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Merge branch 'hzy-patch-1'

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Josh Baker 2016-07-20 06:37:44 -07:00
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README.md
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@ -31,12 +31,12 @@ Features
- In-memory database for [fast reads and writes](https://github.com/tidwall/raft-boltdb#benchmarks)
- Embeddable with a [simple API](https://godoc.org/github.com/tidwall/buntdb)
- [Spatial indexing](#spatial-indexes) for up to 4 dimensions; Useful for Geospatial data
- - Create [custom indexes](#custom-indexes) for any data type
- Create [custom indexes](#custom-indexes) for any data type
- [Built-in types](#built-in-types) that are easy to get up & running; String, Uint, Int, Float
- Flexible [iteration](#iterating) of data; ascending, descending, and ranges
- Durable append-only file format. Adopts the [Redis AOF](http://redis.io/topics/persistence) process
- Option to evict old items with an [expiration](#data-expiration) TTL
- Tight codebase, under 1K loc using the `cloc` command.
- Tight codebase, under 1K loc using the `cloc` command
- ACID semantics with locking [transactions](#transactions) that support rollbacks
Getting Started
@ -79,8 +79,6 @@ func main() {
}
```
It's important to note that BuntDB does not currently support file locking, so avoid accessing the database from multiple processes.
## Transactions
All reads and writes must be performed from inside a transaction. BuntDB can have one write transaction opened at a time, but can have many concurrent read transactions. Each transaction maintains a stable view of the database. In other words, once a transaction has begun, the data for that transaction cannot be changed by other transactions.
@ -256,7 +254,7 @@ user:4:name 63
```
### Spatial Indexes
BuntDB has support for spatial indexes by storing rectangles in an [R-tree](https://en.wikipedia.org/wiki/R-tree). An R-tree is organized in a similar manner as a [B-tree](https://en.wikipedia.org/wiki/B-tree), and both are balanaced trees. But, an R-tree is special because it can operate on data that is in multiple dimensions. This is super handy for Geospatial applications.
BuntDB has support for spatial indexes by storing rectangles in an [R-tree](https://en.wikipedia.org/wiki/R-tree). An R-tree is organized in a similar manner as a [B-tree](https://en.wikipedia.org/wiki/B-tree), and both are balanced trees. But, an R-tree is special because it can operate on data that is in multiple dimensions. This is super handy for Geospatial applications.
To create a spatial index use the `CreateSpatialIndex` function: