This article delves into the internal workings of SQLite's Virtual Machine (VM), specifically how it executes bytecode programs. It explains the interpreter loop, the VM's state encapsulated within the Vdbe object, and the role of VdbeCursors in managing data access. Understanding this low-level execution provides insight into how a robust, embedded database manages atomicity and state.
Read original on Dev.to #architectureSQLite, despite being a serverless, embedded database, employs a sophisticated virtual machine to execute SQL queries compiled into bytecode. This design choice contributes significantly to its reliability and atomicity. The VM ensures that operations are transactional, rolling back any pending transactions if an execution error occurs mid-way, thereby maintaining data consistency.
The heart of SQLite's VM is a simple yet powerful interpreter loop, implemented in the `sqlite3VdbeExec` function. It operates on a prepared statement (a `Vdbe` object) by iteratively fetching, decoding, and executing bytecode instructions. This deterministic loop, primarily a `for` loop containing a large `switch` statement for opcode handling, avoids complex scheduling or deep recursion, prioritizing simplicity and predictability.
sqlite3VdbeExecThe `Vdbe` object is central to the VM's operation, encapsulating all necessary state for program execution. This includes the array of bytecode instructions (`aOp`), the program counter (`pc`), a fixed-size register array (`aMem`) for runtime data, and structures for cursors and other bookkeeping. The pre-allocation of registers by the compiler rather than dynamic allocation during execution is a key design decision for performance and memory predictability.
Above the B-tree cursors, the VM uses `VdbeCursor` objects as an abstraction for data access. Each `VdbeCursor` points to a specific table or index B-tree and supports operations like seeking, iterating, reading, inserting, and deleting records. Their independence is crucial for complex queries involving joins and subqueries, allowing the VM to manage multiple data streams concurrently and consistently.