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leveldb

Jeff Dean, Sanjay Ghemawat

The leveldb library provides a persistent key value store. Keys and values are
arbitrary byte arrays. The keys are ordered within the key value store
according to a user-specified comparator function.

Opening A Database

A leveldb database has a name which corresponds to a file system directory. All
of the contents of database are stored in this directory. The following example
shows how to open a database, creating it if necessary:

#include <cassert>
#include "leveldb/db.h"

leveldb::DB* db;
leveldb::Options options;
options.create_if_missing = true;
leveldb::Status status = leveldb::DB::Open(options, "/tmp/testdb", &db);
assert(status.ok());
...

If you want to raise an error if the database already exists, add the following
line before the leveldb::DB::Open call:

options.error_if_exists = true;

Status

You may have noticed the leveldb::Status type above. Values of this type are
returned by most functions in leveldb that may encounter an error. You can check
if such a result is ok, and also print an associated error message:

leveldb::Status s = ...;
if (!s.ok()) cerr << s.ToString() << endl;

Closing A Database

When you are done with a database, just delete the database object. Example:

... open the db as described above ...
... do something with db ...
delete db;

Reads And Writes

The database provides Put, Delete, and Get methods to modify/query the database.
For example, the following code moves the value stored under key1 to key2.

std::string value;
leveldb::Status s = db->Get(leveldb::ReadOptions(), key1, &value);
if (s.ok()) s = db->Put(leveldb::WriteOptions(), key2, value);
if (s.ok()) s = db->Delete(leveldb::WriteOptions(), key1);

Atomic Updates

Note that if the process dies after the Put of key2 but before the delete of
key1, the same value may be left stored under multiple keys. Such problems can
be avoided by using the WriteBatch class to atomically apply a set of updates:

#include "leveldb/write_batch.h"
...
std::string value;
leveldb::Status s = db->Get(leveldb::ReadOptions(), key1, &value);
if (s.ok()) {
  leveldb::WriteBatch batch;
  batch.Delete(key1);
  batch.Put(key2, value);
  s = db->Write(leveldb::WriteOptions(), &batch);
}

The WriteBatch holds a sequence of edits to be made to the database, and these
edits within the batch are applied in order. Note that we called Delete before
Put so that if key1 is identical to key2, we do not end up erroneously dropping
the value entirely.

Apart from its atomicity benefits, WriteBatch may also be used to speed up
bulk updates by placing lots of individual mutations into the same batch.

Synchronous Writes

By default, each write to leveldb is asynchronous: it returns after pushing the
write from the process into the operating system. The transfer from operating
system memory to the underlying persistent storage happens asynchronously. The
sync flag can be turned on for a particular write to make the write operation
not return until the data being written has been pushed all the way to
persistent storage. (On Posix systems, this is implemented by calling either
fsync(...) or fdatasync(...) or msync(..., MS_SYNC) before the write
operation returns.)

leveldb::WriteOptions write_options;
write_options.sync = true;
db->Put(write_options, ...);

Asynchronous writes are often more than a thousand times as fast as synchronous
writes. The downside of asynchronous writes is that a crash of the machine may
cause the last few updates to be lost. Note that a crash of just the writing
process (i.e., not a reboot) will not cause any loss since even when sync is
false, an update is pushed from the process memory into the operating system
before it is considered done.

Asynchronous writes can often be used safely. For example, when loading a large
amount of data into the database you can handle lost updates by restarting the
bulk load after a crash. A hybrid scheme is also possible where every Nth write
is synchronous, and in the event of a crash, the bulk load is restarted just
after the last synchronous write finished by the previous run. (The synchronous
write can update a marker that describes where to restart on a crash.)

WriteBatch provides an alternative to asynchronous writes. Multiple updates
may be placed in the same WriteBatch and applied together using a synchronous
write (i.e., write_options.sync is set to true). The extra cost of the
synchronous write will be amortized across all of the writes in the batch.

Concurrency

A database may only be opened by one process at a time. The leveldb
implementation acquires a lock from the operating system to prevent misuse.
Within a single process, the same leveldb::DB object may be safely shared by
multiple concurrent threads. I.e., different threads may write into or fetch
iterators or call Get on the same database without any external synchronization
(the leveldb implementation will automatically do the required synchronization).
However other objects (like Iterator and WriteBatch) may require external
synchronization. If two threads share such an object, they must protect access
to it using their own locking protocol. More details are available in the public
header files.

Iteration

The following example demonstrates how to print all key,value pairs in a
database.

leveldb::Iterator* it = db->NewIterator(leveldb::ReadOptions());
for (it->SeekToFirst(); it->Valid(); it->Next()) {
  cout << it->key().ToString() << ": "  << it->value().ToString() << endl;
}
assert(it->status().ok());  // Check for any errors found during the scan
delete it;

The following variation shows how to process just the keys in the range
[start,limit):

for (it->Seek(start);
   it->Valid() && it->key().ToString() < limit;
   it->Next()) {
  ...
}

You can also process entries in reverse order. (Caveat: reverse iteration may be
somewhat slower than forward iteration.)

for (it->SeekToLast(); it->Valid(); it->Prev()) {
  ...
}

Snapshots

Snapshots provide consistent read-only views over the entire state of the
key-value store. ReadOptions::snapshot may be non-NULL to indicate that a
read should operate on a particular version of the DB state. If
ReadOptions::snapshot is NULL, the read will operate on an implicit snapshot
of the current state.

Snapshots are created by the DB::GetSnapshot() method:

leveldb::ReadOptions options;
options.snapshot = db->GetSnapshot();
... apply some updates to db ...
leveldb::Iterator* iter = db->NewIterator(options);
... read using iter to view the state when the snapshot was created ...
delete iter;
db->ReleaseSnapshot(options.snapshot);

Note that when a snapshot is no longer needed, it should be released using the
DB::ReleaseSnapshot interface. This allows the implementation to get rid of
state that was being maintained just to support reading as of that snapshot.

Slice

The return value of the it->key() and it->value() calls above are instances
of the leveldb::Slice type. Slice is a simple structure that contains a length
and a pointer to an external byte array. Returning a Slice is a cheaper
alternative to returning a std::string since we do not need to copy
potentially large keys and values. In addition, leveldb methods do not return
null-terminated C-style strings since leveldb keys and values are allowed to
contain '\0' bytes.

C++ strings and null-terminated C-style strings can be easily converted to a
Slice:

leveldb::Slice s1 = "hello";

std::string str("world");
leveldb::Slice s2 = str;

A Slice can be easily converted back to a C++ string:

std::string str = s1.ToString();
assert(str == std::string("hello"));

Be careful when using Slices since it is up to the caller to ensure that the
external byte array into which the Slice points remains live while the Slice is
in use. For example, the following is buggy:

leveldb::Slice slice;
if (...) {
  std::string str = ...;
  slice = str;
}
Use(slice);

When the if statement goes out of scope, str will be destroyed and the backing
storage for slice will disappear.

Comparators

The preceding examples used the default ordering function for key, which orders
bytes lexicographically. You can however supply a custom comparator when opening
a database. For example, suppose each database key consists of two numbers and
we should sort by the first number, breaking ties by the second number. First,
define a proper subclass of leveldb::Comparator that expresses these rules:

class TwoPartComparator : public leveldb::Comparator {
 public:
  // Three-way comparison function:
  //   if a < b: negative result
  //   if a > b: positive result
  //   else: zero result
  int Compare(const leveldb::Slice& a, const leveldb::Slice& b) const {
    int a1, a2, b1, b2;
    ParseKey(a, &a1, &a2);
    ParseKey(b, &b1, &b2);
    if (a1 < b1) return -1;
    if (a1 > b1) return +1;
    if (a2 < b2) return -1;
    if (a2 > b2) return +1;
    return 0;
  }

  // Ignore the following methods for now:
  const char* Name() const { return "TwoPartComparator"; }
  void FindShortestSeparator(std::string*, const leveldb::Slice&) const {}
  void FindShortSuccessor(std::string*) const {}
};

Now create a database using this custom comparator:

TwoPartComparator cmp;
leveldb::DB* db;
leveldb::Options options;
options.create_if_missing = true;
options.comparator = &cmp;
leveldb::Status status = leveldb::DB::Open(options, "/tmp/testdb", &db);
...

Backwards compatibility

The result of the comparator’s Name method is attached to the database when it
is created, and is checked on every subsequent database open. If the name
changes, the leveldb::DB::Open call will fail. Therefore, change the name if
and only if the new key format and comparison function are incompatible with
existing databases, and it is ok to discard the contents of all existing
databases.

You can however still gradually evolve your key format over time with a little
bit of pre-planning. For example, you could store a version number at the end of
each key (one byte should suffice for most uses). When you wish to switch to a
new key format (e.g., adding an optional third part to the keys processed by
TwoPartComparator), (a) keep the same comparator name (b) increment the
version number for new keys © change the comparator function so it uses the
version numbers found in the keys to decide how to interpret them.

Performance

Performance can be tuned by changing the default values of the types defined in
include/leveldb/options.h.

Block size

leveldb groups adjacent keys together into the same block and such a block is
the unit of transfer to and from persistent storage. The default block size is
approximately 4096 uncompressed bytes. Applications that mostly do bulk scans
over the contents of the database may wish to increase this size. Applications
that do a lot of point reads of small values may wish to switch to a smaller
block size if performance measurements indicate an improvement. There isn’t much
benefit in using blocks smaller than one kilobyte, or larger than a few
megabytes. Also note that compression will be more effective with larger block
sizes.

Compression

Each block is individually compressed before being written to persistent
storage. Compression is on by default since the default compression method is
very fast, and is automatically disabled for uncompressible data. In rare cases,
applications may want to disable compression entirely, but should only do so if
benchmarks show a performance improvement:

leveldb::Options options;
options.compression = leveldb::kNoCompression;
... leveldb::DB::Open(options, name, ...) ....

Cache

The contents of the database are stored in a set of files in the filesystem and
each file stores a sequence of compressed blocks. If options.block_cache is
non-NULL, it is used to cache frequently used uncompressed block contents.

#include "leveldb/cache.h"

leveldb::Options options;
options.block_cache = leveldb::NewLRUCache(100 * 1048576);  // 100MB cache
leveldb::DB* db;
leveldb::DB::Open(options, name, &db);
... use the db ...
delete db
delete options.block_cache;

Note that the cache holds uncompressed data, and therefore it should be sized
according to application level data sizes, without any reduction from
compression. (Caching of compressed blocks is left to the operating system
buffer cache, or any custom Env implementation provided by the client.)

When performing a bulk read, the application may wish to disable caching so that
the data processed by the bulk read does not end up displacing most of the
cached contents. A per-iterator option can be used to achieve this:

leveldb::ReadOptions options;
options.fill_cache = false;
leveldb::Iterator* it = db->NewIterator(options);
for (it->SeekToFirst(); it->Valid(); it->Next()) {
  ...
}

Key Layout

Note that the unit of disk transfer and caching is a block. Adjacent keys
(according to the database sort order) will usually be placed in the same block.
Therefore the application can improve its performance by placing keys that are
accessed together near each other and placing infrequently used keys in a
separate region of the key space.

For example, suppose we are implementing a simple file system on top of leveldb.
The types of entries we might wish to store are:

filename -> permission-bits, length, list of file_block_ids
file_block_id -> data

We might want to prefix filename keys with one letter (say ‘/’) and the
file_block_id keys with a different letter (say ‘0’) so that scans over just
the metadata do not force us to fetch and cache bulky file contents.

Filters

Because of the way leveldb data is organized on disk, a single Get() call may
involve multiple reads from disk. The optional FilterPolicy mechanism can be
used to reduce the number of disk reads substantially.

leveldb::Options options;
options.filter_policy = NewBloomFilterPolicy(10);
leveldb::DB* db;
leveldb::DB::Open(options, "/tmp/testdb", &db);
... use the database ...
delete db;
delete options.filter_policy;

The preceding code associates a Bloom filter based filtering policy with the
database. Bloom filter based filtering relies on keeping some number of bits of
data in memory per key (in this case 10 bits per key since that is the argument
we passed to NewBloomFilterPolicy). This filter will reduce the number of
unnecessary disk reads needed for Get() calls by a factor of approximately
a 100. Increasing the bits per key will lead to a larger reduction at the cost
of more memory usage. We recommend that applications whose working set does not
fit in memory and that do a lot of random reads set a filter policy.

If you are using a custom comparator, you should ensure that the filter policy
you are using is compatible with your comparator. For example, consider a
comparator that ignores trailing spaces when comparing keys.
NewBloomFilterPolicy must not be used with such a comparator. Instead, the
application should provide a custom filter policy that also ignores trailing
spaces. For example:

class CustomFilterPolicy : public leveldb::FilterPolicy {
 private:
  FilterPolicy* builtin_policy_;

 public:
  CustomFilterPolicy() : builtin_policy_(NewBloomFilterPolicy(10)) {}
  ~CustomFilterPolicy() { delete builtin_policy_; }

  const char* Name() const { return "IgnoreTrailingSpacesFilter"; }

  void CreateFilter(const Slice* keys, int n, std::string* dst) const {
    // Use builtin bloom filter code after removing trailing spaces
    std::vector<Slice> trimmed(n);
    for (int i = 0; i < n; i++) {
      trimmed[i] = RemoveTrailingSpaces(keys[i]);
    }
    return builtin_policy_->CreateFilter(&trimmed[i], n, dst);
  }
};

Advanced applications may provide a filter policy that does not use a bloom
filter but uses some other mechanism for summarizing a set of keys. See
leveldb/filter_policy.h for detail.

Checksums

leveldb associates checksums with all data it stores in the file system. There
are two separate controls provided over how aggressively these checksums are
verified:

ReadOptions::verify_checksums may be set to true to force checksum
verification of all data that is read from the file system on behalf of a
particular read. By default, no such verification is done.

Options::paranoid_checks may be set to true before opening a database to make
the database implementation raise an error as soon as it detects an internal
corruption. Depending on which portion of the database has been corrupted, the
error may be raised when the database is opened, or later by another database
operation. By default, paranoid checking is off so that the database can be used
even if parts of its persistent storage have been corrupted.

If a database is corrupted (perhaps it cannot be opened when paranoid checking
is turned on), the leveldb::RepairDB function may be used to recover as much
of the data as possible

Approximate Sizes

The GetApproximateSizes method can used to get the approximate number of bytes
of file system space used by one or more key ranges.

leveldb::Range ranges[2];
ranges[0] = leveldb::Range("a", "c");
ranges[1] = leveldb::Range("x", "z");
uint64_t sizes[2];
leveldb::Status s = db->GetApproximateSizes(ranges, 2, sizes);

The preceding call will set sizes[0] to the approximate number of bytes of
file system space used by the key range [a..c) and sizes[1] to the
approximate number of bytes used by the key range [x..z).

Environment

All file operations (and other operating system calls) issued by the leveldb
implementation are routed through a leveldb::Env object. Sophisticated clients
may wish to provide their own Env implementation to get better control.
For example, an application may introduce artificial delays in the file IO
paths to limit the impact of leveldb on other activities in the system.

class SlowEnv : public leveldb::Env {
  ... implementation of the Env interface ...
};

SlowEnv env;
leveldb::Options options;
options.env = &env;
Status s = leveldb::DB::Open(options, ...);

Porting

leveldb may be ported to a new platform by providing platform specific
implementations of the types/methods/functions exported by
leveldb/port/port.h. See leveldb/port/port_example.h for more details.

In addition, the new platform may need a new default leveldb::Env
implementation. See leveldb/util/env_posix.h for an example.

Other Information

Details about the leveldb implementation may be found in the following
documents:

1. Implementation notes
2. Format of an immutable Table file
3. Format of a log file