On F# and Object Oriented Guilt

I'm writing a key-value database in F#. Because clearly the world needs another key-value database, right?

Actually, I'm doing this to learn F#. I wanted a non-trivial piece of code to write. Something I already know a little bit about.

(My design is a log structured merge tree, conceptually similar to LevelDB or the storage layer of SQLite4. The code is on GitHub.)

As a starting point, I wrote the whole thing in C# first. Then I ported it to F#, in a mostly line-by-line port. My intention was (and still is) to use that port as a starting point, evolving the F# version toward a more functional design.

The final result may not become useful, but I should end up knowing a lot more about F# than I knew when I started.

Learning

Preceding all this code was a lot of reading. I spent plenty of time scouring fsharpforfunandprofit.com and fsharp.org and the F# stuff on MSDN and Stack Overflow.

I learned that F# is closely related to OCaml, about which I knew nothing. But then I learned that OCaml is a descendant of ML, which I vaguely remember from when I took CS 325 as an undergrad with Dr. Campbell. This actually increased my interest, as it tied F# back to a positive experience of mine. (OTOH, if I run across something called L# and find that it has roots in Prolog, my interest shall proceed no further.)

I learned that there is an F# community, and that community is related to (or is a subset of) the functional programming community.

And I picked up on a faint whiff of tension within that community, centered on questions about whether something is purely functional or not. There are purists. And there are pragmatists.

I saw nothing ugly. But I definitely got the impression that I had choices to make, and that I might encounter differing opinions about how I should make those choices.

I decided to just ignore all that and write code. This path has usually served me well.

So I started writing my LSM tree in C#.

Digression: What is a log structured merge tree?

The basic idea of an LSM tree is that a database is implemented as list of lists. Each list is usually called a "sorted run" or a "segment".

The first segment is kept in memory, and is the only one where inserts, updates, and deletes happen.

When the memory segment gets too large, it is flushed out to disk. Once a segment is on disk, it is immutable.

Searching or walking the database requires checking all of the segments. In the proper order -- for a given key, newer segments override later segments.

The more segments there are, the trickier and slower this will be. So we can improve things by merging two disk segments together to form a new one.

The memory segment can be implemented with whatever data structure makes sense. The disk segment is usually something like a B+tree, except it doesn't need to support insert/update/delete, so it's much simpler.

The C# version: OO Everywhere

It's all about ICursor.

public interface ICursor
{
    void Seek(byte[] k, SeekOp sop);
    void First();
    void Last();
    void Next();
    void Prev();
    bool IsValid();
    byte[] Key();
    Stream Value();
    int ValueLength();
    int KeyCompare(byte[] k);
}

(Credit to D. Richard Hipp and the SQLite developers. ICursor is more or less what you would get if you perused the API for the SQLite4 storage engine and translated it to C#.)

This interface defines the methods which can be used to search or iterate over one segment. It's an interface. It doesn't care about how that segment is stored. It could be a memory segment. It could be a disk segment. It could be something else, as long as it plays nicely and follows the rules.

I have three objects which implementat ICursor.

First, there is MemorySegment, which is little more than a wrapper around a System.Collections.Generic.Dictionary<byte[],Stream>. It has a method called OpenCursor() which returns an ICursor. Nothing too interesting here.

The bulk of my code is in dealing with segments on "disk", which are represented as B+trees. To construct a disk segment, call BTreeSegment.Create. Its parameters are a System.IO.Stream (into which the B+tree will be written) and an ICursor (from which the keys and values will be obtained).

To get the ICursor for that BTreeSegment, call BTreeSegment.OpenCursor().

The object that makes it all work is MultiCursor. This is an ICursor that has one or more subcursors. You can search or iterate over a MultiCursor just like any other. Under the hood, it will deal with all the subcursors and present the illusion that they are one segment.

And mostly that's it.

  • To search the database, open a MultiCursor on all the segments and call Seek().

  • To flush a memory segment to disk, pass its cursor to BTreeSegment.Create.

  • To combine any two (or more) segments into one, create a MultiCursor on them and pass it to BTreeSegment.Create.

As I said above, this is not a complete implementation. If this were "LevelDB in F#", there would need to be, for example, something that owns all these segments and makes smart decisions about when to flush the memory segment and when to merge disk segments together. That piece of code is currently absent here.

Porting to F#

Before I started the F# port, I did some soul searching about the overall design. ICursor and its implementations are very elegant. Would I have to give them up in favor of something more functional?

I decided to just ignore all that and write code. This path has usually served me well.

So I proceed to do the line-by-line port to F#:

  • I made a copy of the C# code, which I'll refer to as CsFading.

  • Then I started a new F# library project, which we might call FsGrowing.

  • I changed my xUnit test to reference CsFading instead of my actual C# version.

  • I added a reference from CsFading to [the initially empty] FsGrowing.

Then I executed the following loop:

while (!CsFading.IsEmpty())
{
    var piece = ChooseSomethingFromCFade();
    FsGrowing.AddImplementation(piece);
    CsFading.Remove(piece);
    GetTheTestsPassingAgain();
}

I started with this:

type ICursor =
    abstract member Seek : k:byte[] * sop:SeekOp -> unit
    abstract member First : unit -> unit
    abstract member Last : unit -> unit
    abstract member Next : unit -> unit
    abstract member Prev : unit -> unit
    abstract member IsValid : unit -> bool
    abstract member Key : unit -> byte[]
    abstract member Value : unit -> Stream
    abstract member ValueLength : unit -> int
    abstract member KeyCompare : k:byte[] -> int

And little by little, CsFading got smaller as FsGrowing got bigger.

It was very gratifying when I reached the point where the F# version was passing my test suite.

But I didn't celebrate long. The F# code was a mess. Lots of mutables. Plenty of if-then-else. Nulls. Mutable collections. While loops.

Basically, I had written C# using F# syntax. Even the pseudocode for my approach was imperative.

But there were plenty of positives as well. Porting the C# code to F# actually made the C# code better. It was like a very intensive code review.

And the xUnit tests got very cool when I configured them to run every test four times:

  • Use the C# version
  • Use the F# version
  • Use the C# version to write B+trees and the F# version to read them.
  • Use the F# version to write B+trees and the C# version to read them.

If nothing else, I had convinced myself that full interop between F# and C# was actually quite smooth.

Also, I didn't completely punt on functional stuff during the port. There were a few places where I changed things toward a more F#-ish approach. Here's a function that turned out kinda nicely:

let rec searchLeaf k min max sop le ge = 
    if max < min then
        if sop = SeekOp.SEEK_EQ then -1
        else if sop = SeekOp.SEEK_LE then le
        else ge
    else
        let mid = (max + min) / 2
        let kmid = keyInLeaf(mid)
        let cmp = compareKeyInLeaf mid k
        if 0 = cmp then mid
        else if cmp<0  then searchLeaf k (mid+1) max sop mid ge
        else searchLeaf k min (mid-1) sop le mid

It's a binary search of the sorted key list within a single leaf page of the B+tree. The SeekOp can be used to specify that if the sought key does not exist, the one just before it or after it should be returned.

And yes, searchLeaf would be more idiomatic if it were using pattern matching instead of if-then-else. But at least I got rid of the mutables and the loop and made it recursive! :-)

Anyway, I expected to reach this point with a clear understanding of what to do next. And I didn't have that.

Gleaning from the experience of others

In terms of timing, all of this happened just before and during the Xamarin Evolve conference (which, as I write this, ended today). The C# version was mostly written the week before the conference. The F# port was done during the conference.

And that moment where the F# version passed the test suite, leaving me clueless about how to proceed? That happened Wednesday.

On Thursday, Rachel Reese gave a fantastic session on F#. I left with the impression that maybe a little OO in my F# wasn't so bad.

On Friday, Larry O'Brien gave another fantastic session on F#. And I left with the even stronger impression that even though learning cool functional stuff is great, I don't have to be a functional pursit to benefit from F#.

I also found a fair amount of "Don't feel guilty about OO in F#" in a document called The F# Component Design Guidelines on fsharp.org.

Anyway, for now, ICursor will remain. Maybe there's a more functional way, but right now I don't know what that would look like.

So I'm going to just ignore all that and write code. This path has usually served me well.