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550 lines
21 KiB
550 lines
21 KiB
12 years ago
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<!DOCTYPE html>
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<html>
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<head>
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<link rel="stylesheet" type="text/css" href="doc.css" />
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<title>Leveldb</title>
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</head>
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<body>
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<h1>Leveldb</h1>
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<address>Jeff Dean, Sanjay Ghemawat</address>
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<p>
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The <code>leveldb</code> library provides a persistent key value store. Keys and
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values are arbitrary byte arrays. The keys are ordered within the key
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value store according to a user-specified comparator function.
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<p>
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<h1>Opening A Database</h1>
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<p>
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A <code>leveldb</code> database has a name which corresponds to a file system
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directory. All of the contents of database are stored in this
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directory. The following example shows how to open a database,
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creating it if necessary:
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<p>
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<pre>
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#include <assert>
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#include "leveldb/db.h"
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leveldb::DB* db;
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leveldb::Options options;
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options.create_if_missing = true;
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leveldb::Status status = leveldb::DB::Open(options, "/tmp/testdb", &db);
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assert(status.ok());
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...
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</pre>
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If you want to raise an error if the database already exists, add
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the following line before the <code>leveldb::DB::Open</code> call:
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<pre>
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options.error_if_exists = true;
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</pre>
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<h1>Status</h1>
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<p>
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You may have noticed the <code>leveldb::Status</code> type above. Values of this
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type are returned by most functions in <code>leveldb</code> that may encounter an
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error. You can check if such a result is ok, and also print an
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associated error message:
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<p>
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<pre>
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leveldb::Status s = ...;
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if (!s.ok()) cerr << s.ToString() << endl;
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</pre>
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<h1>Closing A Database</h1>
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<p>
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When you are done with a database, just delete the database object.
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Example:
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<p>
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<pre>
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... open the db as described above ...
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... do something with db ...
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delete db;
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</pre>
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<h1>Reads And Writes</h1>
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<p>
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The database provides <code>Put</code>, <code>Delete</code>, and <code>Get</code> methods to
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modify/query the database. For example, the following code
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moves the value stored under key1 to key2.
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<pre>
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std::string value;
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leveldb::Status s = db->Get(leveldb::ReadOptions(), key1, &value);
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if (s.ok()) s = db->Put(leveldb::WriteOptions(), key2, value);
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if (s.ok()) s = db->Delete(leveldb::WriteOptions(), key1);
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</pre>
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<h1>Atomic Updates</h1>
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<p>
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Note that if the process dies after the Put of key2 but before the
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delete of key1, the same value may be left stored under multiple keys.
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Such problems can be avoided by using the <code>WriteBatch</code> class to
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atomically apply a set of updates:
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<p>
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<pre>
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#include "leveldb/write_batch.h"
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...
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std::string value;
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leveldb::Status s = db->Get(leveldb::ReadOptions(), key1, &value);
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if (s.ok()) {
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leveldb::WriteBatch batch;
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batch.Delete(key1);
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batch.Put(key2, value);
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s = db->Write(leveldb::WriteOptions(), &batch);
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}
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</pre>
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The <code>WriteBatch</code> holds a sequence of edits to be made to the database,
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and these edits within the batch are applied in order. Note that we
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called <code>Delete</code> before <code>Put</code> so that if <code>key1</code> is identical to <code>key2</code>,
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we do not end up erroneously dropping the value entirely.
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<p>
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Apart from its atomicity benefits, <code>WriteBatch</code> may also be used to
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speed up bulk updates by placing lots of individual mutations into the
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same batch.
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<h1>Synchronous Writes</h1>
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By default, each write to <code>leveldb</code> is asynchronous: it
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returns after pushing the write from the process into the operating
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system. The transfer from operating system memory to the underlying
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persistent storage happens asynchronously. The <code>sync</code> flag
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can be turned on for a particular write to make the write operation
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not return until the data being written has been pushed all the way to
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persistent storage. (On Posix systems, this is implemented by calling
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either <code>fsync(...)</code> or <code>fdatasync(...)</code> or
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<code>msync(..., MS_SYNC)</code> before the write operation returns.)
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<pre>
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leveldb::WriteOptions write_options;
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write_options.sync = true;
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db->Put(write_options, ...);
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</pre>
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Asynchronous writes are often more than a thousand times as fast as
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synchronous writes. The downside of asynchronous writes is that a
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crash of the machine may cause the last few updates to be lost. Note
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that a crash of just the writing process (i.e., not a reboot) will not
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cause any loss since even when <code>sync</code> is false, an update
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is pushed from the process memory into the operating system before it
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is considered done.
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<p>
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Asynchronous writes can often be used safely. For example, when
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loading a large amount of data into the database you can handle lost
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updates by restarting the bulk load after a crash. A hybrid scheme is
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also possible where every Nth write is synchronous, and in the event
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of a crash, the bulk load is restarted just after the last synchronous
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write finished by the previous run. (The synchronous write can update
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a marker that describes where to restart on a crash.)
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<p>
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<code>WriteBatch</code> provides an alternative to asynchronous writes.
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Multiple updates may be placed in the same <code>WriteBatch</code> and
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applied together using a synchronous write (i.e.,
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<code>write_options.sync</code> is set to true). The extra cost of
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the synchronous write will be amortized across all of the writes in
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the batch.
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<p>
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<h1>Concurrency</h1>
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<p>
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A database may only be opened by one process at a time.
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The <code>leveldb</code> implementation acquires a lock from the
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operating system to prevent misuse. Within a single process, the
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same <code>leveldb::DB</code> object may be safely shared by multiple
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concurrent threads. I.e., different threads may write into or fetch
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iterators or call <code>Get</code> on the same database without any
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external synchronization (the leveldb implementation will
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automatically do the required synchronization). However other objects
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(like Iterator and WriteBatch) may require external synchronization.
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If two threads share such an object, they must protect access to it
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using their own locking protocol. More details are available in
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the public header files.
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<p>
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<h1>Iteration</h1>
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<p>
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The following example demonstrates how to print all key,value pairs
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in a database.
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<p>
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<pre>
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leveldb::Iterator* it = db->NewIterator(leveldb::ReadOptions());
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for (it->SeekToFirst(); it->Valid(); it->Next()) {
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cout << it->key().ToString() << ": " << it->value().ToString() << endl;
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}
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assert(it->status().ok()); // Check for any errors found during the scan
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delete it;
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</pre>
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The following variation shows how to process just the keys in the
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range <code>[start,limit)</code>:
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<p>
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<pre>
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for (it->Seek(start);
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it->Valid() && it->key().ToString() < limit;
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it->Next()) {
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...
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}
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</pre>
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You can also process entries in reverse order. (Caveat: reverse
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iteration may be somewhat slower than forward iteration.)
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<p>
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<pre>
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for (it->SeekToLast(); it->Valid(); it->Prev()) {
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...
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}
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</pre>
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<h1>Snapshots</h1>
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<p>
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Snapshots provide consistent read-only views over the entire state of
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the key-value store. <code>ReadOptions::snapshot</code> may be non-NULL to indicate
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that a read should operate on a particular version of the DB state.
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If <code>ReadOptions::snapshot</code> is NULL, the read will operate on an
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implicit snapshot of the current state.
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<p>
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Snapshots are created by the DB::GetSnapshot() method:
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<p>
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<pre>
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leveldb::ReadOptions options;
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options.snapshot = db->GetSnapshot();
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... apply some updates to db ...
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leveldb::Iterator* iter = db->NewIterator(options);
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... read using iter to view the state when the snapshot was created ...
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delete iter;
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db->ReleaseSnapshot(options.snapshot);
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</pre>
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Note that when a snapshot is no longer needed, it should be released
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using the DB::ReleaseSnapshot interface. This allows the
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implementation to get rid of state that was being maintained just to
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support reading as of that snapshot.
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<h1>Slice</h1>
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<p>
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The return value of the <code>it->key()</code> and <code>it->value()</code> calls above
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are instances of the <code>leveldb::Slice</code> type. <code>Slice</code> is a simple
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structure that contains a length and a pointer to an external byte
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array. Returning a <code>Slice</code> is a cheaper alternative to returning a
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<code>std::string</code> since we do not need to copy potentially large keys and
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values. In addition, <code>leveldb</code> methods do not return null-terminated
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C-style strings since <code>leveldb</code> keys and values are allowed to
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contain '\0' bytes.
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<p>
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C++ strings and null-terminated C-style strings can be easily converted
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to a Slice:
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<p>
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<pre>
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leveldb::Slice s1 = "hello";
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std::string str("world");
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leveldb::Slice s2 = str;
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</pre>
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A Slice can be easily converted back to a C++ string:
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<pre>
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std::string str = s1.ToString();
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assert(str == std::string("hello"));
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</pre>
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Be careful when using Slices since it is up to the caller to ensure that
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the external byte array into which the Slice points remains live while
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the Slice is in use. For example, the following is buggy:
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<p>
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<pre>
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leveldb::Slice slice;
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if (...) {
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std::string str = ...;
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slice = str;
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}
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Use(slice);
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</pre>
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When the <code>if</code> statement goes out of scope, <code>str</code> will be destroyed and the
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backing storage for <code>slice</code> will disappear.
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<p>
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<h1>Comparators</h1>
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<p>
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The preceding examples used the default ordering function for key,
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which orders bytes lexicographically. You can however supply a custom
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comparator when opening a database. For example, suppose each
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database key consists of two numbers and we should sort by the first
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number, breaking ties by the second number. First, define a proper
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subclass of <code>leveldb::Comparator</code> that expresses these rules:
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<p>
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<pre>
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class TwoPartComparator : public leveldb::Comparator {
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public:
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// Three-way comparison function:
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// if a < b: negative result
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// if a > b: positive result
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// else: zero result
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int Compare(const leveldb::Slice& a, const leveldb::Slice& b) const {
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int a1, a2, b1, b2;
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ParseKey(a, &a1, &a2);
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ParseKey(b, &b1, &b2);
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if (a1 < b1) return -1;
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if (a1 > b1) return +1;
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if (a2 < b2) return -1;
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if (a2 > b2) return +1;
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return 0;
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}
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// Ignore the following methods for now:
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const char* Name() const { return "TwoPartComparator"; }
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void FindShortestSeparator(std::string*, const leveldb::Slice&) const { }
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void FindShortSuccessor(std::string*) const { }
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};
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</pre>
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Now create a database using this custom comparator:
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<p>
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<pre>
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TwoPartComparator cmp;
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leveldb::DB* db;
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leveldb::Options options;
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options.create_if_missing = true;
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options.comparator = &cmp;
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leveldb::Status status = leveldb::DB::Open(options, "/tmp/testdb", &db);
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...
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</pre>
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<h2>Backwards compatibility</h2>
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<p>
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The result of the comparator's <code>Name</code> method is attached to the
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database when it is created, and is checked on every subsequent
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database open. If the name changes, the <code>leveldb::DB::Open</code> call will
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fail. Therefore, change the name if and only if the new key format
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and comparison function are incompatible with existing databases, and
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it is ok to discard the contents of all existing databases.
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<p>
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You can however still gradually evolve your key format over time with
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a little bit of pre-planning. For example, you could store a version
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number at the end of each key (one byte should suffice for most uses).
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When you wish to switch to a new key format (e.g., adding an optional
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third part to the keys processed by <code>TwoPartComparator</code>),
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(a) keep the same comparator name (b) increment the version number
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for new keys (c) change the comparator function so it uses the
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version numbers found in the keys to decide how to interpret them.
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<p>
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<h1>Performance</h1>
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<p>
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Performance can be tuned by changing the default values of the
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types defined in <code>include/leveldb/options.h</code>.
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<p>
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<h2>Block size</h2>
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<p>
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<code>leveldb</code> groups adjacent keys together into the same block and such a
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block is the unit of transfer to and from persistent storage. The
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default block size is approximately 4096 uncompressed bytes.
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Applications that mostly do bulk scans over the contents of the
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database may wish to increase this size. Applications that do a lot
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of point reads of small values may wish to switch to a smaller block
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size if performance measurements indicate an improvement. There isn't
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much benefit in using blocks smaller than one kilobyte, or larger than
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a few megabytes. Also note that compression will be more effective
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with larger block sizes.
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<p>
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<h2>Compression</h2>
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<p>
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Each block is individually compressed before being written to
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persistent storage. Compression is on by default since the default
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compression method is very fast, and is automatically disabled for
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uncompressible data. In rare cases, applications may want to disable
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compression entirely, but should only do so if benchmarks show a
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performance improvement:
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<p>
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<pre>
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leveldb::Options options;
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options.compression = leveldb::kNoCompression;
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|
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... leveldb::DB::Open(options, name, ...) ....
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|
</pre>
|
||
|
|
<h2>Cache</h2>
|
||
|
|
<p>
|
||
|
|
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
|
||
|
|
<code>options.cache</code> is non-NULL, it is used to cache frequently used
|
||
|
|
uncompressed block contents.
|
||
|
|
<p>
|
||
|
|
<pre>
|
||
|
|
#include "leveldb/cache.h"
|
||
|
|
|
||
|
|
leveldb::Options options;
|
||
|
|
options.cache = leveldb::NewLRUCache(100 * 1048576); // 100MB cache
|
||
|
|
leveldb::DB* db;
|
||
|
|
leveldb::DB::Open(options, name, &db);
|
||
|
|
... use the db ...
|
||
|
|
delete db
|
||
|
|
delete options.cache;
|
||
|
|
</pre>
|
||
|
|
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 <code>Env</code>
|
||
|
|
implementation provided by the client.)
|
||
|
|
<p>
|
||
|
|
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:
|
||
|
|
<p>
|
||
|
|
<pre>
|
||
|
|
leveldb::ReadOptions options;
|
||
|
|
options.fill_cache = false;
|
||
|
|
leveldb::Iterator* it = db->NewIterator(options);
|
||
|
|
for (it->SeekToFirst(); it->Valid(); it->Next()) {
|
||
|
|
...
|
||
|
|
}
|
||
|
|
</pre>
|
||
|
|
<h2>Key Layout</h2>
|
||
|
|
<p>
|
||
|
|
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.
|
||
|
|
<p>
|
||
|
|
For example, suppose we are implementing a simple file system on top
|
||
|
|
of <code>leveldb</code>. The types of entries we might wish to store are:
|
||
|
|
<p>
|
||
|
|
<pre>
|
||
|
|
filename -> permission-bits, length, list of file_block_ids
|
||
|
|
file_block_id -> data
|
||
|
|
</pre>
|
||
|
|
We might want to prefix <code>filename</code> keys with one letter (say '/') and the
|
||
|
|
<code>file_block_id</code> 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.
|
||
|
|
<p>
|
||
|
|
<h2>Filters</h2>
|
||
|
|
<p>
|
||
|
|
Because of the way <code>leveldb</code> data is organized on disk,
|
||
|
|
a single <code>Get()</code> call may involve multiple reads from disk.
|
||
|
|
The optional <code>FilterPolicy</code> mechanism can be used to reduce
|
||
|
|
the number of disk reads substantially.
|
||
|
|
<pre>
|
||
|
|
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;
|
||
|
|
</pre>
|
||
|
|
The preceding code associates a
|
||
|
|
<a href="http://en.wikipedia.org/wiki/Bloom_filter">Bloom filter</a>
|
||
|
|
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 <code>Get()</code> 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.
|
||
|
|
<p>
|
||
|
|
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.
|
||
|
|
<code>NewBloomFilterPolicy</code> must not be used with such a comparator.
|
||
|
|
Instead, the application should provide a custom filter policy that
|
||
|
|
also ignores trailing spaces. For example:
|
||
|
|
<pre>
|
||
|
|
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);
|
||
|
|
}
|
||
|
|
|
||
|
|
bool KeyMayMatch(const Slice& key, const Slice& filter) const {
|
||
|
|
// Use builtin bloom filter code after removing trailing spaces
|
||
|
|
return builtin_policy_->KeyMayMatch(RemoveTrailingSpaces(key), filter);
|
||
|
|
}
|
||
|
|
};
|
||
|
|
</pre>
|
||
|
|
<p>
|
||
|
|
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 <code>leveldb/filter_policy.h</code> for detail.
|
||
|
|
<p>
|
||
|
|
<h1>Checksums</h1>
|
||
|
|
<p>
|
||
|
|
<code>leveldb</code> associates checksums with all data it stores in the file system.
|
||
|
|
There are two separate controls provided over how aggressively these
|
||
|
|
checksums are verified:
|
||
|
|
<p>
|
||
|
|
<ul>
|
||
|
|
<li> <code>ReadOptions::verify_checksums</code> 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.
|
||
|
|
<p>
|
||
|
|
<li> <code>Options::paranoid_checks</code> 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.
|
||
|
|
<p>
|
||
|
|
If a database is corrupted (perhaps it cannot be opened when
|
||
|
|
paranoid checking is turned on), the <code>leveldb::RepairDB</code> function
|
||
|
|
may be used to recover as much of the data as possible
|
||
|
|
<p>
|
||
|
|
</ul>
|
||
|
|
<h1>Approximate Sizes</h1>
|
||
|
|
<p>
|
||
|
|
The <code>GetApproximateSizes</code> method can used to get the approximate
|
||
|
|
number of bytes of file system space used by one or more key ranges.
|
||
|
|
<p>
|
||
|
|
<pre>
|
||
|
|
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);
|
||
|
|
</pre>
|
||
|
|
The preceding call will set <code>sizes[0]</code> to the approximate number of
|
||
|
|
bytes of file system space used by the key range <code>[a..c)</code> and
|
||
|
|
<code>sizes[1]</code> to the approximate number of bytes used by the key range
|
||
|
|
<code>[x..z)</code>.
|
||
|
|
<p>
|
||
|
|
<h1>Environment</h1>
|
||
|
|
<p>
|
||
|
|
All file operations (and other operating system calls) issued by the
|
||
|
|
<code>leveldb</code> implementation are routed through a <code>leveldb::Env</code> object.
|
||
|
|
Sophisticated clients may wish to provide their own <code>Env</code>
|
||
|
|
implementation to get better control. For example, an application may
|
||
|
|
introduce artificial delays in the file IO paths to limit the impact
|
||
|
|
of <code>leveldb</code> on other activities in the system.
|
||
|
|
<p>
|
||
|
|
<pre>
|
||
|
|
class SlowEnv : public leveldb::Env {
|
||
|
|
.. implementation of the Env interface ...
|
||
|
|
};
|
||
|
|
|
||
|
|
SlowEnv env;
|
||
|
|
leveldb::Options options;
|
||
|
|
options.env = &env;
|
||
|
|
Status s = leveldb::DB::Open(options, ...);
|
||
|
|
</pre>
|
||
|
|
<h1>Porting</h1>
|
||
|
|
<p>
|
||
|
|
<code>leveldb</code> may be ported to a new platform by providing platform
|
||
|
|
specific implementations of the types/methods/functions exported by
|
||
|
|
<code>leveldb/port/port.h</code>. See <code>leveldb/port/port_example.h</code> for more
|
||
|
|
details.
|
||
|
|
<p>
|
||
|
|
In addition, the new platform may need a new default <code>leveldb::Env</code>
|
||
|
|
implementation. See <code>leveldb/util/env_posix.h</code> for an example.
|
||
|
|
|
||
|
|
<h1>Other Information</h1>
|
||
|
|
|
||
|
|
<p>
|
||
|
|
Details about the <code>leveldb</code> implementation may be found in
|
||
|
|
the following documents:
|
||
|
|
<ul>
|
||
|
|
<li> <a href="impl.html">Implementation notes</a>
|
||
|
|
<li> <a href="table_format.txt">Format of an immutable Table file</a>
|
||
|
|
<li> <a href="log_format.txt">Format of a log file</a>
|
||
|
|
</ul>
|
||
|
|
|
||
|
|
</body>
|
||
|
|
</html>
|