancellationToken = cts.Token
};
var inputBlock = new BufferBlock <string>(opt);
var readLinesBlock =
new TransformBlock <string, string>(
file => File.ReadAllTextAsync(file, cts.Token), opt);
var splitWordsBlock = new TransformBlock <string, string[]>(
text => WordRegex.Value.Split(text).Where(w => !IgnoreWords.Contains(w)).AsSet().ToArray(), opt);
var foundMatchesBlock =
new TransformBlock <string[], WordDistanceStruct[]>(async wordSet =>
{
var matches =
await wordsLookup.Traverse(wl => JaroWinklerModule.bestMatchTask(wordSet, wl, threshold));
return(matches.Flatten().ToArray());
}, opt);
var linkOptions = new DataflowLinkOptions {
PropagateCompletion = true
};
// TODO (7) (for F#)
// Implement a Reactive MailboxProcessor in F#.
// Go to the Fsharp project, Module 3 and follow the instructions (7.a)
// then, uncomment the following code and remove the previous code that uses
// the Agent based on TPL Dataflow
var agent =
new ReactiveAgent.AgentObservable <WordDistanceStruct[], Dictionary <string, HashSet <string> > >
(new Dictionary <string, HashSet <string> >(),
(state, matches) =>
{
var matchesDic = matches
.GroupBy(w => w.Word).ToDictionary(k => k.Key,
v => v.Select(w => w.Match).AsSet());
// Clone is important to be race condition free
// or use an immutable collection
var newState = Clone(state);
foreach (var match in matchesDic)
{
if (newState.TryGetValue(match.Key, out HashSet <string> values))
{
values.AddRange(match.Value);
newState[match.Key] = values;
}
else
{
newState.Add(match.Key, match.Value);
}
}
return(newState);
});
IDisposable disposeAll = new CompositeDisposable(
inputBlock.LinkTo(readLinesBlock, linkOptions),
readLinesBlock.LinkTo(splitWordsBlock, linkOptions),
splitWordsBlock.LinkTo(foundMatchesBlock, linkOptions),
foundMatchesBlock.LinkTo(agent),
agent.AsObservable().Subscribe(
summaryMathces => PrintSummary(summaryMathces))
);
cts.Token.Register(disposeAll.Dispose);
foreach (var file in files)
{
await inputBlock.SendAsync(file, cts.Token);
}
// inputBlock.Complete();
// await foundMatchesBlock.Completion.ContinueWith(_ => disposeAll.Dispose());
}
public static async Task RunFuzzyMatchDataFlow(string[] wordsLookup, IList <string> files)
{
var cts = new CancellationTokenSource();
var opt = new ExecutionDataflowBlockOptions
{
BoundedCapacity = 10,
// TODO, change this value and check what is happening
MaxDegreeOfParallelism = 1,
CancellationToken = cts.Token
};
int fileCount = files.Count;
var inputBlock = new BufferBlock <string>(opt);
var readLinesBlock =
new TransformBlock <string, string>(
async file => await File.ReadAllTextAsync(file, cts.Token), opt);
var splitWordsBlock =
new TransformBlock <string, HashSet <string> >(
text => WordRegex.Value.Split(text).Where(w => !IgnoreWords.Contains(w)).AsSet(), opt);
var batch =
new BatchBlock <HashSet <string> >(fileCount);
var foundMatchesBlock =
new TransformBlock <HashSet <string>[], WordDistanceStruct[]>(
async wordSet =>
{
var wordSetFlatten = wordSet.Flatten().AsSet();
var matches =
await wordsLookup.Traverse(wl =>
JaroWinklerModule.bestMatchTask(wordSetFlatten, wl, threshold));
return(matches.Flatten().ToArray());
}, opt);
// TODO (5)
// Implement a block name "printBlock", which prints the output of
// the foundMatchesBlock using the "PrintSummary" method
// Then link the block to the "foundMatchesBlock" block
// var printBlock = // missing code
var linkOptions = new DataflowLinkOptions {
PropagateCompletion = true
};
IDisposable disposeAll = new CompositeDisposable(
inputBlock.LinkTo(readLinesBlock, linkOptions),
readLinesBlock.LinkTo(splitWordsBlock, linkOptions),
splitWordsBlock.LinkTo(batch, linkOptions),
batch.LinkTo(foundMatchesBlock, linkOptions)
// TODO uncoment this code after
// implemented TODO (5)
// foundMatchesBlock.LinkTo(printBlock)
);
cts.Token.Register(disposeAll.Dispose);
// TODO (6)
// After have completed TODO (5), remove or unlink the printBlock, and replace the output of the "foundMatchesBlock" block
// with Reactive Extensions "AsObservable", maintaining the call to the "PrintSummary" method
foreach (var file in files)
{
await inputBlock.SendAsync(file, cts.Token);
}
inputBlock.Complete();
await foundMatchesBlock.Completion.ContinueWith(_ => disposeAll.Dispose());
}
// C# example
public static async Task RunFuzzyMatchAgentCSharp(string[] wordsLookup, IList <string> files)
{
var cts = new CancellationTokenSource();
var opt = new ExecutionDataflowBlockOptions
{
BoundedCapacity = 10,
MaxDegreeOfParallelism = 4,
CancellationToken = cts.Token
};
var inputBlock = new BufferBlock <string>(opt);
var readLinesBlock =
new TransformBlock <string, string>(
async file => await File.ReadAllTextAsync(file, cts.Token), opt);
var splitWordsBlock =
new TransformBlock <string, string[]>(
text => WordRegex.Value.Split(text).Where(w => !IgnoreWords.Contains(w)).AsSet().ToArray(), opt);
var foundMatchesBlock =
new TransformBlock <string[], WordDistanceStruct[]>(async wordSet =>
{
var matches =
await wordsLookup.Traverse(wl => JaroWinklerModule.bestMatchTask(wordSet, wl, threshold));
return(matches.Flatten().ToArray());
}, opt);
var linkOptions = new DataflowLinkOptions {
PropagateCompletion = true
};
// TODO (7) (for C#)
// Implement a stateful agent using the TPL Dataflow.
// The Agent should have an internal state protected from external access.
// The function passed in the constractor applies a project/reduce to the incoming messages and in the current state,
// to return a new state
// (see AgentAggregator.cs)
var agent = Agent.Start(new Dictionary <string, HashSet <string> >(),
(Dictionary <string, HashSet <string> > state, WordDistanceStruct[] matches) =>
{
var matchesDic = matches
.GroupBy(w => w.Word)
.ToDictionary(
k => k.Key,
v => v.Select(w => w.Match).AsSet());
var newState = Clone(state);
foreach (var match in matchesDic)
{
if (newState.TryGetValue(match.Key, out HashSet <string> values))
{
values.AddRange(match.Value);
newState[match.Key] = values;
}
else
{
newState.Add(match.Key, match.Value);
}
}
return(newState);
});
IDisposable disposeAll = new CompositeDisposable(
inputBlock.LinkTo(readLinesBlock, linkOptions),
readLinesBlock.LinkTo(splitWordsBlock, linkOptions),
splitWordsBlock.LinkTo(foundMatchesBlock, linkOptions),
foundMatchesBlock.LinkTo(agent),
agent.AsObservable()
.Subscribe(
summaryMathces => PrintSummary(summaryMathces))
);
cts.Token.Register(disposeAll.Dispose);
foreach (var file in files)
{
await inputBlock.SendAsync(file, cts.Token);
}
// inputBlock.Complete();
// await foundMatchesBlock.Completion.ContinueWith(_ =>
// disposeAll.Dispose());
}
public static (bool Matched, string Word) CpuMatch(string word)
{
var match = JaroWinklerModule.bestMatch(WordsToSearch, word, 0.9);
return(match.Any() ? (true, match.First().Match) : (false, null));
}
