//! The `dbsp` crate implements a computational engine for continuous analysis
//! of changing data.  With DBSP, a programmer writes code in terms of
//! computations on a complete data set, but DBSP implements it incrementally,
//! meaning that changes to the data set run in time proportional to the size of
//! the change rather than the size of the data set.  This is a major advantage
//! for applications that work with large data sets that change frequently in
//! small ways.
//!
//! The [`tutorial`] is a good place to start for a guided tour.  After that, if
//! you want to look through the API on your own, the [`circuit`] module is a
//! reasonable starting point.  For complete examples, visit the [`examples`][1]
//! directory in the DBSP repository.
//!
//! [1]: https://github.com/feldera/feldera/tree/main/crates/dbsp/examples
//!
//! # Theory
//!
//! DBSP is underpinned by a formal theory:
//!
//! - [Budiu, Chajed, McSherry, Ryzhyk, Tannen. DBSP: Automatic Incremental View
//!   Maintenance for Rich Query Languages, Conference on Very Large Databases, August
//!   2023, Vancouver, Canada](https://www.feldera.com/vldb23.pdf)
//!
//! - Here is [a presentation about DBSP](https://www.youtube.com/watch?v=iT4k5DCnvPU)
//!   at the 2023 Apache Calcite Meetup.
//!
//! The model provides two things:
//!
//! 1. **Semantics.** DBSP defines a formal language of streaming operators and
//!    queries built out of these operators, and precisely specifies how these
//!    queries must transform input streams to output streams.
//!
//! 2. **Algorithm.** DBSP also gives an algorithm that takes an arbitrary query
//!    and generates an incremental dataflow program that implements this query
//!    correctly (in accordance with its formal semantics) and efficiently. Efficiency
//!    here means, in a nutshell, that the cost of processing a set of
//!    input events is proportional to the size of the input rather than the entire
//!    state of the database.
//!
//! # Crate overview
//!
//! This crate consists of several layers.
//!
//! * [`dynamic`] - Types and traits that support dynamic dispatch.  We heavily rely on
//!   dynamic dispatch to limit the amount of monomorphization performed by the compiler when
//!   building complex dataflow graphs, balancing compilation speed and runtime performance.
//!   This module implements the type machinery necessary to support this architecture.
//!
//! * [`typed_batch`] - Strongly type wrappers around dynamically typed batches and traces.
//!
//! * [`trace`] - This module implements batches and traces, which are core DBSP data structures
//!   that represent tables, indexes and changes to tables and indexes.  We provide both in-memory
//!   and persistent batch and trace implementations.
//!
//! * [`operator::dynamic`] - Dynamically typed operator API. Operators transform data streams
//!   (usually carrying data in the form of batches and traces).  DBSP provides many relational
//!   operators, such as map, filter, aggregate, join, etc.  The operator API in this module is
//!   dynamically typed and unsafe.
//!
//! * [`operator`] - Statically typed wrappers around the dynamic API in [`operator::dynamic`].

#![allow(clippy::type_complexity)]

pub mod dynamic;
mod error;
mod hash;
mod num_entries;
//mod ref_pair;

pub mod typed_batch;

#[macro_use]
pub mod circuit;
pub mod algebra;
pub mod ir;
pub mod mimalloc;
pub mod monitor;
pub mod operator;
pub mod profile;
pub mod storage;
pub mod time;
pub mod trace;
pub mod utils;

#[cfg(feature = "backend-mode")]
pub mod mono;

pub use crate::{
    error::{DetailedError, Error},
    hash::default_hash,
    num_entries::NumEntries,
};
// // pub use crate::ref_pair::RefPair;
pub use crate::time::Timestamp;

pub use algebra::{DynZWeight, ZWeight};

pub use circuit::{
    ChildCircuit, Circuit, CircuitHandle, DBSPHandle, NestedCircuit, RootCircuit, Runtime,
    RuntimeError, SchedulerError, Stream,
};
#[cfg(not(feature = "backend-mode"))]
pub use operator::FilterMap;
pub use operator::{
    input::{IndexedZSetHandle, InputHandle, MapHandle, SetHandle, ZSetHandle},
    CmpFunc, OrdPartitionedIndexedZSet, OutputHandle,
};
pub use trace::{DBData, DBWeight};
pub use typed_batch::{
    Batch, BatchReader, FallbackKeyBatch, FallbackValBatch, FallbackWSet, FallbackZSet,
    FileIndexedWSet, FileIndexedZSet, FileKeyBatch, FileValBatch, FileWSet, FileZSet, IndexedZSet,
    OrdIndexedWSet, OrdIndexedZSet, OrdWSet, OrdZSet, Trace, TypedBox, ZSet,
};

#[cfg(doc)]
pub mod tutorial;

// TODO: import from `circuit`.
pub type Scope = u16;
