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132 lines
5.5 KiB
Markdown
132 lines
5.5 KiB
Markdown
# Limbo Database System Design and Implementation
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This is a work-in-progress book on the design and implementation of Limbo.
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## Limbo Overview
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Limbo is an in-process OLTP database system with SQLite compatibility. Unlike
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client-server database systems such as PostgreSQL or MySQL, which require
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applications to communicate over network protocols for SQL execution, an
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in-process database is in your application memory space. This embedded
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architecture eliminates network communication overhead, allowing for the best
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case of low read and write latencies in the order of sub-microseconds.
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Limbo's architecture resembles SQLite's but differs primarily in its
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asynchronous I/O model. This asynchronous design enables applications to
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leverage modern I/O interfaces like `io_uring,` maximizing storage device
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performance. While an in-process database offers significant performance
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advantages, integration with cloud services remains crucial for operations
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like backups. Limbo's asynchronous I/O model facilitates this by supporting
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networked storage capabilities.
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The high-level interface to Limbo is the same as in SQLite:
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* SQLite query language
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* The `sqlite3_prepare()` function for translating SQL statements to programs
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("prepared statements")
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* The `sqlite3_step()` function for executing programs
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If we start with the SQLite query language, you can use the `limbo`
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command, for example, to evaluate SQL statements in the shell:
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```
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limbo> SELECT 'hello, world';
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hello, world
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```
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To execute this SQL statement, the shell uses the `sqlite3_prepare()`
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interface to parse the statement and generate a bytecode program, a step
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called preparing a statement. When a statement is prepared, it can be executed
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using the `sqlite3_step()` function.
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To illustrate the different components of Limbo, we can look at the sequence
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diagram of a query from the CLI to the bytecode virtual machine (VDBE):
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```mermaid
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sequenceDiagram
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participant main as cli/main
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participant Database as core/lib/Database
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participant Connection as core/lib/Connection
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participant Parser as sql/mod/Parser
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participant translate as translate/mod
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participant Statement as core/lib/Statement
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participant Program as vdbe/mod/Program
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main->>Database: open_file
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Database->>main: Connection
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main->>Connection: query(sql)
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Note left of Parser: Parser uses vendored sqlite3-parser
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Connection->>Parser: next()
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Note left of Parser: Passes the SQL query to Parser
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Parser->>Connection: Cmd::Stmt (ast/mod.rs)
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Note right of translate: Translates SQL statement into bytecode
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Connection->>translate:translate(stmt)
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translate->>Connection: Program
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Connection->>main: Ok(Some(Rows { Statement }))
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note right of main: a Statement with <br />a reference to Program is returned
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main->>Statement: step()
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Statement->>Program: step()
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Note left of Program: Program executes bytecode instructions<br />See https://www.sqlite.org/opcode.html
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Program->>Statement: StepResult
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Statement->>main: StepResult
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```
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To drill down into more specifics, we inspect the bytecode program for a SQL
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statement using the `EXPLAIN` command in the shell. For our example SQL
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statement, the bytecode looks as follows:
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```
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limbo> EXPLAIN SELECT 'hello, world';
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addr opcode p1 p2 p3 p4 p5 comment
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---- ----------------- ---- ---- ---- ------------- -- -------
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0 Init 0 4 0 0 Start at 4
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1 String8 0 1 0 hello, world 0 r[1]='hello, world'
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2 ResultRow 1 1 0 0 output=r[1]
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3 Halt 0 0 0 0
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4 Transaction 0 0 0 0
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5 Goto 0 1 0 0
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```
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The instruction set of the virtual machine consists of domain specific
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instructions for a database system. Every instruction consists of an
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opcode that describes the operation and up to 5 operands. In the example
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above, execution starts at offset zero with the `Init` instruction. The
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instruction sets up the program and branches to a instruction at address
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specified in operand `p2`. In our example, address 4 has the
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`Transaction` instruction, which begins a transaction. After that, the
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`Goto` instruction then branches to address 1 where we load a string
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constant `'hello, world'` to register `r[1]`. The `ResultRow` instruction
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produces a SQL query result using contents of `r[1]`. Finally, the
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program terminates with the `Halt` instruction.
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## Frontend
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### Parser
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The parser is the module in the front end that processes SQLite query language input data, transforming it into an abstract syntax tree (AST) for further processing. The parser is an in-tree fork of [lemon-rs](https://github.com/gwenn/lemon-rs), which in turn is a port of SQLite parser into Rust. The emitted AST is handed over to the code generation steps to turn the AST into virtual machine programs.
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### Code generator
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The code generator module takes AST as input and produces virtual machine programs representing executable SQL statements. At high-level, code generation works as follows:
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1. `JOIN` clauses are transformed into equivalent `WHERE` clauses, which simplifies code generation.
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2. `WHERE` clauses are mapped into bytecode loops
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3. `ORDER BY` causes the bytecode program to pass result rows to a sorter before returned to the application.
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4. `GROUP BY` also causes the bytecode programs to pass result rows to an aggregation function before results are returned to the application.
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### Query optimizer
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## Virtual Machine
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## Pager
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## I/O
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