Get Files in ZIP file stored on Azure without downloading it

Recently, I was working on a task where we had to get file entries and names off ZIP files stored on Azure. We had terabytes of data to go through and downloading them was not really an option. In the end of the day, we solved this in a totally different way, but I remained curious if this is possible, and it sure is.

The aim is to get all the entry names of ZIP files stored on an Azure Storage Account. Unfortunately, using our beloved HttpClient isn’t possible (or at least, I didn’t research enough). The reason is that although HttpClient does allow us to access an HttpRequest as a Stream, the Stream itself isn’t seekable (CanSeek: false).

This is why we need to use the Azure.Storage.Blobs API – this allows us to get a Seekable Stream against a File stored in Azure Storage Account. What this means is that we can download specific parts of the ZIP file where the names are stored, rather than the data itself. Here is a detailed diagram on how ZIP files are stored, though this is not needed as the libraries will handle all the heavy lifting for us – The structure of a PKZip file (jmu.edu)

We will also be using the out-of-the-box ZipArchive library. This will allow us to open a Zip File from a Stream. This library is also smart enough to know that if a stream is Seekable, it will seek to the part where the File Names are being stored rather than downloading the whole file.

Therefore, all we need is to open a stream to the ZIP using the Azure.Storage.Blobs, pass it to the ZipArchive library and read the entries out of it. This process ends up essentially almost instant, even for large ZIP files.

using Azure.Storage;
using Azure.Storage.Blobs;
using System;
using System.IO.Compression;
using System.Linq;
using System.Threading.Tasks;
namespace GetZipFileNamesFromAzureZip
{
class Program
{
private const string StorageAccountName = "xxxxxx";
private const string StorageAccountKey = "xxxxxxxxxxxxxxx";
private const string ContainerName = "xxxxxxxxxx";
private const string FileName = "file.zip";
private const string Url = "https://" + StorageAccountName + ".blob.core.windows.net";
static async Task Main(string[] args)
{
BlobServiceClient client = new BlobServiceClient(new Uri(Url), new StorageSharedKeyCredential(StorageAccountName, StorageAccountKey));
var container = client.GetBlobContainerClient(ContainerName);
var blobClient = container.GetBlobClient(FileName);
var stream = await blobClient.OpenReadAsync();
using ZipArchive package = new ZipArchive(stream, ZipArchiveMode.Read);
Console.WriteLine(string.Join(",", package.Entries.Select(x => x.FullName).ToArray()));
}
}
}

Until the next one!

Compressing files on an Azure Storage Account fast and efficiently.

Currently, I am working on a project that requires zipping and compressing files that exist on a storage account. Unfortunately, unless I am missing something, there is no out-of-the box way how to ZIP files on an Azure storage.

There are two major possibilities that I’ve found are:

  • Azure Data Factory – It’s a cloud based ETL storage solution. In my research, I found that this tool can cost quite a lot, since you’re paying for the rented machines and tasks. Data Factory – Data Integration Service | Microsoft Azure
  • Writing a bespoke solution – of course you’ve got the flexibility of doing whatever you want but it probably takes more time to develop, test and such.

Anyway, in my case I’ve decided to write my own application; there were other requirements that I needed to satisfy, which was it too complex for me to implement it in Azure Data Factory. I’ve written the following code (some code omitted for brevity)


CloudBlockBlob blob = targetStorageAccountContainer.GetBlockBlobReference("zipfile.zip");
blob.StreamWriteSizeInBytes = 104_857_600;      

using (Stream dataLakeZipFile = await blob.OpenWriteAsync())
using (var zipStream = new ZipOutputStream(dataLakeZipFile))
{
    DataLakeDirectoryClient sourceDirectoryClient = dataLakeClient.GetDirectoryClient(sourceDataLakeAccount);
    await foreach(var blobItem in sourceDirectoryClient.GetPathsAsync(recursive: true, cancellationToken: cancellationToken))   
    {
        zipStream.PutNextEntry(new ZipEntry(blobItem.Name));
        var httpResponseMessage = await _httpClient.GetAsync(GetFileToAddToZip(blobItem.Name), HttpCompletionOption.ResponseHeadersRead);
        using (Stream httpStream = await httpResponseMessage.Content.ReadAsStreamAsync())
        {
            await httpStream.CopyToAsync(zipStream);
        }

        zipStream.CloseEntry();
    }

    zipStream.Finish();
}  

The following code does this following:

  • Create a reference to the ZIP file that is going to be created on the Storage Account. I also set StreamWriteSizeInBytes to 100MB; the largest. I never experimented with other figures. This refers to how much data to write per block.
  • Open a Stream object against the zip file. This overwrites any file with the same name.
  • Get all the files you need to ZIP. In my case, I am using the DataLake API because our files are on a Storage Account with hierarchical namespaces activated. This will work just as fine if your Storage Account doesn’t use hierarchical namspaces (you can just swap out and use the CloudBlobContainer API).
  • Open a new connection to the destination file and fetch it as a stream.
  • Copy the data received from the stream to the zip stream. This translates into HTTP requests, uploading it back to the Storage Account.
  • Close down all resources when its done.

Importantly, the code downloads files from the storage account and instantly uploads it back to the storage account as a ZIP. This does not store any data on physical disk and uses RAM to buffer the data as its downloaded and uploaded.

Of course, this part is just an excerpt of the whole system needed, but it can be adapted accordingly.

Until the next one!

C# Micro Optimizations Part 2 – In Parameter Modifier

In this series of posts, we’re investigating micro-optimizations in C#. As previously mentioned, these may not be applicable to all; but it’s still fun looking at these concepts.

Let’s visit back the last post – Ref arguments. Ref arguments gave us the power of passing structs by value in an extremely efficient manner.

Mutability of a ref struct

Passing structs by ref brings a major disadvantage – the callee might mutate the value of the struct without the caller ever knowing. What if we need to pass structs in an efficient manner, whilst having peace of mind that the callee doesn’t mutate the struct?

Meet the in parameter modifier- C# 7.2

What does the in parameter modifier do? It allows us to pass the argument by reference and giving us the guarantee that the arguments cannot be modified by the callee. Excellent! Let’s run a quick test and make sure our performance is still comparable when passing by ref. Let’s have a struct with 2 properties – let’s have some work done using two different methods – passing by ref and passing by in.

All code can be viewed here – https://github.com/albertherd/csharpmopt2-in

public class SixteenBitStructBenchmark
{
    [Benchmark]
    [Arguments(100000000)]
    public void BenchmarkIncrementByRef(int limit)
    {
        SixteenBitStruct sixteenBitStruct = new SixteenBitStruct();
        int counter = 0;
        do
        {
            IncrementByRef(ref sixteenBitStruct);
            counter++;
        }
        while (limit != counter);
    }

    [Benchmark]
    [Arguments(100000000)]
    public void BenchmarkIncrementByIn(int limit)
    {
        SixteenBitStruct sixteenBitStruct = new SixteenBitStruct();
        int counter = 0;
        do
        {
            IncrementIn(sixteenBitStruct);
            counter++;
        }
        while (limit != counter);
    }

    private void IncrementByRef(ref SixteenBitStruct sixteenBitStruct)
    {
        double sum = sixteenBitStruct.D1 + sixteenBitStruct.D2;
    }

    private void IncrementIn(in SixteenBitStruct sixteenBitStruct)
    {
        double sum2 = sixteenBitStruct.D1 + sixteenBitStruct.D2;
    }
}

public struct SixteenBitStruct
{
    public double D1 { get; }
    public double D2 { get; }
}

Let’s see how they perform.

Method limit Mean Error StdDev
BenchmarkIncrementByRef 100000000 23.83 ms 0.0272 ms 0.0241 ms
BenchmarkIncrementByIn 100000000 238.21 ms 0.3108 ms 0.2755 ms

Performance loss?

Wait a second – why is IncrementByIn 10x slower than IncrementByRef when we’re accessing 2 properties in the same struct? Let’s have a look at the generated IL.

IncrementByRef

 IL_0000: ldarg.1
IL_0001: call instance float64 InOperator.SixteenBitStruct::get_D1()
# Loads argument 1 (SixteenBitStruct) and call the getter

IncrementByIn

 IL_0000: ldarg.1
# Prepare a new local variable on the evaluation stack
IL_0001: ldobj InOperator.SixteenBitStruct
# Copies the value of SixteenBitStruct into the loaed argument variable
IL_0006: stloc.0
IL_0007: ldloca.s V_0
IL_0009: call instance float64 InOperator.SixteenBitStruct::get_D1()
# Pops the newly created argument into location 0, loads local variable 0 (new copy of SixteenBitStruct) and call the getter

Interesting! When we’ve called the method by ref, the resultant IL just loads the argument and calls the getter. When we’ve called the method by in, the resultant IL creates a copy of the struct before the getter is called. It seems that each time we’re referencing the property, C# is generating a copy of the object for us? We’re facing a by-design feature – a defensive copy.

Why do we encounter a defensive copy?

When calling the getter of our properties, the compiler doesn’t know if the getter mutates the object. Although this is a getter, it’s only by convention that changes aren’t made; there is no language construct that prevents us from changing values in our getter. The compiler must honor the in keyword and generate a defensive copy, just in case the getter modifies the struct.

In the end of the day, a getter is just syntactic sugar for a method. Of course, defensive copies will be generated if methods are called on the struct since the compiles can’t provide any guarantee that the method call won’t mutate the struct.

How do we get around this?

We’ll need instruct the compiler that our struct is immutable, so the compiler doesn’t need to worry about creating defensive copies since values cannot change. C# provides this exact functionality in fact! We can slap the “readonly” keyword (and drop any setters) so that we can guarantee that our struct is now immutable.

Here’s how it looks now

 public readonly struct SixteenBitStruct
{
    public double D1 { get; }
    public double D2 { get; }
}

Revisiting our performance numbers

Let’s re-run our benchmarks and assess the performance.

Method limit Mean Error StdDev
BenchmarkIncrementByRef 100000000 23.93 ms 0.1226 ms 0.1147 ms
BenchmarkIncrementByIn 100000000 24.06 ms 0.2183 ms 0.2042 ms

Far better! Performance is now equal (within margin of error). Some closing thoughts about this:

  • Using the in operator is an excellent feature – it allows the callers to safely assume that the values they are going to pass will not have their values changed.
  • Using the readonly modifier with a struct is another excellent feature – it allows the the developer to safely say that its value is immutable and no changes are allowed.
  • The performance uplift is should be considered as a bonus – the design and infrastructure wins using the in / readonly keywords in these context carry far more value.
  • Don’t ever use the in keyword in conjunction with non-readonly structs. Chances are that the performance gained from passing by ref will be lost by accessing the struct’s properties and methods.

Until the next one!

C# Micro Optimizations Part 1 – Ref Arguments

In this series of posts, we’ll be investigating key areas for micro-optimizations. As the title implies, these are micro-optimizations and may not be applicable for you unless you are writing some high-performance library of have a piece of code running in a tight loop. Nonetheless, it’s still fun to investigate and find these micro-optimizations. Onwards!

Let’s start with a simple one – the ref keyword in method arguments. For this argument, we’re only concerned with value type method arguments – structs.

Since structs are value types, by default, the entire struct is copied over to the callee, irrelevant of the size of the struct. If the struct is big, this is typically a bottleneck since a copy must be created and passed for each call. C# provides a method of overriding this behavior by using the ref keyword. If an argument is marked as ref, a pointer to the struct will be passed rather than an actual copy!

This brings two major advantages:

  • If the struct is bigger than 4 bytes (on a 32 bit machine) or 8 bytes (on a 64 bit machine), passing a struct by ref means that less data copying is taking place.
  • We avoid copying back the data – we do not need to return the data since a reference is passed rather than a copy of the struct.

Let’s see an example – lets consider a struct containing two doubles – a 16 byte struct. Let’s say we have two methods that increments one of the values for us (just to give the loop something to do and not get it optimised away).

One of them accepts a (copy of a) struct, increments its internal values and returns the copy back. This is passed by value, which is the default behavior for a struct.

The other method accepts a struct by ref and increments its internal values. There is no need to return the data back therefore no extra copies were needed. This is not the default behavior, so we’ll need to accompany it with the ref keyword.

The below is the source code in question – find the whole solution here: https://github.com/albertherd/csharpmopt1-ref

[CoreJob]
public class SixteenBytesStructBenchmark
{
    [Benchmark]
    [Arguments(1000000)]
    public void BenchmarkIncrementByRef(int limit)
    {
        SixteenBytesStruct value = new SixteenBytesStruct();
        int counter = 0;
        do
        {
            IncrementByRef(ref value);
            counter++;
        }
        while (limit != counter);
    }
    [Benchmark]
    [Arguments(1000000)]
    public void BenchmarkIncrementByVal(int limit)
    {
        SixteenBytesStruct value = new SixteenBytesStruct();
        int counter = 0;
        do
        {
            value = IncrementByVal(value);
            counter++;
        }
        while (limit != counter);
    }
    private void IncrementByRef(ref SixteenBytesStruct toIncrement)
    {
        toIncrement.d0++;
    }
    private SixteenBytesStruct IncrementByVal(SixteenBytesStruct toIncrement)
    {
        toIncrement.d0++;
        return toIncrement;
    }
}
public struct SixteenBytesStruct
{
    public long d0, d1;
}

The below is the time taken for 1000000 runs – this was executed using .NET core 2.2.1 – benchmarks done using BenchmarkDotNet

Method limit Mean Error StdDev
BenchmarkIncrementByRef 1000000 1.663 ms 0.0139 ms 0.0130 ms
BenchmarkIncrementByVal 1000000 2.872 ms 0.0155 ms 0.0145 ms

We can see that running this in a tight loop, doing the work by ref, in this case, is 72% faster! To what can we attribute this performance change? Let’s have a look at what’s happening behind the scenes.

Doing the work by value

Calling IncrementByVal

IL_000a: ldarg.0 # Load the “this” parameter on evaluation stack (implicit)
IL_000b: ldloc.0 # Load SixteenBytesStruct value on the stack (16 bytes worth of data) from location 0
IL_000c: call instance valuetype Ref.SixteenBytesStruct Ref.SixteenBytesStructBenchmark::IncrementByVal(valuetype Ref.SixteenBytesStruct) # Call IncrementByVal with the loaded arguments
IL_0011: stloc.0 #Captures the returned value and stores it in location 0

IncrementByVal Implementation

IL_0000: ldarga.s toIncrement # Load the argument’s address so processing can begin
..method work – removed for brevity
IL_001a: ldarg.1 # Load the value of the field back so it can be returned
IL_001b: ret

What’s happening here?

  • Push the value of SixteenBytesStruct ready to be captured by the upcoming method call
  • Call IncrementByVal
  • IncrementByVal loads the address of the received value from the caller and does the required work
  • Push the value of the SixteenByteStruct after the work has been done ready to be captured by the caller
  • IncrementByVal Returns
  • Pop the value from replace the value of SixteenBytesStruct with the new one

Doing the work by ref

Calling IncrementByRef

IL_000a: ldarg.0 # Load the “this” parameter on evaluation stack (implicit)
IL_000b: ldloca.s V_0 # Load SixteenBytesStruct’s address on the stack (8 bytes worth of data)
IL_000d: call instance void Ref.SixteenBytesStructBenchmark::IncrementByRef(valuetype Ref.SixteenBytesStructamp;) # Call IncrementByVal with the loaded arguments

IncrementByVal Implementation

IL_0000: ldarg.1 # Load the argument so processing can begin. We’re not calling ldarga.s since this already the struct’s address rather than the actual value
..method work – removed for brevity
IL_0018: ret # Return

What’s happening here?

  • Push the address of SixteenBytesStruct ready to be captured by the upcoming method call
  • Call IncrementByVal
  • IncrementByVal gets value received from the caller (the value is an address) and does the required work
  • IncrementByVal Returns

What does this mean?

One can obviously note that doing the work by ref has significantly less work to do:

  • The callee is pushing 8 bytes instead of 16 bytes
  • The callee loads 8 bytes onto the evaluation stack instead of 16 bytes
  • The callee doesn’t need to push the new value onto the evaluation stack
  • The callee doesn’t need to pop the stack and stored the updated value

Therefore, doing the work by ref is pushing less data when a method call takes place (maximum of 8 bytes, irrespective of the struct size) and is avoiding two data copy instructions, since it does not need to push and pop the new value since there are no return values.

If you increase the size of the struct, the performance gains would be even bigger, as shown in the below graph.

C#RefBenchmark

We can observe some useful information from this graph

  • When it comes to doing operations by ref, performance is basically equivalent all cross the board, irrelevant to the size of the struct.
  • 16 byte, 8 byte and 4 byte structs carry identical performance – they are just separated by the margin of error.
  • 16 byte, 8 byte and 4 byte structs are faster than 2 byte and 1 byte structs. In fact, 1 byte struct ends up clearly slower than a 2 byte struct! It’s very interesting to explore why 1 and 2 byte structs exhibit performance degradation.
  • The rest of the result show a consistent upward trend – which reflect the amount of data copying take place.

What’s very interesting is that a 4 byte integer operates faster by value when compared to 1 byte and 2 byte integers!