Bucket
A bucket is a grouping or storage unit to which data or items are assigned according to a criterion, range, hash, or partitioning scheme.
D3.js in Action, Third Edition
A bin is an interval or group in a distribution that contains data points with values within specified boundaries.
- How it is used
- Groups distribution values into ranges before rendering histograms and violin plots.
- How deep it goes
- Defines buckets, inspects their D3 array boundaries, and walks through histogram and violin-plot rendering.
- Examples
- Uses survey salary brackets, histogram rectangles, and role-based violin plots.
- What you can do after
- Apply it via D3 d3.bin() to preprocess values and render or update distribution charts.
Statistics Slam Dunk
A bin is an interval used to group continuous numeric observations when tabulating or plotting their frequencies.
- How it is used
- Uses intervals to visualize continuous distributions and convert numeric measures into grouped analytical categories.
- How deep it goes
- Defines buckets, recommends a selection rule, demonstrates R implementation, and cautions against relying on visual normality alone.
- Examples
- Demonstrates 15-bin NBA points histograms, paired games-and-wins histograms, and Gini coefficient bands for winning percentages.
- What you can do after
- Apply it via ggplot2 by selecting bucket counts, plotting frequencies, and grouping numeric measures for comparison.
Write Powerful Rust Macros
A bucket is a cloud-infrastructure storage resource that holds collections of objects or similar data.
- How it is used
- Declares named cloud storage and optionally routes its object events to a Lambda function.
- How deep it goes
- Works through parsing a required name and event marker, then defers production retries and state management.
- Examples
- Uses `iac! { bucket unique }`, parser error cases, and bucket-to-Lambda event linking.
- What you can do after
- Build it from scratch as a parsed DSL resource that creates an AWS bucket and optionally links an event target.
Outlier Detection in Python
A bin is an interval or category into which observations are grouped for a histogram or related distribution summary.
- How it is used
- Uses buckets to summarize feature distributions for univariate outlier scoring and synthetic-data generation.
- How deep it goes
- Explains bucket centers, frequencies, probabilities, jitter, and resolution trade-offs, but stops short of deriving optimal bin widths.
- Examples
- Uses speech-feature histograms for HBOS and baseball-feature histograms for synthetic-data generation.
- What you can do after
- Apply buckets via NumPy histograms to score unusual values or sample approximate feature distributions.
Amazon Web Services in Action, Third Edition: An in-depth guide to AWS
A data bucket is a partition containing a subset of the data in a sharded cache.
- How it is used
- Defines a subset of cached data used when sharding distributes keys across nodes.
- How deep it goes
- Explains bucket placement through shards and client-side hashing, but does not detail the hashing algorithm.
- Examples
- Uses an overloaded cache node as the scenario for deciding whether to shard.
- What you can do after
- Evaluate/understand when splitting cached data across nodes may increase capacity.
Read how Amazon Web Services in Action, Third Edition: An in-depth guide to AWS explains bucket →
100 Go Mistakes and How to Avoid Them
A bucket is an internal map storage unit that holds a fixed group of key-value entries and may be supplemented by overflow buckets.
- How it is used
- Explains map collisions, overflow, memory retention after deletion, and shared-bucket mistakes during concurrent access.
- How deep it goes
- Explains eight-element buckets, hash placement, overflow links, and non-shrinking storage, while stopping short of runtime implementation details.
- Examples
- Uses collision figures, one-million-entry memory measurements, a customer cache, and concurrent balance-map code.
- What you can do after
- Diagnose retained map memory and shared-bucket races, then choose locking or deep copying based on iteration cost.
Read how 100 Go Mistakes and How to Avoid Them explains bucket →
Build and Orchestrator in Go (From Scratch)
A bucket is a named grouping of key-value pairs within a BoltDB database.
- How it is used
- Organizes persistent task key-value pairs within BoltDB and gives store operations a named data namespace.
- How deep it goes
- Explains naming, creation, transactional access, serialization, retrieval, and enumeration without descending into BoltDB internals.
- Examples
- Uses tasks and events buckets in database files such as tasks.db, events.db, and worker-specific task files.
- What you can do after
- Operate/configure a named BoltDB bucket through task-store creation, insertion, lookup, listing, counting, and reopening.
Read how Build and Orchestrator in Go (From Scratch) explains bucket →
Just Use Postgres!
A time bucket is a fixed temporal interval used to group time-series observations for aggregation.
- How it is used
- Groups time-series observations into intervals for charts, summaries, rollups, and threshold-based monitoring.
- How deep it goes
- Explains interval assignment, grouping, aggregation, origin, timezone, offset, and continuous-aggregate storage without deeper implementation internals.
- Examples
- Demonstrates workout charts, weekly activity summaries, shifted weekly origins, local-time calculations, and low-heart-rate detection.
- What you can do after
- Apply it via TimescaleDB's time_bucket function to write interval-based SQL summaries and monitoring queries.
DuckDB in Action
A time bucket is a fixed-width temporal interval to which timestamped observations are assigned for grouped analysis.
- How it is used
- Normalizes inconsistent timestamp intervals while aggregating sensor readings during ingestion.
- How deep it goes
- Explains timestamp truncation, optional alignment, grouping, cleaning, and post-ingestion cleanup, but defers broader date-time functions.
- Examples
- Demonstrates one-minute and five-minute source files, 15-minute power averages, and quarter-hour DELETE cleanup.
- What you can do after
- Apply it via DuckDB SQL to group timestamped readings into fixed intervals during ingestion.
Related concepts
- object storepart of · An object store is a storage system that stores and retrieves data as independently addressable objects containing content and associated metadata.
- Objecthas part · java.lang.Object is the root class of Java’s reference-type hierarchy and defines methods inherited by Java reference types.
- hash mappart of · A hash map is a key-value data structure that uses a hash function to locate entries and support efficient lookup, insertion, and removal by key.
- Amazon S3used by · Amazon S3 is Amazon Web Services’ cloud object-storage service, which stores and retrieves data as objects organized in buckets.
- versioningconfigured by · The practice of identifying and managing successive revisions of files, data, models, interfaces, or other artifacts so changes can be tracked and earlier states recovered.
These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.