Overview
Hash Lookup uses a hash table so key search usually avoids scanning or sorted comparisons.
CoreSource checked
Hash Lookup
Finds values by hashing keys directly to likely storage locations.
Quick Facts
Compact metadata for implementation and discovery.
- Category
- Searching
- Difficulty
- Beginner
- Family
- Hash-Based Search
- Tier
- Core
- Status
- Verified
- Review
- Source Checked
- Sources
- 1
- Formulas
- 0
- Relationships
- 2
- Code example
- Ready
- Visualization
- Ready
- Aliases
- Hash Search
Core Concepts
candidate searchhash functionhash lookupstored invarianthash-based searchcandidate spacematch testsearch interval
Quick facts
Complexity
Runtime and memory behavior at a glance.
Best
O(1)
Average
O(1)
Worst
O(n)
Space
O(1)
When to Use
- Use Hash Lookup when you need to hash a key into a table position.
- Use it when the input assumptions match the method's model.
- Use it when you need a clear lookup strategy for known input organization.
- Use it when the method's tradeoffs fit the workload.
When Not to Use
- Avoid it when maintaining the required data layout costs more than the lookup saves.
- Do not treat the O(1) average case as a guarantee; check the O(n) worst case.
- Avoid it when the required output is not associated value.
What It Does
- Hashes a key into a table position
- Checks the matching bucket for the key
Use Cases
- Dictionary lookup
- Set membership
- Caching and memoization
Inputs
- Key
- Hash table
Outputs
- Associated value
- Missing-key result
Pseudocode
- 1.Hash the key
- 2.Map the hash to a bucket
- 3.Check entries in that bucket
- 4.Return the matching value or a missing result
Canonical Example
- Input
- values = [2, 5, 8, 12, 16], target = 12
- Output
- index = 3
- Explanation
- Hash Lookup: The search checks candidate positions until it identifies the target value.
Implementation Notes
- Keep the input contract explicit: Key; Hash table.
- Choose hash and equality behavior together so equal keys land in the same lookup path.
- Decide up front whether not-found results return null, -1, false, or an insertion position.
- Search algorithms should define both success and failure semantics.
Common Pitfalls
- Worst-case lookup depends on collision behavior and table load.
- Using an unstable or poorly distributed hash function can create clustered buckets or wrong comparisons.
- Handle empty, invalid, and boundary inputs before trusting associated value.
- Off-by-one bounds, duplicates, and missing-target behavior should be specified before implementation.
Interactive Mechanism Walkthrough
Indexed Interval & Boundary ProbeShow a key jumping directly to a bucket through a hash value.
Target key: 41low=0, mid=4, high=9
4[0]
9[1]
15[2]
22[3]
27[4]
34[5]
41[6]
49[7]
58[8]
63[9]
Step 1 of 4: Hash the key
hash-lookupNotes
Hash Lookup operates in O(1) time and O(1) space within the Hash-Based Search family. Often compared with Hash Table and Linear Search.
Sources (1)
What each reference supports for this entry.
Introduction to Algorithms (CLRS)
BookAlgorithms textbook support for Hash Lookup invariants, search ordering, correctness argument, or asymptotic analysis.
Open sourceExplore Next
Good next jumps from the relationship graph, ranked for useful discovery.
Relationships
View full relationship pageUsesHash Table
Hash lookup is the query operation implemented by hash table storage.
Related Algorithms
Tags
SearchHashingHash BasedData Structure