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bbolt is a fork of Ben Johnson'sBolt key/value
store. The purpose of this fork is to provide the Go community with an active
maintenance and development target for Bolt; the goal is improved reliability
and stability. bbolt includes bug fixes, performance enhancements, and features
not found in Bolt while preserving backwards compatibility with the Bolt API.
Bolt is a pure Go key/value store inspired by Howard Chu's LMDB project. The goal of the project is to provide a simple,
fast, and reliable database for projects that don't require a full database
server such as Postgres or MySQL.
Since Bolt is meant to be used as such a low-level piece of functionality,
simplicity is key. The API will be small and only focus on getting values
and setting values. That's it.
Project Status
Bolt is stable, the API is fixed, and the file format is fixed. Full unit
test coverage and randomized black box testing are used to ensure database
consistency and thread safety. Bolt is currently used in high-load production
environments serving databases as large as 1TB. Many companies such as
Shopify and Heroku use Bolt-backed services every day.
Project versioning
bbolt uses semantic versioning.
API should not change between patch and minor releases.
New minor versions may add additional features to the API.
This will retrieve the library and update your go.mod and go.sum files.
To run the command line utility, execute:
$ go run go.etcd.io/bbolt/cmd/bbolt@latest
Run go install to install the bbolt command line utility into
your $GOBIN path, which defaults to $GOPATH/bin or $HOME/go/bin if the GOPATH environment variable is not set.
$ go install go.etcd.io/bbolt/cmd/bbolt@latest
Importing bbolt
To use bbolt as an embedded key-value store, import as:
The top-level object in Bolt is a DB. It is represented as a single file on
your disk and represents a consistent snapshot of your data.
To open your database, simply use the bolt.Open() function:
package main
import (
"log"
bolt "go.etcd.io/bbolt"
)
funcmain() {
// Open the my.db data file in your current directory.// It will be created if it doesn't exist.db, err:=bolt.Open("my.db", 0600, nil)
iferr!=nil {
log.Fatal(err)
}
deferdb.Close()
...
}
Please note that Bolt obtains a file lock on the data file so multiple processes
cannot open the same database at the same time. Opening an already open Bolt
database will cause it to hang until the other process closes it. To prevent
an indefinite wait you can pass a timeout option to the Open() function:
Bolt allows only one read-write transaction at a time but allows as many
read-only transactions as you want at a time. Each transaction has a consistent
view of the data as it existed when the transaction started.
Individual transactions and all objects created from them (e.g. buckets, keys)
are not thread safe. To work with data in multiple goroutines you must start
a transaction for each one or use locking to ensure only one goroutine accesses
a transaction at a time. Creating transaction from the DB is thread safe.
Transactions should not depend on one another and generally shouldn't be opened
simultaneously in the same goroutine. This can cause a deadlock as the read-write
transaction needs to periodically re-map the data file but it cannot do so while
any read-only transaction is open. Even a nested read-only transaction can cause
a deadlock, as the child transaction can block the parent transaction from releasing
its resources.
Read-write transactions
To start a read-write transaction, you can use the DB.Update() function:
Inside the closure, you have a consistent view of the database. You commit the
transaction by returning nil at the end. You can also rollback the transaction
at any point by returning an error. All database operations are allowed inside
a read-write transaction.
Always check the return error as it will report any disk failures that can cause
your transaction to not complete. If you return an error within your closure
it will be passed through.
Read-only transactions
To start a read-only transaction, you can use the DB.View() function:
You also get a consistent view of the database within this closure, however,
no mutating operations are allowed within a read-only transaction. You can only
retrieve buckets, retrieve values, and copy the database within a read-only
transaction.
Batch read-write transactions
Each DB.Update() waits for disk to commit the writes. This overhead
can be minimized by combining multiple updates with the DB.Batch()
function:
Concurrent Batch calls are opportunistically combined into larger
transactions. Batch is only useful when there are multiple goroutines
calling it.
The trade-off is that Batch can call the given
function multiple times, if parts of the transaction fail. The
function must be idempotent and side effects must take effect only
after a successful return from DB.Batch().
For example: don't display messages from inside the function, instead
set variables in the enclosing scope:
variduint64err:=db.Batch(func(tx*bolt.Tx) error {
// Find last key in bucket, decode as bigendian uint64, increment// by one, encode back to []byte, and add new key....id=newValuereturnnil
})
iferr!=nil {
return...
}
fmt.Println("Allocated ID %d", id)
Managing transactions manually
The DB.View() and DB.Update() functions are wrappers around the DB.Begin()
function. These helper functions will start the transaction, execute a function,
and then safely close your transaction if an error is returned. This is the
recommended way to use Bolt transactions.
However, sometimes you may want to manually start and end your transactions.
You can use the DB.Begin() function directly but please be sure to close
the transaction.
// Start a writable transaction.tx, err:=db.Begin(true)
iferr!=nil {
returnerr
}
defertx.Rollback()
// Use the transaction..._, err:=tx.CreateBucket([]byte("MyBucket"))
iferr!=nil {
returnerr
}
// Commit the transaction and check for error.iferr:=tx.Commit(); err!=nil {
returnerr
}
The first argument to DB.Begin() is a boolean stating if the transaction
should be writable.
Using buckets
Buckets are collections of key/value pairs within the database. All keys in a
bucket must be unique. You can create a bucket using the Tx.CreateBucket()
function:
You can retrieve an existing bucket using the Tx.Bucket() function:
db.Update(func(tx*bolt.Tx) error {
b:=tx.Bucket([]byte("MyBucket"))
ifb==nil {
returnerrors.New("bucket does not exist")
}
returnnil
})
You can also create a bucket only if it doesn't exist by using the Tx.CreateBucketIfNotExists() function. It's a common pattern to call this
function for all your top-level buckets after you open your database so you can
guarantee that they exist for future transactions.
To delete a bucket, simply call the Tx.DeleteBucket() function.
You can also iterate over all existing top-level buckets with Tx.ForEach():
The Get() function does not return an error because its operation is
guaranteed to work (unless there is some kind of system failure). If the key
exists then it will return its byte slice value. If it doesn't exist then it
will return nil. It's important to note that you can have a zero-length value
set to a key which is different than the key not existing.
Use the Bucket.Delete() function to delete a key from the bucket:
This will delete the key answers from the bucket MyBucket.
Please note that values returned from Get() are only valid while the
transaction is open. If you need to use a value outside of the transaction
then you must use copy() to copy it to another byte slice.
Autoincrementing integer for the bucket
By using the NextSequence() function, you can let Bolt determine a sequence
which can be used as the unique identifier for your key/value pairs. See the
example below.
// CreateUser saves u to the store. The new user ID is set on u once the data is persisted.func (s*Store) CreateUser(u*User) error {
returns.db.Update(func(tx*bolt.Tx) error {
// Retrieve the users bucket.// This should be created when the DB is first opened.b:=tx.Bucket([]byte("users"))
// Generate ID for the user.// This returns an error only if the Tx is closed or not writeable.// That can't happen in an Update() call so I ignore the error check.id, _:=b.NextSequence()
u.ID=int(id)
// Marshal user data into bytes.buf, err:=json.Marshal(u)
iferr!=nil {
returnerr
}
// Persist bytes to users bucket.returnb.Put(itob(u.ID), buf)
})
}
// itob returns an 8-byte big endian representation of v.funcitob(vint) []byte {
b:=make([]byte, 8)
binary.BigEndian.PutUint64(b, uint64(v))
returnb
}
typeUserstruct {
IDint...
}
Iterating over keys
Bolt stores its keys in byte-sorted order within a bucket. This makes sequential
iteration over these keys extremely fast. To iterate over keys we'll use a Cursor:
The cursor allows you to move to a specific point in the list of keys and move
forward or backward through the keys one at a time.
The following functions are available on the cursor:
First() Move to the first key.
Last() Move to the last key.
Seek() Move to a specific key.
Next() Move to the next key.
Prev() Move to the previous key.
Each of those functions has a return signature of (key []byte, value []byte).
You must seek to a position using First(), Last(), or Seek() before calling Next() or Prev(). If you do not seek to a position then these functions will
return a nil key.
When you have iterated to the end of the cursor, then Next() will return a nil key and the cursor still points to the last element if present. When you
have iterated to the beginning of the cursor, then Prev() will return a nil
key and the cursor still points to the first element if present.
If you remove key/value pairs during iteration, the cursor may automatically
move to the next position if present in current node each time removing a key.
When you call c.Next() after removing a key, it may skip one key/value pair.
Refer to pull/611 to get more detailed info.
During iteration, if the key is non-nil but the value is nil, that means
the key refers to a bucket rather than a value. Use Bucket.Bucket() to
access the sub-bucket.
Prefix scans
To iterate over a key prefix, you can combine Seek() and bytes.HasPrefix():
Another common use case is scanning over a range such as a time range. If you
use a sortable time encoding such as RFC3339 then you can query a specific
date range like this:
db.View(func(tx*bolt.Tx) error {
// Assume our events bucket exists and has RFC3339 encoded time keys.c:=tx.Bucket([]byte("Events")).Cursor()
// Our time range spans the 90's decade.min:= []byte("1990-01-01T00:00:00Z")
max:= []byte("2000-01-01T00:00:00Z")
// Iterate over the 90's.fork, v:=c.Seek(min); k!=nil&&bytes.Compare(k, max) <=0; k, v=c.Next() {
fmt.Printf("%s: %s\n", k, v)
}
returnnil
})
Note that, while RFC3339 is sortable, the Golang implementation of RFC3339Nano does not use a fixed number of digits after the decimal point and is therefore not sortable.
ForEach()
You can also use the function ForEach() if you know you'll be iterating over
all the keys in a bucket:
db.View(func(tx*bolt.Tx) error {
// Assume bucket exists and has keysb:=tx.Bucket([]byte("MyBucket"))
b.ForEach(func(k, v []byte) error {
fmt.Printf("key=%s, value=%s\n", k, v)
returnnil
})
returnnil
})
Please note that keys and values in ForEach() are only valid while
the transaction is open. If you need to use a key or value outside of
the transaction, you must use copy() to copy it to another byte
slice.
Nested buckets
You can also store a bucket in a key to create nested buckets. The API is the
same as the bucket management API on the DB object:
Say you had a multi-tenant application where the root level bucket was the account bucket. Inside of this bucket was a sequence of accounts which themselves are buckets. And inside the sequence bucket you could have many buckets pertaining to the Account itself (Users, Notes, etc) isolating the information into logical groupings.
// createUser creates a new user in the given account.funccreateUser(accountIDint, u*User) error {
// Start the transaction.tx, err:=db.Begin(true)
iferr!=nil {
returnerr
}
defertx.Rollback()
// Retrieve the root bucket for the account.// Assume this has already been created when the account was set up.root:=tx.Bucket([]byte(strconv.FormatUint(accountID, 10)))
// Setup the users bucket.bkt, err:=root.CreateBucketIfNotExists([]byte("USERS"))
iferr!=nil {
returnerr
}
// Generate an ID for the new user.userID, err:=bkt.NextSequence()
iferr!=nil {
returnerr
}
u.ID=userID// Marshal and save the encoded user.ifbuf, err:=json.Marshal(u); err!=nil {
returnerr
} elseiferr:=bkt.Put([]byte(strconv.FormatUint(u.ID, 10)), buf); err!=nil {
returnerr
}
// Commit the transaction.iferr:=tx.Commit(); err!=nil {
returnerr
}
returnnil
}
Database backups
Bolt is a single file so it's easy to backup. You can use the Tx.WriteTo()
function to write a consistent view of the database to a writer. If you call
this from a read-only transaction, it will perform a hot backup and not block
your other database reads and writes.
By default, it will use a regular file handle which will utilize the operating
system's page cache. See the Tx
documentation for information about optimizing for larger-than-RAM datasets.
One common use case is to backup over HTTP so you can use tools like cURL to
do database backups:
Or you can open your browser to http://localhost/backup and it will download
automatically.
If you want to backup to another file you can use the Tx.CopyFile() helper
function.
Statistics
The database keeps a running count of many of the internal operations it
performs so you can better understand what's going on. By grabbing a snapshot
of these stats at two points in time we can see what operations were performed
in that time range.
For example, we could start a goroutine to log stats every 10 seconds:
gofunc() {
// Grab the initial stats.prev:=db.Stats()
for {
// Wait for 10s.time.Sleep(10*time.Second)
// Grab the current stats and diff them.stats:=db.Stats()
diff:=stats.Sub(&prev)
// Encode stats to JSON and print to STDERR.json.NewEncoder(os.Stderr).Encode(diff)
// Save stats for the next loop.prev=stats
}
}()
It's also useful to pipe these stats to a service such as statsd for monitoring
or to provide an HTTP endpoint that will perform a fixed-length sample.
Read-Only Mode
Sometimes it is useful to create a shared, read-only Bolt database. To this,
set the Options.ReadOnly flag when opening your database. Read-only mode
uses a shared lock to allow multiple processes to read from the database but
it will block any processes from opening the database in read-write mode.
Bolt is able to run on mobile devices by leveraging the binding feature of the gomobile tool. Create a struct that will
contain your database logic and a reference to a *bolt.DB with a initializing
constructor that takes in a filepath where the database file will be stored.
Neither Android nor iOS require extra permissions or cleanup from using this method.
Database logic should be defined as methods on this wrapper struct.
To initialize this struct from the native language (both platforms now sync
their local storage to the cloud. These snippets disable that functionality for the
database file):
Relational databases structure data into rows and are only accessible through
the use of SQL. This approach provides flexibility in how you store and query
your data but also incurs overhead in parsing and planning SQL statements. Bolt
accesses all data by a byte slice key. This makes Bolt fast to read and write
data by key but provides no built-in support for joining values together.
Most relational databases (with the exception of SQLite) are standalone servers
that run separately from your application. This gives your systems
flexibility to connect multiple application servers to a single database
server but also adds overhead in serializing and transporting data over the
network. Bolt runs as a library included in your application so all data access
has to go through your application's process. This brings data closer to your
application but limits multi-process access to the data.
LevelDB, RocksDB
LevelDB and its derivatives (RocksDB, HyperLevelDB) are similar to Bolt in that
they are libraries bundled into the application, however, their underlying
structure is a log-structured merge-tree (LSM tree). An LSM tree optimizes
random writes by using a write ahead log and multi-tiered, sorted files called
SSTables. Bolt uses a B+tree internally and only a single file. Both approaches
have trade-offs.
If you require a high random write throughput (>10,000 w/sec) or you need to use
spinning disks then LevelDB could be a good choice. If your application is
read-heavy or does a lot of range scans then Bolt could be a good choice.
One other important consideration is that LevelDB does not have transactions.
It supports batch writing of key/values pairs and it supports read snapshots
but it will not give you the ability to do a compare-and-swap operation safely.
Bolt supports fully serializable ACID transactions.
LMDB
Bolt was originally a port of LMDB so it is architecturally similar. Both use
a B+tree, have ACID semantics with fully serializable transactions, and support
lock-free MVCC using a single writer and multiple readers.
The two projects have somewhat diverged. LMDB heavily focuses on raw performance
while Bolt has focused on simplicity and ease of use. For example, LMDB allows
several unsafe actions such as direct writes for the sake of performance. Bolt
opts to disallow actions which can leave the database in a corrupted state. The
only exception to this in Bolt is DB.NoSync.
There are also a few differences in API. LMDB requires a maximum mmap size when
opening an mdb_env whereas Bolt will handle incremental mmap resizing
automatically. LMDB overloads the getter and setter functions with multiple
flags whereas Bolt splits these specialized cases into their own functions.
Caveats & Limitations
It's important to pick the right tool for the job and Bolt is no exception.
Here are a few things to note when evaluating and using Bolt:
Bolt is good for read intensive workloads. Sequential write performance is
also fast but random writes can be slow. You can use DB.Batch() or add a
write-ahead log to help mitigate this issue.
Bolt uses a B+tree internally so there can be a lot of random page access.
SSDs provide a significant performance boost over spinning disks.
Try to avoid long running read transactions. Bolt uses copy-on-write so
old pages cannot be reclaimed while an old transaction is using them.
Byte slices returned from Bolt are only valid during a transaction. Once the
transaction has been committed or rolled back then the memory they point to
can be reused by a new page or can be unmapped from virtual memory and you'll
see an unexpected fault address panic when accessing it.
Bolt uses an exclusive write lock on the database file so it cannot be
shared by multiple processes.
Be careful when using Bucket.FillPercent. Setting a high fill percent for
buckets that have random inserts will cause your database to have very poor
page utilization.
Use larger buckets in general. Smaller buckets causes poor page utilization
once they become larger than the page size (typically 4KB).
Bulk loading a lot of random writes into a new bucket can be slow as the
page will not split until the transaction is committed. Randomly inserting
more than 100,000 key/value pairs into a single new bucket in a single
transaction is not advised.
Bolt uses a memory-mapped file so the underlying operating system handles the
caching of the data. Typically, the OS will cache as much of the file as it
can in memory and will release memory as needed to other processes. This means
that Bolt can show very high memory usage when working with large databases.
However, this is expected and the OS will release memory as needed. Bolt can
handle databases much larger than the available physical RAM, provided its
memory-map fits in the process virtual address space. It may be problematic
on 32-bits systems.
The data structures in the Bolt database are memory mapped so the data file
will be endian specific. This means that you cannot copy a Bolt file from a
little endian machine to a big endian machine and have it work. For most
users this is not a concern since most modern CPUs are little endian.
Because of the way pages are laid out on disk, Bolt cannot truncate data files
and return free pages back to the disk. Instead, Bolt maintains a free list
of unused pages within its data file. These free pages can be reused by later
transactions. This works well for many use cases as databases generally tend
to grow. However, it's important to note that deleting large chunks of data
will not allow you to reclaim that space on disk.
Removing key/values pairs in a bucket during iteration on the bucket using
cursor may not work properly. Each time when removing a key/value pair, the
cursor may automatically move to the next position if present. When users
call c.Next() after removing a key, it may skip one key/value pair.
Refer to Fix cursor automatically moving to next position when delete and put are in the same TXN etcd-io/bbolt#611 for more detailed info.
Bolt is a relatively small code base (<5KLOC) for an embedded, serializable,
transactional key/value database so it can be a good starting point for people
interested in how databases work.
The best places to start are the main entry points into Bolt:
Open() - Initializes the reference to the database. It's responsible for
creating the database if it doesn't exist, obtaining an exclusive lock on the
file, reading the meta pages, & memory-mapping the file.
DB.Begin() - Starts a read-only or read-write transaction depending on the
value of the writable argument. This requires briefly obtaining the "meta"
lock to keep track of open transactions. Only one read-write transaction can
exist at a time so the "rwlock" is acquired during the life of a read-write
transaction.
Bucket.Put() - Writes a key/value pair into a bucket. After validating the
arguments, a cursor is used to traverse the B+tree to the page and position
where the key & value will be written. Once the position is found, the bucket
materializes the underlying page and the page's parent pages into memory as
"nodes". These nodes are where mutations occur during read-write transactions.
These changes get flushed to disk during commit.
Bucket.Get() - Retrieves a key/value pair from a bucket. This uses a cursor
to move to the page & position of a key/value pair. During a read-only
transaction, the key and value data is returned as a direct reference to the
underlying mmap file so there's no allocation overhead. For read-write
transactions, this data may reference the mmap file or one of the in-memory
node values.
Cursor - This object is simply for traversing the B+tree of on-disk pages
or in-memory nodes. It can seek to a specific key, move to the first or last
value, or it can move forward or backward. The cursor handles the movement up
and down the B+tree transparently to the end user.
Tx.Commit() - Converts the in-memory dirty nodes and the list of free pages
into pages to be written to disk. Writing to disk then occurs in two phases.
First, the dirty pages are written to disk and an fsync() occurs. Second, a
new meta page with an incremented transaction ID is written and another fsync() occurs. This two phase write ensures that partially written data
pages are ignored in the event of a crash since the meta page pointing to them
is never written. Partially written meta pages are invalidated because they
are written with a checksum.
If you have additional notes that could be helpful for others, please submit
them via pull request.
Known Issues
bbolt might run into data corruption issue on Linux when the feature ext4: fast commit, which was introduced in
linux kernel version v5.10, is enabled. The fixes to the issue were included in
linux kernel version v5.17, please refer to links below,
BoltDB Viewer - A BoltDB Viewer Can run on Windows、Linux、Android system.
bleve - A pure Go search engine similar to ElasticSearch that uses Bolt as the default storage backend.
bstore - Database library storing Go values, with referential/unique/nonzero constraints, indices, automatic schema management with struct tags, and a query API.
buckets - a bolt wrapper streamlining
simple tx and key scans.
Buildkit - concurrent, cache-efficient, and Dockerfile-agnostic builder toolkit
cayley - Cayley is an open-source graph database using Bolt as optional backend.
ChainStore - Simple key-value interface to a variety of storage engines organized as a chain of operations.
🌰 Chestnut - Chestnut is encrypted storage for Go.
Consul - Consul is service discovery and configuration made easy. Distributed, highly available, and datacenter-aware.
Containerd - An open and reliable container runtime
DVID - Added Bolt as optional storage engine and testing it against Basho-tuned leveldb.
dcrwallet - A wallet for the Decred cryptocurrency.
drive - drive is an unofficial Google Drive command line client for *NIX operating systems.
event-shuttle - A Unix system service to collect and reliably deliver messages to Kafka.
Freehold - An open, secure, and lightweight platform for your files and data.
Go Report Card - Go code quality report cards as a (free and open source) service.
GoWebApp - A basic MVC web application in Go using BoltDB.
GoShort - GoShort is a URL shortener written in Golang and BoltDB for persistent key/value storage and for routing it's using high performent HTTPRouter.
gopherpit - A web service to manage Go remote import paths with custom domains
gokv - Simple key-value store abstraction and implementations for Go (Redis, Consul, etcd, bbolt, BadgerDB, LevelDB, Memcached, DynamoDB, S3, PostgreSQL, MongoDB, CockroachDB and many more)
Ironsmith - A simple, script-driven continuous integration (build - > test -> release) tool, with no external dependencies
Kala - Kala is a modern job scheduler optimized to run on a single node. It is persistent, JSON over HTTP API, ISO 8601 duration notation, and dependent jobs.
MuLiFS - Music Library Filesystem creates a filesystem to organise your music files.
NATS - NATS Streaming uses bbolt for message and metadata storage.
Portainer - A lightweight service delivery platform for containerized applications that can be used to manage Docker, Swarm, Kubernetes and ACI environments.
bbolt
bbolt is a fork of Ben Johnson's Bolt key/value
store. The purpose of this fork is to provide the Go community with an active
maintenance and development target for Bolt; the goal is improved reliability
and stability. bbolt includes bug fixes, performance enhancements, and features
not found in Bolt while preserving backwards compatibility with the Bolt API.
Bolt is a pure Go key/value store inspired by Howard Chu's
LMDB project. The goal of the project is to provide a simple,
fast, and reliable database for projects that don't require a full database
server such as Postgres or MySQL.
Since Bolt is meant to be used as such a low-level piece of functionality,
simplicity is key. The API will be small and only focus on getting values
and setting values. That's it.
Project Status
Bolt is stable, the API is fixed, and the file format is fixed. Full unit
test coverage and randomized black box testing are used to ensure database
consistency and thread safety. Bolt is currently used in high-load production
environments serving databases as large as 1TB. Many companies such as
Shopify and Heroku use Bolt-backed services every day.
Project versioning
bbolt uses semantic versioning.
API should not change between patch and minor releases.
New minor versions may add additional features to the API.
Table of Contents
Getting Started
Installing
To start using
bbolt, install Go and rungo get:This will retrieve the library and update your
go.modandgo.sumfiles.To run the command line utility, execute:
Run
go installto install thebboltcommand line utility intoyour
$GOBINpath, which defaults to$GOPATH/binor$HOME/go/binif theGOPATHenvironment variable is not set.Importing bbolt
To use bbolt as an embedded key-value store, import as:
Opening a database
The top-level object in Bolt is a
DB. It is represented as a single file onyour disk and represents a consistent snapshot of your data.
To open your database, simply use the
bolt.Open()function:Please note that Bolt obtains a file lock on the data file so multiple processes
cannot open the same database at the same time. Opening an already open Bolt
database will cause it to hang until the other process closes it. To prevent
an indefinite wait you can pass a timeout option to the
Open()function:Transactions
Bolt allows only one read-write transaction at a time but allows as many
read-only transactions as you want at a time. Each transaction has a consistent
view of the data as it existed when the transaction started.
Individual transactions and all objects created from them (e.g. buckets, keys)
are not thread safe. To work with data in multiple goroutines you must start
a transaction for each one or use locking to ensure only one goroutine accesses
a transaction at a time. Creating transaction from the
DBis thread safe.Transactions should not depend on one another and generally shouldn't be opened
simultaneously in the same goroutine. This can cause a deadlock as the read-write
transaction needs to periodically re-map the data file but it cannot do so while
any read-only transaction is open. Even a nested read-only transaction can cause
a deadlock, as the child transaction can block the parent transaction from releasing
its resources.
Read-write transactions
To start a read-write transaction, you can use the
DB.Update()function:Inside the closure, you have a consistent view of the database. You commit the
transaction by returning
nilat the end. You can also rollback the transactionat any point by returning an error. All database operations are allowed inside
a read-write transaction.
Always check the return error as it will report any disk failures that can cause
your transaction to not complete. If you return an error within your closure
it will be passed through.
Read-only transactions
To start a read-only transaction, you can use the
DB.View()function:You also get a consistent view of the database within this closure, however,
no mutating operations are allowed within a read-only transaction. You can only
retrieve buckets, retrieve values, and copy the database within a read-only
transaction.
Batch read-write transactions
Each
DB.Update()waits for disk to commit the writes. This overheadcan be minimized by combining multiple updates with the
DB.Batch()function:
Concurrent Batch calls are opportunistically combined into larger
transactions. Batch is only useful when there are multiple goroutines
calling it.
The trade-off is that
Batchcan call the givenfunction multiple times, if parts of the transaction fail. The
function must be idempotent and side effects must take effect only
after a successful return from
DB.Batch().For example: don't display messages from inside the function, instead
set variables in the enclosing scope:
Managing transactions manually
The
DB.View()andDB.Update()functions are wrappers around theDB.Begin()function. These helper functions will start the transaction, execute a function,
and then safely close your transaction if an error is returned. This is the
recommended way to use Bolt transactions.
However, sometimes you may want to manually start and end your transactions.
You can use the
DB.Begin()function directly but please be sure to closethe transaction.
The first argument to
DB.Begin()is a boolean stating if the transactionshould be writable.
Using buckets
Buckets are collections of key/value pairs within the database. All keys in a
bucket must be unique. You can create a bucket using the
Tx.CreateBucket()function:
You can retrieve an existing bucket using the
Tx.Bucket()function:You can also create a bucket only if it doesn't exist by using the
Tx.CreateBucketIfNotExists()function. It's a common pattern to call thisfunction for all your top-level buckets after you open your database so you can
guarantee that they exist for future transactions.
To delete a bucket, simply call the
Tx.DeleteBucket()function.You can also iterate over all existing top-level buckets with
Tx.ForEach():Using key/value pairs
To save a key/value pair to a bucket, use the
Bucket.Put()function:This will set the value of the
"answer"key to"42"in theMyBucketbucket. To retrieve this value, we can use the
Bucket.Get()function:The
Get()function does not return an error because its operation isguaranteed to work (unless there is some kind of system failure). If the key
exists then it will return its byte slice value. If it doesn't exist then it
will return
nil. It's important to note that you can have a zero-length valueset to a key which is different than the key not existing.
Use the
Bucket.Delete()function to delete a key from the bucket:This will delete the key
answersfrom the bucketMyBucket.Please note that values returned from
Get()are only valid while thetransaction is open. If you need to use a value outside of the transaction
then you must use
copy()to copy it to another byte slice.Autoincrementing integer for the bucket
By using the
NextSequence()function, you can let Bolt determine a sequencewhich can be used as the unique identifier for your key/value pairs. See the
example below.
Iterating over keys
Bolt stores its keys in byte-sorted order within a bucket. This makes sequential
iteration over these keys extremely fast. To iterate over keys we'll use a
Cursor:The cursor allows you to move to a specific point in the list of keys and move
forward or backward through the keys one at a time.
The following functions are available on the cursor:
Each of those functions has a return signature of
(key []byte, value []byte).You must seek to a position using
First(),Last(), orSeek()before callingNext()orPrev(). If you do not seek to a position then these functions willreturn a
nilkey.When you have iterated to the end of the cursor, then
Next()will return anilkey and the cursor still points to the last element if present. When youhave iterated to the beginning of the cursor, then
Prev()will return anilkey and the cursor still points to the first element if present.
If you remove key/value pairs during iteration, the cursor may automatically
move to the next position if present in current node each time removing a key.
When you call
c.Next()after removing a key, it may skip one key/value pair.Refer to pull/611 to get more detailed info.
During iteration, if the key is non-
nilbut the value isnil, that meansthe key refers to a bucket rather than a value. Use
Bucket.Bucket()toaccess the sub-bucket.
Prefix scans
To iterate over a key prefix, you can combine
Seek()andbytes.HasPrefix():Range scans
Another common use case is scanning over a range such as a time range. If you
use a sortable time encoding such as RFC3339 then you can query a specific
date range like this:
Note that, while RFC3339 is sortable, the Golang implementation of RFC3339Nano does not use a fixed number of digits after the decimal point and is therefore not sortable.
ForEach()
You can also use the function
ForEach()if you know you'll be iterating overall the keys in a bucket:
Please note that keys and values in
ForEach()are only valid whilethe transaction is open. If you need to use a key or value outside of
the transaction, you must use
copy()to copy it to another byteslice.
Nested buckets
You can also store a bucket in a key to create nested buckets. The API is the
same as the bucket management API on the
DBobject:Say you had a multi-tenant application where the root level bucket was the account bucket. Inside of this bucket was a sequence of accounts which themselves are buckets. And inside the sequence bucket you could have many buckets pertaining to the Account itself (Users, Notes, etc) isolating the information into logical groupings.
Database backups
Bolt is a single file so it's easy to backup. You can use the
Tx.WriteTo()function to write a consistent view of the database to a writer. If you call
this from a read-only transaction, it will perform a hot backup and not block
your other database reads and writes.
By default, it will use a regular file handle which will utilize the operating
system's page cache. See the
Txdocumentation for information about optimizing for larger-than-RAM datasets.
One common use case is to backup over HTTP so you can use tools like
cURLtodo database backups:
Then you can backup using this command:
$ curl http://localhost/backup > my.dbOr you can open your browser to
http://localhost/backupand it will downloadautomatically.
If you want to backup to another file you can use the
Tx.CopyFile()helperfunction.
Statistics
The database keeps a running count of many of the internal operations it
performs so you can better understand what's going on. By grabbing a snapshot
of these stats at two points in time we can see what operations were performed
in that time range.
For example, we could start a goroutine to log stats every 10 seconds:
It's also useful to pipe these stats to a service such as statsd for monitoring
or to provide an HTTP endpoint that will perform a fixed-length sample.
Read-Only Mode
Sometimes it is useful to create a shared, read-only Bolt database. To this,
set the
Options.ReadOnlyflag when opening your database. Read-only modeuses a shared lock to allow multiple processes to read from the database but
it will block any processes from opening the database in read-write mode.
Mobile Use (iOS/Android)
Bolt is able to run on mobile devices by leveraging the binding feature of the
gomobile tool. Create a struct that will
contain your database logic and a reference to a
*bolt.DBwith a initializingconstructor that takes in a filepath where the database file will be stored.
Neither Android nor iOS require extra permissions or cleanup from using this method.
Database logic should be defined as methods on this wrapper struct.
To initialize this struct from the native language (both platforms now sync
their local storage to the cloud. These snippets disable that functionality for the
database file):
Android
iOS
Resources
For more information on getting started with Bolt, check out the following articles:
Comparison with other databases
Postgres, MySQL, & other relational databases
Relational databases structure data into rows and are only accessible through
the use of SQL. This approach provides flexibility in how you store and query
your data but also incurs overhead in parsing and planning SQL statements. Bolt
accesses all data by a byte slice key. This makes Bolt fast to read and write
data by key but provides no built-in support for joining values together.
Most relational databases (with the exception of SQLite) are standalone servers
that run separately from your application. This gives your systems
flexibility to connect multiple application servers to a single database
server but also adds overhead in serializing and transporting data over the
network. Bolt runs as a library included in your application so all data access
has to go through your application's process. This brings data closer to your
application but limits multi-process access to the data.
LevelDB, RocksDB
LevelDB and its derivatives (RocksDB, HyperLevelDB) are similar to Bolt in that
they are libraries bundled into the application, however, their underlying
structure is a log-structured merge-tree (LSM tree). An LSM tree optimizes
random writes by using a write ahead log and multi-tiered, sorted files called
SSTables. Bolt uses a B+tree internally and only a single file. Both approaches
have trade-offs.
If you require a high random write throughput (>10,000 w/sec) or you need to use
spinning disks then LevelDB could be a good choice. If your application is
read-heavy or does a lot of range scans then Bolt could be a good choice.
One other important consideration is that LevelDB does not have transactions.
It supports batch writing of key/values pairs and it supports read snapshots
but it will not give you the ability to do a compare-and-swap operation safely.
Bolt supports fully serializable ACID transactions.
LMDB
Bolt was originally a port of LMDB so it is architecturally similar. Both use
a B+tree, have ACID semantics with fully serializable transactions, and support
lock-free MVCC using a single writer and multiple readers.
The two projects have somewhat diverged. LMDB heavily focuses on raw performance
while Bolt has focused on simplicity and ease of use. For example, LMDB allows
several unsafe actions such as direct writes for the sake of performance. Bolt
opts to disallow actions which can leave the database in a corrupted state. The
only exception to this in Bolt is
DB.NoSync.There are also a few differences in API. LMDB requires a maximum mmap size when
opening an
mdb_envwhereas Bolt will handle incremental mmap resizingautomatically. LMDB overloads the getter and setter functions with multiple
flags whereas Bolt splits these specialized cases into their own functions.
Caveats & Limitations
It's important to pick the right tool for the job and Bolt is no exception.
Here are a few things to note when evaluating and using Bolt:
Bolt is good for read intensive workloads. Sequential write performance is
also fast but random writes can be slow. You can use
DB.Batch()or add awrite-ahead log to help mitigate this issue.
Bolt uses a B+tree internally so there can be a lot of random page access.
SSDs provide a significant performance boost over spinning disks.
Try to avoid long running read transactions. Bolt uses copy-on-write so
old pages cannot be reclaimed while an old transaction is using them.
Byte slices returned from Bolt are only valid during a transaction. Once the
transaction has been committed or rolled back then the memory they point to
can be reused by a new page or can be unmapped from virtual memory and you'll
see an
unexpected fault addresspanic when accessing it.Bolt uses an exclusive write lock on the database file so it cannot be
shared by multiple processes.
Be careful when using
Bucket.FillPercent. Setting a high fill percent forbuckets that have random inserts will cause your database to have very poor
page utilization.
Use larger buckets in general. Smaller buckets causes poor page utilization
once they become larger than the page size (typically 4KB).
Bulk loading a lot of random writes into a new bucket can be slow as the
page will not split until the transaction is committed. Randomly inserting
more than 100,000 key/value pairs into a single new bucket in a single
transaction is not advised.
Bolt uses a memory-mapped file so the underlying operating system handles the
caching of the data. Typically, the OS will cache as much of the file as it
can in memory and will release memory as needed to other processes. This means
that Bolt can show very high memory usage when working with large databases.
However, this is expected and the OS will release memory as needed. Bolt can
handle databases much larger than the available physical RAM, provided its
memory-map fits in the process virtual address space. It may be problematic
on 32-bits systems.
The data structures in the Bolt database are memory mapped so the data file
will be endian specific. This means that you cannot copy a Bolt file from a
little endian machine to a big endian machine and have it work. For most
users this is not a concern since most modern CPUs are little endian.
Because of the way pages are laid out on disk, Bolt cannot truncate data files
and return free pages back to the disk. Instead, Bolt maintains a free list
of unused pages within its data file. These free pages can be reused by later
transactions. This works well for many use cases as databases generally tend
to grow. However, it's important to note that deleting large chunks of data
will not allow you to reclaim that space on disk.
Removing key/values pairs in a bucket during iteration on the bucket using
cursor may not work properly. Each time when removing a key/value pair, the
cursor may automatically move to the next position if present. When users
call
c.Next()after removing a key, it may skip one key/value pair.Refer to Fix cursor automatically moving to next position when delete and put are in the same TXN etcd-io/bbolt#611 for more detailed info.
For more information on page allocation, see this comment.
Reading the Source
Bolt is a relatively small code base (<5KLOC) for an embedded, serializable,
transactional key/value database so it can be a good starting point for people
interested in how databases work.
The best places to start are the main entry points into Bolt:
Open()- Initializes the reference to the database. It's responsible forcreating the database if it doesn't exist, obtaining an exclusive lock on the
file, reading the meta pages, & memory-mapping the file.
DB.Begin()- Starts a read-only or read-write transaction depending on thevalue of the
writableargument. This requires briefly obtaining the "meta"lock to keep track of open transactions. Only one read-write transaction can
exist at a time so the "rwlock" is acquired during the life of a read-write
transaction.
Bucket.Put()- Writes a key/value pair into a bucket. After validating thearguments, a cursor is used to traverse the B+tree to the page and position
where the key & value will be written. Once the position is found, the bucket
materializes the underlying page and the page's parent pages into memory as
"nodes". These nodes are where mutations occur during read-write transactions.
These changes get flushed to disk during commit.
Bucket.Get()- Retrieves a key/value pair from a bucket. This uses a cursorto move to the page & position of a key/value pair. During a read-only
transaction, the key and value data is returned as a direct reference to the
underlying mmap file so there's no allocation overhead. For read-write
transactions, this data may reference the mmap file or one of the in-memory
node values.
Cursor- This object is simply for traversing the B+tree of on-disk pagesor in-memory nodes. It can seek to a specific key, move to the first or last
value, or it can move forward or backward. The cursor handles the movement up
and down the B+tree transparently to the end user.
Tx.Commit()- Converts the in-memory dirty nodes and the list of free pagesinto pages to be written to disk. Writing to disk then occurs in two phases.
First, the dirty pages are written to disk and an
fsync()occurs. Second, anew meta page with an incremented transaction ID is written and another
fsync()occurs. This two phase write ensures that partially written datapages are ignored in the event of a crash since the meta page pointing to them
is never written. Partially written meta pages are invalidated because they
are written with a checksum.
If you have additional notes that could be helpful for others, please submit
them via pull request.
Known Issues
bbolt might run into data corruption issue on Linux when the feature
ext4: fast commit, which was introduced in
linux kernel version v5.10, is enabled. The fixes to the issue were included in
linux kernel version v5.17, please refer to links below,
Please also refer to the discussion in DB cannot be opened after node hard reset etcd-io/bbolt#562.
Writing a value with a length of 0 will always result in reading back an empty
[]byte{}value.Please refer to issues/726#issuecomment-2061694802.
Other Projects Using Bolt
Below is a list of public, open source projects that use Bolt:
simple tx and key scans.
backed by boltdb.
If you are using Bolt in a project please send a pull request to add it to the list.