active_standby 0.9.2

A concurrency primitive for high concurrency reads.
Documentation
A concurrency library for high concurrency reads.

This library is named after the 2 (identical) tables that we hold internally:
- Active - this is the table that all Readers view. This table will never be
  write locked, so readers never face contention.
- Standby - this is the table the the Writer mutates. A writer should face
  minimal contention retrieving this table for mutation since Readers move to
  the Active table when the tables are swapped.

The cost of providing no contention to readers, and minimal contention to
writers is:
1. Memory - Internally we hold 2 copies of the underlying type the user created.
   This is needed to allow there to always be a table that Readers can check out
   without contention.
2. Writer thread CPU usage - The writer must apply all updates twice, once to
   each table. Lock contention for the writer should be less than with a plain
   RwLock due to Readers using the active_table.

The usage is meant to be similar to a RwLock. Some of the inspiration came from
the [left_right](https://crates.io/crates/left-right) crate, so feel free to
check that out. The main differences focus on trying to simplify the client
(creating data structures) and user (using data structures) experiences;
primarily focused on trying to mimic the API/usage of an RwLock.

There are 2 flavors of this algorithm that we offer:
1. Lockless - this variant trades off increased performance against changing the
   API to be less like an RwLock. This avoids the cost of performing
   synchronization on reads, but this requires that each thread/task that is
   going to access the tables, registers in advance. Therefore this centers
   around the AsLockHandle, which is conceptually similar to Arc\<RwLock> (i.e.
   you clone the AsLockHandle and pass the new one to other threads).
2. Shared - this centers around using an AsLock, which is meant to feel like an
   RwLock. These structs can be shared between threads by cloning & sending an
   Arc\<AsLock> (like with RwLock). The main difference is that instead of using
   AsLock\<Vec\<T>>, you would use vec::shared::AsLock\<T>. This is because both
   tables must be updated, so users can't just dereference and mutate the
   underlying table.

An example of where the shared variant can be preferable is a Tonic service.
There you don't spawn a set of tasks/threads where you can pass each of them an
AsLockHandle. You can use an AsLock though and receive a similar experience.

A result of having the two separate tables is that batching becomes more viable.
You can grab a ReadGuard, and handle multiple requests without worrying about
starving the writer since the writer can work on the standby table, as opposed
to with an RwLock. This means multiple requests can be handled without having to
relock the active_table. Similarly you can batch with the Writer without
starving the Readers.

We provide 2 modules:
1. primitives - The components used to build data structures in the
   active_standby model. Users usually don't need to utilize the primitives and
   can instead either utilize the pre-made collections, or generate the wrapper
   for their struct using one of the macros and then just implement the mutable
   API for the generated WriteGuard.
2. collections - Shared and lockless active_standby structs for common
   collections. Each table type has its own AsLock (shared) / AsLockHandle
   (lockless), as opposed to RwLock where you simply pass in the table. This is
   because users can't simply gain write access to the underlying table and then
   mutate it. Instead mutations are done through UpdateTables so that both
   tables will be updated.

Example:
```rust
use std::thread::sleep;
use std::time::Duration;
use std::sync::Arc;
use active_standby::primitives::UpdateTables;

// Client's must implement the mutable interface that they want to offer users
// of their active standby data structure. This is not automatically generated.
struct AddOne {}
impl<'a> UpdateTables<'a, i32, ()> for AddOne {
    fn apply_first(&mut self, table: &'a mut i32) {
        *table = *table + 1;
    }
    fn apply_second(mut self, table: &mut i32) {
        self.apply_first(table);
    }
}

pub mod lockless {
    active_standby::generate_lockless_aslockhandle!(i32);

    impl<'w> WriteGuard<'w> {
        pub fn add_one(&mut self) {
            self.guard.update_tables(super::AddOne {})
        }
    }
}

pub mod shared {
    active_standby::generate_shared_aslock!(i32);

    impl<'w> WriteGuard<'w> {
        pub fn add_one(&mut self) {
            self.guard.update_tables(super::AddOne {})
        }
    }
}

fn run_lockless() {
    let table = lockless::AsLockHandle::new(0);
    let table2 = table.clone();
    let handle = std::thread::spawn(move || {
        while *table2.read() != 1 {
            sleep(Duration::from_micros(100));
        }
    });

    {
        let mut wg = table.write();
        wg.add_one();
    }
    handle.join();
}

fn run_shared() {
    let table = Arc::new(shared::AsLock::new(0));
    let table2 = Arc::clone(&table);
    let handle = std::thread::spawn(move || {
        while *table2.read() != 1 {
            sleep(Duration::from_micros(100));
        }
    });

    {
        let mut wg = table.write();
        wg.add_one();
    }
    handle.join();
}

fn main() {
    run_lockless();
    run_shared();
}
```

If your table has large elements, you may want to save memory by only holding
each element once (e.g. vec::AsLockHandle\<Arc\<i32>>). This can be done safely so
long as no elements of the table are mutated, only inserted and removed. Using a
vector as an example, if you wanted a function that increases the value of the
first element by 1, you would not increment the value behind the Arc. You would
reassign the first element to a new Arc with the incremented value.