Monday, June 17, 2019

Shake from 10,000ft

Summary: A very high-level view of the engineering aspects of Shake.

The theory behind Shake is now well documented in the Build Systems a la Carte paper, but the engineering design of the system is not. This post is a high-level overview of Shake, from 10,000ft (the types are the types I'm thinking of in my mind - read the source code for the ground truth).

Data Storage

At it's heart, the Shake "database" (not really a database) stores a mapping from keys (k) to values (v). That mapping is stored on disk as a list of (k,v) pairs. When Shake computes a new value for k, it appends it to the end of the file. When Shake starts, it loads the list, keeping only the last value for any given k, and producing a Map k v. On disk, each entry is prefixed by its size, so if the file is truncated (e.g. machine shutdown), any trailing incomplete data can be discarded.

When operating in memory, Shake uses the data type Map k (Status v), with the definitions:

data Result v = Result
    {result :: v -- ^ the result associated with the Key
    ,built :: Step -- ^ when it was actually run
    ,changed :: Step -- ^ when it last changed
    ,depends :: [[Id]] -- ^ dependencies

data Status v
    = Loaded (Result v)
    | Running (Either SomeException (Result v) -> IO ())
    | Error SomeException
    | Ready (Result v)

Data is loaded in the Loaded state. When someone demands a key it moves to Running - anyone who subsequently demands it will be added to the callback. After the run completes it becomes either Error or Ready.

Execution Model

Shake runs values in the Action monad, which is a combination of some global state (e.g. settings), per-rule state (e.g. dependencies), continuation monad with IO underlying everything. The execution model of Shake is that every Action computation is either blocked waiting for a Running to complete, or queued/executing with the thread pool. The thread pool has a list of things to do and runs them in a given priority order, respecting parallelism constraints. Most threads start up, do a bit of work, block on a Running and leave it for another item in the thread pool to continue them.

To pause a thread we use continuations, meaning the most important operation on Action (which isn't available to users!) is:

captureRAW :: ((Either SomeException a -> IO ()) -> IO ()) -> Action a

This function stops an Action in its tracks, resuming it when the continuation is called. One invariant of Shake, which is (sadly!) not tracked by the type system is that every continuation passed to captureRAW must be called exactly once.

The symmetry between Running and captureRAW is deliberate, and convenient.

To kick start the thread pool, the user specifies things to run with action - a Shake program completes when all those initial action calls have completed.


The final piece of the puzzle is what Shake actually does to build a key. The core of Shake is abstract over the k and v, but Shake ships with an outer layer of around ten additional rule types -- the most important of which is files. Taking an idealised (and inefficient) file rule, we can think of it as mapping from file paths to file contents. To provide such a rule, we first declare the type mapping:

type instance RuleResult FilePath = String

And then declare the rule. The rule says how to take the key (the filename), whether its dependencies have changed, the old value (the old contents), and produce a new value (the current contents). In addition, the rule must say if the contents have changed in a meaningful way, which causes anyone who depended on them to rebuild.

Shake programs typically call apply which builds a list of keys in parallel, moving all the keys to Loaded (or at least one to Error) before continuing.

Hidden Complexity

There's a number of pieces I haven't mentioned but which hide quite a lot of complexity:

  • Shake operates on any k/v pair, but serialising arbitrary values is hard, so Shake needs to build mapping and translation tables to make that work.
  • Many rules are defined in terms of pattern matches - e.g. **/*.c - that matching logic is tricky.
  • Many rules ultimately call command line programs, so a flexible command line execution API is required.
  • The rules that Shake ships with are highly optimised and have to operate in a variety of circumstances, e.g. with --skip flags etc, so have a lot of cases in them.
  • Shake goes to a lot of effort to make binary serialisation fast, as otherwise that turns into a bottleneck.
  • Exceptions, parallelism and continuations aren't natural bedfellows - the combination requires some care and attention.
  • There are lots of utility functions, UI concerns, profiling features etc.
  • There are lots of tests. Shake is 17K lines of code, of which 4.5K lines is tests.

The Picture Version

Stepping back, the picture diagram looks like:

For all gory details see the source code.


Andy Adams-Moran said...

Typo in Results def? The line with the “built” field starts with a “{“ but should be a “,”

Andy Adams-Moran said...

Also in callback type in Running: too many parens.

Andy Adams-Moran said...

Picture clipped.

Neil Mitchell said...

Thanks Andy! Typo's fixed. The picture doesn't appear clipped for me on Chrome Windows and Chrome iOS - I'm expecting to see However, my CSS file predates markdown, and the HTML blogger generated for the image lacked some tags, so I've fixed all that up in the hope one of them caused it to clip.

meteficha said...

Cool write-up! Do you ever vacuum the data storage?

Neil Mitchell said...

Meteficha: if half the keys are stale (have the same key repeated later) we load everything into memory and write out a fresh storage (with careful tricks to make sure if this process aborts we don't lose anything). We never throw away an unused key, so if the build system changes significantly a clean of the storage may be worthwhile.