Posts June 2026
34 posts
A Bloom filter is a bit array plus k hashes. It can say definitely not in the set, or maybe yes. False positives are the trade for tiny memory — never a false negative.
Read MoreUse TreeSet and TreeMap when keys must stay sorted — O(log n) red-black trees, Navigable ceiling/floor, and a Comparator that stays consistent with equals.
Read MoreA skip list is a layered linked list where higher levels skip ahead. Expected O(log n) search without tree rotations — Redis and ConcurrentSkipListMap use this idea.
Read MoreUse PriorityQueue when you need the next-best element in O(log n) — a heap, not a sorted list, and not a FIFO queue.
Read MoreHands-on lsof recipes for everyday work — find which processes hold files open, bind ports, or leak file descriptors.
Read MoreA Fenwick tree (BIT) stores prefix aggregates in an array using least-significant-bit jumps. Point update and prefix query in O(log n) with less machinery than a segment tree.
Read MoreUse LinkedHashMap when a hash map must iterate in insertion order — or access order with removeEldestEntry for a bounded LRU.
Read MoreA segment tree stores aggregates of array ranges in a binary tree of intervals. Point update and range query in O(log n) without walking the whole slice each time.
Read MoreUse LinkedList only when you need List and Deque on the same nodes — and why it usually loses to ArrayList for indexes and ArrayDeque for ends.
Read MoreHands-on chmod, chown, and umask recipes — decode numeric vs symbolic modes, fix ownership, and understand default permissions for new files.
Read MoreDisjoint sets with find and union: path compression and union by rank so “are these two in the same component?” stays nearly O(1) without storing an adjacency list.
Read MoreUse ArrayDeque as the default deque — a resizable ring buffer for stack and queue work without Vector, Stack, or LinkedList.
Read MoreA trie stores strings by shared prefixes. Autocomplete and dictionary lookup become a walk down characters — not a scan of every word.
Read MoreUse HashMap as the default Map — hash spreading, buckets, treeify, resize, and why a mutable key makes an entry disappear.
Read MoreA graph is vertices and edges. Adjacency list vs matrix, directed vs undirected, weighted vs not — choose the representation before you think about an algorithm.
Read MoreHands-on xargs recipes for everyday work — feed find and grep into commands, batch safely, and place arguments where they belong.
Read MoreUse HashSet for uniqueness and LinkedHashSet when uniqueness still needs insertion order — both are HashMap wrappers, and neither is a sorted set.
Read MoreA binary heap is a complete tree in an array that keeps the next-best element at the root. Min vs max, PriorityQueue in the JDK, and why you will hear Fibonacci heap without implementing one.
Read MoreUse ArrayList as the default List — amortized append, O(1) get, ensureCapacity, and the fail-fast iterator — and know when growth copies the whole array.
Read MoreA B-tree packs many keys per node so one disk page is one hop. Why databases and filesystems use this shape, and how B+ trees keep values in the leaves.
Read MoreHands-on journalctl recipes for everyday work — filter by unit, severity, time range, and boot, then read the results with confidence.
Read MoreUse Map as mappings, not a Collection — get/put, compute and merge, and the keySet/values/entrySet views that write through to the same storage.
Read MoreA red-black tree is a BST painted with color rules that keep height logarithmic without AVL’s strict balance. Why TreeMap and TreeSet use this shape.
Read MoreUse Queue and Deque when the job is the ends — offer/poll versus add/remove, exception versus special value, and why indexes are the wrong primitive.
Read MoreAn AVL tree is a BST that rebalances on insert and delete so height stays O(log n). Balance factors, rotations, and when the extra strictness is worth it versus red-black.
Read MoreHands-on sed recipes for everyday work — substitute text, delete lines, edit files in place, and reshape output in pipelines.
Read MoreUse Set when uniqueness is the job — equals-based membership, no indexes, and why List.contains is the wrong uniqueness type.
Read MoreA BST keeps left < node < right so search is O(height). Why already-sorted inserts become a linked list, and what that does to the bill.
Read MoreUse List as an indexed contract — get/set, subList views, sort/replaceAll, and RandomAccess — without treating every List like an ArrayList.
Read MoreA binary tree is a hierarchical layout: left, right, parent. Height vs size, preorder inorder postorder and level-order as operations of the shape, and what balanced actually promises.
Read MoreThe set ADT is unique membership. HashSet delivers it with a hash table; List.contains is a scan. When TreeSet belongs instead, and what you lose (order).
Read MoreUse Collection and Iterator as the shared contract — optional operations, fail-fast iteration, bulk methods, and removeIf — before you pick ArrayList or HashSet.
Read MoreHands-on ps and pgrep recipes — locate processes by PID, user, memory footprint, or command path without a live monitor.
Read MoreThe Java Collections Framework as a map: hierarchy, glossary, a nulls-order-threads matrix, and a living catalog of every post in this series.
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