Project : Implement SQL-RDBMS from Scratch in C/C++

Discover the project architecture for implementing an rdbms from scratch, leveraging a ready-made b+3 library, a sql parser and engine, a sql interface, and a mathematical expression library.

Understand why the RDBMS project relies on mathematical expression computations by showing how select clauses compute algebraic expressions, where clauses use logical expressions, and the library parses and evaluates them.

Understand how a typical sql query executes from linear scan, apply where filters, group by address with a hash table, compute max salary, and apply having, order by, and limit.

Parse sql queries to classify as select, update, or delete, then generate tokens mapped to sql enums. Define exhaustive keywords, identifiers, and operators in sql enums.h to drive execution.

Explore the SQL enums header, defining generic and specific enums for SQL tokens, data types, operators, keywords, and aggregate functions, to support parsing and extension.

Set up a SQL parser by implementing a main dot c that reads user input and routes create table SQL queries to a dedicated create parser file.

Parse create table statements, link object files with the lexical parser library, build dbms.exe, and verify decimal or double data types while catching errors and encouraging thorough bug fixes.

Explore B+ trees as the core in-memory structure for relational databases. Understand internal nodes with keys and child pointers, and leaf nodes with data pointers and linked traversal.

Explore how a B+ tree adapts to a relational database system, illustrating key serialization and memory layout, and how leaf and internal nodes organize primary keys during SQL table creation.

Learn to integrate a B+ tree library into a C/C++ project, compile with g++ and use CRUD APIs to build an SQL-backed data store.

Define data type enums, model SQL table keys, build a key metadata array for simple and composite keys, and initialize a B+ tree via its API.

Implement a B+ tree key comparison function using a key metadata array and schema data array size, comparing multi-element keys by type and returning -1, 0, or 1 for operations.

Move the main dot C function into a new B+ tree comparison file and rename it the RDBMS key comparison function. Update headers to use SQL enums.

Implement a schema table using a B+ tree to store SQL create table metadata, insert new tables into the catalog, and initialize schema and record tables from the create data.

Implement function by iterating over each column in the C data object, building a key from the column name, populating a schema record, and inserting rows into the schema table.

We implement the record table for the employee SQL table using a B+ tree. If no primary key is provided, return an error and release allocated resources.

Explore the drop table SQL query within the project to implement an SQL-RDBMS from scratch in C/C++.

Define the Idata structure to hold insert into query data, including the table name and column values, with SQL value T as a union for string, int, or double.

Explains implementing the insert into query algorithm, building the key and record from the Idata, validating against the catalog and schema, and inserting into the B+ tree.

Implement the sql insert operation by validating the catalog table, computing key and record sizes, building buffers, checking for duplicates, and inserting with success or error messages.

Evaluate the SQL-RDBMS project implemented in C/C++ at this stage by testing core modules to ensure correctness and readiness for next development steps.

Resolve the enum mismatch between the RDBMS and the expression library by converting sql enum codes to mxpr cp enums with a single converter function.

Explore how linking connects library code to an application, where a static library (.a) with unimplemented foo is completed by the application main to form an executable.

Implement a converter function in the RDBMS app to map SQL enums to the mathematical expression library enums and wire it into the expression parser.

Explore implementing sql select queries as the project’s core, covering where, group by, having, order by, limit, joins, and a rich set of operators and data types.

Explain how select queries rely on mathematical expression trees, parsing expressions from a table into trees and storing results in a query execution plan, with wrappers in the SQL interface.

Implement an API to parse input using a lexical parser, build a mathematical expression tree via the expression library, validate it, and return a pointer with infix to postfix conversion.

Define a query execution plan data structure in shp dot h to store select query attributes, including table names (single or joined) and the expression tree for each column.

Develop a select query parser using a context free grammar, parsing mathematical expressions into expression trees, storing results in a global select structure, and handling a single table.

Test the select query parser by running queries with mathematical expressions (min, max, sine, pow) and multiple tables, validating successful parsing and error handling for unrecognized functions.

Explore implementing the full join operation by forming all possible record combinations from multiple tables, using nested loops and runtime-determined iteration over n lists.

Define the giant row data structure in rdbms struct.h, forward declare the B plus key for a join row pointer, and implement memory management in ship.

Explore stateful iterators for B+ trees and use the Getnext API to iterate leaf nodes left to right, preparing for implementing a join operation in the project.

Explain implementing the join API in c/c++ using two table_iterators: first and next, with a recursive, nested-loop approach that updates the join row from the first and next records.

Run the join api to verify correct join results and print the resulting join rows. Create two simple one-field tables with three values each to observe the nine cross-join records.