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Cache library that promotes keys and values into mochiglobal objects

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fling

Fling is an extraction of an idea in riak_core. The basic idea is a cache manager handles writes and reads to ETS for a period of time, and after the writes are over for a period of time, the manager "promotes" the ETS data into a dynamically constructed and loaded Erlang module.

Rationale

ETS is pretty fast already. Yes, it is. ETS also can have a long tail where get requests can take hundreds or thousands of microseconds instead of the typical 1-3 microseconds.

What we see by abusing the constant pools in Erlang modules is we can chop that latency tail significantly, down from a ceiling of mid-thousands of microseconds to (low) hundreds of microseconds. (Full benchmarks are in progress and forthcoming.)

Concept

The general idea is the caller creates and sets up an ETS table however she wants it to be. The table can be used as normal for inserts, lookups, etc.

At some point, the caller uses fling:manage/4 and fling begins to manage the ETS cache. After a number of ticks (default 5) of X seconds (default 5) fling builds, compiles and loads a module version of the data in ETS.

At that point, the caller can use the dynamically generated module to lookup values.

If a new write comes in, fling accepts the write on the ETS layer and purges the generated module - and begins a countdown to a new generated module.

Drawbacks

Well, first, this pattern does not work well for use cases where writes are frequent. It works best in situations where there is zero to very low write frequency and very high read concurrency.

It keeps two copies of your data around once the module has been loaded. One copy sits around in ETS, unused and unloved for the most part.

Second, the generated module(s) use entries in Erlang's finite atom table. It is possible to exhaust the atom table by creating too many fling modules. In general, each additional module takes 1 atom. The terms used in the generated module are the atoms term and all - so after the first module, the only additional atom is the name of the module itself.

Third, compiling a module takes a long time. For a module with 10000 entries, it takes about 5 wall-clock seconds to construct the abstract syntax tree, compile it into byte code and load it into the run time system.

Example

Here's a quick example to illustrate how this works.

Compile and start up

$ rebar get-deps
$ rebar compile
$ erl -pz ebin deps/*/ebin -s fling

Operation

1> Tid = ets:new(example, []).
2> ModName = fling:gen_module_name().
3> GetKey = fun({K, _V}) -> K end.
4> GetValue = fun({_K, V}) -> V end.
5> Pid = fling:manage(Tid, GetKey, GetValue, ModName).
6> fling:put(Pid, [{a,1},{b,2},{c,3}]).
7> ModeA = fling:mode(Tid, ModName).
8> fling:get(ModeA, a).
9> timer:sleep(60*1000).
10> ModeB = fling:mode(Tid, ModName).
11> fling:get(ModeB, a).
12> fling:get(ModeA, a) == fling:get(ModeB, a).

Basho Bench

If you want to characterize the performance of fling, there is a driver for it in the basho_bench framework. It's on the branch mra/fling.

You will need to update the code_paths directive in the configuration file to match your own filesystem layout.

Tests can be started like this:

$ ./basho_bench examples/fling.config

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