indexing

## What I do - Design efficient indexes - Choose index types - Optimize query performance ## When to use me When creating database indexes. ## Index Types ### B-Tree Index ```python class BTreeIndex: """B-Tree index implementation""" def __init__(self, order: int = 3): self.root = BTreeNode(order) self.order = order def insert(self, key: any, value: any): """Insert key-value pair""" root = self.root if root.is_full(): new_root = BTreeNode(self.order) new_root.children.append(self.root) new_root.split_child(0) self.root = new_root self.root.insert_non_full(key, value) def search(self, key: any) -> any: """Search for key""" return self.root.search(key) ``` ### Hash Index ```python class HashIndex: """Hash-based index""" def __init__(self, size: int = 100): self.buckets = [[] for _ in range(size)] self.size = size def _hash(self, key: any) -> int: return hash(key) % self.size def insert(self, key: any, value: any): """Insert with hash collision handling""" bucket = self._hash(key) self.buckets[bucket].append((key, value)) def search(self, key: any) -> any: """Search for key""" bucket = self._hash(key) for k, v in self.buckets[bucket]: if k == key: return v return None ``` ### Composite Index ```python class CompositeIndex: """Multi-column index""" def __init__(self, columns: List[str]): self.columns = columns self.index = {} def create_key(self, row: dict) -> tuple: """Create composite key from row""" return tuple(row.get(col) for col in self.columns) def insert(self, row: dict): """Insert row into index""" key = self.create_key(row) self.index[key] = row def search(self, **criteria) -> List[dict]: """Search using partial key""" partial = tuple(criteria.get(col) for col in self.columns) return [row for key, row in self.index.items() if key[:len(partial)] == partial] ``` ### Index Selection ```python class IndexSelector: """Choose appropriate indexes""" @staticmethod def recommend_indexes(queries: List[dict]) -> List[dict]: """Recommend indexes based on queries""" recommendations = [] for query in queries: if "WHERE" in query: recommendations.append({ "columns": query["where_columns"], "type": "btree", "reason": "Equality/range query" }) if "ORDER BY" in query: recommendations.append({ "columns": query["order_columns"], "type": "btree", "reason": "Sort optimization" }) return recommendations ```