Package: vectra 0.9.0

The streaming envelope | From a raster to one row per cell | Select by location | Rasterize a streamed point set | Terrain on a streamed DEM | Back from raster to vector | Masking and raster math | Distance to the nearest feature | The cost model | Where to go next

Introduction | Writing and reading data | Filtering and selecting | Transforming columns | String operations | Aggregation | Sorting and slicing | Joins | Window functions | Dates and times | String similarity | Tree traversal | Format backends | Indexes | Incremental operations | Materialized blocks | Inspecting the plan | Where to go next | Cleanup

Two cost models | When a reduction streams in one pass | The offload functor | Localizing coupling by sorting and partitioning | The monoidal reduce, and the law it rests on | The cost tiers | A note on the abstraction | Choosing a path

What vectra does for a distribution model | Align coordinates before extracting | Build a predictor table | Fit in memory when the table fits | Stream when the table is larger than memory | A single pass with collect_chunked() | An out-of-core GLM with chunk_feeder() | Choosing a path

Introduction | The .vtr format | CSV | SQLite | Excel | GeoTIFF | Integer pixel types | Embedded metadata | Point extraction | Streaming conversion pipelines | Batch size | Format comparison

What vectra is | Execution model | Pull-based pipeline | Selection vectors (zero-copy filtering) | Columnar storage | Data sources | Output sinks | Supported verbs | Transformation verbs | Aggregation verbs | Ordering verbs | Join verbs | Window functions | Other verbs | tidyselect support | Supported types | Base types | Annotated types | Coercion rules | Arithmetic and comparison expressions | Join key coercion | bind_rows coercion | NA semantics | Storage | Propagation | is.na() | Ordering guarantees | Streaming vs materializing | Streaming nodes (constant memory per batch) | Materializing nodes | External sort (spill-to-disk) | Join memory model | The .vtr file format | Layout | Version history | Encoding and compression (v4) | Query optimizer | Predicate pushdown | Column pruning | Hidden mutate insertion | explain() contract | Hash indexes (.vtri) | Creating indexes | Index format | How the scan uses indexes | Performance characteristics | Materialized blocks | Exact lookups | Fuzzy lookups | Use case | OpenMP parallelization | Which operations parallelize | Thread safety | Current limitations | Fallback behavior | Grouping preservation | Package conflicts

Introduction | Key specification | Left join | Inner join | Right and full joins | Filtering joins: semi and anti | Cross join | Fuzzy joins | Multi-column keys | Key coercion and NA handling | Memory and performance | Practical guidance

The flat-table problem | The star schema concept | Setting up a schema | Looking up dimension columns | Match reporting | Named keys | Join modes | Reusing the schema | Practical patterns | Pattern 1: filtering before lookup | Pattern 2: aggregation after lookup | Pattern 3: multiple dimensions in one aggregation | Pattern 4: writing results back | When not to use a schema

Introduction | Zone-map pruning | Hash indexes | Composite indexes | Case-insensitive indexes | %in% acceleration | Column pruning | Predicate pushdown | Reading explain() output | Materialized blocks | Practical guidance

Introduction | Basic string functions | Trimming whitespace | Case conversion | String length | Extracting substrings | Prefix and suffix tests | String concatenation | paste0: no separator | paste: custom separator | Multi-column paste | Pattern matching: fixed strings | Filtering with grepl | Replacing with gsub and sub | sub: first match only | Pattern matching: regex | Regex filtering with grepl | Regex replacement with gsub | sub with regex: first match only | str_extract: capturing structured parts | Fuzzy string matching | Levenshtein distance | Damerau-Levenshtein distance | Jaro-Winkler similarity | Choosing a distance metric | Filtering by distance threshold | Ranking by similarity | Fuzzy joins | Basic fuzzy join | Methods: dl, levenshtein, jw | Blocking for performance | Thread control | Block lookups | Exact lookups | Case-insensitive lookups | Fuzzy lookups | Performance | Tier 1: byte-level operations (essentially free) | Tier 2: pattern matching (depends on pattern complexity) | Tier 3: fuzzy distance computation (CPU-bound) | Two-pass string building | Practical guidance | Which distance metric for which use case | Choosing max_dist thresholds | Handling encoding issues | Common cleaning patterns | Combining approaches

Introduction | Streaming pipelines | Batch sizing | Append workflows | Delete and tombstones | Diff between snapshots | External sort | Streaming joins | Multi-file workflows | Format conversion ETL | Memory budget planning | Cleanup